Agaian, Sos; Egiazarian, Karen; Astola, Jaakko
2011-01-01
The Hadamard matrix and Hadamard transform are fundamental problem-solving tools in a wide spectrum of scientific disciplines and technologies, such as communication systems, signal and image processing (signal representation, coding, filtering, recognition, and watermarking), digital logic (Boolean function analysis and synthesis), and fault-tolerant system design. Hadamard Transforms intends to bring together different topics concerning current developments in Hadamard matrices, transforms, and their applications. Each chapter begins with the basics of the theory, progresses to more advanced
Technique of Hadamard transform microscope fluorescence image analysis
Institute of Scientific and Technical Information of China (English)
梅二文; 顾文芳; 曾晓斌; 陈观铨; 曾云鹗
1995-01-01
Hadamard transform spatial multiplexed imaging technique is combined with fluorescence microscope and an instrument of Hadamard transform microscope fluorescence image analysis is developed. Images acquired by this instrument can provide a lot of useful information simultaneously, including three-dimensional Hadamard transform microscope cell fluorescence image, the fluorescence intensity and fluorescence distribution of a cell, the background signal intensity and the signal/noise ratio, etc.
Concatenated wavelet/modified Hadamard-structured discrete cosine transform (MHDCT) coding of images
Barazande-Pour, Majid; Mark, Jon W.
1995-04-01
Wavelet transform (WT) is concatenated with the modified Hadamard-structured discrete cosine transform (MHDCT) to encode image signals. As the outer code, the WT decomposes the image signals into uncorrelated low resolution and detailed signal components. As inner codes, the MHDCT adaptively encodes the low resolution signal, while the detailed signals are encoded using pulse code modulation (PCM). The concatenated coding approach offers the possibility of regulated coding for progressive transmission of the image signals over communication networks. Results of image coding using the concatenated WT/MHDCT coder are presented.
Energy Technology Data Exchange (ETDEWEB)
Love, Steven P [Los Alamos National Laboratory
2008-01-01
Hyperspectral imaging (HSI), in which each pixel contains a high-resolution spectrum, is a powerful technique that can remotely detect, identify, and quantify a multitude of materials and chemicals. The advent of addressable micro-mirror arrays (MMAs) makes possible a new class of programmable hyperspectral imagers that can perform key spectral processing functions directly in the optical hardware, thus alleviating some of HSI's high computational overhead, as well as offering improved signal-to-noise in certain important regimes (e.g. when using uncooled infrared detectors). We have built and demonstrated a prototype UV-Visible micro-mirror hyperspectral imager that is capable not only of matched-filter imaging, but also of full hyperspectral imagery via the Hadamard transform technique. With this instrument, one can upload a chemical-specific spectral matched filter directly to the MMA, producing an image showing the location of that chemical without further processing. Target chemicals are changeable nearly instantaneously simply by uploading new matched-filter patterns to the MMA. Alternatively, the MMA can implement Hadamard mask functions, yielding a full-spectrum hyperspectral image upon inverting the transform. In either case, the instrument can produce the 2D spatial image either by an internal scan, using the MMA itself, or with a traditional external push-broom scan. The various modes of operation are selectable simply by varying the software driving the MMA. Here the design and performance of the prototype is discussed, along with experimental results confirming the signal-to-noise improvement produced by the Hadamard technique in the noisy-detector regime.
Noise, fluctuation, and HADAMARD-transform spectrometry
Nitzsche, Guenter; Riesenberg, Rainer
2003-05-01
The HADAMARD principle is known in optics as a multiplex technique. It describes the mode with the most advantageous increase of the signal-to-noise ratio (SNR) in terms of scanning (Fellget advantage). The maximum increase of SNR, we call it gain, is (n+1)/(2On), where n is the number of multiplexing. It is valid in the case of pure detector noise. The multiplex encoding Hadamard pattern in case of n = 7 is 1110100, whereby 1 stands for a switched on channel performed by a field selector. The signals of all (switched on) channels are detected by a single detector. n measurement steps with a cyclic change of the pattern is necessary to perform the Hadamard transformation and to get the result of each individual channel. In case of n = 7 the theoretical gain is 1.51. For all possible multiplex pattern (1100000, 1110000 and so on) the gain is theoretically investigated. A multiplexing advantage (gain > 1) is reached only by the Hadamard pattern, the inverse Hadamard pattern and for (0111111)-pattern (gain=1.08). Most of the multiplex pattern are disadvantageous. The reason for maximum gain of the HADAMARD transformation is analysed theoretically. Signal fluctuations during the measurement caused by fluctuations of the illumination or by the object under test, reduce the multiplex gain, too. So the limits for realizing a gain are estimated theoretically. Essential is the transformation procedure and its influence on the error propagation. The results could be verified by experiments with array spectrometeres. Requirements are derived by numerical simulation concerning the stability of the signals to be multiplexed. It is simulated the needed stability of the signals with increasing order of multiplexing. So the increase of the multiplex gain is limited by signal fluctuations. A realized 96 channel spectral reader is presented as a modern application of an optical multiplexing arrangement. ! M. Harvid, N. J. A. Sloane, Hadamard Transform Optics, Academic Press, 1979
[The coding correction of slit diffraction in Hadamard transform spectrometer].
Li, Bo; Wang, Shu-Rong; Huang, Yu; Wang, Jun-Bo
2013-08-01
According to the principles of Hadamard transform spectrometer and the slit diffraction characteristics, the influence of spectrometer entrance slit diffraction of Hadamard transform spectrometer on the measurement result was analyzed, for the diffraction case, the Hadamard transform spectrometer instrument structure matrix was studied, and the Hadamard transform spectrometer encoding/decoding method was established. The analysis of incident spectral verified the correctness of the coding/ decoding. This method is very important for the high precision measurement of Hadamard transform spectrometer.
SNR analysis and Hadamard mask modification of DMD Hadamard Transform Near-Infrared spectrometer
Xu, Jia-lin; Liu, Hua; Lin, Chun-bo; Sun, Qiang
2017-01-01
The noise of Hadamard Transform (HT) Near Infrared (NIR) spectrometer includes not only the detector circuit noise but also the illumination noise. Hadamard Transform reduces the detector noise while increases the illumination noise. If the relative power intensity is large, the noise of Hadamard method will be greater than that of scanning method. This will lose the significance of Hadamard Transform. In this paper the SNRs of the Hadamard method and scanning method are analyzed. The condition of boosting SNR of spectrometer by Hadamard transform is given. When the condition is not matched, a Hadamard mask of variable height stripes is proposed which the SNR of Hadamard method can be improved. In this paper a HT NIR spectrometer based on 0.45-inch DMD is designed with the spectrum range from 1350 nm to 2500 nm. Several experiments are done with the designed spectrometer. It is shown that with the Hadamard mask of variable height stripes the average SNR is improved by a factor of 2.2 at the short wavelength band and by a factor of 2.8 on the long wavelength band, and the minimum SNR on the whole wavelength band is improved by a factor of 2.3.
Robust Watermarking in Multiresolution Walsh-Hadamard Transform
Bhatnagar, Gaurav; 10.1109/IADCC.2009.4809134
2009-01-01
In this paper, a newer version of Walsh-Hadamard Transform namely multiresolution Walsh-Hadamard Transform (MR-WHT) is proposed for images. Further, a robust watermarking scheme is proposed for copyright protection using MRWHT and singular value decomposition. The core idea of the proposed scheme is to decompose an image using MR-WHT and then middle singular values of high frequency sub-band at the coarsest and the finest level are modified with the singular values of the watermark. Finally, a reliable watermark extraction scheme is developed for the extraction of the watermark from the distorted image. The experimental results show better visual imperceptibility and resiliency of the proposed scheme against intentional or un-intentional variety of attacks.
Institute of Scientific and Technical Information of China (English)
白军科; 刘学斌; 闫鹏; 胡炳樑
2013-01-01
Hadamard变换成像光谱仪采用多通道探测数字变换技术实现光谱成像.主要介绍了基于数字微镜阵列器件的Hadamard变换成像光谱仪的工作原理与仪器结构,研究设计了一套适用于该Hadamard变换成像光谱仪的实验室辐射定标方案.用远距点光源光路进行CMOS探测器像元响应不均匀性修正,获得相对定标精度达到4.6%；采用太阳模拟光源和均匀平行光路,用光谱辐射度计实现标准辐射亮度的传递进行光谱辐射定标,绝对定标精度达到8.92%.通过实物成像,Hadamard变换成像光谱仪的实验室辐射定标方法精确、实用.%Hadamard transform imaging spectrometer is a multi -channel detection digital transform spectrometer detection technology. The spectromter used this technology to achieving spectral imaging. Based on the digital micromirror array device of the Hadamard transform spectrometer working principles and the instrument, a series of precision laboratory calibration methods were researched and employed for the Hadamard transform imaging spectrometer. A point light source in long distance was used for the pixel response nonuniformity correction of the CMOS detector. The uncertainty of the relative calibration was 4.6%. Solar simulator and spectral radiometer were used in absolute radiation calibration of the whole system, and the uncertainty of the absolute radiation calibration was 8.92%. Both of the uncertainty of relative calibration and the uncertainty of the absolute radiation calibration met the requirements of the projection. By actual objects imaging, the laboratory calibration methods of the Hadamard transform imaging spectrometer are proved accurate.
Fourier and Hadamard transform spectrometers - A limited comparison. II
Harwit, M.; Tai, M. H.
1977-01-01
A mathematical approach was used to compare interferometric spectrometers and Hadamard transform spectrometers. The principle results are reported, noting that the simple Hadamard spectrometer encodes more efficiently than a Michelson interferometer which, in turn, encodes less efficiently than is usually acknowledged. Hirschfeld's (1977) major objections to these findings are discussed, although it is noted that none of his objections is supported by evidence.
High sensitivity imaging based on DMD coding Hadamard Transform%DMD编码哈达玛变换高灵敏成像
Institute of Scientific and Technical Information of China (English)
张毅; 王勇; 岳江; 柏连发
2015-01-01
In order to enhance the image quality of the detector under the condition of Low Level Light (LLL) signal, a method of high sensitivity imaging based on Digital Micromirror Device (DMD) coding Hadamard Transform was proposed. On the basis of the assumptions that the noise of the detector and the signal as well as the noise measured each time are both independent, the influence of the noise to the SNR was analyzed in both HT coding imaging and classical imaging. The result was deduced that the improvement of SNR was related to the length n of coding templates in coding imaging, and the value was √n /2 times of that in classic imaging. In order to reduce the encoding time of the image, the partitions coding method was applied. Results show that, compared with classical imaging modalities, the use of partitions coding Hadamard transform imaging significantly improves the signal to noise ratio of the image, while the coding time of high-resolution images is shortened.%为了增强探测器在微弱光信号条件下的成像质量,提出了一种利用哈达玛变换(Hadamard Transform,HT)实现高灵敏探测的成像方法.基于探测器噪声独立于信号,且每次测量噪声也相互独立的假设,分析了在哈达玛编码成像与经典成像中,噪声对图像信噪比的影响.推导出编码成像的信噪比提升与编码模板长度n有关,约为经典成像信噪比的√n /2 倍.同时采用分区编码的方式,减小了高分辨率图像的编码时间.实验结果表明,与经典成像方式相比,采用分区编码的哈达玛变换成像方法明显的提高了图像的信噪比,同时可以在高分辨率图像条件下,缩短编码时间.
Towards holographic "brain" memory based on randomization and Walsh-Hadamard transformation
Dolev, S.; Frenkel, S.; Hanemann, A.
2013-01-01
The holographic conceptual approach for cognitive processes in human brain is investigated by neuroscientists due to the ability of holography to describe sophisticated phenomena of human perception and cognition. In this work we suggest a new mathematical description for Pribram's holographic or "holonomic" representation approach for the mind. Namely, we consider: (i) randomization of information, and (ii) Walsh-Hadamard spectral representation of holograms, rather than the well-known Fourier transform representation. The randomization reflects the belief that perceptual processes are not direct, but depend on the perceiver's expectations and previous knowledge as well as the information available in the stimulus itself. The use of Fourier transform and in our case Walsh-Hadamard transform reflects the possibility that each neuron or group of neurons encode some information about the entire image rather than the whole information about a part of the image. We demonstrate that the Walsh-Hadamard transform has benefits over the general Fourier transform. The encoding is performed on randomized information that is then represented by a set of spectral Wash-Hadamard coefficients that have holographic properties. Namely, any portion of the set of coefficients defines a "blurry image" of the original data. The values of the coefficients of the Walsh-Hadamard transformation are distributed approximately normally when the information is randomized, ensuring, with high probability, that growing sets of coefficients implies a monotonic gain of information. Moreover the randomization of the original information yields robust code that is able to cope with missing coefficients. The bridge between the randomization and holographic encoding with the well-known holographic human brain assumption may bring an interesting interpretation of the perception phenomena. In particular, holographic encoding fits the mystery of the human memory encoding, where damage of portions leaves a
Discrete Hadamard transformation algorithm's parallelism analysis and achievement
Hu, Hui
2009-07-01
With respect to Discrete Hadamard Transformation (DHT) wide application in real-time signal processing while limitation in operation speed of DSP. The article makes DHT parallel research and its parallel performance analysis. Based on multiprocessor platform-TMS320C80 programming structure, the research is carried out to achieve two kinds of parallel DHT algorithms. Several experiments demonstrated the effectiveness of the proposed algorithms.
Fourier and Hadamard transform spectrometers - A limited comparison
Tai, M. H.; Harwit, M.
1976-01-01
An encoding figure of merit is established for a detector-noise limited Fourier transform spectrometer (FTS) and compared to the comparable figure for a Hadamard transform spectrometer (HTS). The limitation of the Fourier system is partly that it does not truly Fourier analyze the radiation. Instead a cosine squared modulation is imposed on the different spectral frequencies. An additional difficulty is that neither the cosine nor the cosine squared functions form an orthonormal set. This makes the Fellgett's advantage (root-mean-squared figure of merit) for a single detector Michelson interferometer a factor of the square root of (N/8) greater than for a conventional grating instrument - rather than the square root of (N/2). The theoretical limit would be the square root of N.
Encryption of Binary and Non-Binary Data Using Chained Hadamard Transforms
Reddy, Rohith Singi
2010-01-01
This paper presents a new chaining technique for the use of Hadamard transforms for encryption of both binary and non-binary data. The lengths of the input and output sequence need not be identical. The method may be used also for hashing.
Meenakshisundaram, N.
Application of the Hadamard and related transforms on a few generalized quantum baker’s maps have been studied. Effectiveness of the Hadamard transform and a new transform which combines the Fourier and the Hadamard transforms, for simplifying the eigenstates or resonances of the quantization of a few generalized baker’s map namely tetradic baker and lazy baker’s map when the Hilbert space dimension is power of 2 has been done by comparing the participation ratios in the transformed basis with respect to the position basis. Several special family of states based on their maximal compression in either Hadamard transform or the new transform are identified and they are related to the ubiquitous Thue-Morse and allied sequences. Evidence is provided that these special family of states as well as average over all eigenstates exhibits multifractal nature.
Harwit, M.
1977-01-01
Sources of noise and error correcting procedures characteristic of Hadamard transform optical systems were investigated. Reduction of spectral noise due to noise spikes in the data, the effect of random errors, the relative performance of Fourier and Hadamard transform spectrometers operated under identical detector-noise-limited conditions, and systematic means for dealing with mask defects are among the topics discussed. The distortion in Hadamard transform optical instruments caused by moving Masks, incorrect mask alignment, missing measurements, and diffraction is analyzed and techniques for reducing or eliminating this distortion are described.
Lum, Daniel J; Knarr, Samuel H; Howell, John C
2015-10-19
We demonstrate how to efficiently implement extremely high-dimensional compressive imaging of a bi-photon probability distribution. Our method uses fast-Hadamard-transform Kronecker-based compressive sensing to acquire the joint space distribution. We list, in detail, the operations necessary to enable fast-transform-based matrix-vector operations in the joint space to reconstruct a 16.8 million-dimensional image in less than 10 minutes. Within a subspace of that image exists a 3.2 million-dimensional bi-photon probability distribution. In addition, we demonstrate how the marginal distributions can aid in the accuracy of joint space distribution reconstructions.
Liu, Wenjie; Zhang, Xing; Knochenmuss, Richard; Siems, William F.; Hill, Herbert H.
2016-05-01
A high performance liquid chromatograph (HPLC)was interfaced to an atmospheric drift tube ion mobility time of flight mass spectrometry. The power of multidimensional separation was demonstrated using chili pepper extracts. The ambient pressure drift tube ion mobility provided high resolving powers up to 166 for the HPLC eluent. With implementation of Hadamard transform (HT), the duty cycle for the ion mobility drift tube was increased from less than 1% to 50%, and the ion transmission efficiency was improved by over 200 times compared with pulsed mode, improving signal to noise ratio 10 times. HT ion mobility and TOF mass spectrometry provide an additional dimension of separation for complex samples without increasing the analysis time compared with conventional HPLC.
Freeform lens collimating spectrum-folded Hadamard transform near-infrared spectrometer
Wang, Xiaoduo; Liu, Hua; Juschkin, Larissa; Li, Yunpeng; Xu, Jialin; Quan, Xiangqian; Lu, Zhenwu
2016-12-01
A novel Hadamard transform spectrometer collimated by a freeform lens has been designed, which doubles the working spectral range while the spectral resolution is maintained. The freeform lens is designed to redistribute the broadband spectra of the source from 800 nm to 2400 nm into two collimated beams with different wavelengths and different tilting angles, to achieve the folding of spectra on the digital micro-mirror devices (DMD). It is constructed by solving two partial differential equations. The grating diffraction efficiency of the two split beams are more uniform and higher compared with the traditional method. The simulation results show that the bandwidth of the spectrometer is doubled and the spectral resolution is better than 10 nm. The optical system becomes more compact, and the energy efficiency is improved by 11.98% by folding the spectra with one freeform lens and one grating.
Directory of Open Access Journals (Sweden)
Lavish Kansal
2013-03-01
Full Text Available Wireless communications have been developed widelyand rapidly in the modern world especially duringthe last decade. Orthogonal Frequency Division Multiplexing (OFDM has grown to a popularcommunication technique for high speed communication. Besides of the advantages, one of maindisadvantage of OFDM is high peak to average powerratio (PAPR. In this paper, a PAPR reductionmethod is proposed that is based on combining clipping with Walsh Hadamard Transform (WHT.WHT isa precoding technique which is having less complexity compared to the other existing power reductiontechniques and also it can reduce PAPR considerablyand results in no distortion. The performance of theproposed scheme is examined through computer simulations and it is found that power reductions areobtained.
Cheng, Yuan-Kai; Lin, Cheng-Huang; Kuo, Samuel; Yang, Jonathan; Hsiung, Szu-Yuan; Wang, Jia-Lin
2012-01-13
The Hadamard transform-gas chromatography/mass spectrometry (HT-GC/MS) technique was successfully employed for the detection of hexamethyldisiloxane (HMDSO, C(6)H(18)OSi(2)) at the sub-nL/L level in a semiconductor wafer cleanroom. Indoor air samples were collected from the room, according to EPA Method TO-17 using a Tedlar bag where the air samples were allowed to pass through an absorption tube for 24 h. The condensed components were then heated and simultaneously injected into a GC column through a Hadamard-injector, which was operated in accordance with the Hadamard codes. Compared to the single injection used in most GC/MS systems, the signal-to-noise (S/N) ratios were substantially improved after the inverse Hadamard transformation of the encoded chromatogram. Under optimized conditions, when cyclic S-matrix orders of 255, 1023 and 2047 were used, the S/N ratios of the HMDSO signals were substantially improved by 7.4-, 15.1- and 20.1-fold, respectively. These improvements are in good agreement with theoretically calculated values (8.0-, 16.0- and 22.6-fold, respectively). We found that when the HT-GC/MS technique was applied, HMDSO could be detected at the 0.1 nL/L level.
Hadamard Transform Spectrometer Mixed Pixels' Unmixing Method%哈达玛变换光谱仪混合像元解混方法研究
Institute of Scientific and Technical Information of China (English)
闫鹏; 胡炳樑; 刘学斌; 孙威; 李立波; 冯玉涛; 刘永征
2011-01-01
哈达玛变换光谱成像仪是一种采用多通道探测的数字变换光谱技术,介绍了基于数字微镜阵列器件(DMD)的哈达玛变换光谱仪工作原理与仪器结构,对成像传感器所获得的混合像元进行了分析研究,理论推导出了混叠像元的解混合方法,仿真实验结果表明该方法简单有效,对提高混合像元复原光谱精度超过10％.%Hadamard transform imaging spectrometer is a multi-channel digital transform spectrometer detection technology, this paper based on digital micromirror array device (DMD) of the Hadamard transform spectrometer working principle and instrument structure, obtained by the imaging sensor mixed pixel were analyzed, theory derived the solution of pixel aliasing hybrid method, simulation results show that the method is simple and effective to improve the accuracy of mixed pixel spectrum more than 10% recovery.
Directory of Open Access Journals (Sweden)
Padmavathi Kora
2017-06-01
Full Text Available Electrocardiogram (ECG, a non-invasive diagnostic technique, used for detecting cardiac arrhythmia. From last decade industry dealing with biomedical instrumentation and research, demanding an advancement in its ability to distinguish different cardiac arrhythmia. Atrial Fibrillation (AF is an irregular rhythm of the human heart. During AF, the atrial moments are quicker than the normal rate. As blood is not completely ejected out of atria, chances for the formation of blood clots in atrium. These abnormalities in the heart can be identified by the changes in the morphology of the ECG. The first step in the detection of AF is preprocessing of ECG, which removes noise using filters. Feature extraction is the next key process in this research. Recent feature extraction methods, such as Auto Regressive (AR modeling, Magnitude Squared Coherence (MSC and Wavelet Coherence (WTC using standard database (MIT-BIH, yielded a lot of features. Many of these features might be insignificant containing some redundant and non-discriminatory features that introduce computational burden and loss of performance. This paper presents fast Conjugate Symmetric Sequency Ordered Complex Hadamard Transform (CS-SCHT for extracting relevant features from the ECG signal. The sparse matrix factorization method is used for developing fast and efficient CS-SCHT algorithm and its computational performance is examined and compared to that of the HT and NCHT. The applications of the CS-SCHT in the ECG-based AF detection is also discussed. These fast CS-SCHT features are optimized using Hybrid Firefly and Particle Swarm Optimization (FFPSO to increase the performance of the classifier.
Symmetricity of Distribution for One-Dimensional Hadamard Walk
Konno, N; Soshi, T; Konno, Norio; Namiki, Takao; Soshi, Takahiro
2002-01-01
In this paper we study a one-dimensional quantum random walk with the Hadamard transformation which is often called the Hadamard walk. We construct the Hadamard walk using a transition matrix on probability amplitude and give some results on symmetricity of probability distributions for the Hadamard walk.
Lopez Villaverde, Eduardo; Robert, Sebastien; Prada, Claire
2017-09-01
In this paper, defects in a high density polyethylene pipe are imaged with the total focusing method. The viscoelastic attenuation of this material greatly reduces the signal level and leads to a poor signal-to-noise ratio (SNR) due to electronic noise. To improve the image quality, the decomposition of the time reversal operator method is combined with the spatial Hadamard coded transmissions before calculating images in the time domain. Because the Hadamard coding is not compatible with conventional imaging systems, this paper proposes two modified coding methods based on sparse Hadamard matrices with +1/0 coefficients. The SNRs expected with the different spatial codes are demonstrated, and then validated on both simulated and experimental data. Experiments are performed with a transducer array in contact with the base material of a polyethylene pipe. In order to improve the noise filtering procedure, the singular values associated with electronic noise are expressed on the basis of the random matrix theory. This model of noise singular values allows a better identification of the defect response in noisy experimental data. Finally, the imaging method is evaluated in a more industrial inspection configuration, where an immersion array probe is used to image defects in a butt fusion weld with a complex geometry.
On Nega-Hadamard transform of Boolean functions%布尔函数的 Nega-Hada mard变换研究
Institute of Scientific and Technical Information of China (English)
卓泽朋; 崇金凤; 魏仕民; 余磊
2015-01-01
利用Nega-Hadamard变换的性质，研究了bent函数与其对偶函数Nega-Hadamard变换的关系，得出bent函数为negabent函数，其对偶函数也是negabent函数的结果；同时，得到了布尔函数在某个仿射子空间上Nega-Hadamard变换的性质；研究了布尔函数的导数与它的二进制移位关于Nega-Hadamard变换的关系。%By using the properties of Nega-Hadamard transform,this paper studied the relationship between bent function and its dual in the Nega-Hadamard transform.It showed that if bent function was a negabent,then its dual was again negabent. Also,it obtained the property of the Nega-Hadamard transform of Boolean function fin some affine subspace.At last,it pro-vided the relationship between the Nega-Hadamard transforms of the derivatives of fand the dyadic shifts.
An 8×8/4×4 Adaptive Hadamard Transform Based FME VLSI Architecture for 4K×2K H.264/AVC Encoder
Fan, Yibo; Liu, Jialiang; Zhang, Dexue; Zeng, Xiaoyang; Chen, Xinhua
Fidelity Range Extension (FRExt) (i.e. High Profile) was added to the H.264/AVC recommendation in the second version. One of the features included in FRExt is the Adaptive Block-size Transform (ABT). In order to conform to the FRExt, a Fractional Motion Estimation (FME) architecture is proposed to support the 8×8/4×4 adaptive Hadamard Transform (8×8/4×4 AHT). The 8×8/4×4 AHT circuit contributes to higher throughput and encoding performance. In order to increase the utilization of SATD (Sum of Absolute Transformed Difference) Generator (SG) in unit time, the proposed architecture employs two 8-pel interpolators (IP) to time-share one SG. These two IPs can work in turn to provide the available data continuously to the SG, which increases the data throughput and significantly reduces the cycles that are needed to process one Macroblock. Furthermore, this architecture also exploits the linear feature of Hadamard Transform to generate the quarter-pel SATD. This method could help to shorten the long datapath in the second-step of two-iteration FME algorithm. Finally, experimental results show that this architecture could be used in the applications requiring different performances by adjusting the supported modes and operation frequency. It can support the real-time encoding of the seven-mode 4K×2K@24fps or six-mode 4K×2K@30fps video sequences.
Subband/transform functions for image processing
Glover, Daniel
1993-01-01
Functions for image data processing written for use with the MATLAB(TM) software package are presented. These functions provide the capability to transform image data with block transformations (such as the Walsh Hadamard) and to produce spatial frequency subbands of the transformed data. Block transforms are equivalent to simple subband systems. The transform coefficients are reordered using a simple permutation to give subbands. The low frequency subband is a low resolution version of the original image, while the higher frequency subbands contain edge information. The transform functions can be cascaded to provide further decomposition into more subbands. If the cascade is applied to all four of the first stage subbands (in the case of a four band decomposition), then a uniform structure of sixteen bands is obtained. If the cascade is applied only to the low frequency subband, an octave structure of seven bands results. Functions for the inverse transforms are also given. These functions can be used for image data compression systems. The transforms do not in themselves produce data compression, but prepare the data for quantization and compression. Sample quantization functions for subbands are also given. A typical compression approach is to subband the image data, quantize it, then use statistical coding (e.g., run-length coding followed by Huffman coding) for compression. Contour plots of image data and subbanded data are shown.
Complex Hadamard matrices from Sylvester inverse orthogonal matrices
Dita, Petre
2009-01-01
A novel method to obtain parametrizations of complex inverse orthogonal matrices is provided. These matrices are natural generalizations of complex Hadamard matrices which depend on non zero complex parameters. The method we use is via doubling the size of inverse complex conference matrices. When the free parameters take values on the unit circle the inverse orthogonal matrices transform into complex Hadamard matrices, and in this way we find new parametrizations of Hadamard matrices for dim...
Decoding Technique of Concatenated Hadamard Codes and Its Performance
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
The decoding technique of concatenated Hadamard codes and its performance are studied. Efficient softin-soft-out decoding algorithms based on the fast Hadamard transform are developed. Performance required by CDMA mobile or PCS speech services, e.g. , BER= 10-3, can be achieved at Eb/No = 0.9 dB using short interleaving length of 192 bits.
Telkki, Ville-Veikko; Zhivonitko, Vladimir V; Selent, Anne; Scotti, Gianmario; Leppäniemi, Jarmo; Franssila, Sami; Koptyug, Igor V
2014-10-13
The development of microfluidic processes requires information-rich detection methods. Here we introduce the concept of remote detection exchange NMR spectroscopy (RD-EXSY), and show that, along with indirect spatial information extracted from time-of-flight data, it provides unique information about the active regions, reaction pathways, and intermediate products in a lab-on-a-chip reactor. Furthermore, we demonstrate that direct spatial resolution can be added to RD-EXSY efficiently by applying the principles of Hadamard spectroscopy.
A Two-Dimensional Double Dispersed Hadamard Transform Spectrometer%双色散二维阿达玛变换光谱仪
Institute of Scientific and Technical Information of China (English)
刘佳; 石磊; 李凯; 郑信文; 曾立波; 吴琼水
2012-01-01
设计了一种双色散二维调制的阿达玛变换光谱仪,利用光栅在水平方向的谱级色散和棱镜在垂直方向的谱线色散进行二维分光.与传统的二维光谱CCD探测方法不同,该设计独辟蹊径,采用面阵数字微镜对二维光谱进行阿达玛调制,并利用单点式检测器进行光信号的检测.理论计算及光学仿真表明,与传统的二维光谱探测仪器相比,该光谱仪不仅具有高的分辨率,同时还具有很高的信噪比.%A kind of two-dimensional hadamard transform spectrometer was developed. A grating was used for chromatic dispersion of orders and a prism was used for spectral dispersion. Quite different from traditional CCD detection method, a digital micromirror device (DMD) was applied for optical modulation, and a simple point detector was used as the sensor. Compared with traditional two-dimensional spectrometer, it has the advantage of high resolution and signal-noise-ratio, which was proved by theoretical calculation and computer simulation.
Hadamard quantum broadcast channels
Wang, Qingle; Das, Siddhartha; Wilde, Mark M.
2017-10-01
We consider three different communication tasks for quantum broadcast channels, and we determine the capacity region of a Hadamard broadcast channel for these various tasks. We define a Hadamard broadcast channel to be such that the channel from the sender to one of the receivers is entanglement-breaking and the channel from the sender to the other receiver is complementary to this one. As such, this channel is a quantum generalization of a degraded broadcast channel, which is well known in classical information theory. The first communication task we consider is classical communication to both receivers, the second is quantum communication to the stronger receiver and classical communication to other, and the third is entanglement-assisted classical communication to the stronger receiver and unassisted classical communication to the other. The structure of a Hadamard broadcast channel plays a critical role in our analysis: The channel to the weaker receiver can be simulated by performing a measurement channel on the stronger receiver's system, followed by a preparation channel. As such, we can incorporate the classical output of the measurement channel as an auxiliary variable and solve all three of the above capacities for Hadamard broadcast channels, in this way avoiding known difficulties associated with quantum auxiliary variables.
Aghagolzadeh, Sabzali; Ersoy, Okan K.
1992-03-01
Blockwise transform image enhancement techniques are discussed. Previously, transform image enhancement has usually been based on the discrete Fourier transform (DFT) applied to the whole image. Two major drawbacks with the DFT are high complexity of implementation involving complex multiplications and additions, with intermediate results being complex numbers, and the creation of severe block effects if image enhancement is done blockwise. In addition, the quality of enhancement is not very satisfactory. It is shown that the best transforms for transform image coding, namely, the scrambled real discrete Fourier transform, the discrete cosine transform, and the discrete cosine-III transform, are also the best for image enhancement. Three techniques of enhancement discussed in detail are alpha- rooting, modified unsharp masking, and filtering motivated by the human visual system response (HVS). With proper modifications, it is observed that unsharp masking and HVS- motivated filtering without nonlinearities are basically equivalent. Block effects are completely removed by using an overlap-save technique in addition to the best transform.
Circulant conference matrices for new complex Hadamard matrices
Dita, Petre
2011-01-01
The circulant real and complex matrices are used to find new real and complex conference matrices. With them we construct Sylvester inverse orthogonal matrices by doubling the size of inverse complex conference matrices. When the free parameters take values on the unit circle the inverse orthogonal matrices transform into complex Hadamard matrices. The method is used for $n=6$ conference matrices and in this way we find new parametrisations of Hadamard matrices for dimension $ n=12$.
Hadamard partitioned difference families
Buratti, Marco
2017-01-01
We prove that every Hadamard difference set of order $u^2$ leads to a partitioned difference family of any order $v\\equiv4u^2$ (mod $8u^2$) and blocks of sizes $4u^2-2u$, $4u^2$ and $4u^2+2u$ provided that the maximal prime power divisors of $v\\over4u^2$ are all greater than $4u^2+2u$.
Institute of Scientific and Technical Information of China (English)
刘佳; 陈奋飞; 廖乘胜; 许谦; 曾立波; 吴琼水
2011-01-01
构建了一个基于数字微镜技术的新型阿达玛变换近红外光谱仪.光学信号采用光纤引入,以光栅作为分光元件,利用数字微镜代替传统的机械式阿达玛模板进行光学编码调制,使用单点InGaAs红外探测器检测调制后的光信号,通过快速阿达玛解码还原出原始光谱.通过实验检验了光谱仪的分辨率、信噪比、稳定性以及谱图获取速度等指标.实验结果表明,所研制的光谱仪灵敏度高,信噪比高,响应速度快,体积小巧,其在油品检测、食品安全等行业有着广泛的应用前景.%A Hadamard transform near infrared spectrometer based on a digital micromirror device was constructed. The optical signal was collected by optical fiber, a grating was used for light diffraction, a digital micromirror device (DMD) was applied instead of traditional mechanical Hadamard masks for optical modulation, and an InGaAs near infrared detector was used as the optic sensor. The original spectrum was recovered by fast Hadamard transform algrithms. The advantages of the spectrometer, such as high resolution, signal-noise-ratio, stability, sensitivity and response speed were proved by experiments, which indicated that it is very suitable for oil and food-safety applications.
Mubs and Hadamards of Order Six
Bengtsson, I; Ericsson, A; Larsson, J A; Tadej, W; Zyczkowski, K; Bengtsson, Ingemar; Bruzda, Wojciech; Ericsson, Asa; Larsson, Jan-Ake; Tadej, Wojciech; Zyczkowski, Karol
2006-01-01
We report on a search for mutually unbiased bases (MUBs) in 6 dimensions. We find only triplets of MUBs, and thus do not come close to the theoretical upper bound 7. However, we point out that the natural habitat for sets of MUBs is the set of all complex Hadamard matrices of the given order, and we introduce a natural notion of distance between bases in Hilbert space. This allows us to draw a detailed map of where in the landscape the MUB triplets are situated. We use available tools, such as the theory of the discrete Fourier transform, to organise our results. Finally we present some evidence for the conjecture that there exists a four dimensional family of complex Hadamard matrices of order 6. If this conjecture is true the landscape in which one may search for MUBs is much larger than previously thought.
Directory of Open Access Journals (Sweden)
Vladimir A. Batura
2014-11-01
Full Text Available The efficiency of orthogonal transformations application in the frequency algorithms of the digital watermarking of still images is examined. Discrete Hadamard transform, discrete cosine transform and discrete Haar transform are selected. Their effectiveness is determined by the invisibility of embedded in digital image watermark and its resistance to the most common image processing operations: JPEG-compression, noising, changing of the brightness and image size, histogram equalization. The algorithm for digital watermarking and its embedding parameters remain unchanged at these orthogonal transformations. Imperceptibility of embedding is defined by the peak signal to noise ratio, watermark stability– by Pearson's correlation coefficient. Embedding is considered to be invisible, if the value of the peak signal to noise ratio is not less than 43 dB. Embedded watermark is considered to be resistant to a specific attack, if the Pearson’s correlation coefficient is not less than 0.5. Elham algorithm based on the image entropy is chosen for computing experiment. Computing experiment is carried out according to the following algorithm: embedding of a digital watermark in low-frequency area of the image (container by Elham algorithm, exposure to a harmful influence on the protected image (cover image, extraction of a digital watermark. These actions are followed by quality assessment of cover image and watermark on the basis of which efficiency of orthogonal transformation is defined. As a result of computing experiment it was determined that the choice of the specified orthogonal transformations at identical algorithm and parameters of embedding doesn't influence the degree of imperceptibility for a watermark. Efficiency of discrete Hadamard transform and discrete cosine transformation in relation to the attacks chosen for experiment was established based on the correlation indicators. Application of discrete Hadamard transform increases
Hadamard Matrices and Their Applications
Horadam, K J
2011-01-01
In Hadamard Matrices and Their Applications, K. J. Horadam provides the first unified account of cocyclic Hadamard matrices and their applications in signal and data processing. This original work is based on the development of an algebraic link between Hadamard matrices and the cohomology of finite groups that was discovered fifteen years ago. The book translates physical applications into terms a pure mathematician will appreciate, and theoretical structures into ones an applied mathematician, computer scientist, or communications engineer can adapt and use. The first half of the book expl
Simulations of the Hadamard Variance: Probability Distributions and Confidence Intervals.
Ashby, Neil; Patla, Bijunath
2016-04-01
Power-law noise in clocks and oscillators can be simulated by Fourier transforming a modified spectrum of white phase noise. This approach has been applied successfully to simulation of the Allan variance and the modified Allan variance in both overlapping and nonoverlapping forms. When significant frequency drift is present in an oscillator, at large sampling times the Allan variance overestimates the intrinsic noise, while the Hadamard variance is insensitive to frequency drift. The simulation method is extended in this paper to predict the Hadamard variance for the common types of power-law noise. Symmetric real matrices are introduced whose traces-the sums of their eigenvalues-are equal to the Hadamard variances, in overlapping or nonoverlapping forms, as well as for the corresponding forms of the modified Hadamard variance. We show that the standard relations between spectral densities and Hadamard variance are obtained with this method. The matrix eigenvalues determine probability distributions for observing a variance at an arbitrary value of the sampling interval τ, and hence for estimating confidence in the measurements.
Construction of Hadamard States by Pseudo-Differential Calculus
Gérard, C.; Wrochna, M.
2014-01-01
We give a new construction based on pseudo-differential calculus of quasi-free Hadamard states for Klein-Gordon equations on a class of space-times whose metric is well-behaved at spatial infinity. In particular on this class of space-times, we construct all pure Hadamard states whose two-point function (expressed in terms of Cauchy data on a Cauchy surface) is a matrix of pseudo-differential operators. We also study their covariance under symplectic transformations. As an aside, we give a new construction of Hadamard states on arbitrary globally hyperbolic space-times which is an alternative to the classical construction by Fulling, Narcowich and Wald.
Morphological Transform for Image Compression
Directory of Open Access Journals (Sweden)
Luis Pastor Sanchez Fernandez
2008-05-01
Full Text Available A new method for image compression based on morphological associative memories (MAMs is presented. We used the MAM to implement a new image transform and applied it at the transformation stage of image coding, thereby replacing such traditional methods as the discrete cosine transform or the discrete wavelet transform. Autoassociative and heteroassociative MAMs can be considered as a subclass of morphological neural networks. The morphological transform (MT presented in this paper generates heteroassociative MAMs derived from image subblocks. The MT is applied to individual blocks of the image using some transformation matrix as an input pattern. Depending on this matrix, the image takes a morphological representation, which is used to perform the data compression at the next stages. With respect to traditional methods, the main advantage offered by the MT is the processing speed, whereas the compression rate and the signal-to-noise ratio are competitive to conventional transforms.
Searching for partial Hadamard matrices
Álvarez, Víctor; Frau, María-Dolores; Gudiel, Félix; Güemes, María-Belén; Martín, Elena; Osuna, Amparo
2012-01-01
Three algorithms looking for pretty large partial Hadamard matrices are described. Here "large" means that hopefully about a third of a Hadamard matrix (which is the best asymptotic result known so far, [dLa00]) is achieved. The first one performs some kind of local exhaustive search, and consequently is expensive from the time consuming point of view. The second one comes from the adaptation of the best genetic algorithm known so far searching for cliques in a graph, due to Singh and Gupta [SG06]. The last one consists in another heuristic search, which prioritizes the required processing time better than the final size of the partial Hadamard matrix to be obtained. In all cases, the key idea is characterizing the adjacency properties of vertices in a particular subgraph G_t of Ito's Hadamard Graph Delta (4t) [Ito85], since cliques of order m in G_t can be seen as (m+3)*4t partial Hadamard matrices.
Gopinath, T; Kumar, Anil
2006-12-01
Hadamard spectroscopy has earlier been used to speed-up multi-dimensional NMR experiments. In this work, we speed-up the two-dimensional quantum computing scheme, by using Hadamard spectroscopy in the indirect dimension, resulting in a scheme which is faster and requires the Fourier transformation only in the direct dimension. Two and three qubit quantum gates are implemented with an extra observer qubit. We also use one-dimensional Hadamard spectroscopy for binary information storage by spatial encoding and implementation of a parallel search algorithm.
Hadamard Factorization of Stable Polynomials
Loredo-Villalobos, Carlos Arturo; Aguirre-Hernández, Baltazar
2011-11-01
The stable (Hurwitz) polynomials are important in the study of differential equations systems and control theory (see [7] and [19]). A property of these polynomials is related to Hadamard product. Consider two polynomials p,q ∈ R[x]:p(x) = anxn+an-1xn-1+...+a1x+a0q(x) = bmx m+bm-1xm-1+...+b1x+b0the Hadamard product (p × q) is defined as (p×q)(x) = akbkxk+ak-1bk-1xk-1+...+a1b1x+a0b0where k = min(m,n). Some results (see [16]) shows that if p,q ∈R[x] are stable polynomials then (p×q) is stable, also, i.e. the Hadamard product is closed; however, the reciprocal is not always true, that is, not all stable polynomial has a factorization into two stable polynomials the same degree n, if n> 4 (see [15]).In this work we will give some conditions to Hadamard factorization existence for stable polynomials.
A concise guide to complex Hadamard matrices
Tadej, W; Tadej, Wojciech; Zyczkowski, Karol
2005-01-01
Complex Hadamard matrices, consisting of unimodular entries with arbitrary phases, play an important role in the theory of quantum information. We review basic properties of complex Hadamard matrices and present a catalogue of inequivalent cases known for dimension N=2,...,16. In particular, we explicitly write down some families of complex Hadamard matrices for N=12,14 and 16, which we could not find in the existing literature.
Zeeuw, P.M. de; Tai, X.-C.; Lie, K.A.; Chan, T.F.; Osher, S.
2007-01-01
A second order partial differential operator is applied to an image function. To this end we consider both the Laplacian and a more general elliptic operator. By using a multigrid operator known from the so-called approximation property, we derive a multiresolution decomposition of the image without
一种数字微镜控制的近红外阿达玛变换光谱仪%A NIR-Hadamard transform spectrometer controled by digital micromirror
Institute of Scientific and Technical Information of China (English)
李凯; 石磊; 曾立波; 吴琼水
2012-01-01
使用高精度的数字微镜（DMD）阵列代替传统的阿达玛编码模板，使得阿达玛光学编码过程中没有任何机械运动部件，从而大大提高了光谱仪的抗震性和稳定性．利用FPGA和MSP430单片机控制DMD产生阿达玛变换编码模板，并按照特定的时序完成模板的移动、模拟信号／数字信号（A／D）采样脉冲产生与筛选等工作．利用以该模板为核心部件的阿达玛变换光谱仪进行了性能测试实验，结果表明该仪器性能优良，稳定可靠．%The core part of the Hadama transform spectrometer is its masks. Traditional Hada-a's masks was replaced by digital micromirror device (DMD) with high accuracy, making the spectrome ter without any mechanical move parts to improving the stability greatly. FPGA and MSP430 micro- computer were used to control DMD generating Hadamard transform mask, finish the job of mask's cycling movement and the screening of analog-signal/digital-signal(A/D)sampling pulse. Finally, we have tested the spectromenter's ability which are based on this mask. The results show that the in- strument reliable perfor-mance.
DEFF Research Database (Denmark)
Middlemas, Jill
2009-01-01
The article presents an analysis of the visual representations of various figures in the book of Ezekiel with a view towards understanding the rhetorical strategies employed. One of the rhetorical strategies apparent is the evocation of images to abolish them. Furthermore, careful observation...... thought of more specifically as male. It becomes clear that arguments about anthropomorphism and Ezekiel become better informed when greater attention is given to the rhetorical function of the written word. The rejection of other deities as unattractive objects, the cities of ancient Israel and Judah...... as women, and the deity of ancient Israel in any stable form reveal that the prophet(s) is ultimately iconoclastic and aniconic. When the divine image fades from view, to be replaced by an emphasis on the divine word, the need and authorization for representative symbols ceases....
Convex analysis and optimization in Hadamard spaces
Bacak, Miroslav
2014-01-01
This book gives a first systematic account on the subject of convex analysis and optimization in Hadamard spaces. It is primarily aimed at both graduate students and researchers in analysis and optimization.
MERSENNE AND HADAMARD MATRICES CALCULATION BY SCARPIS METHOD
Directory of Open Access Journals (Sweden)
N. A. Balonin
2014-05-01
Full Text Available Purpose. The paper deals with the problem of basic generalizations of Hadamard matrices associated with maximum determinant matrices or not optimal by determinant matrices with orthogonal columns (weighing matrices, Mersenne and Euler matrices, ets.; calculation methods for the quasi-orthogonal local maximum determinant Mersenne matrices are not studied enough sufficiently. The goal of this paper is to develop the theory of Mersenne and Hadamard matrices on the base of generalized Scarpis method research. Methods. Extreme solutions are found in general by minimization of maximum for absolute values of the elements of studied matrices followed by their subsequent classification according to the quantity of levels and their values depending on orders. Less universal but more effective methods are based on structural invariants of quasi-orthogonal matrices (Silvester, Paley, Scarpis methods, ets.. Results. Generalizations of Hadamard and Belevitch matrices as a family of quasi-orthogonal matrices of odd orders are observed; they include, in particular, two-level Mersenne matrices. Definitions of section and layer on the set of generalized matrices are proposed. Calculation algorithms for matrices of adjacent layers and sections by matrices of lower orders are described. Approximation examples of the Belevitch matrix structures up to 22-nd critical order by Mersenne matrix of the third order are given. New formulation of the modified Scarpis method to approximate Hadamard matrices of high orders by lower order Mersenne matrices is proposed. Williamson method is described by example of one modular level matrices approximation by matrices with a small number of levels. Practical relevance. The efficiency of developing direction for the band-pass filters creation is justified. Algorithms for Mersenne matrices design by Scarpis method are used in developing software of the research program complex. Mersenne filters are based on the suboptimal by
Micro Hadamard Transform Near-Infrared Spectrometer%微型MOEMS阿达玛变换近红外光谱仪
Institute of Scientific and Technical Information of China (English)
张智海; 莫祥霞; 郭媛君; 王伟
2011-01-01
提出一种运用微光机电系统(micro-opto-electro-mechanical systems,MOEMS)闪耀光栅,动态产生阿达玛变换模版的微型近红外光谱仪.它具有体积小、价格低、扫描速度快等突出优点.分析了这种新型近红外光谱仪的结构和工作原理,通过对MOEMS闪耀光栅编程,动态生成了 63阶阿达玛模版.实验得到的光谱波形与岛津光谱仪测量结果吻合.检测波长范围为900～1 500nm,分辨率为19nm,单次扣描时间2.4s,信噪比为44.67:1,光路尺寸为70 mm×130 mm,总体重量＜1kg,符合实时、便携的要求.%A new type micro Hadanard transform (HT) near-infrared (NIR) spectrometer is proposed in the present paper. It has a MOEMS (Micro-Opto-Electro-Mechanical Systems) blazed grating HT mask. It has merits of compactness, agility of dynamic mask generation and high scan speed. The structure and theory of this spectrometer are analyzed. The 63-order Hadarmard-S matrix and mask are designed. The mask is dynamically generated by program of MOEMS blazed gratings. The spectrum is in agreement with that measured by Shimadzu spectrometer in experiments. It has a wavelength range between 900 and 1 700 nm, spectral resolution of 19 nm, single scan time of 2.4 s, SNR of 44. 67 ： 1, optical path of 70 mm× 130 mm, and weight under 1 kg. It can meet the requirement of real time detection and portable application.
Recent studies of transform image enhancement
Aghagolzadeh, Sabzali; Ersoy, Okan K.
1992-06-01
Blockwise transform image enhancement techniques are discussed. It is shown that the best transforms for transform image coding, namely, the scrambled real discrete Fourier transform, the discrete cosine transform, and the discrete cosine-III transform, are also the best for image enhancement. Three techniques of enhancement discussed in detail are alpha- rooting, modified unsharp masking, and filtering motivated by the human visual system response (HVS). With proper modifications, it is observed that unsharp masking and HVS- motivated filtering without nonlinearities are basically equivalent. Block effects are completely removed by using an overlap-save technique in addition to the best transform.
Applying GG-Convex Function to Hermite-Hadamard Inequalities Involving Hadamard Fractional Integrals
Directory of Open Access Journals (Sweden)
Zhi Zhang
2014-01-01
Full Text Available By virtue of fractional integral identities, incomplete beta function, useful series, and inequalities, we apply the concept of GG-convex function to derive new type Hermite-Hadamard inequalities involving Hadamard fractional integrals. Finally, some applications to special means of real numbers are demonstrated.
Hadamard Transform Time-of-Flight Spectroscopy
2010-01-26
system presented in Figure 13 were determined by direct fitting of the initial rates data to the Michaelis - Menten equation. Excellent agreement is...trypsin at pH 8.5. The dashed red line in the figure shows a best fit to the Michaelis - Menten equation for the data collected. The error bars in
Wavelet transform based watermark for digital images.
Xia, X G; Boncelet, C; Arce, G
1998-12-07
In this paper, we introduce a new multiresolution watermarking method for digital images. The method is based on the discrete wavelet transform (DWT). Pseudo-random codes are added to the large coefficients at the high and middle frequency bands of the DWT of an image. It is shown that this method is more robust to proposed methods to some common image distortions, such as the wavelet transform based image compression, image rescaling/stretching and image halftoning. Moreover, the method is hierarchical.
Combined Sparsifying Transforms for Compressive Image Fusion
Directory of Open Access Journals (Sweden)
ZHAO, L.
2013-11-01
Full Text Available In this paper, we present a new compressive image fusion method based on combined sparsifying transforms. First, the framework of compressive image fusion is introduced briefly. Then, combined sparsifying transforms are presented to enhance the sparsity of images. Finally, a reconstruction algorithm based on the nonlinear conjugate gradient is presented to get the fused image. The simulations demonstrate that by using the combined sparsifying transforms better results can be achieved in terms of both the subjective visual effect and the objective evaluation indexes than using only a single sparsifying transform for compressive image fusion.
Automated image enhancement using power law transformations
Indian Academy of Sciences (India)
S P Vimal; P K Thiruvikraman
2012-12-01
We propose a scheme for automating power law transformations which are used for image enhancement. The scheme we propose does not require the user to choose the exponent in the power law transformation. This method works well for images having poor contrast, especially to those images in which the peaks corresponding to the background and the foreground are not widely separated.
The IHS Transformations Based Image Fusion
Al-Wassai, Firouz Abdullah; Al-Zuky, Ali A
2011-01-01
The IHS sharpening technique is one of the most commonly used techniques for sharpening. Different transformations have been developed to transfer a color image from the RGB space to the IHS space. Through literature, it appears that, various scientists proposed alternative IHS transformations and many papers have reported good results whereas others show bad ones as will as not those obtained which the formula of IHS transformation were used. In addition to that, many papers show different formulas of transformation matrix such as IHS transformation. This leads to confusion what is the exact formula of the IHS transformation?. Therefore, the main purpose of this work is to explore different IHS transformation techniques and experiment it as IHS based image fusion. The image fusion performance was evaluated, in this study, using various methods to estimate the quality and degree of information improvement of a fused image quantitatively.
Learning doubly sparse transforms for images.
Ravishankar, Saiprasad; Bresler, Yoram
2013-12-01
The sparsity of images in a transform domain or dictionary has been exploited in many applications in image processing. For example, analytical sparsifying transforms, such as wavelets and discrete cosine transform (DCT), have been extensively used in compression standards. Recently, synthesis sparsifying dictionaries that are directly adapted to the data have become popular especially in applications such as image denoising. Following up on our recent research, where we introduced the idea of learning square sparsifying transforms, we propose here novel problem formulations for learning doubly sparse transforms for signals or image patches. These transforms are a product of a fixed, fast analytic transform such as the DCT, and an adaptive matrix constrained to be sparse. Such transforms can be learnt, stored, and implemented efficiently. We show the superior promise of our learnt transforms as compared with analytical sparsifying transforms such as the DCT for image representation. We also show promising performance in image denoising that compares favorably with approaches involving learnt synthesis dictionaries such as the K-SVD algorithm. The proposed approach is also much faster than K-SVD denoising.
MULTIWAVELET TRANSFORM IN COMPRESSION OF MEDICAL IMAGES
Directory of Open Access Journals (Sweden)
V. K. Sudha
2013-05-01
Full Text Available This paper analyses performance of multiwavelets - a variant of wavelet transform on compression of medical images. To do so, two processes namely, transformation for decorrelation and encoding are done. In transformation stage medical images are subjected to multiwavelet transform using multiwavelets such as Geronimo- Hardin-Massopust, Chui Lian, Cardinal 2 Balanced (Cardbal2 and orthogonal symmetric/antsymmetric multiwavelet (SA4. Set partitioned Embedded Block Coder is used as a common platform for encoding the transformed coefficients. Peak Signal to noise ratio, bit rate and Structural Similarity Index are used as metrics for performance analysis. For experiment we have used various medical images such as Magnetic Resonance Image, Computed Tomography and X-ray images.
Color image encryption based on gyrator transform and Arnold transform
Sui, Liansheng; Gao, Bo
2013-06-01
A color image encryption scheme using gyrator transform and Arnold transform is proposed, which has two security levels. In the first level, the color image is separated into three components: red, green and blue, which are normalized and scrambled using the Arnold transform. The green component is combined with the first random phase mask and transformed to an interim using the gyrator transform. The first random phase mask is generated with the sum of the blue component and a logistic map. Similarly, the red component is combined with the second random phase mask and transformed to three-channel-related data. The second random phase mask is generated with the sum of the phase of the interim and an asymmetrical tent map. In the second level, the three-channel-related data are scrambled again and combined with the third random phase mask generated with the sum of the previous chaotic maps, and then encrypted into a gray scale ciphertext. The encryption result has stationary white noise distribution and camouflage property to some extent. In the process of encryption and decryption, the rotation angle of gyrator transform, the iterative numbers of Arnold transform, the parameters of the chaotic map and generated accompanied phase function serve as encryption keys, and hence enhance the security of the system. Simulation results and security analysis are presented to confirm the security, validity and feasibility of the proposed scheme.
Slantlet Transform for Multispectral Image Fusion
Directory of Open Access Journals (Sweden)
Adnan H.M. Al-Helali
2009-01-01
Full Text Available Problem statement: Image fusion is a process by which multispectral and panchromatic images, or some of their features, are combined together to form a high spatial/high spectral resolutions image. The successful fusion of images acquired from different modalities or instruments is a great importance issue in remote sensing applications. Approach: A new method of image fusion was introduced. It was based on a hybrid transform, which is an extension of Ridgelet transform. It used the slantlet transform instead of wavelet transform in the final steps of Ridgelet transform. The slantlet transform was an orthogonal discrete wavelet transform with two zero moments and with improved time localization. Results: Since edges and noise played fundamental role in image understanding, this hybrid transform was proved to be good way to enhance the edges and reduce the noise. Conclusion: The proposed method of fusion presented richer information in spatial and spectral domains simultaneously as well as it had reached an optimum fusion result.
Image Matching by Using Fuzzy Transforms
Directory of Open Access Journals (Sweden)
Ferdinando Di Martino
2013-01-01
Full Text Available We apply the concept of Fuzzy Transform (for short, F-transform for improving the results of the image matching based on the Greatest Eigen Fuzzy Set (for short, GEFS with respect to max-min composition and the Smallest Eigen Fuzzy Set (for short, SEFS with respect to min-max composition already studied in the literature. The direct F-transform of an image can be compared with the direct F-transform of a sample image to be matched and we use suitable indexes to measure the grade of similarity between the two images. We make our experiments on the image dataset extracted from the well-known Prima Project View Sphere Database, comparing the results obtained with this method with that one based on the GEFS and SEFS. Other experiments are performed on frames of videos extracted from the Ohio State University dataset.
Mathematical transforms and image compression: A review
Directory of Open Access Journals (Sweden)
Satish K. Singh
2010-07-01
Full Text Available It is well known that images, often used in a variety of computer and other scientific and engineering applications, are difficult to store and transmit due to their sizes. One possible solution to overcome this problem is to use an efficient digital image compression technique where an image is viewed as a matrix and then the operations are performed on the matrix. All the contemporary digital image compression systems use various mathematical transforms for compression. The compression performance is closely related to the performance by these mathematical transforms in terms of energy compaction and spatial frequency isolation by exploiting inter-pixel redundancies present in the image data. Through this paper, a comprehensive literature survey has been carried out and the pros and cons of various transform-based image compression models have also been discussed.
Image fusion algorithm using nonsubsampled contourlet transform
Xiao, Yang; Cao, Zhiguo; Wang, Kai; Xu, Zhengxiang
2007-11-01
In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for image fusion. Each image from different sensors could be decomposed into a low frequency image and a series of high frequency images of different directions by multi-scale NSCT. For low and high frequency images, they are fused based on local-contrast enhancement and definition respectively. Finally, fused image is reconstructed from low and high frequency fused images. Experiment demonstrates that NSCT could preserve edge significantly and the fusion rule based on region segmentation performances well in local-contrast enhancement.
Image Enhancement Based on Brushlet Transform
Institute of Scientific and Technical Information of China (English)
HUXinwei; YANGXin
2005-01-01
In this paper, the method of image enhancement based on Brushlet transform is discussed. One favorable characteristic of brushlet is the good localization in both time and frequency domain so it allows treatment for a particular range of data. Furthermore, brushlet can be implemented with faster speed than wavelet transform while preserving the same quality thanks for folding technique and Fast Fourier transform (FFT). The innovation ofthis paper is that after first transforming the image from raw data into brushlet coefficients, we will apply a new nonlinear algorithm to the discrete coefficients. The algorithm is described by a curve which takes the main function of image enhancement. Compared to classical methods, the method presented in this paper not only improves the calculation speed but also provides a high-quality image.
Hadamard States and Two-dimensional Gravity
Salehi, H
2001-01-01
We have used a two-dimensional analog of the Hadamard state-condition to study the local constraints on the two-point function of a linear quantum field conformally coupled to a two-dimensional gravitational background. We develop a dynamical model in which the determination of the state of the quantum field is essentially related to the determination of a conformal frame. A particular conformal frame is then introduced in which a two-dimensional gravitational equation is established.
Distance transform for automatic dermatologic images composition
Grana, C.; Pellacani, G.; Seidenari, S.; Cucchiara, R.
2006-03-01
In this paper we focus on the problem of automatically registering dermatological images, because even if different products are available, most of them share the problem of a limited field of view on the skin. A possible solution is then the composition of multiple takes of the same lesion with digital software, such as that for panorama images creation. In this work, to perform an automatic selection of matching points the Harris Corner Detector is used, and to cope with outlier couples we employed the RANSAC method. Projective mapping is then used to match the two images. Given a set of correspondence points, Singular Value Decomposition was used to compute the transform parameters. At this point the two images need to be blended together. One initial assumption is often implicitly made: the aim is to merge two rectangular images. But when merging occurs between more than two images iteratively, this assumption will fail. To cope with differently shaped images, we employed the Distance Transform and provided a weighted merging of images. Different tests were conducted with dermatological images, both with standard rectangular frame and with not typical shapes, as for example a ring due to the objective and lens selection. The successive composition of different circular images with other blending functions, such as the Hat function, doesn't correctly get rid of the border and residuals of the circular mask are still visible. By applying Distance Transform blending, the result produced is insensitive of the outer shape of the image.
Image registration using adaptive polar transform.
Matungka, Rittavee; Zheng, Yuan F; Ewing, Robert L
2009-10-01
Image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration, or analysis. Recently, researchers have introduced image registration techniques using the log-polar transform (LPT) for its rotation and scale invariant properties. However, it suffers from nonuniform sampling which makes it not suitable for applications in which the registered images are altered or occluded. Inspired by LPT, this paper presents a new registration algorithm that addresses the problems of the conventional LPT while maintaining the robustness to scale and rotation. We introduce a novel adaptive polar transform (APT) technique that evenly and effectively samples the image in the Cartesian coordinates. Combining APT with an innovative projection transform along with a matching mechanism, the proposed method yields less computational load and more accurate registration than that of the conventional LPT. Translation between the registered images is recovered with the new search scheme using Gabor feature extraction to accelerate the localization procedure. Moreover an image comparison scheme is proposed for locating the area where the image pairs differ. Experiments on real images demonstrate the effectiveness and robustness of the proposed approach for registering images that are subjected to occlusion and alteration in addition to scale, rotation, and translation.
Generalized Hermite-Hadamard type inequalities involving fractional integral operators.
Set, Erhan; Noor, Muhammed Aslam; Awan, Muhammed Uzair; Gözpinar, Abdurrahman
2017-01-01
In this article, a new general integral identity involving generalized fractional integral operators is established. With the help of this identity new Hermite-Hadamard type inequalities are obtained for functions whose absolute values of derivatives are convex. As a consequence, the main results of this paper generalize the existing Hermite-Hadamard type inequalities involving the Riemann-Liouville fractional integral.
Connecting unextendible maximally entangled base with partial Hadamard matrices
Wang, Yan-Ling; Li, Mao-Sheng; Fei, Shao-Ming; Zheng, Zhu-Jun
2017-03-01
We study the unextendible maximally entangled bases (UMEB) in Cdbigotimes Cd and connect the problem to the partial Hadamard matrices. We show that for a given special UMEB in Cdbigotimes Cd, there is a partial Hadamard matrix which cannot be extended to a Hadamard matrix in Cd. As a corollary, any (d-1)× d partial Hadamard matrix can be extended to a Hadamard matrix, which answers a conjecture about d=5. We obtain that for any d there is a UMEB except for d=p {or} 2p, where p≡ 3mod 4 and p is a prime. The existence of different kinds of constructions of UMEBs in C^{nd}bigotimes C^{nd} for any nin N and d=3× 5 × 7 is also discussed.
Block Hadamard measurement matrix with arbitrary dimension in compressed sensing
Liu, Shaoqiang; Yan, Xiaoyan; Fan, Xiaoping; Li, Fei; Xu, Wen
2017-01-01
As Hadamard measurement matrix cannot be used for compressing signals with dimension of a non-integral power-of-2, this paper proposes a construction method of block Hadamard measurement matrix with arbitrary dimension. According to the dimension N of signals to be measured, firstly, construct a set of Hadamard sub matrixes with different dimensions and make the sum of these dimensions equals to N. Then, arrange the Hadamard sub matrixes in a certain order to form a block diagonal matrix. Finally, take the former M rows of the block diagonal matrix as the measurement matrix. The proposed measurement matrix which retains the orthogonality of Hadamard matrix and sparsity of block diagonal matrix has highly sparse structure, simple hardware implements and general applicability. Simulation results show that the performance of our measurement matrix is better than Gaussian matrix, Logistic chaotic matrix, and Toeplitz matrix.
Image Compression Using Discrete Wavelet Transform
Directory of Open Access Journals (Sweden)
Mohammad Mozammel Hoque Chowdhury
2012-07-01
Full Text Available Image compression is a key technology in transmission and storage of digital images because of vast data associated with them. This research suggests a new image compression scheme with pruning proposal based on discrete wavelet transformation (DWT. The effectiveness of the algorithm has been justified over some real images, and the performance of the algorithm has been compared with other common compression standards. The algorithm has been implemented using Visual C++ and tested on a Pentium Core 2 Duo 2.1 GHz PC with 1 GB RAM. Experimental results demonstrate that the proposed technique provides sufficient high compression ratios compared to other compression techniques.
Image edge detection based on beamlet transform
Institute of Scientific and Technical Information of China (English)
Li Jing; Huang Peikang; Wang Xiaohu; Pan Xudong
2009-01-01
Combining beamlet transform with steerable filters, a new edge detection method based on line gra-dient is proposed. Compared with operators based on point local properties, the edge-detection results with this method achieve higher SNR and position accuracy, and are quite helpful for image registration, object identification, etc. Some edge-detection experiments on optical and SAR images that demonstrate the significant improvement over classical edge operators are also presented. Moreover, the template matching result based on edge information of optical reference image and SAR image also proves the validity of this method.
Almost Hadamard matrices: general theory and examples
Banica, Teodor; Zyczkowski, Karol
2012-01-01
We develop a general theory of "almost Hadamard matrices". These are by definition the matrices $H\\in M_N(\\mathbb R)$ having the property that $U=H/\\sqrt{N}$ is orthogonal, and is a local maximum of the 1-norm on O(N). Our study includes a detailed discussion of the circulant case ($H_{ij}=\\gamma_{j-i}$) and of the two-entry case ($H_{ij}\\in\\{x,y\\}$), with the construction of several families of examples, and some 1-norm computations.
Numerical Quadratures for Hadamard Hypersingular Integrals
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In this paper, we develop Gaussian quadrature formulas for the Hadamard finite part integrals. In our formulas, the classical orthogonal polynomials such as Legendre and Chebyshev polynomials are used to approximate the density function f(x) so that the Gaussian quadrature formulas have degree n - 1. The error estimates of the formulas are obtained. It is found from the numerical examples that the convergence rate and the accuracy of the approximation results are satisfactory. Moreover, the rate and the accuracy can be improved by choosing appropriate weight functions.
Compressive imaging using fast transform coding
Thompson, Andrew; Calderbank, Robert
2016-10-01
We propose deterministic sampling strategies for compressive imaging based on Delsarte-Goethals frames. We show that these sampling strategies result in multi-scale measurements which can be related to the 2D Haar wavelet transform. We demonstrate the effectiveness of our proposed strategies through numerical experiments.
Optical image encryption using multilevel Arnold transform and noninterferometric imaging
Chen, Wen; Chen, Xudong
2011-11-01
Information security has attracted much current attention due to the rapid development of modern technologies, such as computer and internet. We propose a novel method for optical image encryption using multilevel Arnold transform and rotatable-phase-mask noninterferometric imaging. An optical image encryption scheme is developed in the gyrator transform domain, and one phase-only mask (i.e., phase grating) is rotated and updated during image encryption. For the decryption, an iterative retrieval algorithm is proposed to extract high-quality plaintexts. Conventional encoding methods (such as digital holography) have been proven vulnerably to the attacks, and the proposed optical encoding scheme can effectively eliminate security deficiency and significantly enhance cryptosystem security. The proposed strategy based on the rotatable phase-only mask can provide a new alternative for data/image encryption in the noninterferometric imaging.
Generalized graph states based on Hadamard matrices
Energy Technology Data Exchange (ETDEWEB)
Cui, Shawn X. [Department of Mathematics, University of California, Santa Barbara, California 93106 (United States); Yu, Nengkun [Institute for Quantum Computing, University of Waterloo, Waterloo, Ontario N2L 3G1 (Canada); Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario N1G 2W1 (Canada); UTS-AMSS Joint Research Laboratory for Quantum Computation and Quantum Information Processing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Zeng, Bei [Institute for Quantum Computing, University of Waterloo, Waterloo, Ontario N2L 3G1 (Canada); Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario N1G 2W1 (Canada); Canadian Institute for Advanced Research, Toronto, Ontario M5G 1Z8 (Canada)
2015-07-15
Graph states are widely used in quantum information theory, including entanglement theory, quantum error correction, and one-way quantum computing. Graph states have a nice structure related to a certain graph, which is given by either a stabilizer group or an encoding circuit, both can be directly given by the graph. To generalize graph states, whose stabilizer groups are abelian subgroups of the Pauli group, one approach taken is to study non-abelian stabilizers. In this work, we propose to generalize graph states based on the encoding circuit, which is completely determined by the graph and a Hadamard matrix. We study the entanglement structures of these generalized graph states and show that they are all maximally mixed locally. We also explore the relationship between the equivalence of Hadamard matrices and local equivalence of the corresponding generalized graph states. This leads to a natural generalization of the Pauli (X, Z) pairs, which characterizes the local symmetries of these generalized graph states. Our approach is also naturally generalized to construct graph quantum codes which are beyond stabilizer codes.
Digital image transformation and rectification of spacecraft and radar images
Wu, S. S. C.
1985-01-01
The application of digital processing techniques to spacecraft television pictures and radar images is discussed. The use of digital rectification to produce contour maps from spacecraft pictures is described; images with azimuth and elevation angles are converted into point-perspective frame pictures. The digital correction of the slant angle of radar images to ground scale is examined. The development of orthophoto and stereoscopic shaded relief maps from digital terrain and digital image data is analyzed. Digital image transformations and rectifications are utilized on Viking Orbiter and Lander pictures of Mars.
Laser Field Imaging Through Fourier Transform Heterodyne
Energy Technology Data Exchange (ETDEWEB)
Cooke, B.J.; Laubscher, B.E.; Olivas, N.L.; Galbraith, A.E.; Strauss, C.E.; Grubler, A.C.
1999-04-05
The authors present a detection process capable of directly imaging the transverse amplitude, phase, and Doppler shift of coherent electromagnetic fields. Based on coherent detection principles governing conventional heterodyned RADAR/LADAR systems, Fourier Transform Heterodyne incorporates transverse spatial encoding of the reference local oscillator for image capture. Appropriate selection of spatial encoding functions allows image retrieval by way of classic Fourier manipulations. Of practical interest: (1) imaging may be accomplished with a single element detector/sensor requiring no additional scanning or moving components, (2) as detection is governed by heterodyne principles, near quantum limited performance is achievable, (3) a wide variety of appropriate spatial encoding functions exist that may be adaptively configured in real-time for applications requiring optimal detection, and (4) the concept is general with the applicable electromagnetic spectrum encompassing the RF through optical.
Quantum Discrete Cosine Transform for Image Compression
Pang, C Y; Guo, G C; Pang, Chao Yang; Zhou, Zheng Wei; Guo, Guang Can
2006-01-01
Discrete Cosine Transform (DCT) is very important in image compression. Classical 1-D DCT and 2-D DCT has time complexity O(NlogN) and O(N²logN) respectively. This paper presents a quantum DCT iteration, and constructs a quantum 1-D and 2-D DCT algorithm for image compression by using the iteration. The presented 1-D and 2-D DCT has time complexity O(sqrt(N)) and O(N) respectively. In addition, the method presented in this paper generalizes the famous Grover's algorithm to solve complex unstructured search problem.
Electro-optic imaging Fourier transform spectrometer
Chao, Tien-Hsin (Inventor); Znod, Hanying (Inventor)
2009-01-01
An Electro-Optic Imaging Fourier Transform Spectrometer (EOIFTS) for Hyperspectral Imaging is described. The EOIFTS includes an input polarizer, an output polarizer, and a plurality of birefringent phase elements. The relative orientations of the polarizers and birefringent phase elements can be changed mechanically or via a controller, using ferroelectric liquid crystals, to substantially measure the spectral Fourier components of light propagating through the EIOFTS. When achromatic switches are used as an integral part of the birefringent phase elements, the EIOFTS becomes suitable for broadband applications, with over 1 micron infrared bandwidth.
Hadamard states for quantum Abelian duality
Benini, Marco; Dappiaggi, Claudio
2016-01-01
Abelian duality is realized naturally by combining differential cohomology and locally covariant quantum field theory. This leads to a C$^*$-algebra of observables, which encompasses the simultaneous discretization of both magnetic and electric fluxes. We discuss the assignment of physically well-behaved states to such algebra and the properties of the associated GNS triple. We show that the algebra of observables factorizes as a suitable tensor product of three C$^*$-algebras: the first factor encodes dynamical information, while the other two capture topological data corresponding to electric and magnetic fluxes. On the former factor we exhibit a state whose two-point correlation function has the same singular structure of a Hadamard state. Specifying suitable counterparts also on the topological factors we obtain a state for the full theory, providing ultimately a unitary implementation of Abelian duality.
Distributed Storage Codes through Hadamard Designs
Papailiopoulos, Dimitris S
2011-01-01
In distributed storage systems that employ erasure coding, the issue of minimizing the total {\\it repair bandwidth} required to exactly regenerate a storage node after a failure arises. This repair bandwidth depends on the structure of the storage code and the repair strategies used to restore the lost data. Minimizing it requires that undesired data during a repair align in the smallest possible spaces, using the concept of interference alignment (IA). Here, a points-on-a-lattice representation of the symbol extension IA of Cadambe {\\it et al.} provides cues to perfect IA instances which we combine with fundamental properties of Hadamard matrices to construct a new storage code with favorable repair properties. Specifically, we build an explicit $(k+2,k)$ storage code over $\\mathbb{GF}(3)$, whose single systematic node failures can be repaired with bandwidth that matches exactly the theoretical minimum. Moreover, the repair of single parity node failures generates at most the same repair bandwidth as any sys...
Embedding cocyclic D-optimal designs in cocyclic Hadamard matrices
Álvarez, Víctor; Frau, María-Dolores; Gudiel, Félix
2012-01-01
In this paper a method for embedding cocyclic submatrices with ``large'' determinants of orders 2t in certain cocyclic Hadamard matrices of orders 4t is described (t an odd integer). If these determinants attain the largest possible value, we are embedding D-optimal designs. Applications to the pivot values that appear when Gaussian Elimination with complete pivoting is performed on these cocyclic Hadamard matrices are studied.
Parallel image registration method for snapshot Fourier transform imaging spectroscopy
Zhang, Yu; Zhu, Shuaishuai; Lin, Jie; Zhu, Feijia; Jin, Peng
2017-08-01
A fast and precise registration method for multi-image snapshot Fourier transform imaging spectroscopy is proposed. This method accomplishes registration of an image array using the positional relationship between homologous points in the subimages, which are obtained offline by preregistration. Through the preregistration process, the registration problem is converted to the problem of using a registration matrix to interpolate subimages. Therefore, the hardware interpolation of graphics processing unit (GPU) texture memory, which has speed advantages for its parallel computing, can be used to significantly enhance computational efficiency. Compared to a central processing unit, GPU performance showed ˜27 times acceleration in registration efficiency.
A Fractional Random Wavelet Transform Based Image Steganography
G.K. Rajini; RAMACHANDRA REDDY G.
2015-01-01
This study presents a novel technique for image steganography based on Fractional Random Wavelet Transform. This transform has all the features of wavelet transform with randomness and fractional order built into it. The randomness and fractional order in the algorithm brings in robustness and additional layers of security to steganography. The stegano image generated by this algorithm contains both cover image and hidden image and image degradation is not observed in it. The steganography st...
Applying Quaternion Fourier Transforms for Enhancing Color Images
Directory of Open Access Journals (Sweden)
M.I. Khalil
2012-03-01
Full Text Available The Fourier transforms play a critical role in a broad range of image processing applications, including enhancement, analysis, restoration, and compression. Until recently, it was common to use the conventional methods to deal with colored images. These methods are based on RGB decomposition of the colored image by separating it into three separate scalar images and computing the Fourier transforms of these images separately. The computing of the Hypercomplex 2D Fourier transform of a color image as a whole unit has only recently been realized. This paper is concerned with frequency domain noise reduction of color images using quaternion Fourier transforms. The approach is based on obtaining quaternion Fourier transform of the color image and applying the Gaussian filter to it in the frequency domain. The filtered image is then obtained by calculating the inverse quaternion Fourier transforms.
Subband/Transform MATLAB Functions For Processing Images
Glover, D.
1995-01-01
SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.
Subband/Transform MATLAB Functions For Processing Images
Glover, D.
1995-01-01
SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.
Imaging Analysis by Means of Fractional Fourier Transform
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Starting from the diffraction imaging process,we have discussed the relationship between optical imaging system and fractional Fourier transform, and proposed a specific system which can form an inverse amplified image of input function.
Repair Optimal Erasure Codes through Hadamard Designs
Papailiopoulos, Dimitris S; Cadambe, Viveck R
2011-01-01
In distributed storage systems that employ erasure coding, the issue of minimizing the total {\\it communication} required to exactly rebuild a storage node after a failure arises. This repair bandwidth depends on the structure of the storage code and the repair strategies used to restore the lost data. Designing high-rate maximum-distance separable (MDS) codes that achieve the optimum repair communication has been a well-known open problem. In this work, we use Hadamard matrices to construct the first explicit 2-parity MDS storage code with optimal repair properties for all single node failures, including the parities. Our construction relies on a novel method of achieving perfect interference alignment over finite fields with a finite file size, or number of extensions. We generalize this construction to design $m$-parity MDS codes that achieve the optimum repair communication for single systematic node failures and show that there is an interesting connection between our $m$-parity codes and the systematic-...
Hadamard states from light-like hypersurfaces
Dappiaggi, Claudio; Pinamonti, Nicola
2017-01-01
This book provides a rather self-contained survey of the construction of Hadamard states for scalar field theories in a large class of notable spacetimes, possessing a (conformal) light-like boundary. The first two sections focus on explaining a few introductory aspects of this topic and on providing the relevant geometric background material. The notions of asymptotically flat spacetimes and of expanding universes with a cosmological horizon are analysed in detail, devoting special attention to the characterization of asymptotic symmetries. In the central part of the book, the quantization of a real scalar field theory on such class of backgrounds is discussed within the framework of algebraic quantum field theory. Subsequently it is explained how it is possible to encode the information of the observables of the theory in a second, ancillary counterpart, which is built directly on the conformal (null) boundary. This procedure, dubbed bulk-to-boundary correspondence, has the net advantage of allowing t...
Perceptual image coding with discrete cosine transform
Tan, Ee-Leng
2015-01-01
This book first introduces classic as well as recent computational models for just-noticeable-difference (JND) applications. Since the discrete cosine transform (DCT) is applied in many image and video standards (JPEG, MPEG-1/2/4, H.261/3), the book also includes a comprehensive survey of computational models for JND that are based on DCT. The visual factors used in these computational models are reviewed in detail. Further, an extensive comparative analysis of these models using quantitative and qualitative performance criteria is presented, which compares the noise shaping performance of these models with subjective evaluation and the accuracy between the estimated JND thresholds and subjective evaluation. There are many surveys available on computational models for JND; however, these surveys seldom compare the performance of computational models that are based on DCT. The authors’ survey of the computational models and their in-depth review of the visual factors used in them will help readers understand...
Image Steganography using Hybrid Edge Detector and Ridgelet Transform
S.UMA MAHESWARI; D. Jude Hemanth
2015-01-01
Steganography is the art of hiding high sensitive information in digital image, text, video, and audio. In this paper, authors have proposed a frequency domain steganography method operating in the Ridgelet transform. Authors engage the advantage of ridgelet transform, which represents the digital image with straight edges. In the embedding phase, the proposed hybrid edge detector acts as a preprocessing step to obtain the edge image from the cover image, then the edge image is partitioned in...
Hadamard-type fractional differential equations, inclusions and inequalities
Ahmad, Bashir; Ntouyas, Sotiris K; Tariboon, Jessada
2017-01-01
This book focuses on the recent development of fractional differential equations, integro-differential equations, and inclusions and inequalities involving the Hadamard derivative and integral. Through a comprehensive study based in part on their recent research, the authors address the issues related to initial and boundary value problems involving Hadamard type differential equations and inclusions as well as their functional counterparts. The book covers fundamental concepts of multivalued analysis and introduces a new class of mixed initial value problems involving the Hadamard derivative and Riemann-Liouville fractional integrals. In later chapters, the authors discuss nonlinear Langevin equations as well as coupled systems of Langevin equations with fractional integral conditions. Focused and thorough, this book is a useful resource for readers and researchers interested in the area of fractional calculus.
A Workshop on Algebraic Design Theory and Hadamard Matrices
2015-01-01
This volume develops the depth and breadth of the mathematics underlying the construction and analysis of Hadamard matrices and their use in the construction of combinatorial designs. At the same time, it pursues current research in their numerous applications in security and cryptography, quantum information, and communications. Bridges among diverse mathematical threads and extensive applications make this an invaluable source for understanding both the current state of the art and future directions. The existence of Hadamard matrices remains one of the most challenging open questions in combinatorics. Substantial progress on their existence has resulted from advances in algebraic design theory using deep connections with linear algebra, abstract algebra, finite geometry, number theory, and combinatorics. Hadamard matrices arise in a very diverse set of applications. Starting with applications in experimental design theory and the theory of error-correcting codes, they have found unexpected and important ap...
Matrix transformation of digital image and its periodicity
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
The periodicity of a general matrix modular transformation is discussed, and a simple proof of a sufficient and necessary condition that a matrix transformation has periodicity is given. Using a block matrix method, the higher dimensional transformation and its inverse are studied, and a simple algorithm for calculating their periods is put forward. The security of n-dimensional Amold transformation and its inverse is also discussed. The results show that the two transformations are applicable in scrambling and recovering images.
Singularity-preserving image interpolation using wavelet transform extrema extrapolation
Zhai, Guangtao; Zhang, Yang; Zheng, Xiaoshi
2003-09-01
One common task of image interpolation is to enhance the resolution of the image, which means to magnify the image without loss in its clarity. Traditional methods often assume that the original images are smooth enough so as to possess continues derivatives, which tend to blur the edges of the interpolated image. A novel fast image interpolation algorithm based on wavelet transform and multi-resolution analysis is proposed in this paper. It uses interpolation and extrapolation polynomial to estimate the higher resolution informatoin of the image and generate a new sub-band of wavelet transform coefficients to get processed image with shaper edges and preserved singularities.
Image encryption with chaotic map and Arnold transform in the gyrator transform domains
Sang, Jun; Luo, Hongling; Zhao, Jun; Alam, Mohammad S.; Cai, Bin
2017-05-01
An image encryption method combing chaotic map and Arnold transform in the gyrator transform domains was proposed. Firstly, the original secret image is XOR-ed with a random binary sequence generated by a logistic map. Then, the gyrator transform is performed. Finally, the amplitude and phase of the gyrator transform are permutated by Arnold transform. The decryption procedure is the inverse operation of encryption. The secret keys used in the proposed method include the control parameter and the initial value of the logistic map, the rotation angle of the gyrator transform, and the transform number of the Arnold transform. Therefore, the key space is large, while the key data volume is small. The numerical simulation was conducted to demonstrate the effectiveness of the proposed method and the security analysis was performed in terms of the histogram of the encrypted image, the sensitiveness to the secret keys, decryption upon ciphertext loss, and resistance to the chosen-plaintext attack.
Compressive passive millimeter wave imager
Gopalsami, Nachappa; Liao, Shaolin; Elmer, Thomas W; Koehl, Eugene R; Heifetz, Alexander; Raptis, Apostolos C
2015-01-27
A compressive scanning approach for millimeter wave imaging and sensing. A Hadamard mask is positioned to receive millimeter waves from an object to be imaged. A subset of the full set of Hadamard acquisitions is sampled. The subset is used to reconstruct an image representing the object.
Rectification of aerial images using piecewise linear transformation
Liew, L. H.; Lee, B. Y.; Wang, Y. C.; Cheah, W. S.
2014-02-01
Aerial images are widely used in various activities by providing visual records. This type of remotely sensed image is helpful in generating digital maps, managing ecology, monitoring crop growth and region surveying. Such images could provide insight into areas of interest that have lower altitude, particularly in regions where optical satellite imaging is prevented due to cloudiness. Aerial images captured using a non-metric cameras contain real details of the images as well as unexpected distortions. Distortions would affect the actual length, direction and shape of objects in the images. There are many sources that could cause distortions such as lens, earth curvature, topographic relief and the attitude of the aircraft that is used to carry the camera. These distortions occur differently, collectively and irregularly in the entire image. Image rectification is an essential image pre-processing step to eliminate or at least reduce the effect of distortions. In this paper, a non-parametric approach with piecewise linear transformation is investigated in rectifying distorted aerial images. The non-parametric approach requires a set of corresponding control points obtained from a reference image and a distorted image. The corresponding control points are then applied with piecewise linear transformation as geometric transformation. Piecewise linear transformation divides the image into regions by triangulation. Different linear transformations are employed separately to triangular regions instead of using a single transformation as the rectification model for the entire image. The result of rectification is evaluated using total root mean square error (RMSE). Experiments show that piecewise linear transformation could assist in improving the limitation of using global transformation to rectify images.
Moment-Based Method to Estimate Image Affine Transform
Institute of Scientific and Technical Information of China (English)
FENG Guo-rui; JIANG Ling-ge
2005-01-01
The estimation of affine transform is a crucial problem in the image recognition field. This paper resorted to some invariant properties under translation, rotation and scaling, and proposed a simple method to estimate the affine transform kernel of the two-dimensional gray image. Maps, applying to the original, produce some correlative points that can accurately reflect the affine transform feature of the image. Furthermore, unknown variables existing in the kernel of the transform are calculated. The whole scheme only refers to one-order moment,therefore, it has very good stability.
Period of Arnold transformation and its application in image scrambling
Institute of Scientific and Technical Information of China (English)
LI Bing; XU Jia-wei
2005-01-01
With the security problem of image information as the background, some more properties of the period of Arnold transformation of two-dimension were studied by means of introducing a integer sequence. Some new resuits are obtained. Two interesting conjectures on the period of Arnold transformation are given. When making digital images scrambling by Arnold transformation, it is important to know the period of the transformation for the image. As the application of the theory, a new method for computing the periods at last are proposed.
MUTUAL IMAGE TRANSFORMATION ALGORITHMS FOR VISUAL INFORMATION PROCESSING AND RETRIEVAL
Directory of Open Access Journals (Sweden)
G. A. Kukharev
2017-01-01
Full Text Available Subject of Research. The paper deals with methods and algorithms for mutual transformation of related pairs of images in order to enhance the capabilities of cross-modal multimedia retrieval (CMMR technologies. We have thoroughly studied the problem of mutual transformation of face images of various kinds (e.g. photos and drawn pictures. This problem is widely represented in practice. Research is this area is based on existing datasets. The algorithms we have proposed in this paper can be applied to arbitrary pairs of related images due to the unified mathematical specification. Method. We have presented three image transformation algorithms. The first one is based on principal component analysis and Karhunen-Loève transform (1DPCA/1DKLT. Unlike the existing solution, it does not use the training set during the transformation process. The second algorithm assumes generation of an image population. The third algorithm performs the transformation based on two-dimensional principal component analysis and Karhunen-Loève transform (2DPCA/2DKLT. Main Results. The experiments on image transformation and population generation have revealed the main features of each algorithm. The first algorithm allows construction of an accurate and stable model of transition between two given sets of images. The second algorithm can be used to add new images to existing bases and the third algorithm is capable of performing the transformation outside the training dataset. Practical Relevance. Taking into account the qualities of the proposed algorithms, we have provided recommendations concerning their application. Possible scenarios include construction of a transition model for related pairs of images, mutual transformation of the images inside and outside the dataset as well as population generation in order to increase representativeness of existing datasets. Thus, the proposed algorithms can be used to improve reliability of face recognition performed on images
On the numerical calculation of Hadamard finite-part integrals
Directory of Open Access Journals (Sweden)
Ezio Venturino
1998-10-01
Full Text Available In this paper we consider a simple method for calculating integrals possessing strong singularities, to be interpreted in the Hadamard finite-part sense. We partition the original interval of integration and then integrate over the subintervals by using suitably modified low-order Gaussian-type quadratures. Convergence is shown under suitable assumptions and numerical evidence supports the theoretical findings.
Scalar field Hadamard renormalisation in $AdS_{n}$
Kent, Carl
2013-01-01
We outline an analytic method for computing the renormalised vacuum expectation value of the quadratic fluctuations and stress-energy tensor associated with a quantised scalar field propagating on $AdS_{n}$. Explicit results have been obtained using Hadamard renormalisation in the case of a massive neutral scalar field with arbitrary coupling to the curvature, for $n=2$ to $n=11$ inclusive.
Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS): Imaging and Tracking Capability
Zhou, D. K.; Larar, A. M.; Liu, Xu; Reisse, R. A.; Smith, W. L.; Revercomb, H. E.; Bingham, G. E.; Zollinger, L. J.; Tansock, J. J.; Huppi, Ronald J.
2007-01-01
The geosynchronous-imaging Fourier transform spectrometer (GIFTS) engineering demonstration unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. It measures the infrared spectrum in two spectral bands (14.6 to 8.8 microns, 6.0 to 4.4 microns) using two 128 128 detector arrays with a spectral resolution of 0.57/cm with a scan duration of approx. 11 seconds. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of such data to scan desired regions of the globe, from which atmospheric status, cloud parameters, wind field profiles, and other derived products can be retrieved. The GIFTS EDU provides a flexible and accurate testbed for the new challenges of the emerging hyperspectral era. The EDU ground-based measurement experiment, held in Logan, Utah during September 2006, demonstrated its extensive capabilities and potential for geosynchronous and other applications (e.g., Earth observing environmental measurements). This paper addresses the experiment objectives and overall performance of the sensor system with a focus on the GIFTS EDU imaging capability and proof of the GIFTS measurement concept.
Hybrid Coding of Image Sequences by Using Wavelet Transform
Directory of Open Access Journals (Sweden)
M. Surin
2000-04-01
Full Text Available In this paper, a new method of hybrid coding of image sequences byusing wavelet transform is proposed. The basic MPEG scheme with DCT hasbeen modificated in sense of replacement DCT by wavelet transform. Inthe proposed method, the motion estimation and compensation are usedfor motion vectors calculation and different frame between currentframe and compensated frame is coded by using wavelet transform. Someexperimental results of image sequences coding by using a new methodare presented.
Building of one-way Hadamard gate for squeezed coherent states
Podoshvedov, Sergey A.
2013-01-01
We present an optical scheme to conditionally generate even or odd squeezed superpositions of coherent states (SSCSs). The optical setup consists of an unbalanced beam splitter whose transmittance tends to unity, and additional balanced beam splitters and photodetectors in auxiliary modes. Squeezed coherent states with different amplitudes are the input states in the optical scheme. The single-qubit operations are probabilistic and employ two- and three-photon subtractions from initial beams as the driving force. Generation of the even or odd SSCSs is observed in a wide diapason of values of used parameters. We consider a possibility to realize a one-way Hadamard gate for the squeezed coherent states when the base states are transformed into superposition states. States approximating the output states of a Hadamard gate with high fidelity can be realized by imposing restrictions on the values of used parameters. Higher-order subtractions from input beams are necessary to generate the SSCSs with larger amplitudes and higher fidelities. The problem is resolved in a Wigner representation to take into account imperfections of the optical devices.
2D image compression using concurrent wavelet transform
Talukder, Kamrul Hasan; Harada, Koichi
2011-10-01
In the recent years wavelet transform (WT) has been widely used for image compression. As WT is a sequential process, much time is required to transform data. Here a new approach has been presented where the transformation process is executed concurrently. As a result the procedure runs first and the time of transformation is reduced. Multiple threads are used for row and column transformation and the communication among threads has been managed effectively. Thus, the transformation time has been reduced significantly. The proposed system provides better compression ratio and PSNR value with lower time complexity.
Multispectral image pansharpening based on the contourlet transform
Energy Technology Data Exchange (ETDEWEB)
Amro, Israa; Mateos, Javier, E-mail: iamro@correo.ugr.e, E-mail: jmd@decsai.ugr.e [Departamento de Ciencias de la Computacion e I.A., Universidad de Granada, 18071 Granada (Spain)
2010-02-01
Pansharpening is a technique that fuses the information of a low resolution multispectral image (MS) and a high resolution panchromatic image (PAN), usually remote sensing images, to provide a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets based algorithms. Recently, the contourlet transform has been proposed. This transform combines the advantages of the wavelets transform with a more efficient directional information representation. In this paper we propose a new pansharpening method based on contourlets, compare with its wavelet counterpart and assess its performance numerically and visually.
Retina-like sensor image coordinates transformation and display
Cao, Fengmei; Cao, Nan; Bai, Tingzhu; Song, Shengyu
2015-03-01
For a new kind of retina-like senor camera, the image acquisition, coordinates transformation and interpolation need to be realized. Both of the coordinates transformation and interpolation are computed in polar coordinate due to the sensor's particular pixels distribution. The image interpolation is based on sub-pixel interpolation and its relative weights are got in polar coordinates. The hardware platform is composed of retina-like senor camera, image grabber and PC. Combined the MIL and OpenCV library, the software program is composed in VC++ on VS 2010. Experience results show that the system can realizes the real-time image acquisition, coordinate transformation and interpolation.
A Fractional Random Wavelet Transform Based Image Steganography
Directory of Open Access Journals (Sweden)
G.K. Rajini
2015-04-01
Full Text Available This study presents a novel technique for image steganography based on Fractional Random Wavelet Transform. This transform has all the features of wavelet transform with randomness and fractional order built into it. The randomness and fractional order in the algorithm brings in robustness and additional layers of security to steganography. The stegano image generated by this algorithm contains both cover image and hidden image and image degradation is not observed in it. The steganography strives for security and pay load capacity. The performance measures like PeakSignal to Noise Ratio (PSNR, Mean Square Error (MSE, Structural Similarity Index Measure (SSIM and Universal Image Quality Index (UIQI are computed. In this proposed algorithm, imperceptibility and robustness are verified and it can sustain geometric transformations like rotation, scaling and translation and is compared with some of the existing algorithms. The numerical results show the effectiveness of the proposed algorithm.
Terahertz digital holography image denoising using stationary wavelet transform
Cui, Shan-Shan; Li, Qi; Chen, Guanghao
2015-04-01
Terahertz (THz) holography is a frontier technology in terahertz imaging field. However, reconstructed images of holograms are inherently affected by speckle noise, on account of the coherent nature of light scattering. Stationary wavelet transform (SWT) is an effective tool in speckle noise removal. In this paper, two algorithms for despeckling SAR images are implemented to THz images based on SWT, which are threshold estimation and smoothing operation respectively. Denoised images are then quantitatively assessed by speckle index. Experimental results show that the stationary wavelet transform has superior denoising performance and image detail preservation to discrete wavelet transform. In terms of the threshold estimation, high levels of decomposing are needed for better denoising result. The smoothing operation combined with stationary wavelet transform manifests the optimal denoising effect at single decomposition level, with 5×5 average filtering.
Hadamard Transform Time-of-Flight Mass Spectrometry
2010-01-26
determined by direct fitting of the initial rates data to the Michaelis - Menten equation. Excellent agreement is shown amongst the values indicating that...of VGVKVR by trypsin at pH 8.5. The dashed red line in the figure shows a best fit to the Michaelis - Menten equation for the data collected. The
Dynamic Fractal Transform with Applications to Image Data Compression
Institute of Scientific and Technical Information of China (English)
王舟; 余英林
1997-01-01
A recent trend in computer graphics and image processing is to use Iterated Function System(IFS)to generate and describe both man-made graphics and natural images.Jacquin was the first to propose a fully automation gray scale image compression algorithm which is referred to as a typical static fractal transform based algorithm in this paper.By using this algorithm,an image can be condensely described as a fractal transform operator which is the combination of a set of reactal mappings.When the fractal transform operator is iteratedly applied to any initial image,a unique attractro(reconstructed image)can be achieved.In this paper,a dynamic fractal transform is presented which is a modification of the static transform.Instea of being fixed,the dynamic transform operator varies in each decoder iteration,thus differs from static transform operators.The new transform has advantages in improving coding efficiency and shows better convergence for the deocder.
Image Denoising using Adaptive Thresholding in Framelet Transform Domain
Directory of Open Access Journals (Sweden)
R.Vidhya
2012-09-01
Full Text Available Noise will be unavoidable during image acquisition process and denosing is an essential step to improve the image quality. Image denoising involves the manipulation of the image data to produce a visually high quality image. Finding efficient image denoising methods is still valid challenge in image processing. Wavelet denoising attempts to remove the noise present in the imagery while preserving the image characteristics, regardless of its frequency content. Many of the wavelet based denoising algorithms use DWT (Discrete Wavelet Transform in the decomposition stage which is suffering from shift variance. To overcome this, in this paper we proposed the denoising method which uses Framelet transform to decompose the image and performed shrinkage operation to eliminate the noise .The framework describes a comparative study of different thresholding techniques for image denoising in Framelet transform domain. The idea is to transform the data into the Framelet basis, example shrinkage followed by the inverse transform. In this work different shrinkage rules such as universal shrink(US,Visu shrink (VS, Minmax shrink(MS, Sure shrink(SS , Bayes shrink(BS and Normal shrink(NS were incorporated . Results based on different noise such as Gausssian noise, Poission noise , Salt and pepper noise and Speckle noise at (??=10,20 performed in this paper and peak signal to noise ratio (PSNR and Structural similarity index measure(SSIM as a measure of the quality of denoising was performed.
X-Ray image denoising with directional support value transform
Zheng, S.; Hendriks, E.A.; Lei, B.; Hao, W.
2009-01-01
Under the support vector machine framework, the support value analysis-based image fusion has been studied, where the salient features of the original images are represented by their support values. The support value transform (SVT)-based image fusion approach have demonstrated some advantages over
Quaternion Fourier transforms for signal and image processing
Ell, Todd A; Sangwine, Stephen J
2014-01-01
Based on updates to signal and image processing technology made in the last two decades, this text examines the most recent research results pertaining to Quaternion Fourier Transforms. QFT is a central component of processing color images and complex valued signals. The book's attention to mathematical concepts, imaging applications, and Matlab compatibility render it an irreplaceable resource for students, scientists, researchers, and engineers.
Image denoising with the dual-tree complex wavelet transform
Yaseen, Alauldeen S.; Pavlova, Olga N.; Pavlov, Alexey N.; Hramov, Alexander E.
2016-04-01
The purpose of this study is to compare image denoising techniques based on real and complex wavelet-transforms. Possibilities provided by the classical discrete wavelet transform (DWT) with hard and soft thresholding are considered, and influences of the wavelet basis and image resizing are discussed. The quality of image denoising for the standard 2-D DWT and the dual-tree complex wavelet transform (DT-CWT) is studied. It is shown that DT-CWT outperforms 2-D DWT at the appropriate selection of the threshold level.
ISAR Imaging Using Fourier and Wavelet Transforms
2007-12-01
for i=1:45; Imf2=SFABS(1,:,i); Image2=[Image2;Imf2]; end 60 LIST OF REFERENCES [1] George Arfken . Mathematical Methods for Physicists, volume Third...arcs that can be approximated as lines. Consequently, the imaging method is mathematically the same as that used in Inverse Synthetic Aperture Radar...and why it’s not a good approach to our problem. We investigate the results using this time-frequency methods , creating images using synthetic data
Hybrid discrete cosine transform-discrete wavelet transform for progressive image compression
Boukaache, Abdennour; Doghmane, Noureddine
2012-01-01
In this paper, we propose an image compression algorithm that uses a hybrid transform and an improved modified set partitioning in hierarchical trees (SPIHT) coding algorithm. The proposed transform uses the subband discrete cosine transform to decompose the image into multiresolution subbands where the discrete wavelet transform is then used to code the low frequencies. Then, we use the SPIHT coding method to code the transformed coefficients. For the SPIHT algorithm, we have proposed a method to reduce the distortion introduced by the SPIHT technique between the original and reconstructed images. The obtained results show the efficiency of the proposed hybrid method in terms of peak signal-to-noise ratio and visual quality.
Transformation invariant image indexing and retrieval for image databases
Gevers, Th.; Smeulders, A.W.M.
1994-01-01
This paper presents a novel design of an image database system which supports storage, indexing and retrieval of images by content. The image retrieval methodology is based on the observation that images can be discriminated by the presence of image objects and their spatial relations. Images in the
Performance Evaluation of Image Fusion Based on Discrete Cosine Transform
Directory of Open Access Journals (Sweden)
Ramkrishna Patil
2013-05-01
Full Text Available Discrete cosine transform (DCT is used for fusion of two different images and for image compression. Image fusion deals with creating an image by combining portions from other images to obtain an image in which all of the objects are in focus. Two multi focus images are used for image fusion. Different fusion algorithms are used and their performance is evaluated using evaluation metrics such as PSNR, SSIM, Spatial Frequency, Quality Index, Structural Content, Mean Absolute Error. Fusion performance is not good while using the algorithms with block size less than 64x64 and also the block size of 512x512. Contrast, amplitude and energy based image fusion algorithms performed well. The fused images are comparable with the reference image. Only the image size is considered but blurring percentage is not considered. These algorithms are very simple and might be suitable for real time applications
Compressive optical image watermarking using joint Fresnel transform correlator architecture
Li, Jun; Zhong, Ting; Dai, Xiaofang; Yang, Chanxia; Li, Rong; Tang, Zhilie
2017-02-01
A new optical image watermarking technique based on compressive sensing using joint Fresnel transform correlator architecture has been presented. A secret scene or image is first embedded into a host image to perform optical image watermarking by use of joint Fresnel transform correlator architecture. Then, the watermarked image is compressed to much smaller signal data using single-pixel compressive holographic imaging in optical domain. At the received terminal, the watermarked image is reconstructed well via compressive sensing theory and a specified holographic reconstruction algorithm. The preliminary numerical simulations show that it is effective and suitable for optical image security transmission in the coming absolutely optical network for the reason of the completely optical implementation and largely decreased holograms data volume.
Electro-Optic Imaging Fourier Transform Spectral Polarimeter Project
National Aeronautics and Space Administration — Boulder Nonlinear Systems, Inc. (BNS) proposes to develop an Electro-Optic Imaging Fourier Transform Spectral Polarimeter (E-O IFTSP). The polarimetric system is...
A Secret Image Sharing Method Using Integer Wavelet Transform
Directory of Open Access Journals (Sweden)
Li Ching-Chung
2007-01-01
Full Text Available A new image sharing method, based on the reversible integer-to-integer (ITI wavelet transform and Shamir's threshold scheme is presented, that provides highly compact shadows for real-time progressive transmission. This method, working in the wavelet domain, processes the transform coefficients in each subband, divides each of the resulting combination coefficients into shadows, and allows recovery of the complete secret image by using any or more shadows . We take advantages of properties of the wavelet transform multiresolution representation, such as coefficient magnitude decay and excellent energy compaction, to design combination procedures for the transform coefficients and processing sequences in wavelet subbands such that small shadows for real-time progressive transmission are obtained. Experimental results demonstrate that the proposed method yields small shadow images and has the capabilities of real-time progressive transmission and perfect reconstruction of secret images.
Discrete Orthogonal Transforms and Neural Networks for Image Interpolation
Directory of Open Access Journals (Sweden)
J. Polec
1999-09-01
Full Text Available In this contribution we present transform and neural network approaches to the interpolation of images. From transform point of view, the principles from [1] are modified for 1st and 2nd order interpolation. We present several new interpolation discrete orthogonal transforms. From neural network point of view, we present interpolation possibilities of multilayer perceptrons. We use various configurations of neural networks for 1st and 2nd order interpolation. The results are compared by means of tables.
Topology-Preserving Rigid Transformation of 2D Digital Images.
Ngo, Phuc; Passat, Nicolas; Kenmochi, Yukiko; Talbot, Hugues
2014-02-01
We provide conditions under which 2D digital images preserve their topological properties under rigid transformations. We consider the two most common digital topology models, namely dual adjacency and well-composedness. This paper leads to the proposal of optimal preprocessing strategies that ensure the topological invariance of images under arbitrary rigid transformations. These results and methods are proved to be valid for various kinds of images (binary, gray-level, label), thus providing generic and efficient tools, which can be used in particular in the context of image registration and warping.
Trade-off capacities of the quantum Hadamard channels
Bradler, Kamil; Touchette, Dave; Wilde, Mark M
2010-01-01
Coding theorems in quantum Shannon theory express the ultimate rates at which a sender can transmit information over a noisy quantum channel. More often than not, the known formulas expressing these transmission rates are intractable, requiring an optimization over an infinite number of uses of the channel. Researchers have rarely found quantum channels with a tractable classical or quantum capacity, but when such a finding occurs, it demonstrates a complete understanding of that channel's capabilities for transmitting classical or quantum information. Here, we show that the three-dimensional capacity region for entanglement-assisted transmission of classical and quantum information is tractable for the Hadamard class of channels. Examples of Hadamard channels include generalized dephasing channels, cloning channels, and the Unruh channel. The generalized dephasing channels and the cloning channels are natural processes that occur in quantum systems through the loss of quantum coherence or stimulated emission...
Vélez-Rábago, Rodrigo; Solorza-Calderón, Selene; Jordan-Aramburo, Adina
2016-12-01
This work presents an image pattern recognition system invariant to translation, scale and rotation. The system uses the Fourier transform to achieve the invariance to translation and the analytical Forier-Mellin transform for the invariance to scale and rotation. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.
Denoising CT Images using wavelet transform
Directory of Open Access Journals (Sweden)
Lubna Gabralla
2015-05-01
Full Text Available Image denoising is one of the most significant tasks especially in medical image processing, where the original images are of poor quality due the noises and artifacts introduces by the acquisition systems. In this paper, we propose a new image denoising scheme by modifying the wavelet coefficients using soft-thresholding method, we present a comparative study of different wavelet denoising techniques for CT images and we discuss the obtained results. The denoising process rejects noise by thresholding in the wavelet domain. The performance is evaluated using Peak Signal-to-Noise Ratio (PSNR and Mean Squared Error (MSE. Finally, Gaussian filter provides better PSNR and lower MSE values. Hence, we conclude that this filter is an efficient one for preprocessing medical images.
Hu, Yiqun; Xie, Xinwen; Liu, Xingbin; Zhou, Nanrun
2017-07-01
A novel quantum multi-image encryption algorithm based on iteration Arnold transform with parameters and image correlation decomposition is proposed, and a quantum realization of the iteration Arnold transform with parameters is designed. The corresponding low frequency images are obtained by performing 2-D discrete wavelet transform on each image respectively, and then the corresponding low frequency images are spliced randomly to one image. The new image is scrambled by the iteration Arnold transform with parameters, and the gray-level information of the scrambled image is encoded by quantum image correlation decomposition. For the encryption algorithm, the keys are iterative times, added parameters, classical binary and orthonormal basis states. The key space, the security and the computational complexity are analyzed, and all of the analyses show that the proposed encryption algorithm could encrypt multiple images simultaneously with lower computational complexity compared with its classical counterparts.
Spindle extraction method for ISAR image based on Radon transform
Wei, Xia; Zheng, Sheng; Zeng, Xiangyun; Zhu, Daoyuan; Xu, Gaogui
2015-12-01
In this paper, a method of spindle extraction of target in inverse synthetic aperture radar (ISAR) image is proposed which depends on Radon Transform. Firstly, utilizing Radon Transform to detect all straight lines which are collinear with these line segments in image. Then, using Sobel operator to detect image contour. Finally, finding all intersections of each straight line and image contour, the two intersections which have maximum distance between them is the two ends of this line segment and the longest line segment of all line segments is spindle of target. According to the proposed spindle extraction method, one hundred simulated ISAR images which are respectively rotated 0 degrees, 10 degrees, 20 degrees, 30 degrees and 40 degrees in counterclockwise are used to do experiment and the proposed method and the detection results are more close to the real spindle of target than the method based on Hough Transform .
Image compression algorithm using wavelet transform
Cadena, Luis; Cadena, Franklin; Simonov, Konstantin; Zotin, Alexander; Okhotnikov, Grigory
2016-09-01
Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the variation of the compression level of the studied image has been obtained. It is shown that the compression ratio in the range of 8-10 is optimal for environmental monitoring. Under these conditions the compression level is in the range of 1.7 - 4.2, depending on the type of images. It is shown that the algorithm used is more convenient and has more advantages than Winrar. The Haar wavelet algorithm has improved the method of signal and image processing.
Remote sensing image denoising by using discrete multiwavelet transform techniques
Wang, Haihui; Wang, Jun; Zhang, Jian
2006-01-01
We present a new method by using GHM discrete multiwavelet transform in image denoising on this paper. The developments in wavelet theory have given rise to the wavelet thresholding method, for extracting a signal from noisy data. The method of signal denoising via wavelet thresholding was popularized. Multiwavelets have recently been introduced and they offer simultaneous orthogonality, symmetry and short support. This property makes multiwavelets more suitable for various image processing applications, especially denoising. It is based on thresholding of multiwavelet coefficients arising from the standard scalar orthogonal wavelet transform. It takes into account the covariance structure of the transform. Denoising of images via thresholding of the multiwavelet coefficients result from preprocessing and the discrete multiwavelet transform can be carried out by treating the output in this paper. The form of the threshold is carefully formulated and is the key to the excellent results obtained in the extensive numerical simulations of image denoising. We apply the multiwavelet-based to remote sensing image denoising. Multiwavelet transform technique is rather a new method, and it has a big advantage over the other techniques that it less distorts spectral characteristics of the image denoising. The experimental results show that multiwavelet based image denoising schemes outperform wavelet based method both subjectively and objectively.
Automatic Image Registration Algorithm Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
LIU Qiong; NI Guo-qiang
2006-01-01
An automatic image registration approach based on wavelet transform is proposed. This proposed method utilizes multiscale wavelet transform to extract feature points. A coarse-to-fine feature matching method is utilized in the feature matching phase. A two-way matching method based on cross-correlation to get candidate point pairs and a fine matching based on support strength combine to form the matching algorithm. At last, based on an affine transformation model, the parameters are iteratively refined by using the least-squares estimation approach. Experimental results have verified that the proposed algorithm can realize automatic registration of various kinds of images rapidly and effectively.
Optical Image Encryption with Simplified Fractional Hartley Transform
Institute of Scientific and Technical Information of China (English)
LI Xin-Xin; ZHAO Dao-Mu
2008-01-01
We present a new method for image encryption on the basis of simplified fractional Hartley transform (SFRHT). SFRHT is a real transform as Hartley transform (HT) and furthermore, superior to HT in virtue of the advantage that it can also append fractional orders as additional keys for the purpose of improving the system security to some extent. With this method, one can encrypt an image with an intensity-only medium such as a photographic film or a CCD camera by spatially incoherent or coherent illumination. The optical realization is then proposed and computer simulations are also performed to verify the feasibility of this method.
Energy Technology Data Exchange (ETDEWEB)
Rodriguez G, A.; Bowtell, R.; Mansfield, P. [Area de Procesamiento Digital de Senales e Imagenes Biomedicas. Universidad Autonoma Metropolitana Iztapalapa. Mexico D.F. 09340 Mexico (Mexico)
1998-12-31
Velocity maps were studied combining Doyle and Mansfield method (1986) with each of the following transforms: Fourier, window Fourier and wavelet (Mexican hat). Continuous wavelet transform was compared against the two Fourier transform to determine which technique is best suited to study blood maps generated by Half Fourier Echo-Planar Imaging. Coefficient images were calculated and plots of the pixel intensity variation are presented. Finally, contour maps are shown to visualize the behavior of the blood flow in the cardiac chambers for the wavelet technique. (Author)
Multi-sensor image fusion using discrete wavelet frame transform
Institute of Scientific and Technical Information of China (English)
Zhenhua Li(李振华); Zhongliang Jing(敬忠良); Shaoyuan Sun(孙韶媛)
2004-01-01
An algorithm is presented for multi-sensor image fusion using discrete wavelet frame transform (DWFT).The source images to be fused are firstly decomposed by DWFT. The fusion process is the combining of the source coefficients. Before the image fusion process, image segmentation is performed on each source image in order to obtain the region representation of each source image. For each source image, the salience of each region in its region representation is calculated. By overlapping all these region representations of all the source images, we produce a shared region representation to label all the input images. The fusion process is guided by these region representations. Region match measure of the source images is calculated for each region in the shared region representation. When fusing the similar regions, weighted averaging mode is performed; otherwise selection mode is performed. Experimental results using real data show that the proposed algorithm outperforms the traditional pyramid transform based or discrete wavelet transform (DWT) based algorithms in multi-sensor image fusion.
Image fusion with nonsubsampled contourlet transform and sparse representation
Wang, Jun; Peng, Jinye; Feng, Xiaoyi; He, Guiqing; Wu, Jun; Yan, Kun
2013-10-01
Image fusion combines several images of the same scene into a fused image, which contains all important information. Multiscale transform and sparse representation can solve this problem effectively. However, due to the limited number of dictionary atoms, it is difficult to provide an accurate description for image details in the sparse representation-based image fusion method, and it needs a great deal of calculations. In addition, for the multiscale transform-based method, the low-pass subband coefficients are so hard to represent sparsely that they cannot extract significant features from images. In this paper, a nonsubsampled contourlet transform (NSCT) and sparse representation-based image fusion method (NSCTSR) is proposed. NSCT is used to perform a multiscale decomposition of source images to express the details of images, and we present a dictionary learning scheme in NSCT domain, based on which we can represent low-frequency information of the image sparsely in order to extract the salient features of images. Furthermore, it can reduce the calculation cost of the fusion algorithm with sparse representation by the way of nonoverlapping blocking. The experimental results show that the proposed method outperforms both the fusion method based on single sparse representation and multiscale decompositon.
Optical asymmetric image encryption using gyrator wavelet transform
Mehra, Isha; Nishchal, Naveen K.
2015-11-01
In this paper, we propose a new optical information processing tool termed as gyrator wavelet transform to secure a fully phase image, based on amplitude- and phase-truncation approach. The gyrator wavelet transform constitutes four basic parameters; gyrator transform order, type and level of mother wavelet, and position of different frequency bands. These parameters are used as encryption keys in addition to the random phase codes to the optical cryptosystem. This tool has also been applied for simultaneous compression and encryption of an image. The system's performance and its sensitivity to the encryption parameters, such as, gyrator transform order, and robustness has also been analyzed. It is expected that this tool will not only update current optical security systems, but may also shed some light on future developments. The computer simulation results demonstrate the abilities of the gyrator wavelet transform as an effective tool, which can be used in various optical information processing applications, including image encryption, and image compression. Also this tool can be applied for securing the color image, multispectral, and three-dimensional images.
Robust Image Hashing Using Radon Transform and Invariant Features
Directory of Open Access Journals (Sweden)
Y.L. Liu
2016-09-01
Full Text Available A robust image hashing method based on radon transform and invariant features is proposed for image authentication, image retrieval, and image detection. Specifically, an input image is firstly converted into a counterpart with a normalized size. Then the invariant centroid algorithm is applied to obtain the invariant feature point and the surrounding circular area, and the radon transform is employed to acquire the mapping coefficient matrix of the area. Finally, the hashing sequence is generated by combining the feature vectors and the invariant moments calculated from the coefficient matrix. Experimental results show that this method not only can resist against the normal image processing operations, but also some geometric distortions. Comparisons of receiver operating characteristic (ROC curve indicate that the proposed method outperforms some existing methods in classification between perceptual robustness and discrimination.
Image Steganography using Hybrid Edge Detector and Ridgelet Transform
Directory of Open Access Journals (Sweden)
S. Uma Maheswari
2015-05-01
Full Text Available Steganography is the art of hiding high sensitive information in digital image, text, video, and audio. In this paper, authors have proposed a frequency domain steganography method operating in the Ridgelet transform. Authors engage the advantage of ridgelet transform, which represents the digital image with straight edges. In the embedding phase, the proposed hybrid edge detector acts as a preprocessing step to obtain the edge image from the cover image, then the edge image is partitioned into several blocks to operate with straight edges and Ridgelet transform is applied to each block. Then, the most significant gradient vectors (or significant edges are selected to embed the secret data. The proposed method has shown the advantages of imperceptibility of the stego image is increased because the secret data is hidden in the significant gradient vector. Authors employed the hybrid edge detector to obtain the edge image, which increases the embedding capacity. Experimental results demonstrates that peak signal-to-noise (PSNR ratio of stego image generated by this method versus the cover image is guaranteed to be above 49 dB. PSNR is much higher than that of all data hiding techniques reported in the literature.Defence Science Journal, Vol. 65, No. 3, May 2015, pp.214-219, DOI: http://dx.doi.org/10.14429/dsj.65.7871
Electro-Optical Imaging Fourier-Transform Spectrometer
Chao, Tien-Hsin; Zhou, Hanying
2006-01-01
An electro-optical (E-O) imaging Fourier-transform spectrometer (IFTS), now under development, is a prototype of improved imaging spectrometers to be used for hyperspectral imaging, especially in the infrared spectral region. Unlike both imaging and non-imaging traditional Fourier-transform spectrometers, the E-O IFTS does not contain any moving parts. Elimination of the moving parts and the associated actuator mechanisms and supporting structures would increase reliability while enabling reductions in size and mass, relative to traditional Fourier-transform spectrometers that offer equivalent capabilities. Elimination of moving parts would also eliminate the vibrations caused by the motions of those parts. Figure 1 schematically depicts a traditional Fourier-transform spectrometer, wherein a critical time delay is varied by translating one the mirrors of a Michelson interferometer. The time-dependent optical output is a periodic representation of the input spectrum. Data characterizing the input spectrum are generated through fast-Fourier-transform (FFT) post-processing of the output in conjunction with the varying time delay.
Predictive depth coding of wavelet transformed images
Lehtinen, Joonas
1999-10-01
In this paper, a new prediction based method, predictive depth coding, for lossy wavelet image compression is presented. It compresses a wavelet pyramid composition by predicting the number of significant bits in each wavelet coefficient quantized by the universal scalar quantization and then by coding the prediction error with arithmetic coding. The adaptively found linear prediction context covers spatial neighbors of the coefficient to be predicted and the corresponding coefficients on lower scale and in the different orientation pyramids. In addition to the number of significant bits, the sign and the bits of non-zero coefficients are coded. The compression method is tested with a standard set of images and the results are compared with SFQ, SPIHT, EZW and context based algorithms. Even though the algorithm is very simple and it does not require any extra memory, the compression results are relatively good.
Robust Image Watermarking using Fractional Sinc Transformation
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Almas Abbasi
2016-09-01
Full Text Available The increased utilization of internet in sharing and dissemination of digital data makes it is very difficult to maintain copyright and ownership of data. Digital watermarking offers a method for authentication and copyright protection. Digital image watermarking is an important technique for the multimedia content authentication and copyright protection. This paper present a watermarking algorithm making a balance between imperceptibility and robustness based on fractional calculus and also a domain has constructed using fractional Sinc function (FSc. The FSc model the signal as polynomial for watermark embedding. Watermark is embedded in all the coefficients of the image. Cross correlation method based on Neyman-Pearson is used for watermark detection. Moreover fraction rotation expression has constructed to achieve rotation. Experimental results confirmed the proposed technique has good robustness and outperformed another technique in imperceptibility. Furthermore the proposed method enables blind watermark detection where the original image is not required during the watermark detection and thus making it more practical than non-blind watermarking techniques.
View Transformation Based on a Single Outdoor Image
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Shi-Hui Zhang
2013-05-01
Full Text Available Abstract An automatic approach for view transformation based on a single outdoor image is proposed in this paper. First, the hierarchical segmentation method is conducted to segment an outdoor image into several meaningful regions and each region is labelled as sky, ground or standing object. Then, different methods are used to estimate each region's depth according to its label. After that, the obtained depth information is utilized to create a new view image after any rotation, translation and pitch. Finally, the image inpainting work for the missing colour region is accomplished using its neighbour's colour. Extensive experiments show the proposed approach not only improves the accuracy of view transformation, but also performs well even for images with occlusion phenomena.
Remotely sensed image compression based on wavelet transform
Kim, Seong W.; Lee, Heung K.; Kim, Kyung S.; Choi, Soon D.
1995-01-01
In this paper, we present an image compression algorithm that is capable of significantly reducing the vast amount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet transform to remove the spatial redundancy. the transformed images are then encoded by Hilbert-curve scanning and run-length-encoding, followed by Huffman coding. We also present the performance of the proposed algorithm with the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by PSNR (peak signal to noise ratio) and classification capability.
Hermite-Hadamard and Simpson Type Inequalities for Differentiable P-GA-Functions
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İmdat İşcan
2014-01-01
Full Text Available The author introduces the concept of the P-GA-functions, gives Hermite-Hadamard's inequalities for P-GA-functions, and defines a new identity. By using this identity, the author obtains new estimates on generalization of Hadamard and Simpson type inequalities for P-GA-functions. Some applications to special means of real numbers are also given.
SAR image formation with azimuth interpolation after azimuth transform
Doerry; Armin W. , Martin; Grant D. , Holzrichter; Michael W.
2008-07-08
Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.
Sparse Representation through Multi-Resolution Transform for Image Coding
Dr. P. Arockia Jansi Rani
2013-01-01
Having a compact basis is useful both for compression and fordesigning efficient numerical algorithms. In this paper, a newimage coding scheme using a multi-resolution transform knownas Bandelet Transform that provides an optimally compact basisfor images by exploring their directional characteristics isproposed. As this process results in a sparse representation,Zero Vector Pruning is applied in-order to extract the non-zerocoefficients. Further the geometric interpixel redundanciespresent i...
MIXED SCHEME FOR IMAGE EDGE DETECTION BASED ON WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
Xie Hongmei; Yu Bianzhang; Zhao Jian
2004-01-01
A mixed scheme based on Wavelet Transformation (WT) is proposed for image edge detection. The scheme combines the wavelet transform and traditional Sobel and LoG (Laplacian of Gaussian) operator edge-detection algorithms. The precise theory analysis is given to show that the wavelet transformation has an advantage for signal processing. Simulation results show that the new scheme is better than only using the Sobel or LoG methods. Complexity analysis is also given and the conclusion is acceptable, therefore the proposed scheme is effective for edge detection.
The Discrete Fourier Transform on hexagonal remote sensing image
Li, Yalu; Ben, Jin; Wang, Rui; Du, Lingyu
2016-11-01
Global discrete grid system will subdivide the earth recursively to form a multi-resolution grid hierarchy with no Overlap and seamless which help build global uniform spatial reference datum and multi-source data processing mode which takes the position as the object and in the aspect of data structure supports the organization, process and analysis of the remote sensing big data. This paper adopts the base transform to realize the mutual transformation of square pixel and hexagonal pixel. This paper designs the corresponding discrete Fourier transform algorithm for any lattice. Finally, the paper show the result of the DFT of the remote sensing image of the hexagonal pixel.
Image compression for dermatology
Cookson, John P.; Sneiderman, Charles; Colaianni, Joseph; Hood, Antoinette F.
1990-07-01
Color 35mm photographic slides are commonly used in dermatology for education, and patient records. An electronic storage and retrieval system for digitized slide images may offer some advantages such as preservation and random access. We have integrated a system based on a personal computer (PC) for digital imaging of 35mm slides that depict dermatologic conditions. Such systems require significant resources to accommodate the large image files involved. Methods to reduce storage requirements and access time through image compression are therefore of interest. This paper contains an evaluation of one such compression method that uses the Hadamard transform implemented on a PC-resident graphics processor. Image quality is assessed by determining the effect of compression on the performance of an image feature recognition task.
Human Body Image Edge Detection Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
李勇; 付小莉
2003-01-01
Human dresses are different in thousands way.Human body image signals have big noise, a poor light and shade contrast and a narrow range of gray gradation distribution. The application of a traditional grads method or gray method to detect human body image edges can't obtain satisfactory results because of false detections and missed detections. According to tte peculiarity of human body image, dyadic wavelet transform of cubic spline is successfully applied to detect the face and profile edges of human body image and Mallat algorithm is used in the wavelet decomposition in this paper.
High Capacity Secure Image Steganography Based on Contourlet Transform
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Kolsoom Shahryari
2013-09-01
Full Text Available In this paper we propose an image steganography technique which embeds secret data without making explicit modifications to the image. The proposed method simultaneously provides both imperceptibility and undetectability. We decompose image by contourlet transform and determine nonsmooth regions. Embedding data in these regions cause less degradation in image quality. Contourlet sub-bands are divided into 3×3 blocks. Central coefficient of each block is considered for embedding if they belong to edgy regions. Experiments show that this method can achieve high embedding capacity while remains undetectable by Farid's universal steganalysis technique.
Multi-band Image Registration Method Based on Fourier Transform
Institute of Scientific and Technical Information of China (English)
庹红娅; 刘允才
2004-01-01
This paper presented a registration method based on Fourier transform for multi-band images which is involved in translation and small rotation. Although different band images differ a lot in the intensity and features,they contain certain common information which we can exploit. A model was given that the multi-band images have linear correlations under the least-square sense. It is proved that the coefficients have no effect on the registration progress if two images have linear correlations. Finally, the steps of the registration method were proposed. The experiments show that the model is reasonable and the results are satisfying.
Image encryption using P-Fibonacci transform and decomposition
Zhou, Yicong; Panetta, Karen; Agaian, Sos; Chen, C. L. Philip
2012-03-01
Image encryption is an effective method to protect images or videos by transferring them into unrecognizable formats for different security purposes. To improve the security level of bit-plane decomposition based encryption approaches, this paper introduces a new image encryption algorithm by using a combination of parametric bit-plane decomposition along with bit-plane shuffling and resizing, pixel scrambling and data mapping. The algorithm utilizes the Fibonacci P-code for image bit-plane decomposition and the 2D P-Fibonacci transform for image encryption because they are parameter dependent. Any new or existing method can be used for shuffling the order of the bit-planes. Simulation analysis and comparisons are provided to demonstrate the algorithm's performance for image encryption. Security analysis shows the algorithm's ability against several common attacks. The algorithm can be used to encrypt images, biometrics and videos.
Oriented wavelet transform for image compression and denoising.
Chappelier, Vivien; Guillemot, Christine
2006-10-01
In this paper, we introduce a new transform for image processing, based on wavelets and the lifting paradigm. The lifting steps of a unidimensional wavelet are applied along a local orientation defined on a quincunx sampling grid. To maximize energy compaction, the orientation minimizing the prediction error is chosen adaptively. A fine-grained multiscale analysis is provided by iterating the decomposition on the low-frequency band. In the context of image compression, the multiresolution orientation map is coded using a quad tree. The rate allocation between the orientation map and wavelet coefficients is jointly optimized in a rate-distortion sense. For image denoising, a Markov model is used to extract the orientations from the noisy image. As long as the map is sufficiently homogeneous, interesting properties of the original wavelet are preserved such as regularity and orthogonality. Perfect reconstruction is ensured by the reversibility of the lifting scheme. The mutual information between the wavelet coefficients is studied and compared to the one observed with a separable wavelet transform. The rate-distortion performance of this new transform is evaluated for image coding using state-of-the-art subband coders. Its performance in a denoising application is also assessed against the performance obtained with other transforms or denoising methods.
Method of Infrared Image Enhancement Based on Stationary Wavelet Transform
Institute of Scientific and Technical Information of China (English)
QI Fei; LI Yan-jun; ZHANG Ke
2008-01-01
Aiming at the problem, i.e. infrared images own the characters of bad contrast ratio and fuzzy edges, a method to enhance the contrast of infrared image is given, which is based on stationary wavelet transform. After making stationary wavelet transform to an infrared image, denoising is done by the proposed method of double-threshold shrinkage in detail coefficient matrixes that have high noisy intensity. For the approximation coefficient matrix with low noisy intensity, enhancement is done by the proposed method based on histogram. The enhanced image can be got by wavelet coefficient reconstruction. Furthermore, an evaluation criterion of enhancement performance is introduced. The results show that this algorithm ensures target enhancement and restrains additive Gauss white noise effectively. At the same time, its amount of calculation is small and operation speed is fast.
Fingerprint Image Segmentation Algorithm Based on Contourlet Transform Technology
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Guanghua Zhang
2016-09-01
Full Text Available This paper briefly introduces two classic algorithms for fingerprint image processing, which include the soft threshold denoise algorithm of wavelet domain based on wavelet domain and the fingerprint image enhancement algorithm based on Gabor function. Contourlet transform has good texture sensitivity and can be used for the segmentation enforcement of the fingerprint image. The method proposed in this paper has attained the final fingerprint segmentation image through utilizing a modified denoising for a high-frequency coefficient after Contourlet decomposition, highlighting the fingerprint ridge line through modulus maxima detection and finally connecting the broken fingerprint line using a value filter in direction. It can attain richer direction information than the method based on wavelet transform and Gabor function and can make the positioning of detailed features more accurate. However, its ridge should be more coherent. Experiments have shown that this algorithm is obviously superior in fingerprint features detection.
Remote Sensing Image Resolution Enlargement Algorithm Based on Wavelet Transformation
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Samiul Azam
2014-05-01
Full Text Available In this paper, we present a new image resolution enhancement algorithm based on cycle spinning and stationary wavelet subband padding. The proposed technique or algorithm uses stationary wavelet transformation (SWT to decompose the low resolution (LR image into frequency subbands. All these frequency subbands are interpolated using either bicubic or lanczos interpolation, and these interpolated subbands are put into inverse SWT process for generating intermediate high resolution (HR image. Finally, cycle spinning (CS is applied on this intermediate high resolution image for reducing blocking artifacts, followed by, traditional Laplacian sharpening filter is used to make the generated high resolution image sharper. This new technique has been tested on several satellite images. Experimental result shows that the proposed technique outperforms the conventional and the state-of-the-art techniques in terms of peak signal to noise ratio, root mean square error, entropy, as well as, visual perspective.
Efficient blind image restoration using discrete periodic radon transform.
Lun, Daniel P K; Chan, Tommy C L; Hsung, Tai-Chiu; Feng, David Dagan; Chan, Yuk-Hee
2004-02-01
Restoring an image from its convolution with an unknown blur function is a well-known ill-posed problem in image processing. Many approaches have been proposed to solve the problem and they have shown to have good performance in identifying the blur function and restoring the original image. However, in actual implementation, various problems incurred due to the large data size and long computational time of these approaches are undesirable even with the current computing machines. In this paper, an efficient algorithm is proposed for blind image restoration based on the discrete periodic Radon transform (DPRT). With DPRT, the original two-dimensional blind image restoration problem is converted into one-dimensional ones, which greatly reduces the memory size and computational time required. Experimental results show that the resulting approach is faster in almost an order of magnitude as compared with the traditional approach, while the quality of the restored image is similar.
High Etendue Imaging Fourier Transform Spectrometer: initial results
Horton, Richard F.; Conger, Chris A.; Pelligrino, L. S.
1997-10-01
At the Denver meeting, last year, we presented the High Etendue Imaging Fourier Transform Spectrometer, (HEIFTS), theory and optical design. This device uses a new 'image plane interferometer' geometry to produce 'autocorrelation function modulation' in the image plane of a 2D imaging array, such that the phase offset of the modulation varies linearly across the image. As a 2D image is pushbroomed across the imaging, array, the record of an individual scene pixel is recorded for each autocorrelation phase offset. The 3D array of this data is processed to yield an 'autocorrelation function' data cube, which is Fourier transformed to yield a 'wavenumber' hyperspectral data curve. A phase I device has been demonstrated in the laboratory and initial results are presented. The significant increase in signal to noise ratio, which the HEIFTS optical design promises over conventional hyperspectral imaging schemes, has been simulated, and results will be discussed. A Phase II system is being prepared for initial field deployment, and will be described.
Image restoration based on the discrete fraction Fourier transform
Yan, Peimin; Mo, Yu L.; Liu, Hong
2001-09-01
The fractional Fourier transform is the powerful tool for time-variant signal analysis. For space-variant degradation and non-stationary processes the filtering in fractional Fourier domains permits reduction of the error compared with ordinary Fourier domain filtering. In this paper the concept of filtering in fractional Fourier domains is applied to the problem of estimating degraded images. Efficient digital implementation using discrete Hermite eigenvectors can provide similar results to match the continuous outputs. Expressions for the 2D optimal filter function in fractional domains will be given for transform domains characterized by the two rotation angle parameters of the 2D fractional Fourier transform. The proposed method is used to restore images that have several degradations in the experiments. The results show that the method presented in this paper is valid.
Huynh, Nam; Zhang, Edward; Betcke, Marta; Arridge, Simon R.; Beard, Paul; Cox, Ben
2015-03-01
A system for dynamic mapping of broadband ultrasound fields has been designed, with high frame rate photoacoustic imaging in mind. A Fabry-Pérot interferometric ultrasound sensor was interrogated using a coherent light single-pixel camera. Scrambled Hadamard measurement patterns were used to sample the acoustic field at the sensor, and either a fast Hadamard transform or a compressed sensing reconstruction algorithm were used to recover the acoustic pressure data. Frame rates of 80 Hz were achieved for 32x32 images even though no specialist hardware was used for the on-the-fly reconstructions. The ability of the system to obtain photocacoustic images with data compressions as low as 10% was also demonstrated.
Fractional Fourier Transform Applied to Digital Images Encryption
Vilardy, Juan M.; Torres, Cesar O.; Mattos, Lorenzo
2008-04-01
In the present paper a digital algorithm was developed to make phase encryption of digital indexed images to color using the fractional Fourier transform (the images in RGB are converted to indexed before to encrypt). The indexed images are represented by a matrix of M×N pixels (where M defines the height and N is the Width of the image) and a color map (it's a matrix of C×3 elements, where C indicates the colors number of the image and the number 3 indicates the three columns associated with the color components: Red, Green and Blue of each pixel of the matrix of M×N) associated to the matrix of pixels to suitably represent the color information of the image. The indexed image (matrix of M×N pixels) to encrypt is placed as the phase of a complex exponential, then is transformed three times and multiplied in intermediate steps by two random phase masks statistically independent thus to obtain the encrypted image, for decrypt the coding image the encryption procedure is applied in the inverse sense to the conjugated complex of the encrypted image, then is taken the negative of the phase of the resulting function of the decryption process and the original image is obtained this way that had been encrypted; For the color map equal procedure is applied in the encryption/decryption process described previously for the matrix of M×N pixels. In the implemented cryptographic algorithm five keys are used, constituted by three fractional orders and two random phase masks, all these keys are necessary for a correct decryption providing a dependability to the transference of images by means of the communications nets.
A Review of Various Transform Domain Digital Image Fusion for Multifocus Colored Images
Directory of Open Access Journals (Sweden)
Arun Begill
2015-11-01
Full Text Available Image fusion is the idea to enhance the image content by fusing two or more images obtained from visual sensor network. The main goal of image fusion is to eliminate redundant information and merging more useful information from source images. Various transform domain image fusion methods like DWT, SIDWT and DCT, ACMax DCT etc. are developed in recent years. Every method has its own advantages and disadvantages. ACMax Discrete cosine transform (DCT is very efficient approach for image fusion because of its energy compaction property as well as improve quality of image. Furthermore, this technique has also some disadvantages like color artifacts, noise and degrade the sharpness of edges. In this paper ACMax DCT method is integrated with saturation weighting and Joint Trilateral filter to get the high quality image and compare with traditional methods. The results have shown that ACMax DCT with Saturation weighting and Joint Trilateral filter method has outperformed the state of art techniques.
Image Compression using Haar and Modified Haar Wavelet Transform
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Mohannad Abid Shehab Ahmed
2013-04-01
Full Text Available Efficient image compression approaches can provide the best solutions to the recent growth of the data intensive and multimedia based applications. As presented in many papers the Haar matrix–based methods and wavelet analysis can be used in various areas of image processing such as edge detection, preserving, smoothing or filtering. In this paper, color image compression analysis and synthesis based on Haar and modified Haar is presented. The standard Haar wavelet transformation with N=2 is composed of a sequence of low-pass and high-pass filters, known as a filter bank, the vertical and horizontal Haar filters are composed to construct four 2-dimensional filters, such filters applied directly to the image to speed up the implementation of the Haar wavelet transform. Modified Haar technique is studied and implemented for odd based numbers i.e. (N=3 & N=5 to generate many solution sets, these sets are tested using the energy function or numerical method to get the optimum one.The Haar transform is simple, efficient in memory usage due to high zero value spread (it can use sparse principle, and exactly reversible without the edge effects as compared to DCT (Discrete Cosine Transform. The implemented Matlab simulation results prove the effectiveness of DWT (Discrete Wave Transform algorithms based on Haar and Modified Haar techniques in attaining an efficient compression ratio (C.R, achieving higher peak signal to noise ratio (PSNR, and the resulting images are of much smoother as compared to standard JPEG especially for high C.R. A comparison between standard JPEG, Haar, and Modified Haar techniques is done finally which approves the highest capability of Modified Haar between others.
Hyperspectral imaging using the single-pixel Fourier transform technique
Jin, Senlin; Hui, Wangwei; Wang, Yunlong; Huang, Kaicheng; Shi, Qiushuai; Ying, Cuifeng; Liu, Dongqi; Ye, Qing; Zhou, Wenyuan; Tian, Jianguo
2017-03-01
Hyperspectral imaging technology is playing an increasingly important role in the fields of food analysis, medicine and biotechnology. To improve the speed of operation and increase the light throughput in a compact equipment structure, a Fourier transform hyperspectral imaging system based on a single-pixel technique is proposed in this study. Compared with current imaging spectrometry approaches, the proposed system has a wider spectral range (400-1100 nm), a better spectral resolution (1 nm) and requires fewer measurement data (a sample rate of 6.25%). The performance of this system was verified by its application to the non-destructive testing of potatoes.
Stereo matching based on census transformation of image gradients
Stentoumis, C.; Grammatikopoulos, L.; Kalisperakis, I.; Karras, G.; Petsa, E.
2015-05-01
Although multiple-view matching provides certain significant advantages regarding accuracy, occlusion handling and radiometric fidelity, stereo-matching remains indispensable for a variety of applications; these involve cases when image acquisition requires fixed geometry and limited number of images or speed. Such instances include robotics, autonomous navigation, reconstruction from a limited number of aerial/satellite images, industrial inspection and augmented reality through smart-phones. As a consequence, stereo-matching is a continuously evolving research field with growing variety of applicable scenarios. In this work a novel multi-purpose cost for stereo-matching is proposed, based on census transformation on image gradients and evaluated within a local matching scheme. It is demonstrated that when the census transformation is applied on gradients the invariance of the cost function to changes in illumination (non-linear) is significantly strengthened. The calculated cost values are aggregated through adaptive support regions, based both on cross-skeletons and basic rectangular windows. The matching algorithm is tuned for the parameters in each case. The described matching cost has been evaluated on the Middlebury stereo-vision 2006 datasets, which include changes in illumination and exposure. The tests verify that the census transformation on image gradients indeed results in a more robust cost function, regardless of aggregation strategy.
Remote Sensing Image Fusion Using Ica and Optimized Wavelet Transform
Hnatushenko, V. V.; Vasyliev, V. V.
2016-06-01
In remote-sensing image processing, fusion (pan-sharpening) is a process of merging high-resolution panchromatic and lower resolution multispectral (MS) imagery to create a single high-resolution color image. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. However, the pan-sharpening image produced by these methods gets the high color distortion of spectral information. In this paper, to minimize the spectral distortion we propose a remote sensing image fusion method which combines the Independent Component Analysis (ICA) and optimization wavelet transform. The proposed method is based on selection of multiscale components obtained after the ICA of images on the base of their wavelet decomposition and formation of linear forms detailing coefficients of the wavelet decomposition of images brightness distributions by spectral channels with iteratively adjusted weights. These coefficients are determined as a result of solving an optimization problem for the criterion of maximization of information entropy of the synthesized images formed by means of wavelet reconstruction. Further, reconstruction of the images of spectral channels is done by the reverse wavelet transform and formation of the resulting image by superposition of the obtained images. To verify the validity, the new proposed method is compared with several techniques using WorldView-2 satellite data in subjective and objective aspects. In experiments we demonstrated that our scheme provides good spectral quality and efficiency. Spectral and spatial quality metrics in terms of RASE, RMSE, CC, ERGAS and SSIM are used in our experiments. These synthesized MS images differ by showing a better contrast and clarity on the boundaries of the "object of interest - the background". The results show that the proposed approach performs better than some compared methods according to the performance metrics.
A new class of scrambling transformation and its application in the image information covering
Institute of Scientific and Technical Information of China (English)
齐东旭; 邹建成; 韩效宥
2000-01-01
This paper studies two kinds of nonlinear transformations, namely the higher-dimensional Arnold transformation and the higher-dimensional Fibonacci Q-transformation and discusses the scrambling action of the two transformations focusing on the phase space of the digital images. A sufficient and necessary condition that a matrix transformation of digital image has periodicity is given. The results show that the two transformations have potential application in the storage and transportation of image information for the purpose of information security.
Query By Image Content using Discrete Cosine Transform
Directory of Open Access Journals (Sweden)
P.A.Hemalatha
2013-04-01
Full Text Available The need for Query By Image Content (QBIC peaked up due to the increase in the size of image database. The proposed method chooses appropriate feature extraction methods to extract the features, shape and color to enhance the retrieval efficiency and accuracy. It employs SRM (Statistical Region Merging algorithm for segmentation and uses DCT (Discrete Cosine Transform on the segmented image to obtain the shape feature vector. Color feature is obtained by considering the RGB components in the image. The processed feature vectors are collected in the feature database which is then compared with the query image’s feature vector. When the difference matches a specific threshold, the most similar images are retrieved automatically.
Multifractional Fourier Transform Method and Its Applications to Image Encryption
Institute of Scientific and Technical Information of China (English)
RANQiwen; WANGQi; MAJing; TANLiying
2003-01-01
The multiplicity of the fractional Fourier transform(FRFT),which is intrinsic in any fractional operator,has been claimed by several authors,but never across-the-board developed.Particularly,the weight-type FRFT(WFRFT) has not been investigated.Starting with defining the multifractional Fourier transform (MFRFT),we gained the generalization permutation matrix group (GPMG)representation and multiplicity of the MFRFT,and the relationships among the MFRFT the standard WFRFT and the standard CFRFT.Finally,as a application,a novel image encryption method hased on the MFRFT is propounded.Similation results show that this method is safe,practicable and impactful.
On the Dini-Hadamard subdifferential of the difference of two functions
Bot, Radu Ioan
2010-01-01
In this paper we first provide a general formula of inclusion for the Dini-Hadamard epsilon-subdifferential of the difference of two functions and show that it becomes equality in case the functions are directionally approximately starshaped at a given point and a weak topological assumption is fulfilled. To this end we give a useful characterization of the Dini-Hadamard epsilon-subdifferential by means of sponges. The achieved results are employed in the formulation of optimality conditions via the Dini-Hadamard subdifferential for cone-constrained optimization problems having the difference of two functions as objective.
The fuzzy Hough Transform-feature extraction in medical images
Energy Technology Data Exchange (ETDEWEB)
Philip, K.P.; Dove, E.L.; Stanford, W.; Chandran, K.B. (Univ. of Iowa, Iowa City, IA (United States)); McPherson, D.D.; Gotteiner, N.L. (Northwestern Univ., Chicago, IL (United States). Dept. of Internal Medicine)
1994-06-01
Identification of anatomical features is a necessary step for medical image analysis. Automatic methods for feature identification using conventional pattern recognition techniques typically classify an object as a member of a predefined class of objects, but do not attempt to recover the exact or approximate shape of that object. For this reason, such techniques are usually not sufficient to identify the borders of organs when individual geometry varies in local detail, even though the general geometrical shape is similar. The authors present an algorithm that detects features in an image based on approximate geometrical models. The algorithm is based on the traditional and generalized Hough Transforms but includes notions from fuzzy set theory. The authors use the new algorithm to roughly estimate the actual locations of boundaries of an internal organ, and from this estimate, to determine a region of interest around the organ. Based on this rough estimate of the border location, and the derived region of interest, the authors find the final estimate of the true borders with other image processing techniques. The authors present results that demonstrate that the algorithm was successfully used to estimate the approximate location of the chest wall in humans, and of the left ventricular contours of a dog heart obtained from cine-computed tomographic images. The authors use this fuzzy Hough Transform algorithm as part of a larger procedures to automatically identify the myocardial contours of the heart. This algorithm may also allow for more rapid image processing and clinical decision making in other medical imaging applications.
Distance Transform Based Enhancement for Linear Interpolated Images
Institute of Scientific and Technical Information of China (English)
唐莉萍; 曾培峰
2003-01-01
An approach of distance map based image enhancement (DMIE) is proposed. It is applied to conventional interpolations to get sharp images. Edge detection is performed after images are interpolated by linear interpolations. To meet the two conditions set for DMIE, i. e., no abrupt changes and no overboosting, different boosting rate should be used in adjusting pixel intensities. When the boosting rate is determined by using the distance from enhanced pixels to nearest edges, edge-oriented image enhancement is obtained. By using Erosion technique, the range for pixel intensity adjustment is set. Over-enhancement is avoided by limiting the pixel intensities in enhancement within the range.A unified linear-time algorithm for distance transform is adopted to deal with the calculation of Euclidean distance of the images. Its computation complexity is O (N2 ). After the preparation, i. e.,distance transforming and erosion, the images get more and more sharpened while no over-boosting occurs by repeating the enhancement procedure. The simplicity of the enhancement operation makes DMIE suitable for enhancement rate adjusting.
Image encryption techniques based on the fractional Fourier transform
Hennelly, B. M.; Sheridan, J. T.
2003-11-01
The fractional Fourier transform, (FRT), is a generalisation of the Fourier transform which allows domains of mixed spatial frequency and spatial information to be examined. A number of method have recently been proposed in the literature for the encryption of two dimensional information using optical systems based on the FRT. Typically, these methods require random phase screen keys to decrypt the data, which must be stored at the receiver and must be carefully aligned with the received encrypted data. We have proposed a new technique based on a random shifting or Jigsaw transformation. This method does not require the use of phase keys. The image is encrypted by juxtaposition of sections of the image in various FRT domains. The new method has been compared numerically with existing methods and shows comparable or superior robustness to blind decryption. An optical implementation is also proposed and the sensitivity of the various encryption keys to blind decryption is quantified. We also present a second image encryption technique, which is based on a recently proposed method of optical phase retrieval using the optical FRT and one of its discrete counterparts. Numerical simulations of the new algorithm indicates that the sensitivity of the keys is much greater than any of the techniques currently available. In fact the sensitivity appears to be so high that optical implementation, based on existing optical signal processing technology, may be impossible. However, the technique has been shown to be a powerful method of 2-D image data encryption.
Adaptive wavelet transform algorithm for lossy image compression
Pogrebnyak, Oleksiy B.; Ramirez, Pablo M.; Acevedo Mosqueda, Marco Antonio
2004-11-01
A new algorithm of locally adaptive wavelet transform based on the modified lifting scheme is presented. It performs an adaptation of the wavelet high-pass filter at the prediction stage to the local image data activity. The proposed algorithm uses the generalized framework for the lifting scheme that permits to obtain easily different wavelet filter coefficients in the case of the (~N, N) lifting. Changing wavelet filter order and different control parameters, one can obtain the desired filter frequency response. It is proposed to perform the hard switching between different wavelet lifting filter outputs according to the local data activity estimate. The proposed adaptive transform possesses a good energy compaction. The designed algorithm was tested on different images. The obtained simulation results show that the visual and quantitative quality of the restored images is high. The distortions are less in the vicinity of high spatial activity details comparing to the non-adaptive transform, which introduces ringing artifacts. The designed algorithm can be used for lossy image compression and in the noise suppression applications.
Secure image transform domain technique for steganographic applications
Alturki, Faisal T.; Mersereau, Russell M.
2001-08-01
Digital steganography is the art of secretly hiding information inside a multimedia signal in such a way that its very existence is concealed. In this paper, we present a new steganographic technique for covert communications. The technique embeds the hidden information in the transform domain after decorrelating the image samples in the spatial domain using a key. This results in a significant increase in the number of transform coefficients that can be used to transmit the hidden information, and therefore, increases the data embedding capacity. The hidden information is embedded in the transform domain after taking a block DCT of the decorrelated image. A quantization technique is used to embed the hidden data. The decoding process requires the availability of the same key that was used to decorrelate the image samples. By using quantization techniques, the hidden information can be recovered reliably. If the key is not available at the decoder it is impossible to recover the hidden information. Hence, this system is secure against removal attacks. The statistical properties of the cover and the stego image remain identical for small quantization steps. Therefore, the hidden data cannot be detected. The data embedding system is modeled as transmitting information through a Gaussian channel.
Automatic line detection in document images using recursive morphological transforms
Kong, Bin; Chen, Su S.; Haralick, Robert M.; Phillips, Ihsin T.
1995-03-01
In this paper, we describe a system that detects lines of various types, e.g., solid lines and dotted lines, on document images. The main techniques are based on the recursive morphological transforms, namely the recursive opening and closing transforms. The advantages of the transforms are that they can perform binary opening and closing with any sized structuring element simultaneously in constant time per pixel, and that they offer a solution to morphological image analysis problems where the sizes of the structuring elements have to be determined after the examination of the image itself. The system is evaluated on about 1,200 totally ground-truthed IRS tax form images of different qualities. The line detection output is compared with a set of hand-drawn groundtruth lines. The statistics like the number and rate of correct detection, miss detection, and false alarm are calculated. The performance of 32 algorithms for solid line detection are compared to find the best one. The optimal algorithm tuning parameter settings could be estimated on the fly using a regression tree.
Optical image encryption in Fresnel domain using spiral phase transform
Kumar, Ravi; Bhaduri, Basanta
2017-09-01
In this study, we propose a new nonlinear optical image encryption technique using spiral phase transform (SPT). First, the primary image is phase encoded and multiplied with a random amplitude mask (RAM), and using power function, the product is then powered to m. This powered output is Fresnel propagated with distance z 1 and then modulated with a random phase mask (RPM). The modulated image is further Fresnel propagated with distance z 2. Similarly, a security image is also modulated with another RAM and then Fresnel propagated with distance z 3. Next, the two modulated images after Fresnel propagations, are interfered and further Fresnel propagated with distance z 4 to get a complex image. Finally, this complex image is SPT with particular spiral phase function (SPF), to get the final encrypted image for transmission. In the proposed technique, the security keys are Fresnel propagation distances, the security image, RPM, RAMs, power order, m, and order of SPF, q. Numerical simulation results confirm the validity and effectiveness of the proposed technique. The proposed technique is robust against noise and brutal force attacks.
Discrete-cosine-transform-based image compression applied to dermatology
Cookson, John P.; Sneiderman, Charles; Rivera, Christopher
1991-05-01
The research reported in this paper concerns an evaluation of the impact of compression on the quality of digitized color dermatologic images. 35 mm slides of four morphologic types of skin lesions were captured at 1000 pixels per inch (ppi) in 24 bit RGB color, to give an approximate 1K X 1K image. The discrete cosine transform (DCT) algorithm, was applied to the resulting image files to achieve compression ratios of about 7:1, 28:1, and 70:1. The original scans and the decompressed files were written to a 35 mm film recorder. Together with the original photo slides, the slides resulting from digital images were evaluated in a study of morphology recognition and image quality assessment. A panel of dermatologists was asked to identify the morphology depicted and to rate the image quality of each slide. The images were shown in a progression from highest level of compression to original photo slides. We conclude that the use of DCT file compression yields acceptable performance for skin lesion images since differences in morphology recognition performance do not correlate significantly with the use of original photos versus compressed versions. Additionally, image quality evaluation does not correlate significantly with level of compression.
ADAPTIVE TCHEBICHEF MOMENT TRANSFORM IMAGE COMPRESSION USING PSYCHOVISUAL MODEL
Directory of Open Access Journals (Sweden)
Ferda Ernawan
2013-01-01
Full Text Available An extension of the standard JPEG image compression known as JPEG-3 allows rescaling of the quantization matrix to achieve a certain image output quality. Recently, Tchebichef Moment Transform (TMT has been introduced in the field of image compression. TMT has been shown to perform better than the standard JPEG image compression. This study presents an adaptive TMT image compression. This task is obtained by generating custom quantization tables for low, medium and high image output quality levels based on a psychovisual model. A psychovisual model is developed to approximate visual threshold on Tchebichef moment from image reconstruction error. The contribution of each moment will be investigated and analyzed in a quantitative experiment. The sensitivity of TMT basis functions can be measured by evaluating their contributions to image reconstruction for each moment order. The psychovisual threshold model allows a developer to design several custom TMT quantization tables for a user to choose from according to his or her target output preference. Consequently, these quantization tables produce lower average bit length of Huffman code while still retaining higher image quality than the extended JPEG scaling scheme.
Noise Removal in SAR Images using Orthonormal Ridgelet Transform
Directory of Open Access Journals (Sweden)
A. Ravi,
2015-05-01
Full Text Available Development in the field of image processing for reducing speckle noise from digital images/satellite images is a challenging task for image processing applications. Previously many algorithms were proposed to de-speckle the noise in digital images. Here in this article we are presenting experimental results on de-speckling of Synthetic Aperture RADAR (SAR images. SAR images have wide applications in remote sensing and mapping the surfaces of all planets. SAR can also be implemented as "inverse SAR" by observing a moving target over a substantial time with a stationary antenna. Hence denoising of SAR images is an essential task for viewing the information. Here we introduce a transformation technique called ―Ridgelet‖, which is an extension level of wavelet. Ridgelet analysis can be done in the similar way how wavelet analysis was done in the Radon domain as it translates singularities along lines into point singularities under different frequencies. Simulation results were show cased for proving that proposed work is more reliable than compared to other despeckling processes, and the quality of de-speckled image is measured in terms of Peak Signal to Noise Ratio and Mean Square Error.
Walsh-Hadamard-Based 3-D Steganography for Protecting Sensitive Information in Point-of-Care.
Abuadbba, Alsharif; Khalil, Ibrahim
2017-09-01
Remote points-of-care has recently had a lot of attention for their advantages such as saving lives and cost reduction. The transmitted streams usually contain 1) normal biomedical signals (e.g., electrocardiograms) and 2) highly private information (e.g., patient identity). Despite the obvious advantages, the primary concerns are privacy and authenticity of the transferred data. Therefore, this paper introduces a novel steganographic mechanism that ensures 1) strong privacy preservation of private information by random concealing inside the transferred signals employing a key and 2) evidence of originality for the biomedical signals. To maximize hiding, fast Walsh-Hadamard transform is utilized to transform the signals into a group of coefficients. To ensure the lowest distortion, only less-significant values of coefficients are employed. To strengthen security, the key is utilized in a three-dimensional (3-D) random coefficients' reform to produce a 3-D order employed in the concealing process. The resultant distortion has been thoroughly measured in all stages. After extensive experiments on three types of signals, it has been proved that the algorithm has a little impact on the genuine signals ( 1 %). The security evaluation also confirms that unlawful retrieval of the hidden information within rational time is mightily improbable.
Three-Dimensional Image Compression With Integer Wavelet Transforms
Bilgin, Ali; Zweig, George; Marcellin, Michael W.
2000-04-01
A three-dimensional (3-D) image-compression algorithm based on integer wavelet transforms and zerotree coding is presented. The embedded coding of zerotrees of wavelet coefficients (EZW) algorithm is extended to three dimensions, and context-based adaptive arithmetic coding is used to improve its performance. The resultant algorithm, 3-D CB-EZW, efficiently encodes 3-D image data by the exploitation of the dependencies in all dimensions, while enabling lossy and lossless decompression from the same bit stream. Compared with the best available two-dimensional lossless compression techniques, the 3-D CB-EZW algorithm produced averages of 22%, 25%, and 20% decreases in compressed file sizes for computed tomography, magnetic resonance, and Airborne Visible Infrared Imaging Spectrometer images, respectively. The progressive performance of the algorithm is also compared with other lossy progressive-coding algorithms.
Fast Orthogonal Haar Transform Pattern Matching via Image Square Sum.
Li, Yujian; Li, Houjun; Cai, Zhi
2014-09-01
Although using image strip sum, an orthogonal Haar transform (OHT) pattern matching algorithm may have good performance, it requires three subtractions to calculate each Haar projection value on the sliding windows. By establishing a solid mathematical foundation for OHT, this paper based on the concept of image square sum, proposes a novel fast orthogonal Haar transform (FOHT) pattern matching algorithm, from which a Haar projection value can be obtained by only one subtraction. Thus, higher speed-ups can be achieved, while producing the same results with the full search pattern matching. A large number of experiments show that the speed-ups of FOHT are very competitive with OHT in most cases of matching one single pattern, and generally higher than OHT in all cases of matching multiple patterns, exceeding other high-level full search equivalent algorithms.
A Reversible Image Steganographic Algorithm Based on Slantlet Transform
Directory of Open Access Journals (Sweden)
Sushil Kumar
2013-07-01
Full Text Available In this paper we present a reversible imagesteganography technique based on Slantlet transform (SLTand using advanced encryption standard (AES method. Theproposed method first encodes the message using two sourcecodes, viz., Huffman codes and a self-synchronizing variablelength code known as, T-code. Next, the encoded binarystring is encrypted using an improved AES method. Theencrypted data so obtained is embedded in the middle andhigh frequency sub-bands, obtained by applying 2-level ofSLT to the cover-image, using thresholding method. Theproposed algorithm is compared with the existing techniquesbased on wavelet transform. The Experimental results showthat the proposed algorithm can extract hidden message andrecover the original cover image with low distortion. Theproposed algorithm offers acceptable imperceptibility,security (two-layer security and provides robustness againstGaussian and Salt-n-Pepper noise attack.
Discrete wavelet transform core for image processing applications
Savakis, Andreas E.; Carbone, Richard
2005-02-01
This paper presents a flexible hardware architecture for performing the Discrete Wavelet Transform (DWT) on a digital image. The proposed architecture uses a variation of the lifting scheme technique and provides advantages that include small memory requirements, fixed-point arithmetic implementation, and a small number of arithmetic computations. The DWT core may be used for image processing operations, such as denoising and image compression. For example, the JPEG2000 still image compression standard uses the Cohen-Daubechies-Favreau (CDF) 5/3 and CDF 9/7 DWT for lossless and lossy image compression respectively. Simple wavelet image denoising techniques resulted in improved images up to 27 dB PSNR. The DWT core is modeled using MATLAB and VHDL. The VHDL model is synthesized to a Xilinx FPGA to demonstrate hardware functionality. The CDF 5/3 and CDF 9/7 versions of the DWT are both modeled and used as comparisons. The execution time for performing both DWTs is nearly identical at approximately 14 clock cycles per image pixel for one level of DWT decomposition. The hardware area generated for the CDF 5/3 is around 15,000 gates using only 5% of the Xilinx FPGA hardware area, at 2.185 MHz max clock speed and 24 mW power consumption.
Transformation of Image Positions, Rotations, and Sizes into Shift Parameters
DEFF Research Database (Denmark)
Skov Jensen, A.; Lindvold, L.; Rasmussen, E.
1987-01-01
An optical image processing system is described that converts orientation and size to shift properties and simultaneously preserves the positional information as a shift. The system is described analytically and experimentally. The transformed image can be processed further with a classical...... correlator working with a rotational and size-invariant. multiplexed match filter. An optical robot vision system designed on this concept would be able to look at several objects simultaneously and determine their shape, size, orientation, and position with two measurements on the input scene at different...
Image Watermarking Method Using Integer-to-Integer Wavelet Transforms
Institute of Scientific and Technical Information of China (English)
陈韬; 王京春
2002-01-01
Digital watermarking is an efficient method for copyright protection for text, image, audio, and video data. This paper presents a new image watermarking method based on integer-to-integer wavelet transforms. The watermark is embedded in the significant wavelet coefficients by a simple exclusive OR operation. The method avoids complicated computations and high computer memory requirements that are the main drawbacks of common frequency domain based watermarking algorithms. Simulation results show that the embedded watermark is perceptually invisible and robust to various operations, such as low quality joint picture expert group (JPEG) compression, random and Gaussian noises, and smoothing (mean filtering).
Spatial exemplars and metrics for characterizing image compression transform error
Schmalz, Mark S.; Caimi, Frank M.
2001-12-01
The efficient transmission and storage of digital imagery increasingly requires compression to maintain effective channel bandwidth and device capacity. Unfortunately, in applications where high compression ratios are required, lossy compression transforms tend to produce a wide variety of artifacts in decompressed images. Image quality measures (IQMs) have been published that detect global changes in image configuration resulting from the compression or decompression process. Examples include statistical and correlation-based procedures related to mean-squared error, diffusion of energy from features of interest, and spectral analysis. Additional but sparsely-reported research involves local IQMs that quantify feature distortion in terms of objective or subjective models. In this paper, a suite of spatial exemplars and evaluation procedures is introduced that can elicit and measure a wide range of spatial, statistical, or spectral distortions from an image compression transform T. By applying the test suite to the input of T, performance deficits can be highlighted in the transform's design phase, versus discovery under adverse conditions in field practice. In this study, performance analysis is concerned primarily with the effect of compression artifacts on automated target recognition (ATR) algorithm performance. For example, featural distortion can be measured using linear, curvilinear, polygonal, or elliptical features interspersed with various textures or noise-perturbed backgrounds or objects. These simulated target blobs may themselves be perturbed with various types or levels of noise, thereby facilitating measurement of statistical target-background interactions. By varying target-background contrast, resolution, noise level, and target shape, compression transforms can be stressed to isolate performance deficits. Similar techniques can be employed to test spectral, phase and boundary distortions due to decompression. Applicative examples are taken from
The degeneracy of the genetic code and Hadamard matrices
Petoukhov, Sergey V
2008-01-01
The matrix form of the presentation of the genetic code is described as the cognitive form to analyze structures of the genetic code. A similar matrix form is utilized in the theory of signal processing. The Kronecker family of the genetic matrices is investigated, which is based on the genetic matrix [C A; U G], where C, A, U, G are the letters of the genetic alphabet. This matrix in the third Kronecker power is the (8*8)-matrix, which contains 64 triplets. Peculiarities of the degeneracy of the vertebrate mitochondria genetic code are reflected in the symmetrical black-and-white mosaic of this genetic (8*8)-matrix. This mosaic matrix is connected algorithmically with Hadamard matrices unexpectedly, which are famous in the theory of signal processing, quantum mechanics and quantum computers.
Integer wavelet transform for embedded lossy to lossless image compression.
Reichel, J; Menegaz, G; Nadenau, M J; Kunt, M
2001-01-01
The use of the discrete wavelet transform (DWT) for embedded lossy image compression is now well established. One of the possible implementations of the DWT is the lifting scheme (LS). Because perfect reconstruction is granted by the structure of the LS, nonlinear transforms can be used, allowing efficient lossless compression as well. The integer wavelet transform (IWT) is one of them. This is an interesting alternative to the DWT because its rate-distortion performance is similar and the differences can be predicted. This topic is investigated in a theoretical framework. A model of the degradations caused by the use of the IWT instead of the DWT for lossy compression is presented. The rounding operations are modeled as additive noise. The noise are then propagated through the LS structure to measure their impact on the reconstructed pixels. This methodology is verified using simulations with random noise as input. It predicts accurately the results obtained using images compressed by the well-known EZW algorithm. Experiment are also performed to measure the difference in terms of bit rate and visual quality. This allows to a better understanding of the impact of the IWT when applied to lossy image compression.
Fourier-transform Ghost Imaging with Hard X-rays
Yu, Hong; Han, Shensheng; Xie, Honglan; Du, Guohao; Xiao, Tiqiao; Zhu, Daming
2016-01-01
Knowledge gained through X-ray crystallography fostered structural determination of materials and greatly facilitated the development of modern science and technology in the past century. Atomic details of sample structures is achievable by X-ray crystallography, however, it is only applied to crystalline structures. Imaging techniques based on X-ray coherent diffraction or zone plates are capable of resolving the internal structure of non-crystalline materials at nanoscales, but it is still a challenge to achieve atomic resolution. Here we demonstrate a novel lensless Fourier-transform ghost imaging method with pseudo-thermal hard X-rays by measuring the second-order intensity correlation function of the light. We show that high resolution Fourier-transform diffraction pattern of a complex structure can be achieved at Fresnel region, and the amplitude and phase distributions of a sample in spatial domain can be retrieved successfully. The method of lensless X-ray Fourier-transform ghost imaging extends X-ray...
Adaptive wavelet transform algorithm for image compression applications
Pogrebnyak, Oleksiy B.; Manrique Ramirez, Pablo
2003-11-01
A new algorithm of locally adaptive wavelet transform is presented. The algorithm implements the integer-to-integer lifting scheme. It performs an adaptation of the wavelet function at the prediction stage to the local image data activity. The proposed algorithm is based on the generalized framework for the lifting scheme that permits to obtain easily different wavelet coefficients in the case of the (N~,N) lifting. It is proposed to perform the hard switching between (2, 4) and (4, 4) lifting filter outputs according to an estimate of the local data activity. When the data activity is high, i.e., in the vicinity of edges, the (4, 4) lifting is performed. Otherwise, in the plain areas, the (2,4) decomposition coefficients are calculated. The calculations are rather simples that permit the implementation of the designed algorithm in fixed point DSP processors. The proposed adaptive transform possesses the perfect restoration of the processed data and possesses good energy compactation. The designed algorithm was tested on different images. The proposed adaptive transform algorithm can be used for image/signal lossless compression.
Analytical upper bound on optimum joint decoding capacity of Wyner GCMAC using hadamard inequality
Shakir, Muhammad
2011-11-01
This paper presents an original analytical expression for an upper bound on the optimum joint decoding capacity of Wyner circular Gaussian cellular multiple access channel (C-GCMAC) for uniformly distributed mobile terminals (MTs) across the cells. This upper bound is referred to as Hadamard upper bound (HUB) and is a novel application of the Hadamard inequality established by exploiting the Hadamard operation between the channel fading and channel path gain matrices. In this context, we employ an approximation approach based on the estimation of probability density function (PDF) of Hadamard product of two matrices. A closed-form expression has been derived to capture the effect of variable user density in adjacent cells on optimal joint decoding capacity. The results of this paper demonstrate that the analytical HUB based on the proposed approximation approach converges to the theoretical results for medium range of signal to noise ratios and shows a comparable tighter bound on optimum joint decoding capacity. © 2011 IEEE.
Some new operations on Zt x Z2,2-cocyclic Hadamard matrices
Alvarez, Victor; Guemes, Maria Belen
2011-01-01
Following the ideas of [AGG11] about Zt x Z2,2-cocyclic Hadamard matrices, we introduce the notion of diagram, which visually represents any set of coboundaries. Diagrams are a very useful tool for the description and the study of paths and intersections, as described in [AGG11]. Then, we will study four different operations on Zt x Z2,2-cocyclic matrices. These operations will be defined on the set of coboundaries defining the matrix, preserve the Hadamard character of the cocyclic matrices, and allow us to obtain new Hadamard matrices from old ones. We split the set of Hadamard matrices into disjoint orbits, define representatives for them and take advantage of this fact to compute them in an easier way than the usual purely exhaustive way.
Polychromatic Speckle Reduction in Laser Pico-Projectors Using Stationary Dual Hadamard Diffusers
Thomas, W.; Middlebrook, C.
2014-12-01
Speckle from coherent light sources continues to be a limiting factor in the design and manufacturing of laser projectors. Utilizing diffractive diffusers has been an effective method for reducing monochromatic speckle contrast. Color laser projection devices require the use of red, green, and blue laser sources therefore; using a monochromatic diffractive diffuser may not be optimal for color speckle contrast reduction. A new static dual-diffuser system utilizing Hadamard matrices has been designed to reduce full color speckle. This paper analyzes the effectiveness of the new Hadamard diffusers in reducing speckle using three separate RGB laser diodes. A simulation of the Hadamard diffusers is conducted to determine the optimum spacing between the two diffusers for polychromatic speckle reduction. Experimental measured results are presented using the optimal spacing of Hadamard diffusers for RGB color speckle reduction showing 60% reduction in contrast.
Some Hermite–Hadamard Type Inequalities for Geometrically Quasi-Convex Functions
Indian Academy of Sciences (India)
Feng Qi; Bo-Yan Xi
2014-08-01
In the paper, we introduce a new concept ‘geometrically quasi-convex function’ and establish some Hermite–Hadamard type inequalities for functions whose derivatives are of geometric quasi-convexity.
Optimal image-fusion method based on nonsubsampled contourlet transform
Dou, Jianfang; Li, Jianxun
2012-10-01
The optimization of image fusion is researched. Based on the properties of nonsubsampled contourlet transform (NSCT), shift invariance, multiscale and multidirectional expansion, the fusion parameters of the multiscale decompostion scheme is optimized. In order to meet the requirement of feedback optimization, a new image fusion quality metric of image quality index normalized edge association (IQI-NEA) is built. A polynomial model is adopted to establish the relationship between the IQI_NEA metric and several decomposition levels. The optimal fusion includes four steps. First, the source images are decomposed in NSCT domain for several given levels. Second, principal component analysis is adopted to fuse the low frequency coefficients and the maximum fusion rule is utilized to fuse the high frequency coefficients to obtain the fused coefficients and the fused result is reconstructed from the obtained fused coefficients. Third, calculate the fusion quality metric IQI_NEA for the source images and fused images. Finally, the optimal fused image and optimal level are obtained through extremum properties of polynomials function. The visual and statistical results show that the proposed method has optimized the fusion performance compared to the existing fusion schemes, in terms of the visual effects and quantitative fusion evaluation indexes.
A new model of the harmonic control based on Hadamard product
Institute of Scientific and Technical Information of China (English)
Xinjin LIU; Yun ZOU; Xiefei YAN
2009-01-01
In terms of Hadamard product, a new model is proposed for the control of connection coefficients of the state variables of the systems. The control law to stabilize the systems via the regulations of connection coefficients is obtained via a Hadamard product involved bilinear matrix inequalities. This new control model may be of significant applications in many fields, especially may be of some special sense in the emergency control such as isolation and obstruction control.
Novel fringe scanning/Fourier transform method of synthetic imaging
Energy Technology Data Exchange (ETDEWEB)
Crawford, T.M.; Albano, R.K.
1993-08-01
We have developed a one-dimensional theory and a computer model for synthetically imaging scenes using a novel fringe scanning/Fourier transform technique. Our method probes a scene using two interfering beams of slightly different frequency. These beams form a moving fringe pattern which scans the scene and resonates with any spatial frequency components having the same spatial frequency as the scanning fringe pattern. A simple, non-imaging detector above the scene observes any scattered radiation from the scene falling onto it. If a resonance occurs between the scanning fringe pattern and the scene, then the scattered radiation will be modulated at the difference frequency between the two probing beams. By changing the spatial period of the fringe pattern and then measuring the amplitude and phase of the modulated radiation that is scattered from the scene, the Fourier amplitudes and phases of the different spatial frequency components making up the scene can be measured. A synthetic image of the scene being probed can be generated from this Fourier amplitude and phase data by taking the inverse Fourier transform of this information. This technique could be used to image objects using light, ultrasonic, or other electromagnetic or acoustic waves.
Integrated optics in an electrically scanned imaging Fourier transform spectrometer
Breckinridge, James B. (Inventor); Ocallaghan, Fred G. (Inventor)
1982-01-01
An efficient, lightweight and stable, Fourier transform spectrometer was developed. The mechanical slide mechanism needed to create a path difference was eliminated by the use of retro-reflecting mirrors in a monolithic interferometer assembly in which the mirrors are not at 90 degrees to the propagation vector of the radiation, but rather at a small angle. The resulting plane wave fronts create a double-sided inteferogram of the source irradiance distribution which is detected by a charge-coupled device image sensor array. The position of each CCD pixel in the array is an indication of the path difference between the two retro-reflecting mirrors in the monolithic optical structure. The Fourier transform of the signals generated by the image sensor provide the spectral irradiance distribution of the source. For imaging, the interferometer assembly scans the source of irradiation by moving the entire instrument, such as would occur if it was fixedly mounted to a moving platform, i.e., a spacecraft. During scanning, the entrace slot to the monolithic optical structure sends different pixels to corresponding interferograms detected by adjacent columns of pixels of the image sensor.
Research on ghost imaging method based on wavelet transform
Li, Mengying; He, Ruiqing; Chen, Qian; Gu, Guohua; Zhang, Wenwen
2017-09-01
We present an algorithm of extracting the wavelet coefficients of object based on ghost imaging (GI) system. Through modification of the projected random patterns by using a series of templates, wavelet transform GI (WTGI) can directly measure the high frequency components of wavelet coefficients without needing the original image. In this study, we theoretically and experimentally perform the high frequency components of wavelet coefficients detection with an arrow and a letter A based on GI and WTGI. Comparing with the traditional method, the use of the algorithm proposed in this paper can significantly improve the quality of the image of wavelet coefficients in both cases. The special advantages of GI will make the wavelet coefficient detection based on WTGI very valuable in real applications.
Instrument concept of the imaging Fourier transform spectrometer GLORIA
Directory of Open Access Journals (Sweden)
F. Friedl-Vallon
2014-10-01
Full Text Available The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA is an imaging limb emission sounder operating in the thermal infrared region. It is designed to provide measurements of the upper troposphere/lower stratosphere with high spatial and high spectral resolution. The instrument consists of an imaging Fourier transform spectrometer integrated into a gimbal. The assembly can be mounted in the belly pod of the German High Altitude and Long Range research aircraft (HALO and in instrument bays of the Russian M55 Geophysica. Measurements are made in two distinct modes: the chemistry mode emphasises chemical analysis with high spectral resolution, and the dynamics mode focuses on dynamical processes of the atmosphere with very high spatial resolution. In addition, the instrument allows tomographic analyses of air volumes. The first measurement campaigns have shown compliance with key performance and operational requirements.
Geometric registration of images by similarity transformation using two reference points
Kang, Yong Q. (Inventor); Jo, Young-Heon (Inventor); Yan, Xiao-Hai (Inventor)
2011-01-01
A method for registering a first image to a second image using a similarity transformation. The each image includes a plurality of pixels. The first image pixels are mapped to a set of first image coordinates and the second image pixels are mapped to a set of second image coordinates. The first image coordinates of two reference points in the first image are determined. The second image coordinates of these reference points in the second image are determined. A Cartesian translation of the set of second image coordinates is performed such that the second image coordinates of the first reference point match its first image coordinates. A similarity transformation of the translated set of second image coordinates is performed. This transformation scales and rotates the second image coordinates about the first reference point such that the second image coordinates of the second reference point match its first image coordinates.
The fuzzy Hough transform-feature extraction in medical images.
Philip, K P; Dove, E L; McPherson, D D; Gotteiner, N L; Stanford, W; Chandran, K B
1994-01-01
Identification of anatomical features is a necessary step for medical image analysis. Automatic methods for feature identification using conventional pattern recognition techniques typically classify an object as a member of a predefined class of objects, but do not attempt to recover the exact or approximate shape of that object. For this reason, such techniques are usually not sufficient to identify the borders of organs when individual geometry varies in local detail, even though the general geometrical shape is similar. The authors present an algorithm that detects features in an image based on approximate geometrical models. The algorithm is based on the traditional and generalized Hough Transforms but includes notions from fuzzy set theory. The authors use the new algorithm to roughly estimate the actual locations of boundaries of an internal organ, and from this estimate, to determine a region of interest around the organ. Based on this rough estimate of the border location, and the derived region of interest, the authors find the final (improved) estimate of the true borders with other (subsequently used) image processing techniques. They present results that demonstrate that the algorithm was successfully used to estimate the approximate location of the chest wall in humans, and of the left ventricular contours of a dog heart obtained from cine-computed tomographic images. The authors use this fuzzy Hough transform algorithm as part of a larger procedure to automatically identify the myocardial contours of the heart. This algorithm may also allow for more rapid image processing and clinical decision making in other medical imaging applications.
Undersampled Hyperspectral Image Reconstruction Based on Surfacelet Transform
Directory of Open Access Journals (Sweden)
Lei Liu
2015-01-01
Full Text Available Hyperspectral imaging is a crucial technique for military and environmental monitoring. However, limited equipment hardware resources severely affect the transmission and storage of a huge amount of data for hyperspectral images. This limitation has the potentials to be solved by compressive sensing (CS, which allows reconstructing images from undersampled measurements with low error. Sparsity and incoherence are two essential requirements for CS. In this paper, we introduce surfacelet, a directional multiresolution transform for 3D data, to sparsify the hyperspectral images. Besides, a Gram-Schmidt orthogonalization is used in CS random encoding matrix, two-dimensional and three-dimensional orthogonal CS random encoding matrixes and a patch-based CS encoding scheme are designed. The proposed surfacelet-based hyperspectral images reconstruction problem is solved by a fast iterative shrinkage-thresholding algorithm. Experiments demonstrate that reconstruction of spectral lines and spatial images is significantly improved using the proposed method than using conventional three-dimensional wavelets, and growing randomness of encoding matrix can further improve the quality of hyperspectral data. Patch-based CS encoding strategy can be used to deal with large data because data in different patches can be independently sampled.
Medical image segmentation using level set and watershed transform
Zhu, Fuping; Tian, Jie
2003-07-01
One of the most popular level set algorithms is the so-called fast marching method. In this paper, a medical image segmentation algorithm is proposed based on the combination of fast marching method and watershed transformation. First, the original image is smoothed using nonlinear diffusion filter, then the smoothed image is over-segmented by the watershed algorithm. Last, the image is segmented automatically using the modified fast marching method. Due to introducing over-segmentation, the arrival time the seeded point to the boundary of region should be calculated. For other pixels inside the region of the seeded point, the arrival time is not calculated because of the region homogeneity. So the algorithm"s speed improves greatly. Moreover, the speed function is redefined based on the statistical similarity degree of the nearby regions. We also extend our algorithm to 3D circumstance and segment medical image series. Experiments show that the algorithm can fast and accurately obtain segmentation results of medical images.
Adaptive geodesic transform for segmentation of vertebrae on CT images
Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang
2014-03-01
Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.
Zhou, Nanrun; Hu, Yiqun; Gong, Lihua; Li, Guangyong
2017-06-01
A new quantum image encryption scheme is suggested by using the iterative generalized Arnold transforms and the quantum image cycle shift operations. The times of the quantum image cycle shift operations are controlled by a hyper-chaotic sequence generated by a new 4D hyper-chaotic system. The image pixels are scrambled by the iterative generalized Arnold transform, and the values of the pixels are altered by the quantum image cycle shift operations. The four initial conditions of the new 4D hyper-chaotic system are exploited to control the two parameters, the iterative rounds of the generalized Arnold transform and the times of the quantum image cycle shift operations, respectively. Thus, the main keys of the proposed quantum image encryption scheme are the four initial conditions of the new 4D hyper-chaotic system and the key space is relatively large enough. Simulation results and theoretical analyses demonstrate that the proposed quantum image encryption scheme outperforms its classical counterparts apparently.
Parallel transformation of K-SVD solar image denoising algorithm
Liang, Youwen; Tian, Yu; Li, Mei
2017-02-01
The images obtained by observing the sun through a large telescope always suffered with noise due to the low SNR. K-SVD denoising algorithm can effectively remove Gauss white noise. Training dictionaries for sparse representations is a time consuming task, due to the large size of the data involved and to the complexity of the training algorithms. In this paper, an OpenMP parallel programming language is proposed to transform the serial algorithm to the parallel version. Data parallelism model is used to transform the algorithm. Not one atom but multiple atoms updated simultaneously is the biggest change. The denoising effect and acceleration performance are tested after completion of the parallel algorithm. Speedup of the program is 13.563 in condition of using 16 cores. This parallel version can fully utilize the multi-core CPU hardware resources, greatly reduce running time and easily to transplant in multi-core platform.
Fourier-Transform Ghost Imaging with Hard X Rays
Yu, Hong; Lu, Ronghua; Han, Shensheng; Xie, Honglan; Du, Guohao; Xiao, Tiqiao; Zhu, Daming
2016-09-01
Knowledge gained through x-ray crystallography fostered structural determination of materials and greatly facilitated the development of modern science and technology in the past century. However, it is only applied to crystalline structures and cannot resolve noncrystalline materials. Here we demonstrate a novel lensless Fourier-transform ghost imaging method with pseudothermal hard x rays that extends x-ray crystallography to noncrystalline samples. By measuring the second-order intensity correlation function of the light, Fourier-transform diffraction pattern of a complex amplitude sample is achieved at the Fresnel region in our experiment and the amplitude and phase distributions of the sample in the spatial domain are retrieved successfully. For the first time, ghost imaging is experimentally realized with x rays. Since a highly coherent x-ray source is not required, the method can be implemented with laboratory x-ray sources and it also provides a potential solution for lensless diffraction imaging with fermions, such as neutrons and electrons where intensive coherent sources usually are not available.
Optical coherence tomography image denoising using Gaussianization transform
Amini, Zahra; Rabbani, Hossein
2017-08-01
We demonstrate the power of the Gaussianization transform (GT) for modeling image content by applying GT for optical coherence tomography (OCT) denoising. The proposed method is a developed version of the spatially constrained Gaussian mixture model (SC-GMM) method, which assumes that each cluster of similar patches in an image has a Gaussian distribution. SC-GMM tries to find some clusters of similar patches in the image using a spatially constrained patch clustering and then denoise each cluster by the Wiener filter. Although in this method GMM distribution is assumed for the noisy image, holding this assumption on a dataset is not investigated. We illustrate that making a Gaussian assumption on a noisy dataset has a significant effect on denoising results. For this purpose, a suitable distribution for OCT images is first obtained and then GT is employed to map this original distribution of OCT images to a GMM distribution. Then, this Gaussianized image is used as the input of the SC-GMM algorithm. This method, which is a combination of GT and SC-GMM, remarkably improves the results of OCT denoising compared with earlier version of SC-GMM and even produces better visual and numerical results than the state-of-the art works in this field. Indeed, the main advantage of the proposed OCT despeckling method is texture preservation, which is important for main image processing tasks like OCT inter- and intraretinal layer analysis. Thus, to prove the efficacy of the proposed method for this analysis, an improvement in the segmentation of intraretinal layers using the proposed method as a preprocessing step is investigated. Furthermore, the proposed method can achieve the best expert ranking between other contending methods, and the results show the helpfulness and usefulness of the proposed method in clinical applications.
Using appreciative inquiry to transform student nurses’ image of nursing
Directory of Open Access Journals (Sweden)
Motshedisi E. Chauke
2015-02-01
Full Text Available Introduction: Literature provides adequate evidence of a poor perception of nursing within the profession, resulting in high rates of attrition of student nurses and newly qualified nurses. The nursing profession, in particular nurse educators, has an ethical and professional responsibility to find innovative strategies to promote the positive image of nursing amongst student nurses.Purpose: The purpose of the study was to explore the potential of appreciative inquiry (AI as an intervention teaching strategy to transform student nurses’ image of nursing.Design: A quantitative, quasi-experimental, explorative-descriptive design comprising the pretest, appreciative inquiry as intervention, and the post-test was used.Methods: Convenience sampling was used to select third and fourthyear college and university student nurses in the Gauteng province of South Africa for the pre- and the post-test respectively. Data were collected by means of a questionnaire and analysed by SPSS version 20.0.Findings: The pretest results revealed a mix of positive and negative perceptions of the image of nursing amongst student nurses. The negative perceptions of the image of nursing that needed intervention included the working conditions of nurses, and the perception of nursing as a profession that was not respected and appreciated. The post-test results showed a significant and positive change in the student nurses’ perception of the image of nursing as a respected and appreciated profession. Although AI resulted in a negative to positive change in some aspects of student nurses’ image of nursing, the negative perceptions of the working conditions of nurses remained and became more negative. The positive image of gender in nursing was enhanced following the implementation of AI.Conclusion: Appreciative inquiry demonstrated potential as a teaching strategy to produce a positive nursing image change and positive orientation towards nursing amongst student nurses.
Image recombination transform algorithm for superresolution structured illumination microscopy
Zhou, Xing; Lei, Ming; Dan, Dan; Yao, Baoli; Yang, Yanlong; Qian, Jia; Chen, Guangde; Bianco, Piero R.
2016-09-01
Structured illumination microscopy (SIM) is an attractive choice for fast superresolution imaging. The generation of structured illumination patterns made by interference of laser beams is broadly employed to obtain high modulation depth of patterns, while the polarizations of the laser beams must be elaborately controlled to guarantee the high contrast of interference intensity, which brings a more complex configuration for the polarization control. The emerging pattern projection strategy is much more compact, but the modulation depth of patterns is deteriorated by the optical transfer function of the optical system, especially in high spatial frequency near the diffraction limit. Therefore, the traditional superresolution reconstruction algorithm for interference-based SIM will suffer from many artifacts in the case of projection-based SIM that possesses a low modulation depth. Here, we propose an alternative reconstruction algorithm based on image recombination transform, which provides an alternative solution to address this problem even in a weak modulation depth. We demonstrated the effectiveness of this algorithm in the multicolor superresolution imaging of bovine pulmonary arterial endothelial cells in our developed projection-based SIM system, which applies a computer controlled digital micromirror device for fast fringe generation and multicolor light-emitting diodes for illumination. The merit of the system incorporated with the proposed algorithm allows for a low excitation intensity fluorescence imaging even less than 1 W/cm2, which is beneficial for the long-term, in vivo superresolved imaging of live cells and tissues.
Imaging Cells in Flow Cytometer Using Spatial-Temporal Transformation.
Han, Yuanyuan; Lo, Yu-Hwa
2015-08-18
Flow cytometers measure fluorescence and light scattering and analyze multiple physical characteristics of a large population of single cells as cells flow in a fluid stream through an excitation light beam. Although flow cytometers have massive statistical power due to their single cell resolution and high throughput, they produce no information about cell morphology or spatial resolution offered by microscopy, which is a much wanted feature missing in almost all flow cytometers. In this paper, we invent a method of spatial-temporal transformation to provide flow cytometers with cell imaging capabilities. The method uses mathematical algorithms and a spatial filter as the only hardware needed to give flow cytometers imaging capabilities. Instead of CCDs or any megapixel cameras found in any imaging systems, we obtain high quality image of fast moving cells in a flow cytometer using PMT detectors, thus obtaining high throughput in manners fully compatible with existing cytometers. To prove the concept, we demonstrate cell imaging for cells travelling at a velocity of 0.2 m/s in a microfluidic channel, corresponding to a throughput of approximately 1,000 cells per second.
Space, time, error, and power optimization of image compression transforms
Schmalz, Mark S.; Ritter, Gerhard X.; Caimi, Frank M.
2000-11-01
The implementation of an image compression transform on one or more small, embedded processors typically involves stringent constraints on power consumption and form factor. Traditional methods of optimizing compression algorithm performance typically emphasize joint minimization of space and time complexity, often without significant consideration of arithmetic accuracy or power consumption. However, small autonomous imaging platforms typically require joint optimization of space, time, error (or accuracy), and power (STEP) parameters, which the authors call STEP optimization. In response to implementational constraints on space and power consumption, the authors have developed systems and techniques for STEP optimization that are based on recent research in VLSI circuit design, as well as extensive previous work in system optimization. Building on the authors' previous research in embedded processors as well as adaptive or reconfigurable computing, it is possible to produce system-independent STEP optimization that can be customized for a given set of system-specific constraints. This approach is particularly useful when algorithms for image and signal processing (ISP) computer vision (CV), or automated target recognition (ATR), expressed in a machine- independent notation, are mapped to one or more heterogeneous processors (e.g., digital signal processors or DSPs, SIMD mesh processors, or reconfigurable logic). Following a theoretical summary, this paper illustrates various STEP optimization techniques via case studies, for example, real-time compression of underwater imagery on board an autonomous vehicle. Optimization algorithms are taken from the literature, and error profiling/analysis methodologies developed in the authors' previous research are employed. This yields a more rigorous basis for the simulation and evaluation of compression algorithms on a wide variety of hardware models. In this study, image algebra is employed as the notation of choice
Weighted ensemble transform Kalman filter for image assimilation
Directory of Open Access Journals (Sweden)
Sebastien Beyou
2013-01-01
Full Text Available This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF proposed by Papadakis et al. (2010 for the assimilation of image observations. The main focus of this study is on a novel formulation of the Weighted filter with the Ensemble Transform Kalman filter (WETKF, incorporating directly as a measurement model a non-linear image reconstruction criterion. This technique has been compared to the original WEnKF on numerical and real world data of 2-D turbulence observed through the transport of a passive scalar. In particular, it has been applied for the reconstruction of oceanic surface current vorticity fields from sea surface temperature (SST satellite data. This latter technique enables a consistent recovery along time of oceanic surface currents and vorticity maps in presence of large missing data areas and strong noise.
SVD-based digital image watermarking using complex wavelet transform
Indian Academy of Sciences (India)
A Mansouri; A Mahmoudi Aznaveh; F Torkamani Azar
2009-06-01
A new robust method of non-blind image watermarking is proposed in this paper. The suggested method is performed by modiﬁcation on singular value decomposition (SVD) of images in Complex Wavelet Transform (CWT) domain while CWT provides higher capacity than the real wavelet domain. Modiﬁcation of the appropriate sub-bands leads to a watermarking scheme which favourably preserves the quality. The additional advantage of the proposed technique is its robustness against the most of common attacks. Analysis and experimental results show much improved performance of the proposed method in comparison with the pure SVD-based as well as hybrid methods (e.g. DWT-SVD as the recent best SVD-based scheme).
Sato, T; Norton, S J; Linzer, M; Ikeda, O; Hirama, M
1981-02-01
An iterative technique is proposed for improving the quality of reconstructions from projections when the number of projections is small or the angular range of projections is limited. The technique consists of transforming repeatedly between image and transform spaces and applying a priori object information at each iteration. The approach is a generalization of the Gerchberg-Papoulis algorithm, a technique for extrapolating in the Fourier domain by imposing a space-limiting constraint on the object in the spatial domain. A priori object data that may be applied, in addition to truncating the image beyond the known boundaries of the object, include limiting the maximum range of variation of the physical parameter being imaged. The results of computer simulations show clearly how the process of forcing the image to conform to a priori object data reduces artifacts arising from limited data available in the Fourier domain.
Scaling-up Transformation of Multisensor Images with Multiple Resolutions
Directory of Open Access Journals (Sweden)
2009-02-01
Full Text Available For scaling up low resolution multispectral images (LRMIs with high resolution panchromatic image (HRPI, intensity-hue-saturation (IHS can produce satisfactory spatial enhancement but usually introduces spectral distortion in the fused high resolution multispectral images (HRMIs. In this paper, to minimize this problem, we present a generalized intensity modulation (GIM by extending the IHS transform to an arbitrary number of LRMIs, which uses the information of the spectral response functions (SRFs of the multispectral and panchromatic sensors. Before modulation, the generalized intensity is enhanced by injecting details extracted from the HRPI by means of empirical mode decomposition. After the enhanced generalized intensity is substituted for the old one, the HRMIs are obtained through the GIM. Quickbird images are used to illustrate the superiority of this proposed method. Extensive comparison results based on visual analysis and Wald’s protocol demonstrate that the proposed method is more encouraging for scaling up the LRMIs with the HRPI spectrally and spatially than the tested fusion methods.
Continued Development of a Planetary Imaging Fourier Transform Spectrometer (PIFTS)
Sromovsky, L. A.
2002-01-01
This report describes continued efforts to evaluate a breadboard of a Planetary Imaging Fourier Transform Spectrometer (PIFTS). The PIFTS breadboard was developed under prior PIDDP funding. That effort is described in the final report for NASA Grant NAG5-6248 and in two conference papers (Sromovsky et al. 2000; Revercomb et al. 2000). The PIFTS breadboard was designed for near-IR (1-5.2 micrometer imaging of planetary targets with spectral resolving powers of several hundred to several thousand, using an InSb detector array providing at least 64x64 pixels imaging detail. The major focus of the development effort was to combine existing technologies to produce a small and low power design compatible with a very low mass flyable instrument. The objective of this grant (NAG5-10729) was further characterization of the breadboard performance, including intercomparisons with the highly accurate non-imaging Advanced Emitted Radiance Interferometer (AERI) (Revercomb et al. 1994; Best et al. 1997).
Hadamard's formula and couplings of SLEs with free field
Izyurov, Konstantin
2010-01-01
The relation between level lines of Gaussian free fields (GFF) and SLE(4)-type curves was discovered by O. Schramm and S. Sheffield. A weak interpretation of this relation is the existence of a coupling of the GFF and a random curve, in which the curve behaves like a level line of the field. In the present paper we study these couplings for the free field with different boundary conditions. We provide a unified way to determine the law of the curve (i.e. to compute the driving process of the Loewner chain) given boundary conditions of the field, and to prove existence of the coupling. The proof is reduced to the verification of two simple properties of the mean and covariance of the field, which always relies on Hadamard's formula and properties of harmonic functions. Examples include combinations of Dirichlet, Neumann and Riemann-Hilbert boundary conditions. In doubly connected domains, the standard annulus SLE(4) is coupled with a compactified GFF obeying Neumann boundary conditions on the inner boundary. W...
Seshadri, M. D.
1992-01-01
In this dissertation research, we have demonstrated the need for integration of various imaging methodologies, such as image reconstruction from projections, image processing, pattern and feature recognition using chain codes and the Hough transform. Further an integration of these image processing techniques have been brought about for medical imaging systems. An example of this is, classification and identification of brain scans, into normal, haemorrhaged, and lacunar infarcted brain scans. Low level processing was performed using LOG and a variation of LOG. Intermediate level processing used contour completion and chain encoding. Hough transform was used to detect any analytic shapes in the edge images. All these information were used by the data abstraction routine which also extracted information from the user, in the form of a general query. These were input into a backpropagation, which is a very popular supervised neural network. During learning process an output vector was supplied by the expert to the neural network. While performing the neural network compared the input and with the help of the weight matrix computed the output. This output was compared with the expert's opinion and a percentage deviation was calculated. In the case of brain scans this value was about 95%, when the test input vector did not vary, by more than two pixels with the training or learning input vector. A good classification of the brain scans were performed using the integrated imaging system. Identification of various organs in the abdominal region was also successful, within 90% recognition rate, depending on the noise in the image.
Image fusion using wavelet transform and its application to asymmetric cryptosystem and hiding.
Mehra, Isha; Nishchal, Naveen K
2014-03-10
Image fusion is a popular method which provides better quality fused image for interpreting the image data. In this paper, color image fusion using wavelet transform is applied for securing data through asymmetric encryption scheme and image hiding. The components of a color image corresponding to different wavelengths (red, green, and blue) are fused together using discrete wavelet transform for obtaining a better quality retrieved color image. The fused color components are encrypted using amplitude- and phase-truncation approach in Fresnel transform domain. Also, the individual color components are transformed into different cover images in order to result disguising information of input image to an attacker. Asymmetric keys, Fresnel propagation parameters, weighing factor, and three cover images provide enlarged key space and hence enhanced security. Computer simulation results support the idea of the proposed fused color image encryption scheme.
Image Transformation using Modified Kmeans clustering algorithm for Parallel saliency map
Directory of Open Access Journals (Sweden)
Aman Sharma
2013-08-01
Full Text Available to design an image transformation system is Depending on the transform chosen, the input and output images may appear entirely different and have different interpretations. Image Transformationwith the help of certain module like input image, image cluster index, object in cluster and color index transformation of image. K-means clustering algorithm is used to cluster the image for bettersegmentation. In the proposed method parallel saliency algorithm with K-means clustering is used to avoid local minima and to find the saliency map. The region behind that of using parallel saliency algorithm is proved to be more than exiting saliency algorithm.
TRANSFORMATION ALGORITHM FOR IMAGES OBTAINED BY OMNIDIRECTIONAL CAMERAS
Directory of Open Access Journals (Sweden)
V. P. Lazarenko
2015-01-01
Full Text Available Omnidirectional optoelectronic systems find their application in areas where a wide viewing angle is critical. However, omnidirectional optoelectronic systems have a large distortion that makes their application more difficult. The paper compares the projection functions of traditional perspective lenses and omnidirectional wide angle fish-eye lenses with a viewing angle not less than 180°. This comparison proves that distortion models of omnidirectional cameras cannot be described as a deviation from the classic model of pinhole camera. To solve this problem, an algorithm for transforming omnidirectional images has been developed. The paper provides a brief comparison of the four calibration methods available in open source toolkits for omnidirectional optoelectronic systems. Geometrical projection model is given used for calibration of omnidirectional optical system. The algorithm consists of three basic steps. At the first step, we calculate he field of view of a virtual pinhole PTZ camera. This field of view is characterized by an array of 3D points in the object space. At the second step the array of corresponding pixels for these three-dimensional points is calculated. Then we make a calculation of the projection function that expresses the relation between a given 3D point in the object space and a corresponding pixel point. In this paper we use calibration procedure providing the projection function for calibrated instance of the camera. At the last step final image is formed pixel-by-pixel from the original omnidirectional image using calculated array of 3D points and projection function. The developed algorithm gives the possibility for obtaining an image for a part of the field of view of an omnidirectional optoelectronic system with the corrected distortion from the original omnidirectional image. The algorithm is designed for operation with the omnidirectional optoelectronic systems with both catadioptric and fish-eye lenses
Digital Image Scrambling Technology Based on the Symmetry of Arnold Transform
Institute of Scientific and Technical Information of China (English)
YANG Ya-li; CAI Na; NI Guo-qiang
2006-01-01
An improved digital image scrambling method based on Arnold transform is proposed. The method can be used for the rectangle image by splitting rectangle image into several square images. Furthermore, a pretreatment is added to speeding up the process and enhancing the scrambling effect. The recovering of the scrambled image depends on the reverse Arnold transform that has the same cycle times with the Arnold transform. The recovering is lossless and need not calculating the period of the Arnold transform. Finally, experimental results show the robustness of the method.
Adaptive lifting scheme of wavelet transforms for image compression
Wu, Yu; Wang, Guoyin; Nie, Neng
2001-03-01
Aiming at the demand of adaptive wavelet transforms via lifting, a three-stage lifting scheme (predict-update-adapt) is proposed according to common two-stage lifting scheme (predict-update) in this paper. The second stage is updating stage. The third is adaptive predicting stage. Our scheme is an update-then-predict scheme that can detect jumps in image from the updated data and it needs not any more additional information. The first stage is the key in our scheme. It is the interim of updating. Its coefficient can be adjusted to adapt to data to achieve a better result. In the adaptive predicting stage, we use symmetric prediction filters in the smooth area of image, while asymmetric prediction filters at the edge of jumps to reduce predicting errors. We design these filters using spatial method directly. The inherent relationships between the coefficients of the first stage and the other stages are found and presented by equations. Thus, the design result is a class of filters with coefficient that are no longer invariant. Simulation result of image coding with our scheme is good.
Adaptive image fusion based on nonsubsampled contourlet transform
Zhang, Xiongmei; Li, Junshan; Yi, Zhaoxiang; Yang, Wei
2007-11-01
Multiresolution-based image fusion has been the focus of considerable research attention in recent years with a number of algorithms proposed. In most of the algorithms, however, the parameter configuration is usually based on experience. This paper proposes an adaptive image fusion algorithm based on the nonsubsampled contourlet transform (NSCT), which realizes automatic parameter adjustment and gets rid of the adverse effect caused by artificial factors. The algorithm incorporates the quality metric of structural similarity (SSIM) into the NSCT fusion framework. The SSIM value is calculated to assess the fused image quality, and then it is fed back to the fusion algorithm to achieve a better fusion by directing parameters (level of decomposition and flag of decomposition direction) adjustment. Based on the cross entropy, the local cross entropy (LCE) is constructed and used to determine an optimal choice of information source for the fused coefficients at each scale and direction. Experimental results show that the proposed method achieves the best fusion compared to three other methods judged on both the objective metrics and visual inspection and exhibits robust against varying noises.
Sun, Zhiwei; Zhi, Ya'nan; Liu, Liren; Sun, Jianfeng; Zhou, Yu; Hou, Peipei
2013-09-01
The synthetic aperture imaging ladar (SAIL) systems typically generate large amounts of data difficult to compress with digital method. This paper presents an optical SAIL processor based on compensation of quadratic phase of echo in azimuth direction and two dimensional Fourier transform. The optical processor mainly consists of one phase-only liquid crystal spatial modulator(LCSLM) to load the phase data of target echo and one cylindrical lens to compensate the quadratic phase and one spherical lens to fulfill the task of two dimensional Fourier transform. We show the imaging processing result of practical target echo obtained by a synthetic aperture imaging ladar demonstrator. The optical processor is compact and lightweight and could provide inherent parallel and the speed-of-light computing capability, it has a promising application future especially in onboard and satellite borne SAIL systems.
Multi-modal Color Medical Image Fusion Using Quaternion Discrete Fourier Transform
Nawaz, Qamar; Xiao, Bin; Hamid, Isma; Jiao, Du
2016-12-01
Multimodal image fusion is a process of combining multiple images, generated by identical or diverse imaging modalities, to get precise inside information about the same body organ. In recent years, various multimodal image fusion algorithms have been proposed to fuse medical image. However, most of them focus on fusing grayscale images. This paper proposes a novel algorithm for the fusion of multimodal color medical images. The proposed algorithm divides source images into blocks, converts each RGB block into quaternion representation and transforms them from special domain to frequency domain by applying quaternion discrete Fourier transform. The fused coefficients are obtained by calculating and comparing contrast values of corresponding coefficients in transformed blocks. The resultant fused image is reconstructed by merging all the blocks after applying inverse quaternion discrete Fourier transform on each block. Experimental evaluation demonstrates that the proposed algorithm qualitatively outperforms many existing state-of-the-art multimodal image fusion algorithms.
High-Throughput Screening Using Fourier-Transform Infrared Imaging
Directory of Open Access Journals (Sweden)
Erdem Sasmaz
2015-06-01
Full Text Available Efficient parallel screening of combinatorial libraries is one of the most challenging aspects of the high-throughput (HT heterogeneous catalysis workflow. Today, a number of methods have been used in HT catalyst studies, including various optical, mass-spectrometry, and gas-chromatography techniques. Of these, rapid-scanning Fourier-transform infrared (FTIR imaging is one of the fastest and most versatile screening techniques. Here, the new design of the 16-channel HT reactor is presented and test results for its accuracy and reproducibility are shown. The performance of the system was evaluated through the oxidation of CO over commercial Pd/Al2O3 and cobalt oxide nanoparticles synthesized with different reducer-reductant molar ratios, surfactant types, metal and surfactant concentrations, synthesis temperatures, and ramp rates.
Multifocus image fusion scheme based on nonsubsampled contourlet transform
Zhou, Xinxing; Wang, Dianhong; Duan, Zhijuan; Li, Dongming
2011-06-01
This paper proposes a novel multifocus image fusion scheme based on nonsubsampled contourlet transform (NSCT). The selection principles for different subband coefficients in NSCT domain are discussed in detail. In order to be consistent with the characteristics of the human visual system and improve the robustness of the fusion algorithm to the noise, the NSCT-DCT energy is first developed. Based on it, the clarity measure and bandpass energy contrast are defined and employed to motivate the pulse coupled neural networks (PCNN) for the fusion of lowpass and bandpass subbands, respectively. The performance of the proposed fusion scheme is assessed by experiments and the results demonstrate that the algorithm proposed in the paper compares favorably to wavelet-based, contourlet-based and NSCTbased fusion algorithms in terms of visual appearances and objective criterion.
An Asymmetric Image Encryption Based on Phase Truncated Hybrid Transform
Khurana, Mehak; Singh, Hukum
2017-09-01
To enhance the security of the system and to protect it from the attacker, this paper proposes a new asymmetric cryptosystem based on hybrid approach of Phase Truncated Fourier and Discrete Cosine Transform (PTFDCT) which adds non linearity by including cube and cube root operation in the encryption and decryption path respectively. In this cryptosystem random phase masks are used as encryption keys and phase masks generated after the cube operation in encryption process are reserved as decryption keys and cube root operation is required to decrypt image in decryption process. The cube and cube root operation introduced in the encryption and decryption path makes system resistant against standard attacks. The robustness of the proposed cryptosystem has been analysed and verified on the basis of various parameters by simulating on MATLAB 7.9.0 (R2008a). The experimental results are provided to highlight the effectiveness and suitability of the proposed cryptosystem and prove the system is secure.
Calibration of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS)
Best, F. A.; Revercomb, H. E.; Bingham, G. E.; Knuteson, R. O.; Tobin, D. C.; LaPorte, D. D.; Smith, W. L.
2001-01-01
The NASA New Millennium Program's Geostationary Imaging Fourier Transform Spectrometer (GIFTS) requires highly accurate radiometric and spectral calibration in order to carry out its mission to provide water vapor, wind, temperature, and trace gas profiling from geostationary orbit. A calibration concept has been developed for the GIFTS Phase A instrument design. The in-flight calibration is performed using views of two on-board blackbody sources along with cold space. A radiometric calibration uncertainty analysis has been developed and used to show that the expected performance for GIFTS exceeds its top level requirement to measure brightness temperature to better than 1 K. For the Phase A GIFTS design, the spectral calibration is established by the highly stable diode laser used as the reference for interferogram sampling, and verified with comparisons to atmospheric calculations.
An Approach to Integer Wavelet Transform for Medical Image Compression in PACS
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
We study an approach to integer wavelet transform for lossless compression of medical image in medical picture archiving and communication system (PACS). By lifting scheme a reversible integer wavelet transform is generated, which has the similar features with the corresponding biorthogonal wavelet transform. Experimental results of the method based on integer wavelet transform are given to show better performance and great applicable potentiality in medical image compression.
The Design of Lens Imaging System by Means of Fractional Fourier Transform
Institute of Scientific and Technical Information of China (English)
CHEN Jiannong; XU Qiang; D.R.Selviah
2002-01-01
The relation between the 2nd fractional Fourier transform and the imaging process of an optical system is discussed. By changing the coordinate scales of the input plane in respect to the magnification of the optical imaging system, the fractional Fourier transform can be a powerful tool in designing specific imaging system. The Gaussian imaging formula of single lens is obtained by using the tool. Finally the procedures are generalized for designing a double-lens imaging system through an example.
EFFICIENT RETRIEVAL TECHNIQUES FOR IMAGES USING ENHANCED UNIVARIATE TRANSFORMATION APPROACH
DR.S.P.VICTOR,; MRS.V.NARAYANI,; S. Rajkumar
2010-01-01
Image mining is a process to find valid, useful, and understandable knowledge from large image sets or image databases. Image mining combines the areas of content-based image retrieval, image understanding, data mining and databases. Image mining deals with the extraction of knowledge, image data relationship, or other patterns not explicitly stored in the images. It uses methods from computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial i...
2014-09-18
DEVELOPMENT OF IMAGING FOURIER -TRANSFORM SPECTROSCOPY FOR THE CHARACTERIZATION OF TURBULENT JET FLAMES DISSERTATION Jacob L. Harley, Captain, USAF...work of the U.S. Government and is not subject to copyright protection in the United States. AFIT-ENP-DS-14-S-13 DEVELOPMENT OF IMAGING FOURIER -TRANSFORM...DISTRIBUTION UNLIMITED AFIT-ENP-DS-14-S-13 DEVELOPMENT OF IMAGING FOURIER -TRANSFORM SPECTROSCOPY FOR THE CHARACTERIZATION OF TURBULENT JET FLAMES Jacob L
ON THE ESTIMATIONS OF BOUNDS FOR DETERMINANT OF HADAMARD PRODUCT OF H-MATRICES
Institute of Scientific and Technical Information of China (English)
Yao-tang Li; Ji-cheng Li
2001-01-01
In this paper, some estimations of bounds for determinant of Hadamard product of H-matrices are given. The main result is the following: if A ＝ (aij) and B = (bij) are nonsingular H-matrices of order n and IIin=1 aiibii > 0, and Aκ and Bκ,k = 1,2,... ,n,are the k × k leading principal submatrices of A and B, respectively, thenwhere Ml(Aκ) denotes the comparison matrix of Aκ.Key words: H-matrix, Determinant, Hadamard product.
Inequalities of Furuta and Mond–Pečarić on the Hadamard product
Directory of Open Access Journals (Sweden)
Takahasi Sin-El
2000-01-01
Full Text Available As a continuation of (J. Mičić, Y. Seo, S.-E. Takahasi and M. Tominaga, Inequalities of Furuta and Mond–Pečarić, Math. Ineq. Appl., 2 (1999, 83–111, we shall discuss complementary results to Jensen's type inequalities on the Hadamard product of positive operators, which is based on the idea due to Furuta and Mond–Pečarić. We shall show Hadamard product versions of operator inequalities associated with extensions of Hölder–McCarthy and Kantorovich inequalities established by Furuta, Ky Fan and Mond–Pečarić.
Hermite-Hadamard type inequalities for the generalized k-fractional integral operators.
Set, Erhan; Choi, Junesang; Gözpinar, Abdurrahman
2017-01-01
We firstly give a modification of the known Hermite-Hadamard type inequalities for the generalized k-fractional integral operators of a function with respect to another function. We secondly establish several Hermite-Hadamard type inequalities for the generalized k-fractional integral operators of a function with respect to another function. The results presented here, being very general, are pointed out to be specialized to yield some known results. Relevant connections of the various results presented here with those involving relatively simple fractional integral operators are also indicated.
Singh, Phool; Yadav, A. K.; Singh, Kehar
2017-04-01
A novel scheme for image encryption of phase images is proposed, using fractional Hartley transform followed by Arnold transform and singular value decomposition in the frequency domain. Since the plaintext is a phase image, the mask used in the spatial domain is a random amplitude mask. The proposed scheme has been validated for grayscale images and is sensitive to the encryption parameters such as the order of the Arnold transform and the fractional orders of the Hartley transform. We have also evaluated the scheme's resistance to the well-known noise and occlusion attacks.
Lossless Image Compression Using A Simplified MED Algorithm with Integer Wavelet Transform
Directory of Open Access Journals (Sweden)
Mohamed M. Fouad
2013-11-01
Full Text Available In this paper, we propose a lossless (LS image compression technique combining a prediction step with the integer wavelet transform. The prediction step proposed in this technique is a simplified version of the median edge detector algorithm used with JPEG-LS. First, the image is transformed using the prediction step and a difference image is obtained. The difference image goes through an integer wavelet transform and the transform coefficients are used in the lossless codeword assignment. The algorithm is simple and test results show that it yields higher compression ratios than competing techniques. Computational cost is also kept close to competing techniques.
Compressing subbanded image data with Lempel-Ziv-based coders
Glover, Daniel; Kwatra, S. C.
1993-01-01
A method of improving the compression of image data using Lempel-Ziv-based coding is presented. Image data is first processed with a simple transform, such as the Walsh Hadamard Transform, to produce subbands. The subbanded data can be rounded to eight bits or it can be quantized for higher compression at the cost of some reduction in the quality of the reconstructed image. The data is then run-length coded to take advantage of the large runs of zeros produced by quantization. Compression results are presented and contrasted with a subband compression method using quantization followed by run-length coding and Huffman coding. The Lempel-Ziv-based coding in conjunction with run-length coding produces the best compression results at the same reconstruction quality (compared with the Huffman-based coding) on the image data used.
Region-based image denoising through wavelet and fast discrete curvelet transform
Gu, Yanfeng; Guo, Yan; Liu, Xing; Zhang, Ye
2008-10-01
Image denoising always is one of important research topics in the image processing field. In this paper, fast discrete curvelet transform (FDCT) and undecimated wavelet transform (UDWT) are proposed for image denoising. A noisy image is first denoised by FDCT and UDWT separately. The whole image space is then divided into edge region and non-edge regions. After that, wavelet transform is performed on the images denoised by FDCT and UDWT respectively. Finally, the resultant image is fused through using both of edge region wavelet cofficients of the image denoised by FDCT and non-edge region wavelet cofficients of the image denoised by UDWT. The proposed method is validated through numerical experiments conducted on standard test images. The experimental results show that the proposed algorithm outperforms wavelet-based and curvelet-based image denoising methods and preserve linear features well.
Choi, Hyun Ho; Lee, Ju Hwan; Kim, Sung Min; Park, Sung Yun
2015-01-01
Here, the speckle noise in ultrasonic images is removed using an image fusion-based denoising method. To optimize the denoising performance, each discrete wavelet transform (DWT) and filtering technique was analyzed and compared. In addition, the performances were compared in order to derive the optimal input conditions. To evaluate the speckle noise removal performance, an image fusion algorithm was applied to the ultrasound images, and comparatively analyzed with the original image without the algorithm. As a result, applying DWT and filtering techniques caused information loss and noise characteristics, and did not represent the most significant noise reduction performance. Conversely, an image fusion method applying SRAD-original conditions preserved the key information in the original image, and the speckle noise was removed. Based on such characteristics, the input conditions of SRAD-original had the best denoising performance with the ultrasound images. From this study, the best denoising technique proposed based on the results was confirmed to have a high potential for clinical application.
A visual basic program for principal components transformation of digital images
Carr, James R.
1998-04-01
Principal components transformation of multispectral and hyperspectral digital imagery is useful for: (1) reducing the number of useful bands, a distinct advantage when using hyperspectral imagery; (2) obtaining image bands that are orthogonal (statistically independent); (3) improving supervised and unsupervised classification; and (4) image compression. A Visual Basic program is presented for principal components transformation of digital images using principal components analysis or correspondence analysis. Principal components analysis is well known for this application. Correspondence analysis is only recently applied for such transformation. The program can import raw digital images, with or without header records; or, the program can accept Windows bitmap (BMP) files. After transformation, output, transformed images can be exported in raw or BMP format. The program can be used as a simple file format conversion program (raw to BMP or BMP to raw) without performing principal components transformation. An application demonstrates the use of the program.
Quantum Image Encryption Based on Iterative Framework of Frequency-Spatial Domain Transforms
Wang, Han; Wang, Jian; Geng, Ya-Cong; Song, Yan; Liu, Ji-Qiang
2017-10-01
A novel quantum image encryption and decryption algorithm based on iteration framework of frequency-spatial domain transforms is proposed. In this paper, the images are represented in the flexible representation for quantum images (FRQI). Previous quantum image encryption algorithms are realized by spatial domain transform to scramble the position information of original images and frequency domain transform to encode the color information of images. But there are some problems such as the periodicity of spatial domain transform, which will make it easy to recover the original images. Hence, we present the iterative framework of frequency-spatial domain transforms. Based on the iterative framework, the novel encryption algorithm uses Fibonacci transform and geometric transform for many times to scramble the position information of the original images and double random-phase encoding to encode the color information of the images. The encryption keys include the iterative time t of the Fibonacci transform, the iterative time l of the geometric transform, the geometric transform matrix G i which is n × n matrix, the classical binary sequences K (k0k1{\\ldots } k_{2^{2n}-1}) and D(d0d1{\\ldots } d_{2^{2n}-1}). Here the key space of Fibonacci transform and geometric transform are both estimated to be 226. The key space of binary sequences is (2 n× n ) × (2 n× n ). Then the key space of the entire algorithm is about 2^{2{n2}+52}. Since all quantum operations are invertible, the quantum image decryption algorithm is the inverse of the encryption algorithm. The results of numerical simulation and analysis indicate that the proposed algorithm has high security and high sensitivity.
Directory of Open Access Journals (Sweden)
Hui Huang
2017-01-01
Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.
An Approach to 2D Wavelet Transform and Its Use for Image Compression
Directory of Open Access Journals (Sweden)
R. Vargic
1998-12-01
Full Text Available In this paper is constructed a new type of two-dimensional wavelet transform. Construction is based on lifting scheme. We transform 1D wavelets with symmetrical factorisation to their 2D counterparts. Comparison to existing similar 2D wavelet constructions is given. Application for image compression is given using progressive (SP1HT and classical type transform coder.
Dong, Jian; Kudo, Hiroyuki
2017-03-01
Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.
Efficient image coding method based on adaptive Gabor discrete cosine transforms
Wang, Hang; Yan, Hong
1993-01-01
The Gabor transform is very useful for image compression, but its implementation is very complicated and time consuming because the Gabor elementary functions are not mutually orthogonal. An efficient algorithm that combines the successive overrelaxation iteration and the look-up table techniques can be used to carry out the Gabor transform. The performance of the Gabor transform can be improved by using a modified transform, a Gabor discrete cosine transform (DCT). We present an adaptive Gabor DCT image coding algorithm. Experimental results show that a better performance can be achieved with the adaptive Gabor DCT than with the Gabor DCT.
Compton scattered imaging based on the V-line radon transform and its medical imaging applications.
Nguyen, M K; Regniery, R; Truong, T T; Zaidi, H
2010-01-01
The Radon transform (RT) on straight lines deals as mathematical foundation for many tomographic modalities (e.g. Xray scanner, Positron Emission Tomography), using only primary radiation. In this paper, we consider a new RT defined on a pair of half-lines forming a letter V, arising from the modeling a two-dimensional emission imaging process by Compton scattered gamma rays. We establish its analytic inverse, which is shown to support the feasibility of the reconstruction of a two-dimensional image from scattered radiation collected on a one-dimensional collimated camera. Moreover, a filtered back-projection inversion method is also constructed. Its main advantages are algorithmic efficiency and computational rapidity. We present numerical simulations to illustrate the working. To sum up, the V-line RT leads not only to a new imaging principle, but also to a new concept of detector with high energetic resolution capable to collect the scattered radiation.
An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm
Directory of Open Access Journals (Sweden)
Kai Hu
2015-01-01
Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.
Reversible Integer Wavelet Transform for the Joint of Image Encryption and Watermarking
Directory of Open Access Journals (Sweden)
Bin Wang
2015-01-01
Full Text Available In recent years, signal processing in the encrypted domain has attracted considerable research interest, especially embedding watermarking in encrypted image. In this work, a novel joint of image encryption and watermarking based on reversible integer wavelet transform is proposed. Firstly, the plain-image is encrypted by chaotic maps and reversible integer wavelet transform. Then the lossless watermarking is embedded in the encrypted image by reversible integer wavelet transform and histogram modification. Finally an encrypted image containing watermarking is obtained by the inverse integer wavelet transform. What is more, the original image and watermarking can be completely recovered by inverse process. Numerical experimental results and comparing with previous works show that the proposed scheme possesses higher security and embedding capacity than previous works. It is suitable for protecting the image information.
Image denoising algorithm of refuge chamber by combining wavelet transform and bilateral filtering
Institute of Scientific and Technical Information of China (English)
Zhang Weipeng
2013-01-01
In order to preferably identify infrared image of refuge chamber,reduce image noises of refuge chamber and retain more image details,we propose the method of combining two-dimensional discrete wavelet transform and bilateral denoising.First,the wavelet transform is adopted to decompose the image of refuge chamber,of which low frequency component remains unchanged.Then,three high-frequency components are treated by bilateral filtering,and the image is reconstructed.The result shows that the combination of bilateral filtering and wavelet transform for image denoising can better retain the details which are included in the image,while providing better visual effect.This is superior to using either bilateral filtering or wavelet transform alone.It is useful for perfecting emergency refuge system of coal.
Hadamard renormalized scalar field theory on anti-de Sitter space-time
Kent, Carl
2014-01-01
We consider a real massive free quantum scalar field with arbitrary curvature coupling on $n$-dimensional anti-de Sitter space-time. We use Hadamard renormalization to find the vacuum expectation values of the quadratic field fluctuations and the stress-energy tensor, presenting explicit results for $n=2$ to $n=11$ inclusive.
Directory of Open Access Journals (Sweden)
Atiq Ur Rehman
2016-01-01
Full Text Available We have discussed the generalization of Hermite-Hadamard inequality introduced by Lupaş for convex functions on coordinates defined in a rectangle from the plane. Also we define that mappings are related to it and their properties are discussed.
Hermite-Hadamard type inequalities for GA-s-convex functions
Directory of Open Access Journals (Sweden)
İmdat İşcan
2014-10-01
Full Text Available In this paper, The author introduces the concepts of the GA-s-convex functions in the first sense and second sense and establishes some integral inequalities of Hermite-Hadamard type related to the GA-s-convex functions. Some applications to special means of real numbers are also given.
Inequalities of Hadamard Type for r-Convex Functions in Carnot Groups
Institute of Scientific and Technical Information of China (English)
Ming-bao Sun; Xiao-ping Yang
2004-01-01
For a Carnot group G,we establish the relationship between extended mean values and r-convex functions which is introduced in this paper,which is a class of inequalities of Hadamard type for r-convex function on G.
Hadamard upper bound on optimum joint decoding capacity of Wyner Gaussian cellular MAC
Shakir, Muhammad
2011-09-01
This article presents an original analytical expression for an upper bound on the optimum joint decoding capacity of Wyner circular Gaussian cellular multiple access channel (C-GCMAC) for uniformly distributed mobile terminals (MTs). This upper bound is referred to as Hadamard upper bound (HUB) and is a novel application of the Hadamard inequality established by exploiting the Hadamard operation between the channel fading matrix G and the channel path gain matrix Ω. This article demonstrates that the actual capacity converges to the theoretical upper bound under the constraints like low signal-to-noise ratios and limiting channel path gain among the MTs and the respective base station of interest. In order to determine the usefulness of the HUB, the behavior of the theoretical upper bound is critically observed specially when the inter-cell and the intra-cell time sharing schemes are employed. In this context, we derive an analytical form of HUB by employing an approximation approach based on the estimation of probability density function of trace of Hadamard product of two matrices, i.e., G and Ω. A closed form of expression has been derived to capture the effect of the MT distribution on the optimum joint decoding capacity of C-GCMAC. This article demonstrates that the analytical HUB based on the proposed approximation approach converges to the theoretical upper bound results in the medium to high signal to noise ratio regime and shows a reasonably tighter bound on optimum joint decoding capacity of Wyner GCMAC.
Hermite-Hadamard and Simpson-Like Type Inequalities for Differentiable Harmonically Convex Functions
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İmdat İşcan
2014-01-01
Full Text Available A new identity for differentiable functions is derived. A consequence of the identity is that the author establishes some new general inequalities containing all of the Hermite-Hadamard and Simpson-like types for functions whose derivatives in absolute value at certain power are harmonically convex. Some applications to special means of real numbers are also given.
A quantum protocol to win the graph colouring game on all Hadamard graphs
Avis, D; Kikuchi, Y; Sasaki, Y; Avis, David; Hasegawa, Jun; Kikuchi, Yosuke; Sasaki, Yuuya
2005-01-01
This paper deals with graph colouring games, an example of pseudo-telepathy, in which two provers can convince a verifier that a graph $G$ is $c$-colourable where $c$ is less than the chromatic number of the graph. They win the game if they convince the verifier. It is known that the players cannot win if they share only classical information, but they can win in some cases by sharing entanglement. The smallest known graph where the players win in the quantum setting, but not in the classical setting, was found by Galliard, Tapp and Wolf and has 32,768 vertices. It is a connected component of the Hadamard graph $G_N$ with $N=c=16$. Their protocol applies only to Hadamard graphs where $N$ is a power of 2. We propose a protocol that applies to all Hadamard graphs. Combined with a result of Frankl, this shows that the players can win on any induced subgraph of $G_{12}$ having 1609 vertices, with $c=12$. Combined with a result of Frankl and Rodl, our result shows that all sufficiently large Hadamard graphs yield ...
Proximal Point Method for a Special Class of Nonconvex Functions on Hadamard Manifolds
Bento, G C; Oliveira, P R
2008-01-01
The proximal point method for special class of nonconvex optimization problems on Hadamard manifold is presented in this paper. The well definiteness of the sequence generated by the proximal point method is guaranteed. Moreover, is proved that each accumulation point of this sequence satisfies the necessary optimality conditions and, under additional assumptions, the convergence of it for a minimizer is obtained.
Twin image elimination in digital holography by combination of Fourier transformations
Choudhury, Debesh
2013-01-01
We present a new technique for removing twin image in in-line digital Fourier holography using a combination of Fourier transformations. Instead of recording only a Fourier transform hologram of the object, we propose to record a combined Fourier transform hologram by simultaneously recording the hologram of the Fourier transform and the inverse Fourier transform of the object with suitable weighting coefficients. Twin image is eliminated by appropriate inverse combined Fourier transformation and proper choice of the weighting coefficients. An optical configuration is presented for recording combined Fourier transform holograms. Simulations demonstrate the feasibility of twin image elimination. The hologram reconstruction is sensitive to phase aberrations of the object, thereby opening a way for holographic phase sensing.
Digital watermarking for still image based on discrete fractional fourier transform
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Presents a digital watermarking technique based on discrete fractional Fourier transform(DFRFT), discusses the transformation of the original image by DFRFT, and the modification of DFRFT coefficients of the original image by the information of watermark, and concludes from experimental results that the proposed tech nique is robust to lossy compression attack.
Multispectral and panchromatic image fusion based on unsubsampled contourlet transform
Liu, Hui; Yuan, Yan; Su, Lijuan; Hu, Liang; Zhang, Siyuan
2013-12-01
In order to achieve the high-resolution multispectral image, we proposed an algorithm for MS image and PAN image fusion based on NSCT and improved fusion rule. This method takes into account two aspects, the spectral similarity between fused image and the original MS image and enhancing the spatial resolution of the fused image. According to local spectral similarity between MS and PAN images, it can help to select high frequency detail coefficients from PAN image, which are injected into MS image then. Thus, spectral distortion is limited; the spatial resolution is enhanced. The experimental results demonstrate that the proposed fusion algorithm perform some improvements in integrating MS and PAN images.
Image fusion based on nonsubsampled contourlet transform for infrared and visible light image
Adu, Jianhua; Gan, Jianhong; Wang, Yan; Huang, Jian
2013-11-01
In this paper, a new method based on nonsubsampled contourlet transform (NSCT) is proposed to fuse the infrared image and the visible light image, which will produce a new fused image by which the target can be identified more easily. Firstly, two original images were decomposed into low frequency subband coefficients and the bandpass direction subband coefficients by using NSCT. Secondly, the selection of the low frequency subband coefficient and the bandpass direction subband coefficient is discussed in detail. The low frequency subband coefficients are selected based on the regional visual characteristics. For the selection of bandpass direction subband coefficients, this paper proposes a minimum regional cross-gradient method, and the cross-gradient is gained by calculating the gradient between the pixel of bandpass subbands and the adjacent pixel in the fused image of the low-frequency components. Comparison experiments have been performed on different image sets, and experimental results demonstrate that the proposed method performs better in both subjective and objective qualities.
Image processing with the radial Hilbert transform of photo-thermal imaging for carious detection
El-Sharkawy, Yasser H.
2014-03-01
Knowledge of heat transfer in biological bodies has many diagnostic and therapeutic applications involving either raising or lowering of temperature, and often requires precise monitoring of the spatial distribution of thermal histories that are produced during a treatment protocol. The present paper therefore aims to design and implementation of laser therapeutic and imaging system used for carious tracking and drilling by develop a mathematical algorithm using Hilbert transform for edge detection of photo-thermal imaging. photothermal imaging has the ability to penetrate and yield information about an opaque medium well beyond the range of conventional optical imaging. Owing to this ability, Q- switching Nd:YAG laser at wavelength 1064 nm has been extensively used in human teeth to study the sub-surface deposition of laser radiation. The high absorption coefficient of the carious rather than normal region rise its temperature generating IR thermal radiation captured by high resolution thermal camera. Changing the pulse repetition frequency of the laser pulses affects the penetration depth of the laser, which can provide three-dimensional (3D) images in arbitrary planes and allow imaging deep within a solid tissue.
Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub-Pixel Image Registration
2003-03-01
AFIT/GE/ENG/03-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION THESIS Daniel L. Ward Second...position of the United States Air Force, Department of Defense, or the United States Government. AFIT/GE/ENG/03-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED...O3-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION THESIS Daniel Lee Ward, B.S.E.E. Second
Pisani, Marco; Zucco, Massimo
2009-05-11
An imaging spectrometer based on a Fabry-Perot interferometer is presented. The Fabry-Perot interferometer scans the mirror distance up to contact and the intensity modulated light signal is transformed using a Fourier Transform based algorithm, as the Michelson based Fourier Transform Spectrometers does. The resulting instrument has the advantage of a compact, high numerical aperture, high luminosity hyperspectral imaging device. Theory of operation is described along with one experimental realization and preliminary results.
Implementation of Texture Based Image Retrieval Using M-band Wavelet Transform
Institute of Scientific and Technical Information of China (English)
LiaoYa-li; Yangyan; CaoYang
2003-01-01
Wavelet transform has attracted attention because it is a very useful tool for signal analyzing. As a fundamental characteristic of an image, texture traits play an important role in the human vision system for recognition and interpretation of images. The paper presents an approach to implement texture-based image retrieval using M-band wavelet transform. Firstly the traditional 2-band wavelet is extended to M-band wavelet transform. Then the wavelet moments are computed by M-band wavelet coefficients in the wavelet domain. The set of wavelet moments forms the feature vector related to the texture distribution of each wavelet images. The distances between the feature vectors describe the similarities of different images. The experimental result shows that the M-band wavelet moment features of the images are effective for image indexing.The retrieval method has lower computational complexity, yet it is capable of giving better retrieval performance for a given medical image database.
Implementation of Texture Based Image Retrieval Using M-band Wavelet Transform
Institute of Scientific and Technical Information of China (English)
Liao Ya-li; Yang Yan; Cao Yang
2003-01-01
Wavelet transform has attracted attention because it is a very useful tool for signal analyzing. As a fundamental characteristic of an image, texture traits play an important role in the human vision system for recognition and interpretation of images. The paper presents an approach to implement texture-based image retrieval using M-band wavelet transform. Firstly the traditional 2-band wavelet is extended to M-band wavelet transform. Then the wavelet moments are computed by M-band wavelet coefficients in the wavelet domain. The set of wavelet moments forms the feature vector related to the texture distribution of each wavelet images. The distances between the feature vectors describe the similarities of different images. The experimental result shows that the M-band wavelet moment features of the images are effective for image indexing. The retrieval method has lower computational complexity, yet it is capable of giving better retrieval performance for a given medical image database.
Bhowmik, Mrinal Kanti; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas
2010-01-01
This paper investigates the multiresolution level-1 and level-2 Quotient based Fusion of thermal and visual images. In the proposed system, the method-1 namely "Decompose then Quotient Fuse Level-1" and the method-2 namely "Decompose-Reconstruct then Quotient Fuse Level-2" both work on wavelet transformations of the visual and thermal face images. The wavelet transform is well-suited to manage different image resolution and allows the image decomposition in different kinds of coefficients, while preserving the image information without any loss. This approach is based on a definition of an illumination invariant signature image which enables an analytic generation of the image space with varying illumination. The quotient fused images are passed through Principal Component Analysis (PCA) for dimension reduction and then those images are classified using a multi-layer perceptron (MLP). The performances of both the methods have been evaluated using OTCBVS and IRIS databases. All the different classes have been ...
Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging.
Zhang, Shuanghui; Liu, Yongxiang; Li, Xiang; Bi, Guoan
2016-04-28
This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP) estimation and the maximum likelihood estimation (MLE) are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT) and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression.
Institute of Scientific and Technical Information of China (English)
CHEN Lin-Fei; ZHAO Dao-Mu
2006-01-01
@@ We propose a new method to add different images together by optical implementation that is realized by the multi-exposure based on fractional Fourier transform hologram. Partial image fusion is proposed and realized by this method. Multiple images encryption can also be implemented by the multi-exposure of the hologram based on fractional Fourier transform. Computer simulations prove that this method is valid.
Directory of Open Access Journals (Sweden)
R. Krishnamoorthy
2012-05-01
Full Text Available In this paper, a new lossy to lossless image coding scheme combined with Orthogonal Polynomials Transform and Integer Wavelet Transform is proposed. The Lifting Scheme based Integer Wavelet Transform (LS-IWT is first applied on the image in order to reduce the blocking artifact and memory demand. The Embedded Zero tree Wavelet (EZW subband coding algorithm is used in this proposed work for progressive image coding which achieves efficient bit rate reduction. The computational complexity of lower subband coding of EZW algorithm is reduced in this proposed work with a new integer based Orthogonal Polynomials transform coding. The normalization and mapping are done on the subband of the image for exploiting the subjective redundancy and the zero tree structure is obtained for EZW coding and so the computation complexity is greatly reduced in this proposed work. The experimental results of the proposed technique also show that the efficient bit rate reduction is achieved for both lossy and lossless compression when compared with existing techniques.
New algorithms for processing images in the transform-compressed domain
Chang, Shih-Fu
1995-04-01
Future multimedia applications involving images and video will require technologies enabling users to manipulate image and video data as flexibly as traditional text and numerical data. However, vast amounts of image and video data mandate the use of image compression, which makes direct manipulation and editing of image data difficult. To explore the maximum synergistic relationships between image manipulation and compression, we extend our prior study of transform-domain image manipulation techniques to more complicated image operations such as rotation, shearing, and line-wise special effects. We propose to extract the individual image rows (columns) first and then apply the previously proposed transform-domain filtering and scaling techniques. The transform-domain rotation and line-wise operations can be accomplished by calculating the summation of products of nonzero transform coefficients and some precalculated special matrices. The overall computational complexity depends on the compression rate of the input images. For highly-compressed images, the transform-domain technique provides great potential for improving the computation speed.
Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform
Bai, Xiangzhi; Zhou, Fugen; Xue, Bindang
2011-03-01
Infrared imaging sensor is sensitive to the variation of imaging environment, which may affect the quality of the obtained images and blur the regions of interest in infrared image. So, it is very important to enhance infrared image. In infrared image, the gray values of the regions of interest are bright or dim image regions, which are different from the surrounding regions. The new top-hat transform could extract image regions which are different from its surrounding regions. In light of this, an infrared image enhancement algorithm through contrast enhancement is proposed in this paper based on multiscale new top-hat transform. Firstly, the multiscale white and black new top-hat transforms are used to extract the multiscale light and dark infrared image regions. Then, the final light and dark infrared image regions for image enhancement are constructed by using the extracted multiscale light and dark infrared image regions. Finally, the contrast of the infrared image is enhanced through a power strategy. Experimental results on different infrared images show that the proposed algorithm could well enhance infrared image and make the possible interested targets brighter, which is very helpful for target detection and recognition.
MULTI-SPECTRAL AND HYPERSPECTRAL IMAGE FUSION USING 3-D WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
Zhang Yifan; He Mingyi
2007-01-01
Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspectral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR) method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.
Image Registration Using Log Polar Transform and Fft Based Scale Invariant
Directory of Open Access Journals (Sweden)
Mr. Divyang Patel,
2014-05-01
Full Text Available Image registration is the fundamental task used to match two or more partially overlapping images taken, for example, at different times, from different sensors, or from different viewpoints and stitch these images into one panoramic image comprising the whole scene. It is a fundamental image processing technique and is very useful in integrating information from different sensors, finding changes in images taken at different times, inferring three-dimensional information from stereo images, and recognizing model-based objects. Some techniques are proposed to find a geometrical transformation that relates the points of an image to their corresponding points of another image. To register two images, the coordinate transformation between a pair of images must be found. In this paper, we have proposed an algorithm that is based on Log-Polar Transform and first we roughly estimate the angle, scale and translation between two images. The proposed algorithm can recover scale value up to 5.85. The robustness of this algorithm is verified on different images with similarity transformation and in the presence of noise.
Iterative Refinement of Transformation Parameters for Image Registration
Jharna Majumdar; B. Vanathy; S. Lekshmi
2010-01-01
Image registration is an important process in high-level image interpretation systems developed for civilian and defense applications. Registration is carried out in two phases: namely feature extraction and feature correspondence. The basic building block of feature based image registration scheme involves matching feature points that are extracted from a sensed image to their counter parts in the reference image. Features may be control points, corners, junctions or interest points. The obj...
CT and MR Image Fusion Scheme in Nonsubsampled Contourlet Transform Domain
Ganasala, Padma; Kumar, Vinod
2014-01-01
Fusion of CT and MR images allows simultaneous visualization of details of bony anatomy provided by CT image and details of soft tissue anatomy provided by MR image. This helps the radiologist for the precise diagnosis of disease and for more effective interventional treatment procedures. This paper aims at designing an effective CT and MR image fusion method. In the proposed method, first source images are decomposed by using nonsubsampled contourlet transform (NSCT) which is a shift-invaria...
Chen, Chenglong; Ni, Jiangqun; Shen, Zhaoyi; Shi, Yun Qing
2017-06-01
Geometric transformations, such as resizing and rotation, are almost always needed when two or more images are spliced together to create convincing image forgeries. In recent years, researchers have developed many digital forensic techniques to identify these operations. Most previous works in this area focus on the analysis of images that have undergone single geometric transformations, e.g., resizing or rotation. In several recent works, researchers have addressed yet another practical and realistic situation: successive geometric transformations, e.g., repeated resizing, resizing-rotation, rotation-resizing, and repeated rotation. We will also concentrate on this topic in this paper. Specifically, we present an in-depth analysis in the frequency domain of the second-order statistics of the geometrically transformed images. We give an exact formulation of how the parameters of the first and second geometric transformations influence the appearance of periodic artifacts. The expected positions of characteristic resampling peaks are analytically derived. The theory developed here helps to address the gap left by previous works on this topic and is useful for image security and authentication, in particular, the forensics of geometric transformations in digital images. As an application of the developed theory, we present an effective method that allows one to distinguish between the aforementioned four different processing chains. The proposed method can further estimate all the geometric transformation parameters. This may provide useful clues for image forgery detection.
National Research Council Canada - National Science Library
Heilmann, René; Gräfe, Markus; Nolte, Stefan; Szameit, Alexander
2014-01-01
.... In our work we close this gap and present Hadamard, Pauli-X, and rotation gates of high fidelity for photonic polarisation qubits on chip by employing a reorientation of the optical axis of birefringent waveguides...
Directory of Open Access Journals (Sweden)
Banyat Sroysang
2014-01-01
Full Text Available Some new Hermite-Hadamard type inequalities for differentiable convex functions were presented by Xi and Qi. In this paper, we present new generalizations on the Xi-Qi inequalities.
A new method of medical image fusion based on nonsubsampled contourlet transform
Xu, Xuebin; Zhang, Xinman; Zhang, Deyun
2008-12-01
To improve the normal medical image fusion algorithm in order to avoid the loss of the detailed information in the processes of medical image fusion, a multiscale medical image fusion method based on nonsubsampled contourlet transform(NSCT) is proposed in this paper. First, the source images(MRI and CT images) are decomposed by using nonsubsampled contourlet transform. Then, the details of contourlet coefficients are fused on each corresponding levels with a vision feature fusion operator. Finally, the fused image will be obtained by taking the inverse nonsubsampled contourlet transformation. The experimental results show that the effect of the nonsubsampled contourlet-based method is obviously improved, and the proposed method can effectively preserve the detailed information of the source images.
A Fresnelet-Based Encryption of Medical Images using Arnold Transform
Directory of Open Access Journals (Sweden)
Muhammad Nazeer
2013-04-01
Full Text Available Medical images are commonly stored in digital media and transmitted via Internet for certain uses. If a medical information image alters, this can lead to a wrong diagnosis which may create a serious health problem. Moreover, medical images in digital form can easily be modified by wiping off or adding small pieces of information intentionally for certain illegal purposes. Hence, the reliability of medical images is an important criterion in a hospital information system. In this paper, the Fresnelet transform is employed along with appropriate handling of the Arnold transform and the discrete cosine transform to provide secure distribution of medical images. This method presents a new data hiding system in which steganography and cryptography are used to prevent unauthorized data access. The experimental results exhibit high imperceptibility for embedded images and significant encryption of information images.
Speckle reduction algorithm for laser underwater image based on curvelet transform
Institute of Scientific and Technical Information of China (English)
Wei Ni; Baolong Guo; Liu Yang; Peiyan Fei
2006-01-01
@@ Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information.
Application of adaptive wavelet transforms via lifting in image data compression
Ye, Shujiang; Zhang, Ye; Liu, Baisen
2008-10-01
The adaptive wavelet transforms via lifting is proposed. In the transform, update filter is selected by the signal's character. Perfect reconstruction is possible without any overhead cost. To make sure the system's stability, in the lifting scheme of adaptive wavelet, update step is placed before prediction step. The Adaptive wavelet transforms via lifting is benefit for the image compression, because of the high stability, the small coefficients of high frequency parts, and the perfect reconstruction. With the adaptive wavelet transforms via lifting and the SPIHT, the image compression is realized in this paper, and the result is pleasant.
A method of image compression based on lifting wavelet transform and modified SPIHT
Lv, Shiliang; Wang, Xiaoqian; Liu, Jinguo
2016-11-01
In order to improve the efficiency of remote sensing image data storage and transmission we present a method of the image compression based on lifting scheme and modified SPIHT(set partitioning in hierarchical trees) by the design of FPGA program, which realized to improve SPIHT and enhance the wavelet transform image compression. The lifting Discrete Wavelet Transform (DWT) architecture has been selected for exploiting the correlation among the image pixels. In addition, we provide a study on what storage elements are required for the wavelet coefficients. We present lena's image using the 3/5 lifting scheme.
Assessment of illumination conditions in a single-pixel imaging configuration
Garoi, Florin; Udrea, Cristian; Damian, Cristian; Logofǎtu, Petre C.; Colţuc, Daniela
2016-12-01
Single-pixel imaging based on multiplexing is a promising technique, especially in applications where 2D detectors or raster scanning imaging are not readily applicable. With this method, Hadamard masks are projected on a spatial light modulator to encode an incident scene and a signal is recorded at the photodiode detector for each of these masks. Ultimately, the image is reconstructed on the computer by applying the inverse transform matrix. Thus, various algorithms were optimized and several spatial light modulators already characterized for such a task. This work analyses the imaging quality of such a single-pixel arrangement, when various illumination conditions are used. More precisely, the main comparison is made between coherent and incoherent ("white light") illumination and between two multiplexing methods, namely Hadamard and Scanning. The quality of the images is assessed by calculating their SNR, using two relations. The results show better images are obtained with "white light" illumination for the first method and coherent one for the second.
A graph theory practice on transformed image: a random image steganography.
Thanikaiselvan, V; Arulmozhivarman, P; Subashanthini, S; Amirtharajan, Rengarajan
2013-01-01
Modern day information age is enriched with the advanced network communication expertise but unfortunately at the same time encounters infinite security issues when dealing with secret and/or private information. The storage and transmission of the secret information become highly essential and have led to a deluge of research in this field. In this paper, an optimistic effort has been taken to combine graceful graph along with integer wavelet transform (IWT) to implement random image steganography for secure communication. The implementation part begins with the conversion of cover image into wavelet coefficients through IWT and is followed by embedding secret image in the randomly selected coefficients through graph theory. Finally stegoimage is obtained by applying inverse IWT. This method provides a maximum of 44 dB peak signal to noise ratio (PSNR) for 266646 bits. Thus, the proposed method gives high imperceptibility through high PSNR value and high embedding capacity in the cover image due to adaptive embedding scheme and high robustness against blind attack through graph theoretic random selection of coefficients.
Image Enhancement and Background Detection Using Morphological Transformation
Directory of Open Access Journals (Sweden)
Nikesh T. Gadare
2014-02-01
Full Text Available This paper deals with enhancement of images and background detection using Mathematical Morphological [MM] theory on dark images. Due to poor lightening the background of the image is not clear. This image can be enhanced by lightening the back ground with various morphological operations. Basically, Weber’s Law Operator is used to analyze dark images which are carried out by two methods such as Image background detection by block analysis while second operator utilize opening by reconstruction to define multi background notion. Some Morphological operations such as (Erosion, Dilation, Compound operation such as Opening by reconstruction, Erosion-Dilation method and Block Analysis is used to detect the background of images. Analysis of above mention methods illustrated through the processing of images with different dark background images.
Using the generalized Radon transform for detection of curves in noisy images
DEFF Research Database (Denmark)
Toft, Peter Aundal
1996-01-01
In this paper the discrete generalized Radon transform will be investigated as a tool for detection of curves in noisy digital images. The discrete generalized Radon transform maps an image into a parameter domain, where curves following a specific parameterized curve form will correspond to a peak...... in the parameter domain. A major advantage of the generalized Radon transform is that the curves are allowed to intersect. This enables a thresholding algorithm in the parameter domain for simultaneous detection of curve parameters. A threshold level based on the noise level in the image is derived. A numerical...
PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform
Institute of Scientific and Technical Information of China (English)
LIU Meijie; DAI Yongshou; ZHANG Jie; ZHANG Xi; MENG Junmin; XIE Qinchuan
2015-01-01
Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral in-formation, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be im-proved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transfor-mation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar (ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensi-ty-saturation (HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue (RGB) space, and the optical image from the China-Brazil Earth Resources Satellite (CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis (PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea
An Image Hiding Scheme Using 3D Sawtooth Map and Discrete Wavelet Transform
Directory of Open Access Journals (Sweden)
Ruisong Ye
2012-07-01
Full Text Available An image encryption scheme based on the 3D sawtooth map is proposed in this paper. The 3D sawtooth map is utilized to generate chaotic orbits to permute the pixel positions and to generate pseudo-random gray value sequences to change the pixel gray values. The image encryption scheme is then applied to encrypt the secret image which will be imbedded in one host image. The encrypted secret image and the host image are transformed by the wavelet transform and then are merged in the frequency domain. Experimental results show that the stego-image looks visually identical to the original host one and the secret image can be effectively extracted upon image processing attacks, which demonstrates strong robustness against a variety of attacks.
Lossless image compression with projection-based and adaptive reversible integer wavelet transforms.
Deever, Aaron T; Hemami, Sheila S
2003-01-01
Reversible integer wavelet transforms are increasingly popular in lossless image compression, as evidenced by their use in the recently developed JPEG2000 image coding standard. In this paper, a projection-based technique is presented for decreasing the first-order entropy of transform coefficients and improving the lossless compression performance of reversible integer wavelet transforms. The projection technique is developed and used to predict a wavelet transform coefficient as a linear combination of other wavelet transform coefficients. It yields optimal fixed prediction steps for lifting-based wavelet transforms and unifies many wavelet-based lossless image compression results found in the literature. Additionally, the projection technique is used in an adaptive prediction scheme that varies the final prediction step of the lifting-based transform based on a modeling context. Compared to current fixed and adaptive lifting-based transforms, the projection technique produces improved reversible integer wavelet transforms with superior lossless compression performance. It also provides a generalized framework that explains and unifies many previous results in wavelet-based lossless image compression.
Regular Discrete Cosine Transform and its Application to Digital Images Representation
Directory of Open Access Journals (Sweden)
Yuri A. Gadzhiev
2011-06-01
Full Text Available Discrete cosine transform DCT-I, unlike DCT-II, does not concentrate the energy of a transformed vector sufficiently well, so it is not used practically for the purposes of digital image compression. By performing regular normalization of the basic cosine transform matrix, we obtain a discrete cosine transform which has the same cosine basis as DCT-I, coincides as DCT-I with its own inverse transform, but unlike DCT-I, it does not reduce the proper ability of cosine transform to the energy concentration. In this paper we consider briefly the properties of this transform, its possible integer implementation for the case of 8x8-matrix, its applications to the image itself and to the preliminary rgb colour space transformations, furthermore we investigate some models of quantization, perform an experiment for the estimation of the level of digital images compression and the quality achieved by use of this transform. This experiment shows that the transform can be sufficiently effective for practical use, but the question of its comparative effectiveness with respect to DCT-II remains open.
Multiple color-image fusion and watermarking based on optical interference and wavelet transform
Abuturab, Muhammad Rafiq
2017-02-01
A novel multiple color-image fusion and watermarking using optical interference and wavelet transform is proposed. In this method, each secret color image is encoded into three phase-only masks (POMs). One POM is constructed as user identity key and the other two POMs are generated as user identity key modulated by corresponding secret color image in gyrator transform domain without using any time-consuming iterative computations or post-processing of the POMs to remove inherent silhouette problem. The R, G, and B channels of different user identity keys POM are then individually multiplied to get three multiplex POMs, which are exploited as encrypted images. Similarly the R, G, and B channels of other two POMs are independently multiplied to obtain two sets of three multiplex POMs. The encrypted images are fused with gray-level cover image to produce the final encrypted image as watermarked image. The secret color images are shielded by encrypted images (which have no information about secret images) as well as cover image (which reveals no information about encrypted images). These two remarkable features of the proposed system drastically reduce the probability of the encrypted images to be searched and attacked. Each individual user has an identity key and two phase-only keys as three decryption keys besides transformation angles regarded as additional keys. Theoretical analysis and numerical simulation results validate the feasibility of the proposed method.
A mixed transform approach for efficient compression of medical images.
Ramaswamy, A; Mikhael, W B
1996-01-01
A novel technique is presented to compress medical data employing two or more mutually nonorthogonal transforms. Both lossy and lossless compression implementations are considered. The signal is first resolved into subsignals such that each subsignal is compactly represented in a particular transform domain. An efficient lossy representation of the signal is achieved by superimposing the dominant coefficients corresponding to each subsignal. The residual error, which is the difference between the original signal and the reconstructed signal is properly formulated. Adaptive algorithms in conjunction with an optimization strategy are developed to minimize this error. Both two-dimensional (2-D) and three-dimensional (3-D) approaches for the technique are developed. It is shown that for a given number of retained coefficients, the discrete cosine transform (DCT)-Walsh mixed transform representation yields a more compact representation than using DCT or Walsh alone. This lossy technique is further extended for the lossless case. The coefficients are quantized and the signal is reconstructed. The resulting reconstructed signal samples are rounded to the nearest integer and the modified residual error is computed. This error is transmitted employing a lossless technique such as the Huffman coding. It is shown that for a given number of retained coefficients, the mixed transforms again produces the smaller rms-modified residual error. The first-order entropy of the error is also smaller for the mixed-transforms technique than for the DCT, thus resulting in smaller length Huffman codes.
Directory of Open Access Journals (Sweden)
TAO Feixiang
2015-08-01
Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.
A new adaptive algorithm for image denoising based on curvelet transform
Chen, Musheng; Cai, Zhishan
2013-10-01
The purpose of this paper is to study a method of denoising images corrupted with additive white Gaussian noise. In this paper, the application of the time invariant discrete curvelet transform for noise reduction is considered. In curvelet transform, the frame elements are indexed by scale, orientation and location parameters. It is designed to represent edges and the singularities along curved paths more efficiently than the wavelet transform. Therefore, curvelet transform can get better results than wavelet method in image denoising. In general, image denoising imposes a compromise between noise reduction and preserving significant image details. To achieve a good performance in this respect, an efficient and adaptive image denoising method based on curvelet transform is presented in this paper. Firstly, the noisy image is decomposed into many levels to obtain different frequency sub-bands by curvelet transform. Secondly, efficient and adaptive threshold estimation based on generalized Gaussian distribution modeling of sub-band coefficients is used to remove the noisy coefficients. The choice of the threshold estimation is carried out by analyzing the standard deviation and threshold. Ultimately, invert the multi-scale decomposition to reconstruct the denoised image. Here, to prove the performance of the proposed method, the results are compared with other existent algorithms such as hard and soft threshold based on wavelet. The simulation results on several testing images indicate that the proposed method outperforms the other methods in peak signal to noise ratio and keeps better visual in edges information reservation as well. The results also suggest that curvelet transform can achieve a better performance than the wavelet transform in image denoising.
Directory of Open Access Journals (Sweden)
Min Wang
2015-01-01
Full Text Available This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD, with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts, with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with image rotations and the enhancement of the directional features: to filter the diagonal part, one needs first to rotate it 45 degrees and rotate it back after filtering. Finally, reconstruct the image from the low-frequency part and the filtered high-frequency parts by the inverse wavelet transform to get the final denoising image. Experiments show the effectiveness of this method, compared with relevant methods.
De-Noising SPECT Images from a Typical Collimator Using Wavelet Transform
Directory of Open Access Journals (Sweden)
Farshid Babapour Mofrad
2009-12-01
Full Text Available Introduction: SPECT is a diagnostic imaging technique the main disadvantage of which is the existence of Poisson noise. So far, different methods have been used by scientists to improve SPECT images. The Wavelet Transform is a new method for de-noising which is widely used for noise reduction and quality enhancement of images. The purpose of this paper is evaluation of noise reduction in SPECT images by wavelet. Material and Methods: To calculate and simulate noise in images, it is common in nuclear medicine to use Monte Carlo techniques. The SIMIND software was used to simulate SPECT images in this research. The simulated and real images formed using the current typical (hexagonal collimator were de-noised by different types of wavelets. Results: The best type of wavelet was selected for SPECT images. The results demonstrated that the best type of wavelet in the simulated and real images increased Signal to Noise Ratio (SNR by 33% and 45% respectively. Also, Coefficient of Variation (CV decreased by 77% and 71% respectively, while Contrast of Recovery (CR was reduced by only 4% and 9% respectively. Conclusion: Comparing the results for real SPECT images in this paper with previously acquired results in real PET images, it can be concluded that the images of both nuclear medicine systems using Wavelet Transform differ in SNR and CR by only 5% and 7% respectively, and in CV by about 20%. Therefore, wavelet transform is applicable for nuclear medicine image de-noising.
Institute of Scientific and Technical Information of China (English)
Changjiang Zhang; Xiaodong Wang; Haoran Zhang
2005-01-01
A new contrast enhancement algorithm for image is proposed employing wavelet neural network (WNN)and stationary wavelet transform (SWT). Incomplete Beta transform (IBT) is used to enhance the global contrast for image. In order to avoid the expensive time for traditional contrast enhancement algorithms,which search optimal gray transform parameters in the whole gray transform parameter space, a new criterion is proposed with gray level histogram. Contrast type for original image is determined employing the new criterion. Gray transform parameter space is given respectively according to different contrast types,which shrinks the parameter space greatly. Nonlinear transform parameters are searched by simulated annealing algorithm (SA) so as to obtain optimal gray transform parameters. Thus the searching direction and selection of initial values of simulated annealing is guided by the new parameter space. In order to calculate IBT in the whole image, a kind of WNN is proposed to approximate the IBT. Having enhanced the global contrast to input image, discrete SWT is done to the image which has been processed by previous global enhancement method, local contrast enhancement is implemented by a kind of nonlinear operator in the high frequency sub-band images of each decomposition level respectively. Experimental results show that the new algorithm is able to adaptively enhance the global contrast for the original image while it also extrudes the detail of the targets in the original image well. The computation complexity for the new algorithm is O(MN) log(MN), where M and N are width and height of the original image, respectively.
Krishnaveni, M; Subashini, P
2009-01-01
A new fangled method for ship wake detection in synthetic aperture radar (SAR) images is explored here. Most of the detection procedure applies the Radon transform as its properties outfit more than any other transformation for the detection purpose. But still it holds problems when the transform is applied to an image with a high level of noise. Here this paper articulates the combination between the radon transformation and the shrinkage methods which increase the mode of wake detection process. The latter shrinkage method with RT maximize the signal to noise ratio hence it leads to most optimal detection of lines in the SAR images. The originality mainly works on the denoising segment of the proposed algorithm. Experimental work outs are carried over both in simulated and real SAR images. The detection process is more adequate with the proposed method and improves better than the conventional methods.
Quantum image encryption based on generalized affine transform and logistic map
Liang, Hao-Ran; Tao, Xiang-Yang; Zhou, Nan-Run
2016-07-01
Quantum circuits of the generalized affine transform are devised based on the novel enhanced quantum representation of digital images. A novel quantum image encryption algorithm combining the generalized affine transform with logistic map is suggested. The gray-level information of the quantum image is encrypted by the XOR operation with a key generator controlled by the logistic map, while the position information of the quantum image is encoded by the generalized affine transform. The encryption keys include the independent control parameters used in the generalized affine transform and the logistic map. Thus, the key space is large enough to frustrate the possible brute-force attack. Numerical simulations and analyses indicate that the proposed algorithm is realizable, robust and has a better performance than its classical counterpart in terms of computational complexity.
On the optimum joint decoding capacity of wyner circular GCMAC by exploiting hadamard inequality
Shakir, Muhammad
2010-09-01
This paper presents an original expression of the theoretical upper bound for the optimum joint decoding capacity of Wyner Circular Gaussian Cellular Multiple Access Channel (C-GCMAC). This upper bound is a novel application of the Hadamard inequality established by exploiting the Hadamard operation between the channel fading (G) and channel slow gain (Ω) matrices. This paper demonstrates that the theoretical upper bound converges to the actual capacity for negligible channel slow gain among the mobile terminals and the base stations for the entire range of Signal to Noise Ratios (SNRs). The behaviour of the theoretical bound is critically observed when the intercell and the intra-cell time sharing schemes are employed. © 2010 IEEE.
Hadamard states for a scalar field in anti-de Sitter spacetime with arbitrary boundary conditions
Dappiaggi, Claudio
2016-01-01
We consider a real, massive scalar field on ${\\rm PAdS}_{d+1}$, the Poincar\\'e domain of the $(d+1)$-dimensional AdS spacetime. We first determine all admissible boundary conditions that can be applied on the conformal boundary, noting that there exist instances where "bound states" solutions are present. Then, we address the problem of constructing the two-point function for the ground state satisfying those boundary conditions, finding ultimately an explicit closed form. In addition, we investigate the singularities of the resulting two-point functions, showing that they are consistent with the requirement of being of Hadamard form in every globally hyperbolic subregion of ${\\rm PAdS}_{d+1}$ and proposing a new definition of Hadamard states which applies to ${\\rm PAdS}_{d+1}$.
Quantum computation with coherent spin states and the close Hadamard problem
Adcock, Mark R. A.; Høyer, Peter; Sanders, Barry C.
2016-04-01
We study a model of quantum computation based on the continuously parameterized yet finite-dimensional Hilbert space of a spin system. We explore the computational powers of this model by analyzing a pilot problem we refer to as the close Hadamard problem. We prove that the close Hadamard problem can be solved in the spin system model with arbitrarily small error probability in a constant number of oracle queries. We conclude that this model of quantum computation is suitable for solving certain types of problems. The model is effective for problems where symmetries between the structure of the information associated with the problem and the structure of the unitary operators employed in the quantum algorithm can be exploited.
Medical image compression with embedded-wavelet transform
Cheng, Po-Yuen; Lin, Freddie S.; Jannson, Tomasz
1997-10-01
The need for effective medical image compression and transmission techniques continues to grow because of the huge volume of radiological images captured each year. The limited bandwidth and efficiency of current networking systems cannot meet this need. In response, Physical Optics Corporation devised an efficient medical image management system to significantly reduce the storage space and transmission bandwidth required for digitized medical images. The major functions of this system are: (1) compressing medical imagery, using a visual-lossless coder, to reduce the storage space required; (2) transmitting image data progressively, to use the transmission bandwidth efficiently; and (3) indexing medical imagery according to image characteristics, to enable automatic content-based retrieval. A novel scalable wavelet-based image coder was developed to implement the system. In addition to its high compression, this approach is scalable in both image size and quality. The system provides dramatic solutions to many medical image handling problems. One application is the efficient storage and fast transmission of medical images over picture archiving and communication systems. In addition to reducing costs, the potential impact on improving the quality and responsiveness of health care delivery in the US is significant.
Contour Extraction in Prostate Ultrasound Images Using the Wavelet Transform and Snakes
2007-11-02
signal noise levels. In this paper we present a semi-automatic prostate contour extraction scheme, which is based on the wavelet transform and active...contour models, or snakes. The ultrasound image is first decomposed into edge naps at different resolutions via the wavelet transform . Seed points are
Directory of Open Access Journals (Sweden)
Mahavir Dhoka
2014-06-01
Full Text Available In recent years, data protection is one of important aspect because of cases like piracy, copyright and ownership issues. Digital watermark seems to be solution to the problem. In our paper, we proposed a method of invisible watermark to medical image using Biorthogonal wavelet filter and transformed domain watermark embedding. Generally watermark is embedded in original image either directly or in transform of original image. In our method, we transformed both original image and watermark using discrete wavelet transform and Biorthogonal wavelet filter coefficients. We specifically follow this method considering the case of medical images. As medical images are low contrast images and are taken at high precision with special equipment, so it is not expected that any one will claim for its ownership. Hence we tried to develop a method which will recover watermark through medical image considering any kind of attacks. We tested our method on multiple medical images and listed down results and comparison is made on basis of PSNR and normalised correlation (NC. From the values of NC, we concluded that our method gives better recovery of watermark from watermarked image.
Biomedical Image Processing Using FCM Algorithm Based on the Wavelet Transform
Institute of Scientific and Technical Information of China (English)
YAN Yu-hua; WANG Hui-min; LI Shi-pu
2004-01-01
An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced.
A maximum noise fraction transform with improved noise estimation for hyperspectral images
Institute of Scientific and Technical Information of China (English)
LIU Xiang; ZHANG Bing; GAO LianRu; CHEN DongMei
2009-01-01
Feature extraction is often performed to reduce spectral dimension of hyperspectral images before image classification.The maximum noise fraction (MNF) transform is one of the most commonly used spectral feature extraction methods.The spectral features in several bands of hyperspectral images are submerged by the noise.The MNF transform is advantageous over the principle component (PC) transform because it takes the noise information in the spatial domain into consideration.However,the experiments described in this paper demonstrate that classification accuracy is greatly influenced by the MNF transform when the ground objects are mixed together.The underlying mechanism of it is revealed and analyzed by mathematical theory.In order to improve the performance of classification after feature extraction when ground objects are mixed in hyperspectral images,a new MNF transform,with an Improved method of estimating hyperspectral Image noise covariance matrix (NCM),is presented.This improved MNF transform is applied to both the simulated data and real data.The results show that compared with the classical MNF transform,this new method enhanced the ability of feature extraction and increased classification accuracy.
Image Compression Using Wavelet Transform Based on the Lifting Scheme and its Implementation
Directory of Open Access Journals (Sweden)
A Alice Blessie
2011-05-01
Full Text Available This paper presents image compression using 9/7 wavelet transform based on the lifting scheme. This is simulated using ISE simulator and implemented in FPGA. The 9/7 wavelet transform performs well for the low frequency components. Implementation in FPGA is since because of its partial reconfiguration. The project mainly aims at retrieving the smooth images without any loss. This design may be used for both lossy and lossless compression.
The Fermionic Signature Operator and Hadamard States in the Presence of a Plane Electromagnetic Wave
Finster, Felix
2016-01-01
We give a non-perturbative construction of a distinguished state for the quantized Dirac field in Minkowski space in the presence of a time-dependent external field of the form of a plane electromagnetic wave. By explicit computation of the fermionic signature operator, it is shown that the Dirac operator has the strong mass oscillation property. We prove that the resulting fermionic projector state is a Hadamard state.
Directory of Open Access Journals (Sweden)
Jessada Tariboon
2014-01-01
Full Text Available We study existence and uniqueness of solutions for a problem consisting of nonlinear Langevin equation of Hadamard-Caputo type fractional derivatives with nonlocal fractional integral conditions. A variety of fixed point theorems are used, such as Banach’s fixed point theorem, Krasnoselskii’s fixed point theorem, Leray-Schauder’s nonlinear alternative, and Leray-Schauder’s degree theory. Enlightening examples illustrating the obtained results are also presented.
Menke, Jan; Helms, Gunther; Larsen, Jörg
2010-01-01
The purpose of this experimental study was to evaluate whether the effective k-space coverage of MR images can in principle be viewed after multidimensional Fourier transform back to k-space. A water-soaked sponge phantom providing homogeneous k-space pattern was imaged with different standard MR sequences, utilizing elliptic acquisitions, partial-Fourier acquisitions and elliptic filtering as imaging examples. The resulting MR images were Fourier-transformed to the spatial frequency domain (the k-space) to visualize their effective k-space coverage. These frequency domain images are named "backtransformed k-space images." For a quantitative assessment, the sponge phantom was imaged with three-dimensional partial-Fourier sequences while varying the partial acquisition parameters in slice and phase direction. By linear regression analysis, the k-space coverage as expected from the sequence menu parameters was compared to the effective k-space coverage as observed in the backtransformed k-space images. The k-space coverage of elliptic and partial-Fourier acquisitions became visible in the backtransformed k-space images, as well as the effect of elliptic filtering. The expected and the observed k-space coverage showed a highly significant correlation (r=.99, PFourier-transforming MR images of a sponge phantom back to k-space. This method could be used for several purposes including sequence parameter optimization, basic imaging research, and to enhance a visual understanding of k-space, especially in three-dimensional MR imaging.
Revealing of steganograms with data, which are hidden in transformation domain of digital images
Directory of Open Access Journals (Sweden)
D. O. Progonov
2014-06-01
Full Text Available Introduction. The paper is devoted to analysis the correlation and fractal properties of bright¬ness fluctuation the steganograms. The case of multistage embedding the modified stegodata in transformation domain of digital images is considered. Data hiding in transformation domain of digital images. The Gunjal method of message hiding in digital images is investigated. The method is based on usage of Arnold transform for mangling the stegodata. Embedding of modified message is carried out by applying of two-dimensional discrete wavelet transform and block two-dimensional discrete cosine transform. Multifractal detrended fluctuation analysis of digital images. The correlation and fractal characteristics of the digital images noise components are consider. It is shown the advanta¬ges of multifractal detrended fluctuation analysis over classic detrended fluctuation analysis – the representation of signal fluctuation as set of monofractal aggregates with corresponding generalized Hurst exponents. Conclusion. Data hiding in transformation domain of digital images leads to smoothing of spectrum the generalized Hurst exponents and narrowing the multifractal spectrum of fluctuations. It is established that ascertained disclosure features do not depend on degree of container filling.
Non-moving Hadamard matrix diffusers for speckle reduction in laser pico-projectors.
Thomas, Weston; Middlebrook, Christopher
2014-12-12
Personal electronic devices such as cell phones and tablets continue to decrease in size while the number of features and add-ons keep increasing. One particular feature of great interest is an integrated projector system. Laser pico-projectors have been considered, but the technology has not been developed enough to warrant integration. With new advancements in diode technology and MEMS devices, laser-based projection is currently being advanced for pico-projectors. A primary problem encountered when using a pico-projector is coherent interference known as speckle. Laser speckle can lead to eye irritation and headaches after prolonged viewing. Diffractive optical elements known as diffusers have been examined as a means to lower speckle contrast. This paper presents a binary diffuser known as a Hadamard matrix diffuser. Using two static in-line Hadamard diffusers eliminates the need for rotation or vibration of the diffuser for temporal averaging. Two Hadamard diffusers were fabricated and contrast values measured showing good agreement with theory and simulated values.
Non-moving Hadamard matrix diffusers for speckle reduction in laser pico-projectors
Thomas, Weston; Middlebrook, Christopher
2014-12-01
Personal electronic devices such as cell phones and tablets continue to decrease in size while the number of features and add-ons keep increasing. One particular feature of great interest is an integrated projector system. Laser pico-projectors have been considered, but the technology has not been developed enough to warrant integration. With new advancements in diode technology and MEMS devices, laser-based projection is currently being advanced for pico-projectors. A primary problem encountered when using a pico-projector is coherent interference known as speckle. Laser speckle can lead to eye irritation and headaches after prolonged viewing. Diffractive optical elements known as diffusers have been examined as a means to lower speckle contrast. This paper presents a binary diffuser known as a Hadamard matrix diffuser. Using two static in-line Hadamard diffusers eliminates the need for rotation or vibration of the diffuser for temporal averaging. Two Hadamard diffusers were fabricated and contrast values measured showing good agreement with theory and simulated values.
Kakita, Veera Mohana Rao; Kupče, Eriks; Bharatam, Jagadeesh
2015-02-01
Unambiguous measurement of homonuclear scalar couplings (J) in multi-spin scalar network systems is not straightforward. Further, the direct measurement of J-couplings is obscured in solid-state samples due to the dipolar and chemical shift anisotropy (CSA)-dominated line broadening, even under the magic angle spinning (MAS). We present a new multiple frequency selective spin-echo method based on Hadamard matrix encoding, for simultaneous measurement of multiple homonuclear scalar couplings (J) in the solid-state. In contrast to the Hadamard encoded selective excitation schemes known for the solution-state, herein the selectivity is achieved during refocusing period. The Hadamard encoded refocusing scheme concurrently allows to create the spin-spin commutation property between number of spin-pairs of choice in uniformly labelled molecules, which, therefore avoids (1) the repetition of the double selective refocusing experiments for each spin-pair and (2) the synthesis of expensive selective labelled molecules. The experimental scheme is exemplified for determining (1)JCC and (3)JCC values in (13)C6l-Histidine.HCl molecule, which are found to be in excellent agreement with those measured in conventional double frequency selective refocusing mode as well as in the solution-state. This method can be simply extended to 2D/3D pulse schemes and be applied to small bio-molecular solids.
Fitzpatrick, J. Michael; Pickens, David R.; Mandava, Venkateswara R.; Grefenstette, John J.
1988-06-01
In the diagnosis of arteriosclerosis, radio-opaque dye is injected into the interior of the arteries to make them visible. Because of its increased contrast sensitivity, digital subtraction angiography has the potential for providing diagnostic images of arteries with reduced dye volumes. In the conventional technique, a mask image, acquired before the introduction of the dye, is subtracted from the contrast image, acquired after the dye is introduced, to produce a difference image in which only the dye in the arteries is visible. The usefulness of this technique has been severely limited by the image degradation caused by patient motion during image acquisition. This motion produces artifacts in the difference image that obscure the arteries. One technique for dealing with this problem is to reduce the degradation by means of image registration. The registration is carried out by means of a geometrical transformation of the mask image before subtraction so that it is in registration with the contrast image. This paper describes our technique for determining an optimal transformation. We employ a one-to-one elastic mapping and the Jacobian of that mapping to produce a geometrical image transformation. We choose a parameterized class of such mappings and use a heuristic search algorithm to optimize the parameters to minimize the severity of the motion artifacts. To increase the speed of the optimization process we use a statistical image comparison technique that provides a quick approximate evaluation of each image transformation. We present the experimental results of the application of our registration system to mask-contrast pairs, for images acquired from a specially designed phantom (described in a companion paper), and for clinical images.
Comparison on Integer Wavelet Transforms in Spherical Wavelet Based Image Based Relighting
Institute of Scientific and Technical Information of China (English)
WANGZe; LEEYin; LEUNGChising; WONGTientsin; ZHUYisheng
2003-01-01
To provide a good quality rendering in the Image based relighting (IBL) system, tremendous reference images under various illumination conditions are needed. Therefore data compression is essential to enable interactive action. And the rendering speed is another crucial consideration for real applications. Based on Spherical wavelet transform (SWT), this paper presents a quick representation method with Integer wavelet transform (IWT) for the IBL system. It focuses on comparison on different IWTs with the Embedded zerotree wavelet (EZW) used in the IBL system. The whole compression procedure contains two major compression steps. Firstly, SWT is applied to consider the correlation among different reference images. Secondly, the SW transformed images are compressed with IWT based image compression approach. Two IWTs are used and good results are showed in the simulations.
Dual tree complex wavelet transform based denoising of optical microscopy images.
Bal, Ufuk
2012-12-01
Photon shot noise is the main noise source of optical microscopy images and can be modeled by a Poisson process. Several discrete wavelet transform based methods have been proposed in the literature for denoising images corrupted by Poisson noise. However, the discrete wavelet transform (DWT) has disadvantages such as shift variance, aliasing, and lack of directional selectivity. To overcome these problems, a dual tree complex wavelet transform is used in our proposed denoising algorithm. Our denoising algorithm is based on the assumption that for the Poisson noise case threshold values for wavelet coefficients can be estimated from the approximation coefficients. Our proposed method was compared with one of the state of the art denoising algorithms. Better results were obtained by using the proposed algorithm in terms of image quality metrics. Furthermore, the contrast enhancement effect of the proposed method on collagen fıber images is examined. Our method allows fast and efficient enhancement of images obtained under low light intensity conditions.
LFMCW based MIMO imaging processing with keystone transform
Dorp, P. van
2013-01-01
In this paper, a new signal processing technique for Multiple-Input Multiple-Output (MIMO) image processing of a Linear Frequency-Modulated Continuous Wave (LFMCW) automotive radar was developed. The image is the range-speed-direction data cube. The technique comprises two improvements to the
Multiple information encryption by user-image-based gyrator transform hologram
Abuturab, Muhammad Rafiq
2017-05-01
A novel multiple information encryption by user-image-based gyrator transform hologram is proposed. In encryption process, each channel of the user image is phase encoded, modulated by random phase function and then gyrator transformed to get the gyrator spectrum of user image. Subsequently, each channel of the secret image is normalized, phase encoded, multiplied by modulated user image, and then gyrator transformed to obtain the gyrator spectrum of secret image. The encrypted digital hologram is recorded by the interference between the gyrator spectrum of user image and the spherical wave function. Similarly, the digital hologram for decryption is recorded by the interference between the gyrator spectrum of secret image and the spherical wave function. The multiple encrypted digital holograms are multiplexed into a final encoded hologram and the corresponding digital holograms for decryption are multiplexed into a final hologram for decryption. The wavelength and radius of the spherical wave function, and angle of gyrator transform are all essential keys for decryption. The proposed system has two main features. First, the encrypted hologram has no information about secret image. Second, the hologram for decryption used as identification key. Consequently the two marked security layers of information protection are achieved. The proposal can be realized by optoelectronic system. Numerical simulation results demonstrate the feasibility and security of the proposed technique.
Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges
Lemeshewsky, George P.; Schowengerdt, Robert A.
2000-01-01
Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.
Shinbori, Eiji; Takagi, Mikio
1992-11-01
A new image magnification method, called 'IM-GPDCT' (image magnification applying the Gerchberg-Papoulis (GP) iterative algorithm with discrete cosine transform (DCT)), is described and its performance evaluated. This method markedly improves image quality of a magnified image using a concept which restores the spatial high frequencies which are conventionally lost due to use of a low pass filter. These frequencies are restored using two known constraints applied during iterative DCT: (1) correct information in a passband is known and (2) the spatial extent of an image is finite. Simulation results show that the IM- GPDCT outperforms three conventional interpolation methods from both a restoration error and image quality standpoint.
A new Watermarking System based on Discrete Cosine Transform (DCT) in color biometric images.
Dogan, Sengul; Tuncer, Turker; Avci, Engin; Gulten, Arif
2012-08-01
This paper recommend a biometric color images hiding approach An Watermarking System based on Discrete Cosine Transform (DCT), which is used to protect the security and integrity of transmitted biometric color images. Watermarking is a very important hiding information (audio, video, color image, gray image) technique. It is commonly used on digital objects together with the developing technology in the last few years. One of the common methods used for hiding information on image files is DCT method which used in the frequency domain. In this study, DCT methods in order to embed watermark data into face images, without corrupting their features.
Implementation of the 2-D Wavelet Transform into FPGA for Image
León, M.; Barba, L.; Vargas, L.; Torres, C. O.
2011-01-01
This paper presents a hardware system implementation of the of discrete wavelet transform algoritm in two dimensions for FPGA, using the Daubechies filter family of order 2 (db2). The decomposition algorithm of this transform is designed and simulated with the Hardware Description Language VHDL and is implemented in a programmable logic device (FPGA) XC3S1200E reference, Spartan IIIE family, by Xilinx, take advantage the parallels properties of these gives us and speeds processing that can reach them. The architecture is evaluated using images input of different sizes. This implementation is done with the aim of developing a future images encryption hardware system using wavelet transform for security information.
Grid-Based Fourier Transform Phase Contrast Imaging
Tahir, Sajjad
Low contrast in x-ray attenuation imaging between different materials of low electron density is a limitation of traditional x-ray radiography. Phase contrast imaging offers the potential to improve the contrast between such materials, but due to the requirements on the spatial coherence of the x-ray beam, practical implementation of such systems with tabletop (i.e. non-synchrotron) sources has been limited. One recently developed phase imaging technique employs multiple fine-pitched gratings. However, the strict manufacturing tolerances and precise alignment requirements have limited the widespread adoption of grating-based techniques. In this work, we have investigated a technique recently demonstrated by Bennett et al. that utilizes a single grid of much coarser pitch. Our system consisted of a low power 100 microm spot Mo source, a CCD with 22 microm pixel pitch, and either a focused mammography linear grid or a stainless steel woven mesh. Phase is extracted from a single image by windowing and comparing data localized about harmonics of the grid in the Fourier domain. A Matlab code was written to perform the image processing. For the first time, the effects on the diffraction phase contrast and scattering amplitude images of varying grid types and periods, and of varying the window function type used to separate the harmonics, and the window widths, were investigated. Using the wire mesh, derivatives of the phase along two orthogonal directions were obtained and new methods investigated to form improved phase contrast images.
D City Transformations by Time Series of Aerial Images
Adami, A.
2015-02-01
Recent photogrammetric applications, based on dense image matching algorithms, allow to use not only images acquired by digital cameras, amateur or not, but also to recover the vast heritage of analogue photographs. This possibility opens up many possibilities in the use and enhancement of existing photos heritage. The research of the original figuration of old buildings, the virtual reconstruction of disappeared architectures and the study of urban development are some of the application areas that exploit the great cultural heritage of photography. Nevertheless there are some restrictions in the use of historical images for automatic reconstruction of buildings such as image quality, availability of camera parameters and ineffective geometry of image acquisition. These constrains are very hard to solve and it is difficult to discover good dataset in the case of terrestrial close range photogrammetry for the above reasons. Even the photographic archives of museums and superintendence, while retaining a wealth of documentation, have no dataset for a dense image matching approach. Compared to the vast collection of historical photos, the class of aerial photos meets both criteria stated above. In this paper historical aerial photographs are used with dense image matching algorithms to realize 3d models of a city in different years. The models can be used to study the urban development of the city and its changes through time. The application relates to the city centre of Verona, for which some time series of aerial photographs have been retrieved. The models obtained in this way allowed, right away, to observe the urban development of the city, the places of expansion and new urban areas. But a more interesting aspect emerged from the analytical comparison between models. The difference, as the Euclidean distance, between two models gives information about new buildings or demolitions. As considering accuracy it is necessary point out that the quality of final
Wu, Changdong; Liu, Zhigang; Jiang, Hua
2017-05-01
The quality of image enhancement plays an important role in the catenary fault diagnosis system based on the image processing technique. It is necessary to enhance the low contrast image of catenary for better detecting the state of catenary part. The Non-subsampled Contourlet transform (NSCT) is the improved Contourlet transform (CT), which can effectively solve the problem of artifact phenomenon in the enhanced catenary image. Besides, choosing the enhancement function and the filter of the NSCT will directly influence the image enhancement effect. In this paper, the proposed method is implemented by combining the NSCT with the nonlinear enhancement function to enhance the catenary image. First, how to choose the filter of the NSCT is discussed. Second, the NSCT is used to decompose the image. Then, the chosen nonlinear enhancement function is used to process the decomposed coefficient of the NSCT. Finally, the NSCT is inversed to obtain the enhanced image. In this paper, we evaluate our algorithm using the lifting wavelet transform, retinex enhancement method, dark channel enhancement method, curvelet transform, and CT method as a comparison to enhance a group of randomly selected low contrast catenary images, respectively. The results of comparative experiments conducted show that the proposed method can effectively enhance the catenary image, the contrast of image is improved, the catenary parts are obvious, and the artifact phenomenon is effectively eliminated, where image details (edges, textures, or smooth areas) are also well preserved. Besides, the values (detail variance-background variance, signal-to-noise ratio, and edge preservation index) of measuring the image enhancement capacity are improved, while the mean squared error value is decreased when compared to the CT method. These indicate that the proposed method is an excellent catenary image enhancement approach.
Image Stability Requirements For a Geostationary Imaging Fourier Transform Spectrometer (GIFTS)
Bingham, G. E.; Cantwell, G.; Robinson, R. C.; Revercomb, H. E.; Smith, W. L.
2001-01-01
A Geostationary Imaging Fourier Transform Spectrometer (GIFTS) has been selected for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. Our paper will discuss one of the key GIFTS measurement requirements, Field of View (FOV) stability, and its impact on required system performance. The GIFTS NMP mission is designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS payload is a versatile imaging FTS with programmable spectral resolution and spatial scene selection that allows radiometric accuracy and atmospheric sounding precision to be traded in near real time for area coverage. The GIFTS sensor combines high sensitivity with a massively parallel spatial data collection scheme to allow high spatial resolution measurement of the Earth's atmosphere and rapid broad area coverage. An objective of the GIFTS mission is to demonstrate the advantages of high spatial resolution (4 km ground sample distance - gsd) on temperature and water vapor retrieval by allowing sampling in broken cloud regions. This small gsd, combined with the relatively long scan time required (approximately 10 s) to collect high resolution spectra from geostationary (GEO) orbit, may require extremely good pointing control. This paper discusses the analysis of this requirement.
Infrared and multi-type images fusion algorithm based on contrast pyramid transform
Xu, Hua; Wang, Yan; Wu, Yujing; Qian, Yunsheng
2016-09-01
A fusion algorithm for infrared and multi-type images based on contrast pyramid transform (CPT) combined with Otsu method and morphology is proposed in this paper. Firstly, two sharpened images are combined to the first fused image based on information entropy weighted scheme. Afterwards, two enhanced images and the first fused one are decomposed into a series of images with different dimensions and spatial frequencies. To the low-frequency layer, the Otsu method is applied to calculate the optimal segmentation threshold of the first fused image, which is subsequently used to determine the pixel values in top layer fused image. With respect to the high-frequency layers, the top-bottom hats morphological transform is employed to each layer before maximum selection criterion. Finally, the series of decomposed images are reconstructed and then superposed with the enhanced image processed by morphological gradient operation as a second fusion to get the final fusion image. Infrared and visible images fusion, infrared and low-light-level (LLL) images fusion, infrared intensity and infrared polarization images fusion, and multi-focus images fusion are discussed in this paper. Both experimental results and objective metrics demonstrate the effectiveness and superiority of the proposed algorithm over the conventional ones used to compare.
All-optical image processing and compression based on Haar wavelet transform.
Parca, Giorgia; Teixeira, Pedro; Teixeira, Antonio
2013-04-20
Fast data processing and compression methods based on wavelet transform are fundamental tools in the area of real-time 2D data/image analysis, enabling high definition applications and redundant data reduction. The need for information processing at high data rates motivates the efforts on exploiting the speed and the parallelism of the light for data analysis and compression. Among several schemes for optical wavelet transform implementation, the Haar transform offers simple design and fast computation, plus it can be easily implemented by optical planar interferometry. We present an all optical scheme based on an asymmetric couplers network for achieving fast image processing and compression in the optical domain. The implementation of Haar wavelet transform through a 3D passive structure is supported by theoretical formulation and simulations results. Asymmetrical coupler 3D network design and optimization are reported and Haar wavelet transform, including compression, was achieved, thus demonstrating the feasibility of our approach.
A hyperspectral images compression algorithm based on 3D bit plane transform
Zhang, Lei; Xiang, Libin; Zhang, Sam; Quan, Shengxue
2010-10-01
According the analyses of the hyper-spectral images, a new compression algorithm based on 3-D bit plane transform is proposed. The spectral coefficient is higher than the spatial. The algorithm is proposed to overcome the shortcoming of 1-D bit plane transform for it can only reduce the correlation when the neighboring pixels have similar values. The algorithm calculates the horizontal, vertical and spectral bit plane transform sequentially. As the spectral bit plane transform, the algorithm can be easily realized by hardware. In addition, because the calculation and encoding of the transform matrix of each bit are independent, the algorithm can be realized by parallel computing model, which can improve the calculation efficiency and save the processing time greatly. The experimental results show that the proposed algorithm achieves improved compression performance. With a certain compression ratios, the algorithm satisfies requirements of hyper-spectral images compression system, by efficiently reducing the cost of computation and memory usage.
Directory of Open Access Journals (Sweden)
Byambaa Dorj
2016-01-01
Full Text Available The next promising key issue of the automobile development is a self-driving technique. One of the challenges for intelligent self-driving includes a lane-detecting and lane-keeping capability for advanced driver assistance systems. This paper introduces an efficient and lane detection method designed based on top view image transformation that converts an image from a front view to a top view space. After the top view image transformation, a Hough transformation technique is integrated by using a parabolic model of a curved lane in order to estimate a parametric model of the lane in the top view space. The parameters of the parabolic model are estimated by utilizing a least-square approach. The experimental results show that the newly proposed lane detection method with the top view transformation is very effective in estimating a sharp and curved lane leading to a precise self-driving capability.
A Review Comparison of Wavelet and Cosine Image Transforms
Directory of Open Access Journals (Sweden)
Vinay Jeengar
2012-10-01
Full Text Available Image compression is the methodology of reducing the data space required to store an image or video. It finds great application in transferring videos and images over the web to reduce data transfer time and resource consumption. A number of methods based on DCT and DWT have been proposed in the past like JPEG, MPEG, EZW, SPIHT etc. The paper presents a review comparison between DCT and DWT compression techniques based on multiple important evaluation parameters like (i mean squared error and SNR for different threshold values (ii SNR values and mean squared error for different coefficients (iii SNR values and mean squared error for different window size. In addition, the paper also makes two advanced studies (i CPU utilization and compression ratio for different window sizes (ii SNR and compression with different compression ratio. The experimentation is performed on multiple 8x8 jpeg images.
Transforming the image of nursing: the evidence for assurance.
Wocial, Lucia D; Sego, Kelly; Rager, Carrie; Laubersheimer, Shellee; Everett, Linda Q
2014-01-01
A nurse's uniform influences perceptions about nursing practice and thus contributes significantly to the overall image of a nurse. A nurse's uniform also can represent the brand of an organization, the tangible and intangible attributes that distinguish an organization from its competitors. The rebranding of a major health care system provided a unique opportunity to refine the "image of nurses" within the organization. This article describes the planning, evidence gathering, and implementation of a major initiative to promote professional nursing practice.
Abuturab, Muhammad Rafiq
2015-10-01
A novel method of group multiple-image encoding and watermarking using coupled logistic maps and gyrator wavelet transform is presented. The proposed method employs three different groups of multiple images. The color images of each group are individually segregated into R, G, and B channels. Each channel is first permutated by using a sequence of chaotic pairs generated with a system of two symmetrically coupled identical logistic maps and then gyrator transformed. The gyrator spectrum of each channel is multiplied together and then modulated by a random phase function to obtain a corresponding multiplex channel. The encoded multiplex image is restituted through a concatenation of R, G, and B multiplex channels. The phase and amplitude functions of the first, second, and third groups of encoded multiplex images are generated. The host image is a single-level 2D discrete wavelet transformed to decompose into LL, HL, LH, and HH subbands. HL, LH, and HH subbands are then replaced with phase functions of the first, second, and third groups, respectively. Finally, the resultant image is an inverse single-level 2D discrete wavelet transformed to construct a watermarked image. The three groups of multiple images are protected not only by the encryption algorithm but also visually by the host image. Thus, a high level of security can be achieved. Each group includes group decryption keys, and each image of the group comprises individual decryption keys beside parameters of coupled logistic maps and gyrator transform. As a result, the key space is very large. The decryption system can be realized by using an optoelectronic device. The numerical simulation results confirm the validity and security of the proposed scheme.
Research on application for integer wavelet transform for lossless compression of medical image
Zhou, Zude; Li, Quan; Long, Quan
2003-09-01
This paper proposes an approach based on using lifting scheme to construct integer wavelet transform whose purpose is to realize the lossless compression of images. Then researches on application of medical image, software simulation of corresponding algorithm and experiment result are presented in this paper. Experiment shows that this method could improve the compression ration and resolution.
A NOVEL ALGORITHM OF MULTI-SENSOR IMAGE FUSION BASED ON WAVELET PACKET TRANSFORM
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In order to enhance the image information from multi-sensor and to improve the abilities of theinformation analysis and the feature extraction, this letter proposed a new fusion approach in pixel level bymeans of the Wavelet Packet Transform (WPT). The WPT is able to decompose an image into low frequencyband and high frequency band in higher scale. It offers a more precise method for image analysis than Wave-let Transform (WT). Firstly, the proposed approach employs HIS (Hue, Intensity, Saturation) transform toobtain the intensity component of CBERS (China-Brazil Earth Resource Satellite) multi-spectral image. ThenWPT transform is employed to decompose the intensity component and SPOT (Systeme Pour I'Observationde la Therre ) image into low frequency band and high frequency band in three levels. Next, two high fre-quency coefficients and low frequency coefficients of the images are combined by linear weighting strategies.Finally, the fused image is obtained with inverse WPT and inverse HIS. The results show the new approachcan fuse details of input image successfully, and thereby can obtain a more satisfactory result than that of HM(Histogram Matched)-based fusion algorithm and WT-based fusion approach.
Super-resolution image restoration algorithms based on orthogonal discrete wavelet transform
Liu, Yang-yang; Jin, Wei-qi
2005-02-01
Several new super-resolution image restoration algorithms based on orthogonal discrete wavelet transform are proposed, by using orthogonal discrete wavelet transform and generalized cross validation ,and combining with Luck-Richardson super-resolution image restoration algorithm (LR) and Luck-Richardson algorithm based on Poisson-Markov model (MPML). Orthogonal discrete wavelet transform analyzed in both space and frequency domain has the capability of indicating local features of a signal, and concentrating the signal power to a few coefficients in wavelet transform domain. After an original image is "Symlets" orthogonal discrete wavelet transformed, an asymptotically optimal threshold is determined by minimizing generalized cross validation, and high frequency subbands in each decomposition level are denoised with soft threshold processes to converge respectively to those with maximum signal-noise-ratio, when the method is incorporated with existed super-resolution image algorithms, details of original image, especially of those with low signal-noise-ratio, could be well recovered. Single operation wavelet LR algorithm(SWLR),single operation wavelet MPML algorithm(SW-MPML) and MPML algorithm based on single operation and wavelet transform (MPML- SW) are some operative algorithms proposed based on the method. According to the processing results to simulating and practical images , because of the only one operation, under the guarantee of rapid and effective restoration processing, in comparison with LR and MPML, all the proposed algorithms could retain image details better, and be more suitable to low signal-noise-ratio images, They could also reduce operation time for up to hundreds times of iteratives, as well as, avoid the iterative operation of self-adaptive parameters in MPML, improve operating speed and precision. They are practical and instantaneous to some extent in the field of low signal-noise-ratio image restoration.
Energy Technology Data Exchange (ETDEWEB)
LACKS,S.A.
2003-10-09
Transformation, which alters the genetic makeup of an individual, is a concept that intrigues the human imagination. In Streptococcus pneumoniae such transformation was first demonstrated. Perhaps our fascination with genetics derived from our ancestors observing their own progeny, with its retention and assortment of parental traits, but such interest must have been accelerated after the dawn of agriculture. It was in pea plants that Gregor Mendel in the late 1800s examined inherited traits and found them to be determined by physical elements, or genes, passed from parents to progeny. In our day, the material basis of these genetic determinants was revealed to be DNA by the lowly bacteria, in particular, the pneumococcus. For this species, transformation by free DNA is a sexual process that enables cells to sport new combinations of genes and traits. Genetic transformation of the type found in S. pneumoniae occurs naturally in many species of bacteria (70), but, initially only a few other transformable species were found, namely, Haemophilus influenzae, Neisseria meningitides, Neisseria gonorrheae, and Bacillus subtilis (96). Natural transformation, which requires a set of genes evolved for the purpose, contrasts with artificial transformation, which is accomplished by shocking cells either electrically, as in electroporation, or by ionic and temperature shifts. Although such artificial treatments can introduce very small amounts of DNA into virtually any type of cell, the amounts introduced by natural transformation are a million-fold greater, and S. pneumoniae can take up as much as 10% of its cellular DNA content (40).
DEFF Research Database (Denmark)
Peters, Terri
2011-01-01
Artiklen diskuterer ordet "transformation" med udgangspunkt i dels hvorledes ordet bruges i arkitektfaglig terminologi og dels med fokus på ordets potentielle indhold og egnethed i samme teminologi.......Artiklen diskuterer ordet "transformation" med udgangspunkt i dels hvorledes ordet bruges i arkitektfaglig terminologi og dels med fokus på ordets potentielle indhold og egnethed i samme teminologi....
DEFF Research Database (Denmark)
Peters, Terri
2011-01-01
Artiklen diskuterer ordet "transformation" med udgangspunkt i dels hvorledes ordet bruges i arkitektfaglig terminologi og dels med fokus på ordets potentielle indhold og egnethed i samme teminologi.......Artiklen diskuterer ordet "transformation" med udgangspunkt i dels hvorledes ordet bruges i arkitektfaglig terminologi og dels med fokus på ordets potentielle indhold og egnethed i samme teminologi....
Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao
2016-12-01
To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.
Min Wang; Zhen Li; Xiangjun Duan; Wei Li
2015-01-01
This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD), with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts), with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with i...
Optical color image hiding scheme based on chaotic mapping and Hartley transform
Liu, Zhengjun; Zhang, Yu; Liu, Wei; Meng, Fanyi; Wu, Qun; Liu, Shutian
2013-08-01
We present a color image encryption algorithm by using chaotic mapping and Hartley transform. The three components of color image are scrambled by Baker mapping. The coordinates composed of the scrambled monochrome components are converted from Cartesian coordinates to spherical coordinates. The data of azimuth angle is normalized and regarded as the key. The data of radii and zenith angle are encoded under the help of optical Hartley transform with scrambled key. An electro-optical encryption structure is designed. The final encrypted image is constituted by two selected color components of output in real number domain.
A simplification of the fractional Hartley transform applied to image security system in phase
Jimenez, Carlos J.; Vilardy, Juan M.; Perez, Ronal
2017-01-01
In this work we develop a new encryption system for encoded image in phase using the fractional Hartley transform (FrHT), truncation operations and random phase masks (RPMs). We introduce a simplification of the FrHT with the purpose of computing this transform in an efficient and fast way. The security of the encryption system is increased by using nonlinear operations, such as the phase encoding and the truncation operations. The image to encrypt (original image) is encoded in phase and the truncation operations applied in the encryption-decryption system are the amplitude and phase truncations. The encrypted image is protected by six keys, which are the two fractional orders of the FrHTs, the two RPMs and the two pseudorandom code images generated by the amplitude and phase truncation operations. All these keys have to be correct for a proper recovery of the original image in the decryption system. We present digital results that confirm our approach.
Multi-image gradient-based algorithms for motion measurement using wavelet transform
Institute of Scientific and Technical Information of China (English)
2008-01-01
A multi-image wavelet transform motion estimation algorithm based on gradient methods is presented by using the characteristic of wavelet transfom.In this algorithm,the accuracy can be improved greatly using data in many images to measure motions between two images.In combination with the reliability measure for constraints function,the reliable data constraints of the images were decomposed with multi-level simultaneous wavelet transform rather than the traditional coarse-to-fine approach.Compared with conventional methods,this motion measurement algorithm based on multi-level simultaneous wavelet transform avoids propagating errors between the decomposed levels.Experimental simulations show that the implementation of this algo rithm is simple,and the measurement accuracy is improved.
Mesh-based phase contrast Fourier transform imaging
Tahir, Sajjad; Bashir, Sajid; MacDonald, C. A.; Petruccelli, Jonathan C.
2017-04-01
Traditional x-ray radiography is limited by low attenuation contrast in materials of low electron density. Phase contrast imaging offers the potential to improve the contrast between such materials, but due to the requirements on the spatial coherence of the x-ray beam, practical implementation of such systems with tabletop (i.e. non-synchrotron) sources has been limited. One phase imaging technique employs multiple fine-pitched gratings. However, the strict manufacturing tolerances and precise alignment requirements have limited the widespread adoption of grating-based techniques. In this work, we have investigated a recently developed technique that utilizes a single grid of much coarser pitch. Our system consisted of a low power 100 μm spot Mo source, a CCD with 22 μm pixel pitch, and either a focused mammography linear grid or a stainless steel woven mesh. Phase is extracted from a single image by windowing and comparing data localized about harmonics of the mesh in the Fourier domain. The effects on the diffraction phase contrast and scattering amplitude images of varying grid types and periods, and of varying the width of the window function used to separate the harmonics were investigated. Using the wire mesh, derivatives of the phase along two orthogonal directions were obtained and combined to form improved phase contrast images.
Diffusion filtering in image processing based on wavelet transform
Institute of Scientific and Technical Information of China (English)
LIU Feng
2006-01-01
The nonlinear diffusion filtering in image processing bases on the heat diffusion equations. Its key is the control of diffusion amount. In the previous models, the diffusivity depends on the gradients of images. So it is easily affected by noises. This paper first gives a new multiscale computational technique for diffusivity. Then we proposed a class of nonlinear wavelet diffusion (NWD) models that are used to restore images. The NWD model has strong ability to resist noise.But it, like the previous models, requires higher computational effort. Thus, by simplifying the NWD, we establish linear wavelet diffusion (LWD) models that consist of advection and diffusion. Since there exists the advection, the LWD filter is anisotropic, and hence can well preserve edges although the diffusion at edges is isotropic. The advantage is that the LWD model is easy to be analyzed and has lesser computational load. Finally, a variety of numerical experiments compared with the previous model are shown.
A Digital Image Watermarking Method in the Discrete Cosine Transformation Domain
Directory of Open Access Journals (Sweden)
Mohammad Reza Khammar
2012-01-01
Full Text Available In this paper, a watermarking method has been proposed based on Discrete Cosine Transform(DCT which can be used in order to protect copyrighting and to provide right of image ownership. In this method, the original image transferred to DCT domain after dividing into non-overlapped blocks 8×8 and to the same method, watermark image which can be whether a firm mark or any desired image from owner of the art work, after dividing into non-overlapped blocks 4×4, transferred to DCT domain. Watermark image coefficients after one step coding composed with low frequency coefficients of original image and create the final watermark image. On the other hand, the process of reforming watermarked image and extracting the original watermark on the secondary side is extractable by using original image and with reverse mechanism. Experiments show that this method in encountering with a number of routine attacks has a good resistance.
Iacchetta, Alexander S.; Fienup, James R.; Leisawitz, David T.
2016-07-01
Image reconstruction algorithms for wide-field spatio-spectral interferometry require knowledge of registration parameters associated with low-resolution image measurements at various baseline orientations, such that the images can be registered to within the fine resolution of the final desired image. We have developed an image registration procedure that combines a nonlinear optimization algorithm with the sub-pixel precision of chirp z-transform resampling, particularly for rotation and translation, of bandlimited images with non-radially symmetric aberrations. We show the accuracy of this image registration technique on simulated images that have a complexity comparable to scenes observed experimentally with NASA's wide-field imaging interferometry testbed. Registration to within a tenth of a pixel for translation and within three arcminutes for rotation is demonstrated at the largest simulated noise levels.
Sharma, K. K.; Jain, Heena
2013-01-01
The security of digital data including images has attracted more attention recently, and many different image encryption methods have been proposed in the literature for this purpose. In this paper, a new image encryption method using wavelet packet decomposition and discrete linear canonical transform is proposed. The use of wavelet packet decomposition and DLCT increases the key size significantly making the encryption more robust. Simulation results of the proposed technique are also presented.
Digital Image Watermarking Based on DiscreteWavelet Transform
Institute of Scientific and Technical Information of China (English)
丁玮; 闫伟齐; 齐东旭
2002-01-01
This paper aims at digital watermark which is a new popular research topic recently, presents some methods to embed digital watermark based on modifying frequency coefficients in discrete wavelettransfor(DWT)domain.First,thepresent progress of digital watermark is briefly introduced; after that, starting from Pitas's method and discarding hispseudo random number method, the authors use a digital image scrambling technology as preprocessing fordigital watermarking. Then the authors discuss how to embed a 1-bit digital image as watermark in frequency domain. Finallyanotherdigital watermarking method is given in which 3-D DWT is used to transformagivendigitalimage.Basedontheexperimentalresults, it is shown that the proposed methods are robust to a large extent.
Baker, W.R.
1959-08-25
Transformers of a type adapted for use with extreme high power vacuum tubes where current requirements may be of the order of 2,000 to 200,000 amperes are described. The transformer casing has the form of a re-entrant section being extended through an opening in one end of the cylinder to form a coaxial terminal arrangement. A toroidal multi-turn primary winding is disposed within the casing in coaxial relationship therein. In a second embodiment, means are provided for forming the casing as a multi-turn secondary. The transformer is characterized by minimized resistance heating, minimized external magnetic flux, and an economical construction.
Indian Academy of Sciences (India)
Atluri Srikrishna; M Pompapathi; G Srinivasa Rao
2015-04-01
The objective of contrast operators consists in normalizing the gray levels of the input image for the purpose of avoiding abrupt changes in intensity among different regions. In this paper morphological transformations are used to detect the background in color images characterized by poor lighting. The disadvantage of contrast enhancement as studied in previous contrast enhancement algorithms is over illumination. An efficient algorithm is introduced to tackle the problem of over illumination by controlling the intensities at dark and bright regions of an image and preserve the geometry of the object. Finally the performance of the proposed algorithm is illustrated through the processing of gray scale images and color images with different backgrounds.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Using the Rador transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linesr texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.
Directory of Open Access Journals (Sweden)
Mrinal Kanti Bhowmik
2010-05-01
Full Text Available This paper investigates Quotient based Fusion of thermal and visual images, which were individually passed through level-1 and level-2 multiresolution analyses. In the proposed system, the method-1 namely "Decompose then Quotient Fuse Level-1" and the method-2 namely "Decompose-Reconstruct in level-2 and then Fuse Quotients", both work on wavelet transformations of the visual and thermal face images. The wavelet transform is well-suited to manage different image resolutions and allows the image decomposition in different kinds of coefficients, while preserving the image information without any loss. This approach is based on a definition of an illumination invariant signature image which enables an analytic generation of the image space with varying illumination. The quotient fused images are passed through Principal Component Analysis (PCA for dimension reduction and then those images are classified using a multi-layer perceptron (MLP. The performances of both the methods have been evaluated using OTCBVS and IRIS databases. All the different classes have been tested separately, among them the maximum recognition result for a class is 100% and the minimum recognition rate for a class is 73%.
A Complete Image Compression Scheme Based on Overlapped Block Transform with Post-Processing
Kwan, C.; Li, B.; Xu, R.; Li, X.; Tran, T.; Nguyen, T.
2006-12-01
A complete system was built for high-performance image compression based on overlapped block transform. Extensive simulations and comparative studies were carried out for still image compression including benchmark images (Lena and Barbara), synthetic aperture radar (SAR) images, and color images. We have achieved consistently better results than three commercial products in the market (a Summus wavelet codec, a baseline JPEG codec, and a JPEG-2000 codec) for most images that we used in this study. Included in the system are two post-processing techniques based on morphological and median filters for enhancing the perceptual quality of the reconstructed images. The proposed system also supports the enhancement of a small region of interest within an image, which is of interest in various applications such as target recognition and medical diagnosis
Image Sequence Fusion and Denoising Based on 3D Shearlet Transform
Directory of Open Access Journals (Sweden)
Liang Xu
2014-01-01
Full Text Available We propose a novel algorithm for image sequence fusion and denoising simultaneously in 3D shearlet transform domain. In general, the most existing image fusion methods only consider combining the important information of source images and do not deal with the artifacts. If source images contain noises, the noises may be also transferred into the fusion image together with useful pixels. In 3D shearlet transform domain, we propose that the recursive filter is first performed on the high-pass subbands to obtain the denoised high-pass coefficients. The high-pass subbands are then combined to employ the fusion rule of the selecting maximum based on 3D pulse coupled neural network (PCNN, and the low-pass subband is fused to use the fusion rule of the weighted sum. Experimental results demonstrate that the proposed algorithm yields the encouraging effects.
Musatenko, Yurij S.; Kurashov, Vitalij N.
1998-10-01
The paper presents improved version of our new method for compression of correlated image sets Optimal Image Coding using Karhunen-Loeve transform (OICKL). It is known that Karhunen-Loeve (KL) transform is most optimal representation for such a purpose. The approach is based on fact that every KL basis function gives maximum possible average contribution in every image and this contribution decreases most quickly among all possible bases. So, we lossy compress every KL basis function by Embedded Zerotree Wavelet (EZW) coding with essentially different loss that depends on the functions' contribution in the images. The paper presents new fast low memory consuming algorithm of KL basis construction for compression of correlated image ensembles that enable our OICKL system to work on common hardware. We also present procedure for determining of optimal losses of KL basic functions caused by compression. It uses modified EZW coder which produce whole PSNR (bitrate) curve during the only compression pass.
Lahmiri, Salim; Gargour, Christian S; Gabrea, Marcel
2014-10-01
An automated diagnosis system that uses complex continuous wavelet transform (CWT) to process retina digital images and support vector machines (SVMs) for classification purposes is presented. In particular, each retina image is transformed into two one-dimensional signals by concatenating image rows and columns separately. The mathematical norm of phase angles found in each one-dimensional signal at each level of CWT decomposition are relied on to characterise the texture of normal images against abnormal images affected by exudates, drusen and microaneurysms. The leave-one-out cross-validation method was adopted to conduct experiments and the results from the SVM show that the proposed approach gives better results than those obtained by other methods based on the correct classification rate, sensitivity and specificity.
Super-resolution image restoration algorithm based on orthogonal discrete wavelet transform
Institute of Scientific and Technical Information of China (English)
Yangyang Liu(刘扬阳); Weiqi Jin(金伟其); Binghua Su(苏秉华)
2004-01-01
By using orthogonal discrete wavelet transform(ODWT)and generalized cross validation(GCV),and combining with Luck-Richardson algorithm based on Poisson-Markovmodel (MPML),several new superresolution image restoration algorithms are proposed.According to simulation experiments for practical images,all the proposed algor ithms could retain image details better than MPML,and be more suitable to low signal-to-noise ratio(SNR)images.The single operation wavelet MPML(SW-MPML)algorithm and MPML algorithm based on single operation wavelet transform(MPML-SW)avoid the iterative operation of self-adaptive parameter in MPML particularly,and improve operating speed and precision.They are instantaneous to super-resolution image restoration process and have extensive application foreground.
The segmentation of FMI image based on 2-D dyadic wavelet transform
Liu, Rui-Lin; Wu, Yue-Qi; Liu, Jian-Hua; Ma, Yong
2005-06-01
A key aspect in extracting quantitative information from FMI logs is to segment the FMI image to get images of pores, vugs and fractures. A segmentation method based on the dyadic wavelet transform in 2-D is introduced in this paper. The first step is to find all the edge pixels of the FMI image using the 2-D wavelet transform. The second step is to calculate a segmentation threshold based on the average value of the edge pixels. Field data processing examples show that sub-images of vugs and fractures can be correctly separated from original FMI data continuously and automatically along the depth axis. The image segmentation lays the foundation for in-situ parameter calculation.
Directory of Open Access Journals (Sweden)
Saleh Shahbeig
2013-02-01
Full Text Available According to many medical and biometric applications of retinal images, the automatic and accurate extraction of the retinal blood vessels is very important. In this paper, an effective method is introduced to extract the blood vessels from the background of colored images of retina. In this algorithm, by applying the equalizer function on the retinal images, the brightness of the images is considerably uniformed. Because of high ability of Curvelet transform in introducing image borders in various scale and directions, borders and, consequently the contrast of retinal images can be enhanced. Therefore, the enhanced retinal image can be prepared for the extraction of blood vessels by improving Curvelet coefficients of the retinal images, adaptively and locally. Since the blood vessels in retinal images are distributed in various directions, we use the adaptive weighted morphology operators to extract the blood vessels from retinal images. Morphology operators based on reconstruction are used to refine the appeared frills with the size of smaller than arterioles in images properly. Finally, by analyzing the connected component in the images and applying adaptive filter on the components locally, all residual frills are refined from the images. The proposed algorithm in this paper has been evaluated by the images in the DRIVE database. The results how that the blood vessels are extracted from background of the retinal images of DRIVE database with the high accuracy of 96.15%, which in turn shows the high ability of the proposed algorithm in extracting the retinal blood vessels.
Kanai, Takayuki; Kadoya, Noriyuki; Ito, Kengo; Onozato, Yusuke; Cho, Sang Yong; Kishi, Kazuma; Dobashi, Suguru; Umezawa, Rei; Matsushita, Haruo; Takeda, Ken; Jingu, Keiichi
2014-01-01
Deformable image registration (DIR) is fundamental technique for adaptive radiotherapy and image-guided radiotherapy. However, further improvement of DIR is still needed. We evaluated the accuracy of B-spline transformation-based DIR implemented in elastix. This registration package is largely based on the Insight Segmentation and Registration Toolkit (ITK), and several new functions were implemented to achieve high DIR accuracy. The purpose of this study was to clarify whether new functions ...
Double-image encryption based on discrete fractional random transform and chaotic maps
Li, Huijuan; Wang, Yurong
2011-07-01
A novel double-image encryption algorithm is proposed, based on discrete fractional random transform and chaotic maps. The random matrices used in the discrete fractional random transform are generated by using a chaotic map. One of the two original images is scrambled by using another chaotic map, and then encoded into the phase of a complex matrix with the other original image as its amplitude. Then this complex matrix is encrypted by the discrete fractional random transform. By applying the correct keys which consist of initial values, control parameters, and truncated positions of the chaotic maps, and fractional orders, the two original images can be recovered without cross-talk. Numerical simulation has been performed to test the validity and the security of the proposed encryption algorithm. Encrypting two images together by this algorithm creates only one encrypted image, whereas other single-image encryption methods create two encrypted images. Furthermore, this algorithm requires neither the use of phase keys nor the use of matrix keys. In this sense, this algorithm can raise the efficiency when encrypting, storing or transmitting.
Singh, Hukum
2016-05-01
An optical color image encryption in the Fractional Wavelet Transform (FWT) domain is carried out. The original images are segregated into three colors components: R (red), G (green) and B (blue). After that the components are encrypted separately using double random phase encoding (DRPE) in the FWT domain. Random phase masks (RPMs) are used in the input as well as in Fourier plane. The images to be encrypted are transformed with the discrete wavelet transform (DWT), the resulting coefficients from the DWT are multiplied each one by masks different form RPM. Masks are independent each other and the results are applied an inverse discrete Wavelet Transform (IDWT), obtaining the encrypted images. The input images are recovered from their corresponding encrypted images by using the correct parameters of the FWT, and its digital implementation has been performed using MATLAB 7.6.0 (R2008a). The mother wavelet family and fractional orders associated with the FWT are extra keys that access difficulty an attacker; thereby the scheme is more secure as compared to conventional techniques. The sensitivity of proposed scheme is verified with encryption parameters, occlusions, and noise attacks.
Medical image denoising using dual tree complex thresholding wavelet transform and Wiener filter
Directory of Open Access Journals (Sweden)
Hilal Naimi
2015-01-01
Full Text Available Image denoising is the process to remove the noise from the image naturally corrupted by the noise. The wavelet method is one among various methods for recovering infinite dimensional objects like curves, densities, images, etc. The wavelet techniques are very effective to remove the noise because of their ability to capture the energy of a signal in few energy transform values. The wavelet methods are based on shrinking the wavelet coefficients in the wavelet domain. We propose in this paper, a denoising approach basing on dual tree complex wavelet and shrinkage with the Wiener filter technique (where either hard or soft thresholding operators of dual tree complex wavelet transform for the denoising of medical images are used. The results proved that the denoised images using DTCWT (Dual Tree Complex Wavelet Transform with Wiener filter have a better balance between smoothness and accuracy than the DWT and are less redundant than SWT (StationaryWavelet Transform. We used the SSIM (Structural Similarity Index Measure along with PSNR (Peak Signal to Noise Ratio and SSIM map to assess the quality of denoised images.
A curvelet transform approach for the fusion of MR and CT images
Ali, F. E.; El-Dokany, I. M.; Saad, A. A.; Abd El-Samie, F. E.
2010-02-01
There are several medical imaging techniques such as the magnetic resonance (MR) and the computed tomography (CT) techniques. Both techniques give sophisticated characteristics of the region to be imaged. This paper proposes a curvelet based approach for fusing MR and CT images to obtain images with as much detail as possible, for the sake of medical diagnosis. This approach is based on the application of the additive wavelet transform (AWT) on both images and the segmentation of their detail planes into small overlapping tiles. The ridgelet transform is then applied on each of these tiles, and the fusion process is performed on the ridgelet transforms of the tiles. Simulation results show the superiority of the proposed curvelet fusion approach to the traditional fusion techniques like the multiresolution discrete wavelet transform (DWT) technique and the principal component analysis (PCA) technique. The fusion of MR and CT images in the presence of noise is also studied and the results reveal that unlike the DWT fusion technique, the proposed curvelet fusion approach doesn't require denoising.
Bautista, Pinky A; Yagi, Yukako
2011-01-01
In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.
Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura
2016-09-01
The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.
Image encryption based on the reality-preserving multiple-parameter fractional Fourier transform
Lang, Jun
2012-05-01
In recent years, a number of methods have been proposed in the literature for the encryption of two-dimensional information by using the fractional Fourier transform, but most of their encryptions are complex values and need digital hologram technique to record information, which is inconvenient for digital transmission. In this paper, we propose a new approach for image encryption based on the real-valuedness and decorrelation property of the reality-preserving multiple-parameter fractional Fourier transform in order to meet the requirements of the secure image transmission. In the proposed scheme, the original and encrypted images are respectively in the spatial domain and the reality-preserving multiple-parameter fractional Fourier transformed domain determined by the encryption keys. Numerical simulations are performed to demonstrate that the proposed method is reliable and more robust to blind decryption than several existing methods.
An asymmetric color image encryption method by using deduced gyrator transform
Yao, Lili; Yuan, Caojin; Qiang, Junjie; Feng, Shaotong; Nie, Shouping
2017-02-01
An encryption algorithm is proposed by using the properties of deduced gyrator transform (GT). After being transformed by the GT algorithm and multiplied by a phase distribution p*, the spectrum modulus of the input image is considered to be the encrypted image by further performing Fourier transformation. To resist the attack from iterative phase retrieval, the red, green and blue components of the input image is modulated by a random phase mask and then combined using convolution. The encryption result is real-valued, which is convenient for display, transmission and storage. In the decryption process, the three original color components can be recovered with decryption keys which are different from the encryption keys. An optoelectronic hybrid system for the encryption process is also presented. Computer simulations are presented to demonstrate its performance, and the security of the proposed system is analyzed as well.
A DISCRETE WAVELET TRANSFORM – SINGULAR VALUE DECOMPOSITION SYSTEM FOR IMAGE CODING
Directory of Open Access Journals (Sweden)
H. de Jesús Ochoa-Domínguez,
2007-08-01
Full Text Available A system that combines techniques of wavelet transform (DWT and singular value decomposition (SVD toencode images is presented. The image is divided into tiles or blocks of 64x64 pixels. The decision criterionas to which transform to use is based on the standard deviation of the 8x8 pixel subblocks of the tile toencode. A successive approximation quantizer is used to encode the subbands and vector quantization/scalarquantization is used to encode the SVD eigenvectors/eigenvalues, respectively. For coding color images, theRGB components are transformed into YCbCr before encoding in 4:2:0 format. Results show that theproposed system outperforms the JPEG and approaches the JPEG2000.
2007-11-02
be approved in the near future. The main features of JPEG2000 are use of wavelet transform and ROI (Region of Interest) method. It is expected that... wavelet transform is more effective than Fourier transform for ultrasonic echo signal/image processing. Furthermore, ROI method seems to be appropriate...compression method of medical images. The purpose of this paper is to investigate the effectiveness of wavelet transform compared with DCT (JPEG) and
A Fragile Watermarking Based on Legendre Transform for Color Images (Fwltci
Directory of Open Access Journals (Sweden)
S. K.Ghosal
2013-08-01
Full Text Available In this paper, a Legendre transformation (LT based fragile watermarking technique has been proposed forcolor image authentication. The authentication is done by inserting the watermark into the carrier imagesin transform domain. An initial pixel adjustment has been applied on each pixel component to keep thepixel value positive and less than or equal to the maximum. The Legendre transformation (LT is applied oneach pair of pixel components of the carrier image in row major order. The first transformed componentcan fabricate two bits whereas the second component fabricates three bits of authenticating watermarkstarting from the least significant bit position (LSB-0. A post adjustment is also applied to keep theembedded components closer to the original without affecting the least three significant bits. The inverseLegendre transform (ILT is applied on each adjusted pair to re-generate the watermarked image. Duringinverse transform, at if the second pixel component of the adjusted pair become fractional, then the LSB-2of the first component is set to one; otherwise is set to zero. The reverse procedure is applied at thedestination to retrieve back the watermark which in turn is verified for authentication through a messagedigest. Experimental results conform that the proposed algorithm has improvised the payload and PSNRover Varsaki et. al’s Method [6] and LTCIA technique [7].
Automatic Side-Scan Sonar Image Enhancement in Curvelet Transform Domain
Directory of Open Access Journals (Sweden)
Yan Zhou
2015-01-01
Full Text Available We propose a novel automatic side-scan sonar image enhancement algorithm based on curvelet transform. The proposed algorithm uses the curvelet transform to construct a multichannel enhancement structure based on human visual system (HVS and adopts a new adaptive nonlinear mapping scheme to modify the curvelet transform coefficients in each channel independently and automatically. Firstly, the noisy and low-contrast sonar image is decomposed into a low frequency channel and a series of high frequency channels by using curvelet transform. Secondly, a new nonlinear mapping scheme, which coincides with the logarithmic nonlinear enhancement characteristic of the HVS perception, is designed without any parameter tuning to adjust the curvelet transform coefficients in each channel. Finally, the enhanced image can be reconstructed with the modified coefficients via inverse curvelet transform. The enhancement is achieved by amplifying subtle features, improving contrast, and eliminating noise simultaneously. Experiment results show that the proposed algorithm produces better enhanced results than state-of-the-art algorithms.
Subpixel shift with Fourier transform to achieve efficient and high-quality image interpolation
Chen, Qin-Sheng; Weinhous, Martin S.
1999-05-01
A new approach to image interpolation is proposed. Different from the conventional scheme, the interpolation of a digital image is achieved with a sub-unity coordinate shift technique. In the approach, the original image is first shifted by sub-unity distances matching the locations where the image values need to be restored. The original and the shifted images are then interspersed together, yielding an interpolated image. High quality sub-unity image shift which is crucial to the approach is accomplished by implementing the shift theorem of Fourier transformation. It is well known that under the Nyquist sampling criterion, the most accurate image interpolation can be achieved with the interpolating function (sinc function). A major drawback is its computation efficiency. The present approach can achieve an interpolation quality as good as that with the sinc function since the sub-unity shift in Fourier domain is equivalent to shifting the sinc function in spatial domain, while the efficiency, thanks to the fast Fourier transform, is very much improved. In comparison to the conventional interpolation techniques such as linear or cubic B-spline interpolation, the interpolation accuracy is significantly enhanced. In order to compensate for the under-sampling effects in the interpolation of 3D medical images owing to a larger inter-slice distance, proper window functions were recommended. The application of the approach to 2- and 3-D CT and MRI images produced satisfactory interpolation results.
Yang, Zhixiang; He, Xiufeng; Xu, Jia
2011-10-01
As a new image multiscale geometric analysis tool, the nonsubsampled contourlet transform (NSCT) has many advantages such as multiscale, localization and multidirection, and can efficiently capture the geometric information of images. Therefore, when the NSCT is introduced to image fusion, the characteristics of original images can be taken better and more information for fusion can be obtained. In this paper, a novel fusion algorithm for fusion of the synthetic aperture radar (SAR) image and multispectral images using conjointly the intensity-hue-saturation (IHS) transform and NSCT is proposed. In the proposed method, atrous wavelet is adopted to extract the detail information in low frequency parts fusion, and a new salience measure named as local inner product is introduced to select the high frequency coefficients. A PALSAR HH image of ALOS satellite despeckled by the Lee-sigma filter and HJ-1 multispectral images are used to evaluate the performance and efficiency of the proposed method. The fused images of each method are evaluated by qualitative and quantitative comparison and analysis compared with some traditional fusion rules. The experimental results indicate that the proposed method has the merits of better preservation of image definition and less loss of spectral information.
Adaptive cosine transform image coding with variable block size and constant block distortion
Daut, David G.; Wu, Jia-Chyi
1996-02-01
An adaptive discrete cosine transform (DCT) image coding system is implemented with the same average distortion designated for each variable size image block. The variable block size segmentation is performed using a quadtree data structure by dividing the perceptually more important regions of an image into smaller size blocks compared to the size of blocks containing lesser amounts of spatial activity. Due to the nonstationarity of real-world images, each image block is described by a space-varying nonstationary Gauss-Markov random field. The space-varying autoregressive parameters are estimated using an on-line modified least- squares estimator. For each assumed space-varying nonstationary image block, a constant average distortion is assigned and the code rate for each image block is allowed to vary in order to meet the fixed distortion criterion. Simulation results show that reconstructed images coded at low average distortion, based on an assumed space-varying nonstationary image model, using variable size blocks and with variable bit rate per block possess high-quality subjective (visual) and objective (measured) quality at low average bit rates. Performance gains are achieved due to the distortion being distributed more uniformly among the blocks as compared with fixed-rate, stationary image transform coding schemes.
Block-based SVD image watermarking in spatial and transform domains
Ghazy, Rania A.; Abbas, Alaa M.; Al-Zubi, Nayel; Hassan, Emad S.; El-Fishawy, Nawal A.; Hadhoud, Mohiy M.; Dessouky, Moawad I.; El-Rabaie, El-Sayed M.; Alshebeili, Saleh A.; Abd El-Samie, Fathi E.
2015-07-01
The idea of this paper is to implement an efficient block-by-block singular value (SV) decomposition digital image watermarking algorithm, which is implemented in both the spatial and transforms domains. The discrete wavelet transform (DWT), the discrete cosine transform and the discrete Fourier transform are exploited for this purpose. The original image or one of its transforms is segmented into non-overlapping blocks, and consequently the image to be inserted as a watermark is embedded in the SVs of these blocks. Embedding the watermark on a block-by-block manner ensures security and robustness to attacks such like Gaussian noise, cropping and compression. The proposed algorithm can also be used for colour image watermarking. A comparison study between the proposed block-based watermarking algorithm and the method of Liu is performed for watermarking in all domains. Simulation results ensure that the proposed algorithm is more effective than the traditional method of Liu, especially when the watermarking is performed in the DWT domain.
Bijaoui, A.
2013-03-01
The image restoration is today an important part of the astrophysical data analysis. The denoising and the deblurring can be efficiently performed using multiscale transforms. The multiresolution analysis constitutes the fundamental pillar for these transforms. The discrete wavelet transform is introduced from the theory of the approximation by translated functions. The continuous wavelet transform carries out a generalization of multiscale representations from translated and dilated wavelets. The à trous algorithm furnishes its discrete redundant transform. The image denoising is first considered without any hypothesis on the signal distribution, on the basis of the a contrario detection. Different softening functions are introduced. The introduction of a regularization constraint may improve the results. The application of Bayesian methods leads to an automated adaptation of the softening function to the signal distribution. The MAP principle leads to the basis pursuit, a sparse decomposition on redundant dictionaries. Nevertheless the posterior expectation minimizes, scale per scale, the quadratic error. The proposed deconvolution algorithm is based on a coupling of the wavelet denoising with an iterative inversion algorithm. The different methods are illustrated by numerical experiments on a simulated image similar to images of the deep sky. A white Gaussian stationary noise was added with three levels. In the conclusion different important connected problems are tackled.
Institute of Scientific and Technical Information of China (English)
胡强; 丁亚军; 盛祎; 颜佩; 邹孝; 钱盛友
2016-01-01
A method of noninvasive temperature estimation for high intensity focused ultrasound (HIFU)therapy based on gray level co-occurrence matrix of Hadamard spectral image (Hadamard-GLCM)is presented.The fresh pork was ir-radiated in vitro by HIFU,the subtraction image is obtained from real-time B-mode ultrasound images before and after ir-radiation.Hadamard-GLCM’s moment of inertia(HGMI)as the parameters about the temperature information was sepa-rated from spectral image which was obtained from the subtraction image by use of Hadamard’s transform.The results show that not only the Hadamard-GLCM’s moment of inertia in single group data can be a very well linear fitting with the temperature,but the multiple sets of pictures data can also do.The scope of multiple sets of pictures data are very close proximity and the fitting is very close to 1,this method has the smaller error,higher temperature resolution and stronger fault tolerance.Compared with the traditional temperature estimation method,this method has obviously advantages that it is able to provide the real-time basis for the effective HIFU treatment of noninvasive temperature estimation.%本文提出了一种基于哈达玛变换的频谱图像灰度共生矩阵（Hadamard-GLCM）的高强度聚焦超声治疗无损测温方法。利用高强度聚焦超声辐照新鲜离体猪肉组织，获取辐照前后的 B 超图像的减影图像，采用 Had-amard 变换对其进行处理，获取频谱图像，将频谱图像的灰度共生矩阵惯性矩作为反应温度变化的信息参数。实验表明：不仅单组数据的 Hadamard-GLCM惯性矩（HGMI）和温度能很好的线性拟合，而且多组数据的 Had-amard-GLCM惯性矩与温度也成近似的线性关系，而且斜率非常接近，拟合度更接近1，误差小，对温度的分辨能力高，容错能力强，与传统的测温方法相比有着明显的优势，能为 HIFU 治疗过程中的无损测温提供有效的实时依据。
Vividness and Transformation of Mental Images in Karate
Directory of Open Access Journals (Sweden)
Maria Guarnera
2016-07-01
Full Text Available Background: Systematic reviews have shown that imagery improves performance in motor tasks. Objective: In order to observe the function of imagery in sport, this study investigated modifications in Imagery Ability, in terms of both controllability (i.e., the accurateness with which an image can be operated mentally and vividness (i.e., the precision richness of an image, in competitive and recreational karateka. Method: Thirty volunteers karateka completed the Vividness of Visual Imagery Questionnaire, the Vividness of Movement Imagery Questionnaire-2, and the Subtraction of parts Task. Results: Competitive athletes reported higher scores on imagery ability than recreational athletes. No correlations were found between the variables of Vividness and the Subtraction of parts Task for any of the two groups. All analyses were two-tailed with α at .05. Conclusion: The study has risen the investigation in the particular ambit of imagery ability, providing an additional support for the multidimensional nature of mental imagery and for its usefulness in athletes. Keywords: imagery, motor tasks, karate, static vividness
Wang, Yong-Ying; Wang, Yu-Rong; Wang, Yong; Li, Hui-Juan; Sun, Wen-Jia
2007-07-01
A new method of optical image encryption with binary Fourier transform computer-generated hologram (CGH) and pixel-scrambling technology is presented. In this method, the orders of the pixel scrambling, as well as the encrypted image, are used as the keys to decrypt the original image. Therefore, higher security is achieved. Furthermore, the encrypted image is binary, so it is easy to be fabricated and robust against noise and distortion. Computer simulation results are given to verify the feasibility of this method and its robustness against occlusion and additional noise.
Region-based fusion of infrared and visible images using nonsubsampled contourlet transform
Institute of Scientific and Technical Information of China (English)
Baolong Guo; Qiang Zhang; Ye Hou
2008-01-01
With the nonsubsampled contourlet transform (NSCT), a novel region-segmentation-based fusion algorithm for infrared (IR) and visible images is presented.The IR image is segmented according to the physical features of the target.The source images are decomposed by the NSCT, and then, different fusion rules for the target regions and the background regions are employed to merge the NSCT coefficients respectively.Finally, the fused image is obtained by applying the inverse NSCT.Experimental results show that the proposed algorithm outperforms the pixel-based methods, including the traditional wavelet-based method and NSCT-based method.
SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES
Directory of Open Access Journals (Sweden)
A. Rezaeian
2015-12-01
Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.
Wavelet transform to discriminate between crop and weed in agronomic images
Bossu, Jérémie; Gée, Christelle; Truchetet, Frédéric
2007-09-01
In precision agriculture, the reduction of herbicide applications requires an accurate detection of weed patches. From image detection, to quantify weed infestations, it would be necessary to identify crop rows from line detection algorithm and to discriminate weed from crop. Our laboratory developed several methods for line detection based on Hough Transform, double Hough Transform or Gabor filtering. The Hough Transform is well adapted to image affected by perspective deformations but the computation burden is heavy and on-line applications are hardly handled. To lighten this problem, we have used a Gabor filter to enhance the crop rows present into the image but, if this method is robust with parallel crop rows (without perspective distortions), it implies to deform image with an inverse projection matrix to be applied in the case of an embedded camera. We propose, in order to implement a filter in the scale / space domain, to use a discrete dyadic wavelet transform. Thus, we can extract the vertical details contained in various parts of the image from different levels of resolution. Each vertical detail level kept allows to enhance the crop rows in a specific part of the initial image. The combination of these details enable us to discriminate crop from weeds with a simple logical operation. This spatial method, thanks to the fast wavelet transform algorithm, can be easily implemented for a real time application and it leads to better results than those obtained from Gabor filtering. For this method, the weed infestation rate is estimated and the performance are compared to those given by other methods. A discussion concludes about the ability of this method to detect the crop rows in agronomic images. Finally we consider the ability of this spatial-only approach to classify weeds from crop.
Tan, Ru-Chao; Lei, Tong; Zhao, Qing-Min; Gong, Li-Hua; Zhou, Zhi-Hong
2016-12-01
To improve the slow processing speed of the classical image encryption algorithms and enhance the security of the private color images, a new quantum color image encryption algorithm based on a hyper-chaotic system is proposed, in which the sequences generated by the Chen's hyper-chaotic system are scrambled and diffused with three components of the original color image. Sequentially, the quantum Fourier transform is exploited to fulfill the encryption. Numerical simulations show that the presented quantum color image encryption algorithm possesses large key space to resist illegal attacks, sensitive dependence on initial keys, uniform distribution of gray values for the encrypted image and weak correlation between two adjacent pixels in the cipher-image.
Performance Analysis of Multi Spectral Band Image Compression using Discrete Wavelet Transform
Directory of Open Access Journals (Sweden)
S. S. Ramakrishnan
2012-01-01
Full Text Available Problem statement: Efficient and effective utilization of transmission bandwidth and storage capacity have been a core area of research for remote sensing images. Hence image compression is required for multi-band satellite imagery. In addition, image quality is also an important factor after compression and reconstruction. Approach: In this investigation, the discrete wavelet transform is used to compress the Landsat5 agriculture and forestry image using various wavelets and the spectral signature graph is drawn. Results: The compressed image performance is analyzed using Compression Ratio (CR, Peak Signal to Noise Ratio (PSNR. The compressed image using dmey wavelet is selected based on its Digital Number Minimum (DNmin and Digital Number Maximum (DNmax. Then it is classified using maximum likelihood classification and the accuracy is determined using error matrix, kappa statistics and over all accuracy. Conclusion: Hence the proposed compression technique is well suited to compress the agriculture and forestry multi-band image.
Ganesan, Karthikeyan; Acharya, U Rajendra; Chua, Chua Kuang; Min, Lim Choo; Abraham, Thomas K
2014-12-01
Mammograms are one of the most widely used techniques for preliminary screening of breast cancers. There is great demand for early detection and diagnosis of breast cancer using mammograms. Texture based feature extraction techniques are widely used for mammographic image analysis. In specific, wavelets are a popular choice for texture analysis of these images. Though discrete wavelets have been used extensively for this purpose, spherical wavelets have rarely been used for Computer-Aided Diagnosis (CAD) of breast cancer using mammograms. In this work, a comparison of the performance between the features of Discrete Wavelet Transform (DWT) and Spherical Wavelet Transform (SWT) based on the classification results of normal, benign and malignant stage was studied. Classification was performed using Linear Discriminant Classifier (LDC), Quadratic Discriminant Classifier (QDC), Nearest Mean Classifier (NMC), Support Vector Machines (SVM) and Parzen Classifier (ParzenC). We have obtained a maximum classification accuracy of 81.73% for DWT and 88.80% for SWT features using SVM classifier.
Predict brain MR image registration via sparse learning of appearance and transformation.
Wang, Qian; Kim, Minjeong; Shi, Yonghong; Wu, Guorong; Shen, Dinggang
2015-02-01
We propose a new approach to register the subject image with the template by leveraging a set of intermediate images that are pre-aligned to the template. We argue that, if points in the subject and the intermediate images share similar local appearances, they may have common correspondence in the template. In this way, we learn the sparse representation of a certain subject point to reveal several similar candidate points in the intermediate images. Each selected intermediate candidate can bridge the correspondence from the subject point to the template space, thus predicting the transformation associated with the subject point at the confidence level that relates to the learned sparse coefficient. Following this strategy, we first predict transformations at selected key points, and retain multiple predictions on each key point, instead of allowing only a single correspondence. Then, by utilizing all key points and their predictions with varying confidences, we adaptively reconstruct the dense transformation field that warps the subject to the template. We further embed the prediction-reconstruction protocol above into a multi-resolution hierarchy. In the final, we refine our estimated transformation field via existing registration method in effective manners. We apply our method to registering brain MR images, and conclude that the proposed framework is competent to improve registration performances substantially. Copyright © 2014 Elsevier B.V. All rights reserved.
Medical Image De-Noising Schemes using Wavelet Transform with Fixed form Thresholding
Directory of Open Access Journals (Sweden)
Nadir Mustafa
2015-10-01
Full Text Available Medical Imaging is currently a hot area of bio-medical engineers, researchers and medical doctors as it is extensively used in diagnosing of human health and by health care institutes. The imaging equipment is the device, which is used for better image processing and highlighting the important features. These images are affected by random noise during acquisition, analyzing and transmission process. This condition results in the blurry image visible in low contrast. The Image De-noising System (IDs is used as a tool for removing image noise and preserving important data. Image de-noising is one of the most interesting research areas among researchers of technology-giants and academic institutions. For Criminal Identification Systems (CIS & Magnetic Resonance Imaging (MRI, IDs is more beneficial in the field of medical imaging. This paper proposes an algorithm for de-noising medical images using different types of wavelet transform, such as Haar, Daubechies, Symlets and Bi-orthogonal. In this paper noise image quality has been evaluated using filter assessment parameters like Peak Signal to Noise Ratio (PSNR, Mean Square Error (MSE and Variance, It has been observed to form the numerical results that, the presentation of proposed algorithm reduced the mean square error and achieved best value of peak signal to noise ratio (PSNR. In this paper, the wavelet based de-noising algorithm has been investigated on medical images along with threshold.
Institute of Scientific and Technical Information of China (English)
HU; Xingtang; ZHANG; Bing; ZHANG; Xia; ZHENG; Lanfen; TONG; Qingxi
2006-01-01
Starting with a fractal-based image-compression algorithm based on wavelet transformation for hyperspectral images, the authors were able to obtain more spectral bands with the help of of hyperspectral remote sensing. Because large amounts of data and limited bandwidth complicate the storage and transmission of data measured by TB-level bits, it is important to compress image data acquired by hyperspectral sensors such as MODIS, PHI, and OMIS; otherwise, conventional lossless compression algorithms cannot reach adequate compression ratios. Other loss-compression methods can reach high compression ratios but lack good image fidelity, especially for hyperspectral image data. Among the third generation of image compression algorithms, fractal image compression based on wavelet transformation is superior to traditional compression methods,because it has high compression ratios and good image fidelity, and requires less computing time. To keep the spectral dimension invariable, the authors compared the results of two compression algorithms based on the storage-file structures of BSQ and of BIP, and improved the HV and Quadtree partitioning and domain-range matching algorithms in order to accelerate their encode/decode efficiency. The authors' Hyperspectral Image Process and Analysis System (HIPAS) software used a VC++6.0 integrated development environment (IDE), with which good experimental results were obtained. Possible modifications of the algorithm and limitations of the method are also discussed.
CT and MR image fusion scheme in nonsubsampled contourlet transform domain.
Ganasala, Padma; Kumar, Vinod
2014-06-01
Fusion of CT and MR images allows simultaneous visualization of details of bony anatomy provided by CT image and details of soft tissue anatomy provided by MR image. This helps the radiologist for the precise diagnosis of disease and for more effective interventional treatment procedures. This paper aims at designing an effective CT and MR image fusion method. In the proposed method, first source images are decomposed by using nonsubsampled contourlet transform (NSCT) which is a shift-invariant, multiresolution and multidirection image decomposition transform. Maximum entropy of square of the coefficients with in a local window is used for low-frequency sub-band coefficient selection. Maximum weighted sum-modified Laplacian is used for high-frequency sub-bands coefficient selection. Finally fused image is obtained through inverse NSCT. CT and MR images of different cases have been used to test the proposed method and results are compared with those of the other conventional image fusion methods. Both visual analysis and quantitative evaluation of experimental results shows the superiority of proposed method as compared to other methods.
Gaseous effluent monitoring and identification using an imaging Fourier transform spectrometer
Energy Technology Data Exchange (ETDEWEB)
Carter, M.R.; Bennett, C.L.; Fields, D.J.; Hernandez, J.
1993-10-01
We are developing an imaging Fourier transform spectrometer for chemical effluent monitoring. The system consists of a 2-D infrared imaging array in the focal plane of a Michelson interferometer. Individual images are coordinated with the positioning of a moving mirror in the Michelson interferometer. A three dimensional data cube with two spatial dimensions and one interferogram dimension is then Fourier transformed to produce a hyperspectral data cube with one spectral dimension and two spatial dimensions. The spectral range of the instrument is determined by the choice of optical components and the spectral range of the focal plane array. Measurements in the near UV, visible, near IR, and mid-IR ranges are possible with the existing instrument. Gaseous effluent monitoring and identification measurements will be primarily in the ``fingerprint`` region of the spectrum, ({lambda} = 8 to 12 {mu}m). Initial measurements of effluent using this imaging interferometer in the mid-IR will be presented.
Multiple-image encryption based on phase mask multiplexing in fractional Fourier transform domain.
Liansheng, Sui; Meiting, Xin; Ailing, Tian
2013-06-01
A multiple-image encryption scheme is proposed based on the phase retrieval process and phase mask multiplexing in the fractional Fourier transform domain. First, each original gray-scale image is encoded into a phase only function by using the proposed phase retrieval process. Second, all the obtained phase functions are modulated into an interim, which is encrypted into the final ciphertext by using the fractional Fourier transform. From a plaintext image, a group of phase masks is generated in the encryption process. The corresponding decrypted image can be recovered from the ciphertext only with the correct phase mask group in the decryption process. Simulation results show that the proposed phase retrieval process has high convergence speed, and the encryption algorithm can avoid cross-talk; in addition, its encrypted capacity is considerably enhanced.
Gaseous effluent monitoring and identification using an imaging Fourier transform spectrometer
Energy Technology Data Exchange (ETDEWEB)
Carter, M.R.; Bennett, C.L.; Fields, D.J.; Hernandez, J.
1993-10-01
We are developing an imaging Fourier transform spectrometer for chemical effluent monitoring. The system consists of a 2-D infrared imaging array in the focal plane of a Michelson interferometer. Individual images are coordinated with the positioning of a moving mirror in the Michelson interferometer. A three dimensional data cube with two spatial dimensions and one interferogram dimension is then Fourier transformed to produce a hyperspectral data cube with one spectral dimension and two spatial dimensions. The spectral range of the instrument is determined by the choice of optical components and the spectral range of the focal plane array. Measurements in the near UV, visible, near IR, and mid-IR ranges are possible with the existing instrument. Gaseous effluent monitoring and identification measurements will be primarily in the ``fingerprint`` region of the spectrum, ({lambda} = 8 to 12 {mu}m). Initial measurements of effluent using this imaging interferometer in the mid-IR will be presented.
Study on improvement of the laser uniformity transformation of overlapping-image waveguide cavity
Institute of Scientific and Technical Information of China (English)
Zebin Fan; Junchang Li; Chongguang Li; Kun Ma
2005-01-01
@@ After propagating through the overlapping-image integral mirror, the interference fringe is a major factor that affects the uniformity of the image plane. In this paper, a He-Ne laser is used as light source, and the complex amplitude of the incident laser beam is modulated by an alternating electric field controlled vibrating mirror that is placed before the optical system. The experimental results show that after propagating through the overlapping-image integral mirror, not only the contrast of the interference fringes on the image plane is depressed, but also the uniformity of the intensity distribution of the transformed light beam is improved. Finally, based on the experimental results, two optical systems that can be applied to high power laser uniformity transformation are presented.
Improvement of Anomoly Detection Algorithms in Hyperspectral Images using Discrete Wavelet Transform
Baghbidi, Mohsen Zare; Nilchi, Ahmad Reza Naghsh; Homayouni, Saeid; 10.5121/sipij.2011.2402
2012-01-01
Recently anomaly detection (AD) has become an important application for target detection in hyperspectral remotely sensed images. In many applications, in addition to high accuracy of detection we need a fast and reliable algorithm as well. This paper presents a novel method to improve the performance of current AD algorithms. The proposed method first calculates Discrete Wavelet Transform (DWT) of every pixel vector of image using Daubechies4 wavelet. Then, AD algorithm performs on four bands of "Wavelet transform" matrix which are the approximation of main image. In this research some benchmark AD algorithms including Local RX, DWRX and DWEST have been implemented on Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral datasets. Experimental results demonstrate significant improvement of runtime in proposed method. In addition, this method improves the accuracy of AD algorithms because of DWT's power in extracting approximation coefficients of signal, which contain the main behaviour of sig...
IMPROVEMENT OF ANOMALY DETECTION ALGORITHMS IN HYPERSPECTRAL IMAGES USING DISCRETE WAVELET TRANSFORM
Kamal Jamshidi; Mohsen Zare Baghbidi; Ahmad Reza Naghsh Nilchi; Saeid Homayouni
2012-01-01
Recently anomaly detection (AD) has become an important application for target detection in hyperspectral remotely sensed images. In many applications, in addition to high accuracy of detection we need a fast and reliable algorithm as well. This paper presents a novel method to improve the performance of current AD algorithms. The proposed method first calculates Discrete Wavelet Transform (DWT) of every pixel vector of image using Daubechies4 wavelet. Then, AD algorithm performs on four band...
Guocheng Yang; Meiling Li; Leiting Chen; Jie Yu
2015-01-01
We propose a novel medical image fusion scheme based on the statistical dependencies between coefficients in the nonsubsampled contourlet transform (NSCT) domain, in which the probability density function of the NSCT coefficients is concisely fitted using generalized Gaussian density (GGD), as well as the similarity measurement of two subbands is accurately computed by Jensen-Shannon divergence of two GGDs. To preserve more useful information from source images, the new fusion rules are devel...
Institute of Scientific and Technical Information of China (English)
Xiao-Hui Yang; Li-Cheng Jiao; Deng-Feng Li
2009-01-01
A directional filter algorithm for intensity synthetic aperture radar (SAR) image based on nonsubsampled contourlet transform (NSCT) and immune clonal selection (ICS) is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.
High-contrast active cavitation imaging technique based on multiple bubble wavelet transform.
Lu, Shukuan; Xu, Shanshan; Liu, Runna; Hu, Hong; Wan, Mingxi
2016-08-01
In this study, a unique method that combines the ultrafast active cavitation imaging technique with multiple bubble wavelet transform (MBWT) for improving cavitation detection contrast was presented. The bubble wavelet was constructed by the modified Keller-Miksis equation that considered the mutual effect among bubbles. A three-dimensional spatial model was applied to simulate the spatial distribution of multiple bubbles. The effects of four parameters on the signal-to-noise ratio (SNR) of cavitation images were evaluated, including the following: initial radii of bubbles, scale factor in the wavelet transform, number of bubbles, and the minimum inter-bubble distance. And the other two spatial models and cavitation bubble size distributions were introduced in the MBWT method. The results suggested that in the free-field experiments, the averaged SNR of images acquired by the MBWT method was improved by 7.16 ± 0.09 dB and 3.14 ± 0.14 dB compared with the values of images acquired by the B-mode and single bubble wavelet transform (SBWT) methods. In addition, in the tissue experiments, the averaged cavitation-to-tissue ratio of cavitation images acquired by the MBWT method was improved by 4.69 ± 0.25 dB and 1.74± 0.29 dB compared with that of images acquired by B-mode and SBWT methods.
A method based on IHS cylindrical transform model for quality assessment of image fusion
Zhu, Xiaokun; Jia, Yonghong
2005-10-01
Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.
Institute of Scientific and Technical Information of China (English)
Zhao Bin; Quan Taifan; Wang Jinrong
2005-01-01
The imaging and target detection methods for stepped frequency signal based on the wavelet transform and its power spectrum are investigated. Not only an imaging and target detection algorithm for stepped frequency signal based on the wavelet transform, but also its respective power spectrum are proposed. The multisampling property of stepped frequency signal is studied and wavelet transform is well suited for analyzing the signal. After multisampling property of stepped frequency signal being studied, it is shown that the wavelet transform is appropriate to analyze the signal. Based on the theory, the wavelet power spectrum analysis is applied to obtain the target range profile and the binary wavelet transform is used to perform target detection. To determine a suitable wavelet scaling for imaging of range profile' s MMW radar, the distance resolution △R technique is proposed. The effectiveness of this new method is evaluated using simulated noisy radar signal. Results show that the proposed method can bring out the exactness and low computational complexity of this method.
Manu V T; Philomina Simon
2012-01-01
Image fusion produces a single fused image from a set of input images. A new method for image fusion is proposed based on Weighted Average Merging Method (WAMM) in the Non Subsampled Contourlet Transform (NSCT) domain. A performance analysis on various statistical fusion rules are also analysed both in NSCT and Wavelet domain. Analysis has been made on medical images, remote sensing images and multi focus images. Experimental results shows that the proposed method, WAMM obtained better resu...
Ground target detection based on discrete cosine transform and Rényi entropy for imaging ladar
Xu, Yuannan; Chen, Weili; Li, Junwei; Dong, Yanbing
2016-01-01
The discrete cosine transform (DCT) due to its excellent properties that the images can be represented in spatial/spatial-frequency domains, has been applied in sequence data analysis and image fusion. For intensity and range images of ladar, through the DCT using one dimension window, the statistical property of Rényi entropy for images is studied. We also analyzed the change of Rényi entropy's statistical property in the ladar intensity and range images when the man-made objects appear. From this foundation, a novel method for generating saliency map based on DCT and Rényi entropy is proposed. After that, ground target detection is completed when the saliency map is segmented using a simple and convenient threshold method. For the ladar intensity and range images, experimental results show the proposed method can effectively detect the military vehicles from complex earth background with low false alarm.
Spatial and Transform Domain Filtering Method for Image De-noising: A Review
Directory of Open Access Journals (Sweden)
Vandana Roy
2013-09-01
Full Text Available Present investigation reveals the quantum of work carried in the filtering methods for image de-noising. An image is often gets corrupted by various noises that are visible or invisible while being gathered, coded, acquired and transmitted. Noise influences various process parameters that may cause a quality problem for further image processing. De-noising of natural images is appears to be very simple however when considered under practical situations becomes complex. It has been cited by various author that parameter such as type and quantum of noise, image etc. through single algorithm or approach becomes cumbersome when results are optimized. In order to improve the quality of an image noise must be removed when the image is pre-processed and the important signal features like edge details should be retained as much as possible. The search on efficient image de-noising methods is still a valid challenge at the crossing of functional analysis and statistics. This paper reviews significant de-noising methods (spatial and transform domain method and their salient features and applications. One filter in each category has been taken in consideration to understand the characteristics of both spatial and transform domain filters.
A progressive transmission image coder using linear phase uniform filterbanks as block transforms.
Tran, T D; Nguyen, T Q
1999-01-01
This paper presents a novel image coding scheme using M-channel linear phase perfect reconstruction filterbanks (LPPRFBs) in the embedded zerotree wavelet (EZW) framework introduced by Shapiro (1993). The innovation here is to replace the EZWs dyadic wavelet transform by M-channel uniform-band maximally decimated LPPRFBs, which offer finer frequency spectrum partitioning and higher energy compaction. The transform stage can now be implemented as a block transform which supports parallel processing and facilitates region-of-interest coding/decoding. For hardware implementation, the transform boasts efficient lattice structures, which employ a minimal number of delay elements and are robust under the quantization of lattice coefficients. The resulting compression algorithm also retains all the attractive properties of the EZW coder and its variations such as progressive image transmission, embedded quantization, exact bit rate control, and idempotency. Despite its simplicity, our new coder outperforms some of the best image coders published previously in the literature, for almost all test images (especially natural, hard-to-code ones) at almost all bit rates.
An imaging algorithm based on keystone transform for one-stationary bistatic SAR of spotlight mode
Qiu, Xiaolan; Behner, Florian; Reuter, Simon; Nies, Holger; Loffeld, Otmar; Huang, Lijia; Hu, Donghui; Ding, Chibiao
2012-12-01
This article proposes an imaging algorithm based on Keystone Transform for bistatic SAR with a stationary receiver. It can efficiently be applied to high-resolution spotlight mode, and can directly be process the bistatic SAR data which have been ranged compressed by the synchronization reference pulses. Both simulation and experimental results validate the good performance of this algorithm.
Institute of Scientific and Technical Information of China (English)
Wang Na; Zhang Li; Zhou Xiao'an; Jia Chuanying; Li Xia
2005-01-01
This letter exploits fundamental characteristics of a wavelet transform image to form a progressive octave-based spatial resolution. Each wavelet subband is coded based on zeroblock and quardtree partitioning ordering scheme with memory optimization technique. The method proposed in this letter is of low complexity and efficient for Internet plug-in software.
DEFF Research Database (Denmark)
Rogge, Derek; Bachmann, Martin; Rivard, Benoit
2014-01-01
-line surveys, or temporal data sets as computational burden becomes significant. In this paper we present a spatial-spectral approach to deriving high signal quality eigenvectors for image transformations which possess an inherently ability to reduce the effects of noise. The approach applies a spatial...
Rotated Walsh-Hadamard Spreading with Robust Channel Estimation for a Coded MC-CDMA System
Directory of Open Access Journals (Sweden)
Raulefs Ronald
2004-01-01
Full Text Available We investigate rotated Walsh-Hadamard spreading matrices for a broadband MC-CDMA system with robust channel estimation in the synchronous downlink. The similarities between rotated spreading and signal space diversity are outlined. In a multiuser MC-CDMA system, possible performance improvements are based on the chosen detector, the channel code, and its Hamming distance. By applying rotated spreading in comparison to a standard Walsh-Hadamard spreading code, a higher throughput can be achieved. As combining the channel code and the spreading code forms a concatenated code, the overall minimum Hamming distance of the concatenated code increases. This asymptotically results in an improvement of the bit error rate for high signal-to-noise ratio. Higher convolutional channel code rates are mostly generated by puncturing good low-rate channel codes. The overall Hamming distance decreases significantly for the punctured channel codes. Higher channel code rates are favorable for MC-CDMA, as MC-CDMA utilizes diversity more efficiently compared to pure OFDMA. The application of rotated spreading in an MC-CDMA system allows exploiting diversity even further. We demonstrate that the rotated spreading gain is still present for a robust pilot-aided channel estimator. In a well-designed system, rotated spreading extends the performance by using a maximum likelihood detector with robust channel estimation at the receiver by about 1 dB.
Finding a Hadamard Matrix by Simulated Annealing of Spin-Vectors
Suksmono, Andriyan Bayu
2016-01-01
Reformulation of a combinatorial problem into optimization of a statistical-mechanics system, enables finding a better solution using heuristics derived from a physical process, such as by the SA (Simulated Annealing). In this paper, we present a Hadamard matrix (H-matrix) searching method based on the SA on an Ising model. By equivalence, an H-matrix can be converted into an SH (Semi-normalized Hadamard) matrix; whose first columns are unity vector and the rest ones are vectors with equal number of -1 and +1 called SH-vectors. We define SH spin-vectors to represent the SH vectors, which play the role of the spins on the Ising model. The topology of the lattice is generalized into a graph, whose edges represent orthogonality relationship among the SH spin-vectors. Started from a randomly generated quasi H-matrix Q, which is a matrix similar to the SH-matrix without imposing orthogonality, we perform the SA. The transitions of Q are conducted by random exchange of {+,-} spin-pair within the SH-spin vectors whi...
补差集与Hadamard矩阵%Supplementary difference sets and Hadamard matrices
Institute of Scientific and Technical Information of China (English)
娄联堂; 夏明远; 左国新
2001-01-01
In this article we obtain 2s-｛q2;q(q-1)/2;2s-2q(q-2)｝ supplementary difference sets(SDSs) for q=2s+1k+2s-1(s≥2), q is a prime power, prove that there exist Hadamard matrices of order 2tq2 for t≥s. Let q be any odd number. We prove that there exists a s=s(q) so that there is an Hadamard matrix of order 2tq for t≥s.%对任何奇素数幂q=2s+1k+2s-1(s≥2)构造出了2s-{q2;q(q-1)/2;2s-2q(q-2)｝补差集, 证明了存在2tq2阶Hadamard矩阵(t≥s), 并且对任何奇自然数q证明了存在s=s(q), 对任意t≥s存在2tq阶Hadamard矩阵.
On a Fast p-ary m-Sequence Transform
Institute of Scientific and Technical Information of China (English)
唐小虎; 范平志
2004-01-01
m-Sequences have been used widely in many applications, but the corresponding computation of the correlation-detection is overwhelming N2 operations, where N is the length of the m-sequence, such that it is unpractical. In this paper, a transform from p-ary m-sequence matrices to generalized Hadamard matrices is developed; and then by the fast generalized Hadamard matrices transform, a fast p-ary m-sequence transform is developed. The results show that the computation can be dramatically reduced from N2 to NlogpN operations, so the fast p-ary m-sequence transform could enable a rapid correlation-detection at the receiver.
Directory of Open Access Journals (Sweden)
Yasuhisa Fujiki
Full Text Available Functional fluorescence imaging has been widely applied to analyze spatio-temporal patterns of cellular dynamics in the brain and spinal cord. However, it is difficult to integrate spatial information obtained from imaging data in specific regions of interest across multiple samples, due to large variability in the size, shape and internal structure of samples. To solve this problem, we attempted to standardize transversely sectioned spinal cord images focusing on the laminar structure in the gray matter. We employed three standardization methods, the affine transformation (AT, the angle-dependent transformation (ADT and the combination of these two methods (AT+ADT. The ADT is a novel non-linear transformation method developed in this study to adjust an individual image onto the template image in the polar coordinate system. We next compared the accuracy of these three standardization methods. We evaluated two indices, i.e., the spatial distribution of pixels that are not categorized to any layer and the error ratio by the leave-one-out cross validation method. In this study, we used neuron-specific marker (NeuN-stained histological images of transversely sectioned cervical spinal cord slices (21 images obtained from 4 rats to create the standard atlas and also to serve for benchmark tests. We found that the AT+ADT outperformed other two methods, though the accuracy of each method varied depending on the layer. This novel image standardization technique would be applicable to optical recording such as voltage-sensitive dye imaging, and will enable statistical evaluations of neural activation across multiple samples.
图像压缩编码中Walsh变换与DCT变换及其比较%Walsh Transform and DCT Transform in Image Compression Coding
Institute of Scientific and Technical Information of China (English)
龙清
2011-01-01
图像变换是图像处理的基础,是图像压缩的第一步.在图像压缩中,DCT变换因其变换效果好而被广泛采用,成为目前最常用的图像压缩变换方法,而Walsh变换还未被广泛采用.通过对这两种变换的算法分析以及Matlab仿真实验和峰值信噪比的对比,结果表明,Walsh变换在算法上比DCT简单,实现较为容易,其变换性能并不亚于DCT变换,在某些量化级上甚至还优于DCT变换,Walsh变换有着广泛的应用前景.%Image transform is the foundation of image processing and the first step of image compression coding. Because of its good effect in image transform, the DCT transform has been used widely, and has became the most common transform method in image compression coding. By analyzing the DCT transform and Walsh transform, and comparing the MATLAB simulation experiment with PSNR, the results show that the Walsh transform is not inferior to the DCT transform in performance, and in some quantitative level it is superior to the DCT transform. Besides, the Walsh transform is simpler than the DCT in algorithm. It can be used widely in future.
Edge detection based on object tree image representation and wavelet transform
Institute of Scientific and Technical Information of China (English)
屈彦呈; 王常虹; 庄显义
2003-01-01
In applications such as image retrieval and recognition, precise edge detection for interested regions plays a decisive role. Existing methods generally take little care about local characteristics, or become time-consuming if every detail is considered. In the paper, a new method is put forward based on the combination of effective image representation and multiscale wavelet analysis. A new object tree image representation is introduced. Then a series of object trees are constructed based on wavelet transform modulus maxima at different scales in descending order. Computation is only needed for interested regions. Implementation steps are also given with an illustrative example.
Double-image encryption based on joint transform correlation and phase-shifting interferometry
Institute of Scientific and Technical Information of China (English)
Lina Shen; Jun Li; Hongsen Chang
2007-01-01
An image encryption method combining the joint transform correlator (JTC) architecture with phaseshifting interferometry to realize double random-phase encoding is proposed. The encrypted field and the decrypting key are registered as holograms by phase-shifting interferometry. This method can encrypt two images simultaneously to improve the encryption efficiency of the methods based on JTC architecture, and eliminate the system alignment constraint of the methods based on Mach-Zehnder interferometer (MZI)architecture. Its feasibility and validity are verified by computer simulations. Moreover, image encryption and decryption can be achieved at high speed optically or digitally. The encrypted data are suitable for Internet transmission.
Zhang, Yushu; Xiao, Di; Wen, Wenying; Tian, Yuan
2013-12-01
In some special multimedia applications, only the regions with semantic information should be provided better protection whereas the other smooth regions can be free of encryption. However, most of the existing multimedia security schemes only consider bits and pixels rather than semantic information during their encryption. Motivated by this, we propose an edge-based lightweight image encryption scheme using chaos-based reversible hidden transform and multiple-order discrete fractional cosine transform. An image is first carried out by the edge detection based on advanced CNN structure with adaptive thresholds to assess data significance in the image. The detection output is a binary image, in which a “1” reflects the detected pixel whereas a “0” is opposite. Both the detected image and the original image are divided into non-overlapping pixel blocks in the same way, respectively. Whether each block is encrypted or not depends on the significance judged by the corresponding detected block. The significant block is performed by reversible hidden transform followed by multiple-order discrete fractional cosine transform parameters and orders of these two transforms are determined by a two dimensional cross chaotic map. Experiment results show the significant contour features of an image that have been largely hidden only by encrypting about half pixels in the average sense. The keys are extremely sensitive and the proposed scheme can resist noise attack to some extent.
Fetal skull analysis in ultrasound images based on iterative randomized Hough transform
Shen, Yufei; Yu, Jinhua; Shen, Yuzhong; Wang, Yuanyuan
2009-02-01
Analysis of ultrasound fetal head images is a daily routine for medical professionals in obstetrics. The contours of fetal skulls often appear discontinuous and irregular in clinical ultrasound images, making it difficult to measure the fetal head size automatically. In addition, the presence of heavy noise in ultrasound images is another challenge for computer aided automatic fetal head detection. In this paper, we first utilize the stick method to suppress the noise and compute an adaptive threshold for fetal skull segmentation. Morphological thinning is then performed to obtain a skeleton image, which is used as an input to the Hough transform. Finally, automatic fetal skull detection is realized by Iterative Randomized Hough Transform (IRHT). The elliptic eccentricity is used in the IRHT to reduce the number of invalid accumulations in the parameter space, improving the detection accuracy. Furthermore, the target region is adaptively adjusted in the IRHT. To evaluate the performance of IRHT, we also developed a simulation user interface for comparing results produced by the conventional randomized Hough transform (RHT) and the IRHT. Experimental results showed that the proposed method is effective for automatic fetal head detection in ultrasound images.
Singh, Hukum
2016-12-01
A cryptosystem for securing image encryption is considered by using double random phase encoding in Fresnel wavelet transform (FWT) domain. Random phase masks (RPMs) and structured phase masks (SPMs) based on devil's vortex toroidal lens (DVTL) are used in spatial as well as in Fourier planes. The images to be encrypted are first Fresnel transformed and then single-level discrete wavelet transform (DWT) is apply to decompose LL,HL, LH and HH matrices. The resulting matrices from the DWT are multiplied by additional RPMs and the resultants are subjected to inverse DWT for the encrypted images. The scheme is more secure because of many parameters used in the construction of SPM. The original images are recovered by using the correct parameters of FWT and SPM. Phase mask SPM based on DVTL increases security that enlarges the key space for encryption and decryption. The proposed encryption scheme is a lens-less optical system and its digital implementation has been performed using MATLAB 7.6.0 (R2008a). The computed value of mean-squared-error between the retrieved and the input images shows the efficacy of scheme. The sensitivity to encryption parameters, robustness against occlusion, entropy and multiplicative Gaussian noise attacks have been analysed.
STEGO TRANSFORMATION OF SPATIAL DOMAIN OF COVER IMAGE ROBUST AGAINST ATTACKS ON EMBEDDED MESSAGE
Directory of Open Access Journals (Sweden)
Kobozeva A.
2014-04-01
Full Text Available One of the main requirements to steganografic algorithm to be developed is robustness against disturbing influences, that is, to attacks against the embedded message. It was shown that guaranteeing the stego algorithm robustness does not depend on whether the additional information is embedded into the spatial or transformation domain of the cover image. Given the existing advantages of the spatial domain of the cover image in organization of embedding and extracting processes, a sufficient condition for ensuring robustness of such stego transformation was obtained in this work. It was shown that the amount of brightness correction related to the pixels of the cover image block is similar to the amount of correction related to the maximum singular value of the corresponding matrix of the block in case of embedding additional data that ensures robustness against attacks on the embedded message. Recommendations were obtained for selecting the size of the cover image block used in stego transformation as one of the parameters determining the calculation error of stego message. Given the inversely correspondence between the stego capacity of the stego channel being organized and the size of the cover image block, l=8 value was recommended.
An Image Filter Based on Multiobjective Genetic Algorithm and Shearlet Transformation
Directory of Open Access Journals (Sweden)
Zhi-yong Fan
2013-01-01
Full Text Available Rician noise pollutes magnetic resonance imaging (MRI data, making data’s postprocessing difficult. In order to remove this noise and avoid loss of details as much as possible, we proposed a filter algorithm using both multiobjective genetic algorithm (MOGA and Shearlet transformation. Firstly, the multiscale wavelet decomposition is applied to the target image. Secondly, the MOGA target function is constructed by evaluation methods, such as signal-to-noise ratio (SNR and mean square error (MSE. Thirdly, MOGA is used with optimal coefficients of Shearlet wavelet threshold value in a different scale and a different orientation. Finally, the noise-free image could be obtained through inverse wavelet transform. At the end of the paper, experimental results show that this proposed algorithm eliminates Rician noise more effectively and yields better peak signal-to-noise ratio (PSNR gains compared with other traditional filters.
Dong, Bing; Qin, Shun; Hu, Xinqi
2013-09-01
Large-aperture segmented primary mirror will be widely used in next-generation space-based and ground-based telescopes. The effects of intersegment gaps, obstructions, position and figure errors of segments, which are all involved in the pupil plane, on the image quality metric should be analyzed using diffractive imaging theory. Traditional Fast Fourier Transform (FFT) method is very time-consuming and costs a lot of memory especially in dealing with large pupil-sampling matrix. A Partial Fourier Transform (PFT) method is first proposed to substantially speed up the computation and reduce memory usage for diffractive imaging analysis. Diffraction effects of a 6-meter segmented mirror including 18 hexagonal segments are simulated and analyzed using PFT method. The influence of intersegment gaps and position errors of segments on Strehl ratio is quantitatively analyzed by computing the Point Spread Function (PSF). By comparing simulation results with theoretical results, the correctness and feasibility of PFT method is confirmed.
Medical Image Watermarking in Sub-block Three-dimensional Discrete Cosine Transform Domain
Directory of Open Access Journals (Sweden)
Baoru Han
2016-03-01
Full Text Available Digital watermarking can be applied to protection of medical images privacy, hiding of patient's diagnosis information and so on. In order to improve the ability of resisting geometric attacks, a new watermarking algorithm for medical volume data in sub-block three-dimensional discrete cosine transform domain is presented. The original watermarking image is scrambled by a Chebyshev chaotic neural network so as to improve watermarking security. Sub-block three-dimensional discrete cosine transform and perceptual hashing are used to construct zero-watermarking. In this way it does not produce medical image distortion and gives the algorithm the ability to resist geometric attacks. Experimental results show that the algorithm has good security, and it has good robustness to various geometric attacks.
Wei, Zhao; Tao, Feng; Jun, Wang
2013-10-01
An efficient, robust, and accurate approach is developed for image registration, which is especially suitable for large-scale change and arbitrary rotation. It is named the adequately sampling polar transform and weighted angular projection function (ASPT-WAPF). The proposed ASPT model overcomes the oversampling problem of conventional log-polar transform. Additionally, the WAPF presented as the feature descriptor is robust to the alteration in the fovea area of an image, and reduces the computational cost of the following registration process. The experimental results show two major advantages of the proposed method. First, it can register images with high accuracy even when the scale factor is up to 10 and the rotation angle is arbitrary. However, the maximum scaling estimated by the state-of-the-art algorithms is 6. Second, our algorithm is more robust to the size of the sampling region while not decreasing the accuracy of the registration.
Zhong, Zhi; Qin, Haitao; Liu, Lei; Zhang, Yabin; Shan, Mingguang
2017-03-20
A novel approach for silhouette-free image encryption based on interference is proposed using discrete multiple-parameter fractional Fourier transform (DMPFrFT), which generalizes from fractional Fourier transform. An original image is firstly applied by chaotic pixel scrambling (CPS) and then encoded into the real part of a complex signal. Using interference principle, the complex signal generates three phase-only masks in DMPFrFT domain. The silhouette of the original image cannot be extracted using one or two of the three phase-only masks. The parameters of both CPS and DMPFrFT can also serve as encryption keys to extend the key space, which further enhance the level of cryptosystem security. Numerical simulations are demonstrated to show the feasibility and validity of this approach.
Zhang, Miao; Tong, Xiaojun
2017-07-01
This paper proposes a joint image encryption and compression scheme based on a new hyperchaotic system and curvelet transform. A new five-dimensional hyperchaotic system based on the Rabinovich system is presented. By means of the proposed hyperchaotic system, a new pseudorandom key stream generator is constructed. The algorithm adopts diffusion and confusion structure to perform encryption, which is based on the key stream generator and the proposed hyperchaotic system. The key sequence used for image encryption is relation to plain text. By means of the second generation curvelet transform, run-length coding, and Huffman coding, the image data are compressed. The joint operation of compression and encryption in a single process is performed. The security test results indicate the proposed methods have high security and good compression effect.
CW-THz image contrast enhancement using wavelet transform and Retinex
Chen, Lin; Zhang, Min; Hu, Qi-fan; Huang, Ying-Xue; Liang, Hua-Wei
2015-10-01
To enhance continuous wave terahertz (CW-THz) scanning images contrast and denoising, a method based on wavelet transform and Retinex theory was proposed. In this paper, the factors affecting the quality of CW-THz images were analysed. Second, an approach of combination of the discrete wavelet transform (DWT) and a designed nonlinear function in wavelet domain for the purpose of contrast enhancing was applied. Then, we combine the Retinex algorithm for further contrast enhancement. To evaluate the effectiveness of the proposed method in qualitative and quantitative, it was compared with the adaptive histogram equalization method, the homomorphic filtering method and the SSR(Single-Scale-Retinex) method. Experimental results demonstrated that the presented algorithm can effectively enhance the contrast of CW-THZ image and obtain better visual effect.
Full-field optical coherence tomography image restoration based on Hilbert transformation
Na, Jihoon; Choi, Woo June; Choi, Eun Seo; Ryu, Seon Young; Lee, Byeong Ha
2007-02-01
We propose the envelope detection method that is based on Hilbert transform for image restoration in full-filed optical coherence tomography (FF-OCT). The FF-OCT system presenting a high-axial resolution of 0.9 μm was implemented with a Kohler illuminator based on Linnik interferometer configuration. A 250 W customized quartz tungsten halogen lamp was used as a broadband light source and a CCD camera was used as a 2-dimentional detector array. The proposed image restoration method for FF-OCT requires only single phase-shifting. By using both the original and the phase-shifted images, we could remove the offset and the background signals from the interference fringe images. The desired coherent envelope image was obtained by applying Hilbert transform. With the proposed image restoration method, we demonstrate en-face imaging performance of the implemented FF-OCT system by presenting a tilted mirror surface, an integrated circuit chip, and a piece of onion epithelium.
Optical image encryption based on a joint Fresnel transform correlator with double optical wedges.
Shen, Xueju; Dou, Shuaifeng; Lei, Ming; Chen, Yudan
2016-10-20
An optical cryptosystem based on the joint Fresnel transform correlator (JFTC) with double optical wedges is designed. The designed cryptosystem retains the two major advantages of JTC-based optical cryptosystems. First, the encrypted image is real-valued and therefore is easier to record and transmit. Second, the encryption process is simplified, since it doesn't require accurate alignment of optical elements or the generation of the complex conjugate of the key. Also, the designed optical cryptosystem can produce a decrypted image with higher quality than a JTC-based optical cryptosystem, because the original encrypted image is divided by the Fresnel transform power distribution of the key mask to generate the new encrypted image, which significantly reduces the noise during the decryption process. Simulation results showed that the correlation coefficient of the decrypted image and the original image can reach as large as 0.9819 after denoising and adequately selecting half-central interval a and encrypted image width w. Another improvement relative to JTC-based optical cryptosystems is that the attack resistibility gets enhanced due to the nonlinearity of the encryption process as well as the additional key parameter a, which enlarges the key space.
Sui, Liansheng; Duan, Kuaikuai; Liang, Junli; Hei, Xinhong
2014-05-05
A double-image encryption is proposed based on the discrete fractional random transform and logistic maps. First, an enlarged image is composited from two original images and scrambled in the confusion process which consists of a number of rounds. In each round, the pixel positions of the enlarged image are relocated by using cat maps which are generated based on two logistic maps. Then the scrambled enlarged image is decomposed into two components. Second, one of two components is directly separated into two phase masks and the other component is used to derive the ciphertext image with stationary white noise distribution by using the cascaded discrete fractional random transforms generated based on the logistic map. The cryptosystem is asymmetric and has high resistance against to the potential attacks such as chosen plaintext attack, in which the initial values of logistic maps and the fractional orders are considered as the encryption keys while two decryption keys are produced in the encryption process and directly related to the original images. Simulation results and security analysis verify the feasibility and effectiveness of the proposed encryption scheme.
Image encryption using the Gyrator transform and random phase masks generated by using chaos
Vilardy, Juan M.; Jimenez, Carlos J.; Perez, Ronal
2017-06-01
The Gyrator transform (GT), chaotic random phase masks (CRPMs) and a random permutation of the Jigsaw transform (JT) are utilized to design an images encryption-decryption system. The encryption-decryption system is based on the double random phase encoding (DRPE) in the Gyrator domain (GD), this technique uses two random phase masks (RPMs) to encode the image to encrypt (original image) into a random noise. The RPMs are generated by using chaos, these masks are CRPMs. The parameters of the chaotic function have the control of the generation of the CRPMs. We apply a random permutation to the resulting image of the DRPE technique, with the purpose of obtaining an encrypted image with a higher randomness. In order to successfully retrieve the original image (without errors or noise-free) at the output of the decryption system is necessary to have all the proper keys, which are: the rotation angles of the GTs, the parameters of the chaotic function utilized to generate the two CRPMs and the random permutation of the JT. We check and analyze the validity of the image encryption and decryption systems by means of computing simulations.
Triple-image encryption based on phase-truncated Fresnel transform and basic vector operation.
Pan, Xuemei; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi
2015-10-01
A triple-image encryption method is proposed that is based on phase-truncated Fresnel transform (PTFT), basic vector composition, and XOR operation. In the encryption process, two random phase masks, with one each placed at the input plane and the transform plane, are generated by basic vector resolution operations over the first and the second plaintext images, and then a ciphered image in the input plane is fabricated by XOR encoding for the third plaintext image. When the cryptosystem is illuminated by an on-axis plane, assisted by PTFT, the ciphered image is finally encrypted into an amplitude-only noise-like image in the output plane. During decryption, possessing the correct private key, decryption keys, and the assistant geometrical parameter keys, and placing them at the corresponding correct positions, the original three plaintext images can be successfully decrypted by inverse PTFT, basic vector composition, and XOR decoding. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.
APPLICATION OF TWO-DIMENSIONAL WAVELET TRANSFORM IN NEAR-SHORE X-BAND RADAR IMAGES
Institute of Scientific and Technical Information of China (English)
FENG Xiang-bo; YAN Yi-xin; ZHANG Wei
2011-01-01
Among existing remote sensing applications, land-based X-band radar is an effective technique to monitor the wave fields,and spatial wave information could be obtained from the radar images.Two-dimensional Fourier Transform (2-D FT) is the common algorithm to derive the spectra of radar images.However, the wave field in the nearshore area is highly non-homogeneous due to wave refraction, shoaling, and other coastal mechanisms.When applied in nearshore radar images, 2-D FT would lead to ambiguity of wave characteristics in wave number domain.In this article, we introduce two-dimensional Wavelet Transform (2-D WT) to capture the non-homogeneity of wave fields from nearshore radar images.The results show that wave number spectra by 2-D WT at six parallel space locations in the given image clearly present the shoaling of nearshore waves.Wave number of the peak wave energy is increasing along the inshore direction, and dominant direction of the spectra changes from South South West (SSW) to West South West (WSW).To verify the results of2-D WT, wave shoaling in radar images is calculated based on dispersion relation.The theoretical calculation results agree with the results of 2-D WT on the whole.The encouraging performance of 2-D WT indicates its strong capability of revealing the non-homogeneity of wave fields in nearshore X-band radar images.
Bento, G C; Oliveira, P R
2008-01-01
Local convergence analysis of the proximal point method for special class of nonconvex function on Hadamard manifold is presented in this paper. The well definedness of the sequence generated by the proximal point method is guaranteed. Moreover, is proved that each cluster point of this sequence satisfies the necessary optimality conditions and, under additional assumptions, its convergence for a minimizer is obtained.
Directory of Open Access Journals (Sweden)
J. K. Mandal
2013-01-01
Full Text Available In this paper, a fragile watermarking based on two-dimensional Separable Discrete Hartley Transform hasbeen proposed for color image authentication (FWSDHTCIA. Two dimensional SDHT is applied on each2 × 2 sub-image block of the carrier image in row major order and produces four frequency components intransform domain. Due to the high sensitivity of human eye on green channel, only one authenticatingmessage/image bit is fabricated at the second bit position of each frequency component for every 2 × 2green sub-matrix. Unlikely, in every 2 × 2 red and blue sub-matrices, two bits from the authenticatingmessage/image are fabricated at the second and third bit position of each frequency component as thehuman eye is less sensitive on red and blue channels as compared to green. After fabricating theauthenticating watermark (message/image, a frequency adjustment strategy has been applied to get backthe less distorted watermarked image in spatial domain. A delicate re-adjustment has been incorporated inthe first frequency component of each 2 × 2 mask, to keep the quantum value positive in spatial domainwithout hampering the authenticating watermark bits. Two dimensional inverse SDHT (ISDHT is appliedon each 2 × 2 sub-mask as post embedding operation to produce the watermarked image. At the receivingend reverse operation is performed to extract the stream which is compared to the original stream forauthentication. Experimental results conform that the proposed algorithm has improvised the payload andPSNR values over SDHTIWCIA [7] scheme which is previously proposed by us. Also, the proposedFWSDHTCIA scheme produces much better result than the Discrete Cosine Transform (DCT, QuaternionFourier Transformation (QFT and Spatio-Chromatic DFT (SCDFT based techniques.
Zhang, Leihong; Liang, Dong; Li, Bei; Kang, Yi; Pan, Zilan; Zhang, Dawei; Gao, Xiumin; Ma, Xiuhua
2016-07-01
On the basis of analyzing the cosine light field with determined analytic expression and the pseudo-inverse method, the object is illuminated by a presetting light field with a determined discrete Fourier transform measurement matrix, and the object image is reconstructed by the pseudo-inverse method. The analytic expression of the algorithm of computational ghost imaging based on discrete Fourier transform measurement matrix is deduced theoretically, and compared with the algorithm of compressive computational ghost imaging based on random measurement matrix. The reconstruction process and the reconstruction error are analyzed. On this basis, the simulation is done to verify the theoretical analysis. When the sampling measurement number is similar to the number of object pixel, the rank of discrete Fourier transform matrix is the same as the one of the random measurement matrix, the PSNR of the reconstruction image of FGI algorithm and PGI algorithm are similar, the reconstruction error of the traditional CGI algorithm is lower than that of reconstruction image based on FGI algorithm and PGI algorithm. As the decreasing of the number of sampling measurement, the PSNR of reconstruction image based on FGI algorithm decreases slowly, and the PSNR of reconstruction image based on PGI algorithm and CGI algorithm decreases sharply. The reconstruction time of FGI algorithm is lower than that of other algorithms and is not affected by the number of sampling measurement. The FGI algorithm can effectively filter out the random white noise through a low-pass filter and realize the reconstruction denoising which has a higher denoising capability than that of the CGI algorithm. The FGI algorithm can improve the reconstruction accuracy and the reconstruction speed of computational ghost imaging.
Validation of a high-content screening assay using whole-well imaging of transformed phenotypes.
Ramirez, Christina N; Ozawa, Tatsuya; Takagi, Toshimitsu; Antczak, Christophe; Shum, David; Graves, Robert; Holland, Eric C; Djaballah, Hakim
2011-06-01
Automated microscopy was introduced two decades ago and has become an integral part of the discovery process as a high-content screening platform with noticeable challenges in executing cell-based assays. It would be of interest to use it to screen for reversers of a transformed cell phenotype. In this report, we present data obtained from an optimized assay that identifies compounds that reverse a transformed phenotype induced in NIH-3T3 cells by expressing a novel oncogene, KP, resulting from fusion between platelet derived growth factor receptor alpha (PDGFRα) and kinase insert domain receptor (KDR), that was identified in human glioblastoma. Initial image acquisitions using multiple tiles per well were found to be insufficient as to accurately image and quantify the clusters; whole-well imaging, performed on the IN Cell Analyzer 2000, while still two-dimensional imaging, was found to accurately image and quantify clusters, due largely to the inherent variability of their size and well location. The resulting assay exhibited a Z' value of 0.79 and a signal-to-noise ratio of 15, and it was validated against known effectors and shown to identify only PDGFRα inhibitors, and then tested in a pilot screen against a library of 58 known inhibitors identifying mostly PDGFRα inhibitors as reversers of the KP induced transformed phenotype. In conclusion, our optimized and validated assay using whole-well imaging is robust and sensitive in identifying compounds that reverse the transformed phenotype induced by KP with a broader applicability to other cell-based assays that are challenging in HTS against chemical and RNAi libraries.
Kamal, Hussain A.; Cherri, Abdallah K.
2009-04-01
Being a popular choice among the biometric features, the fingerprint has long been used for identification and verification purposes by security agencies. In this paper, additional images are included in the input joint images in a joint transform correlator (JTC) to achieve a fast real-time fingerprint verification. In the proposed scheme, in addition to the reference and the target image, the input joint image has a complementary reference image and a complementary target image. At the correlation output of the JTC, the cross-correlation peak value between the reference and the complementary target image and the cross-correlation peak value between the complementary reference and the target images are used as the criteria to perform the recognition of the target in the input scene. It will be shown that these two cross-correlation peak values will be zero if and only if the input target matches the reference image. The scheme is employed to verify binary characters and binarized fingerprint images.
IMPROVEMENT OF ANOMALY DETECTION ALGORITHMS IN HYPERSPECTRAL IMAGES USING DISCRETE WAVELET TRANSFORM
Directory of Open Access Journals (Sweden)
Kamal Jamshidi
2012-01-01
Full Text Available Recently anomaly detection (AD has become an important application for target detection in hyperspectralremotely sensed images. In many applications, in addition to high accuracy of detection we need a fast andreliable algorithm as well. This paper presents a novel method to improve the performance of current ADalgorithms. The proposed method first calculates Discrete Wavelet Transform (DWT of every pixel vectorof image using Daubechies4 wavelet. Then, AD algorithm performs on four bands of “Wavelet transform”matrix which are the approximation of main image. In this research some benchmark AD algorithmsincluding Local RX, DWRX and DWEST have been implemented on Airborne Visible/Infrared ImagingSpectrometer (AVIRIS hyperspectral datasets. Experimental results demonstrate significant improvementof runtime in proposed method. In addition, this method improves the accuracy of AD algorithms becauseof DWT’s power in extracting approximation coefficients of signal, which contain the main behaviour ofsignal, and abandon the redundant information in hyperspectral image data.
High-definition Fourier transform infrared spectroscopic imaging of prostate tissue
Wrobel, Tomasz P.; Kwak, Jin Tae; Kadjacsy-Balla, Andre; Bhargava, Rohit
2016-03-01
Histopathology forms the gold standard for cancer diagnosis and therapy, and generally relies on manual examination of microscopic structural morphology within tissue. Fourier-Transform Infrared (FT-IR) imaging is an emerging vibrational spectroscopic imaging technique, especially in a High-Definition (HD) format, that provides the spatial specificity of microscopy at magnifications used in diagnostic surgical pathology. While it has been shown for standard imaging that IR absorption by tissue creates a strong signal where the spectrum at each pixel is a quantitative "fingerprint" of the molecular composition of the sample, here we show that this fingerprint also enables direct digital pathology without the need for stains or dyes for HD imaging. An assessment of the potential of HD imaging to improve diagnostic pathology accuracy is presented.
De-Noising Ultrasound Images of Colon Tumors Using Daubechies Wavelet Transform
Moraru, Luminita; Moldovanu, Simona; Nicolae, Mariana Carmen
2011-10-01
In this paper, we present a new approach to analysis of the cancer of the colon in ultrasonography. A speckle suppression method was presented. Daubechies wavelet transform is used due to its approximate shift invariance property and extra information in imaginary plane of complex wavelet domain when compared to real wavelet domain. The methods that we propose have provided quite satisfactory results and show the usefulness of image processing techniques in the diagnosis by means of medical imaging. Local echogenicity variance of ROI is utilized so as to compare with local echogenicity distribution within entire acquired image. Also the image was analyzed using the histogram which interprets the gray-level of images. Such information is valuable for the discrimination of tumors. The aim of this work is not the substitution of the specialist, but the generation of a series of parameters which reduce the need of carrying out the biopsy.
Montejo, Ludguier D.; Jia, Jingfei; Kim, Hyun K.; Hielscher, Andreas H.
2013-03-01
We apply the Fourier Transform to absorption and scattering coefficient images of proximal interphalangeal (PIP) joints and evaluate the performance of these coefficients as classifiers using receiver operator characteristic (ROC) curve analysis. We find 25 features that yield a Youden index over 0.7, 3 features that yield a Youden index over 0.8, and 1 feature that yields a Youden index over 0.9 (90.0% sensitivity and 100% specificity). In general, scattering coefficient images yield better one-dimensional classifiers compared to absorption coefficient images. Using features derived from scattering coefficient images we obtain an average Youden index of 0.58 +/- 0.16, and an average Youden index of 0.45 +/- 0.15 when using features from absorption coefficient images.
Directory of Open Access Journals (Sweden)
Liang Xu
2013-01-01
Full Text Available In the nonsubsampled contourlet transform (NSCT domain, a novel image fusion algorithm based on the visual attention model and pulse coupled neural networks (PCNNs is proposed. For the fusion of high-pass subbands in NSCT domain, a saliency-motivated PCNN model is proposed. The main idea is that high-pass subband coefficients are combined with their visual saliency maps as input to motivate PCNN. Coefficients with large firing times are employed as the fused high-pass subband coefficients. Low-pass subband coefficients are merged to develop a weighted fusion rule based on firing times of PCNN. The fused image contains abundant detailed contents from source images and preserves effectively the saliency structure while enhancing the image contrast. The algorithm can preserve the completeness and the sharpness of object regions. The fused image is more natural and can satisfy the requirement of human visual system (HVS. Experiments demonstrate that the proposed algorithm yields better performance.
Choi, Heejin; Wadduwage, Dushan; Matsudaira, Paul T; So, Peter T C
2014-10-01
A depth resolved hyperspectral imaging spectrometer can provide depth resolved imaging both in the spatial and the spectral domain. Images acquired through a standard imaging Fourier transform spectrometer do not have the depth-resolution. By post processing the spectral cubes (x, y, λ) obtained through a Sagnac interferometer under uniform illumination and structured illumination, spectrally resolved images with depth resolution can be recovered using structured light illumination algorithms such as the HiLo method. The proposed scheme is validated with in vitro specimens including fluorescent solution and fluorescent beads with known spectra. The system is further demonstrated in quantifying spectra from 3D resolved features in biological specimens. The system has demonstrated depth resolution of 1.8 μm and spectral resolution of 7 nm respectively.
Sang, Jun; Zhao, Jun; Xiang, Zhili; Cai, Bin; Xiang, Hong
2015-08-05
Gyrator transform has been widely used for image encryption recently. For gyrator transform-based image encryption, the rotation angle used in the gyrator transform is one of the secret keys. In this paper, by analyzing the properties of the gyrator transform, an improved particle swarm optimization (PSO) algorithm was proposed to search the rotation angle in a single gyrator transform. Since the gyrator transform is continuous, it is time-consuming to exhaustedly search the rotation angle, even considering the data precision in a computer. Therefore, a computational intelligence-based search may be an alternative choice. Considering the properties of severe local convergence and obvious global fluctuations of the gyrator transform, an improved PSO algorithm was proposed to be suitable for such situations. The experimental results demonstrated that the proposed improved PSO algorithm can significantly improve the efficiency of searching the rotation angle in a single gyrator transform. Since gyrator transform is the foundation of image encryption in gyrator transform domains, the research on the method of searching the rotation angle in a single gyrator transform is useful for further study on the security of such image encryption algorithms.
Directory of Open Access Journals (Sweden)
Jun Sang
2015-08-01
Full Text Available Gyrator transform has been widely used for image encryption recently. For gyrator transform-based image encryption, the rotation angle used in the gyrator transform is one of the secret keys. In this paper, by analyzing the properties of the gyrator transform, an improved particle swarm optimization (PSO algorithm was proposed to search the rotation angle in a single gyrator transform. Since the gyrator transform is continuous, it is time-consuming to exhaustedly search the rotation angle, even considering the data precision in a computer. Therefore, a computational intelligence-based search may be an alternative choice. Considering the properties of severe local convergence and obvious global fluctuations of the gyrator transform, an improved PSO algorithm was proposed to be suitable for such situations. The experimental results demonstrated that the proposed improved PSO algorithm can significantly improve the efficiency of searching the rotation angle in a single gyrator transform. Since gyrator transform is the foundation of image encryption in gyrator transform domains, the research on the method of searching the rotation angle in a single gyrator transform is useful for further study on the security of such image encryption algorithms.
Image Reconstruction from Under sampled Fourier Data Using the Polynomial Annihilation Transform
Energy Technology Data Exchange (ETDEWEB)
Archibald, Richard K. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gelb, Anne [Arizona State Univ., Mesa, AZ (United States); Platte, Rodrigo [Arizona State Univ., Mesa, AZ (United States)
2015-09-09
Fourier samples are collected in a variety of applications including magnetic resonance imaging and synthetic aperture radar. The data are typically under-sampled and noisy. In recent years, l^{1} regularization has received considerable attention in designing image reconstruction algorithms from under-sampled and noisy Fourier data. The underlying image is assumed to have some sparsity features, that is, some measurable features of the image have sparse representation. The reconstruction algorithm is typically designed to solve a convex optimization problem, which consists of a fidelity term penalized by one or more l^{1} regularization terms. The Split Bregman Algorithm provides a fast explicit solution for the case when TV is used for the l1l1 regularization terms. Due to its numerical efficiency, it has been widely adopted for a variety of applications. A well known drawback in using TV as an l^{1} regularization term is that the reconstructed image will tend to default to a piecewise constant image. This issue has been addressed in several ways. Recently, the polynomial annihilation edge detection method was used to generate a higher order sparsifying transform, and was coined the “polynomial annihilation (PA) transform.” This paper adapts the Split Bregman Algorithm for the case when the PA transform is used as the l^{1} regularization term. In so doing, we achieve a more accurate image reconstruction method from under-sampled and noisy Fourier data. Our new method compares favorably to the TV Split Bregman Algorithm, as well as to the popular TGV combined with shearlet approach.
A novel polar format algorithm for SAR images utilizing post azimuth transform interpolation.
Energy Technology Data Exchange (ETDEWEB)
Holzrichter, Michael Warren; Martin, Grant D.; Doerry, Armin Walter
2005-09-01
SAR phase history data represents a polar array in the Fourier space of a scene being imaged. Polar Format processing is about reformatting the collected SAR data to a Cartesian data location array for efficient processing and image formation. In a real-time system, this reformatting or ''re-gridding'' operation is the most processing intensive, consuming the majority of the processing time; it also is a source of error in the final image. Therefore, any effort to reduce processing time while not degrading image quality is valued. What is proposed in this document is a new way of implementing real-time polar-format processing through a variation on the traditional interpolation/2-D Fast Fourier Transform (FFT) algorithm. The proposed change is based upon the frequency scaling property of the Fourier Transform, which allows a post azimuth FFT interpolation. A post azimuth processing interpolation provides overall benefits to image quality and potentially more efficient implementation of the polar format image formation process.
Optical multiple-image encryption based on phase encoding algorithm in the Fresnel transform domain
Huang, Jian-Ji; Hwang, Hone-Ene; Chen, Chun-Yuan; Chen, Ching-Mu
2012-10-01
A novel method of the optical multiple-image encryption based on the modified Gerchberg-Saxton algorithm (MGSA) is presented. This proposed method with an architecture of two adjacent phase only functions (POFs) in the Fresnel transform (FrT) domain that can extremely increase capacity of system for completely avoiding the crosstalk between the decrypted images. Each encrypted target image is separately encoded into a POF by using the MGSA which is with constraining the encrypted target image. Each created POF is then added to a prescribed fixed POF composed of a proposed MGSA-based phase encoding algorithm. Not only the wavelength and multiple-position parameters in the FrT domain as keys to increase system security, the created POFs are also served mutually as the encryption keys to decrypt target image based on cascading two POFs scheme. Compared with prior methods [23,24], the main advantages of this proposed encryption system is that it does not need any transformative lenses and that makes it very efficient and easy to implement optically. Simulation results show that this proposed encryption system can successfully achieve the multiple-image encryption with multiple-position keys, which is more advantageous in security than previous work [24] for its decryption process with only two POFs keys to accomplish this task.
Institute of Scientific and Technical Information of China (English)
Ding Lu; Weimin Jin
2011-01-01
A novel fully phase color image encryption/decryption scheme based on joint fractional Fourier transform correlator (JFRTC) and phase retrieval algorithm (PRA) is proposed. The security of the system is enhanced by the fractional order as a new added key. This method takes full advantage of the parallel processing features of the optical system and could optically realize single-channel color image encryption.The system and operation procedures are simplified. The simulation results of a color image indicate that the new method provides efficient solutions with a strong sense of security.%@@ A novel fully phase color image encryption/decryption scheme based on joint fractional Fourier transform correlator (JFRTC) and phase retrieval algorithm (PRA) is proposed. The security of the system is enhanced by the fractional order as a new added key. This method takes full advantage of the parallel processing features of the optical system and could optically realize single-channel color image encryption. The system and operation procedures are simplified. The simulation results of a color image indicate that the new method provides efficient solutions with a strong sense of security.
Fusion of multi-voltage digital radiography images based on nonsubsampled contourlet transform.
Yanjie, Qi; Liming, Wang
2016-01-01
In order to increase the single digital radiography (DR) image information of the composite component in the industry, the different DR images are captured at different voltages so as to get the structural information at different thickness region firstly. Secondly, the original DR images are decomposed by nonsubsampled contourlet transform (NSCT), and the low-frequency subbands are fused by the role of principle component analysis (PCA), and the modified central energy role is used to carry out the high-frequency directional subbands fusion. The false edges are extracted, and the values of the high-frequency subband coefficients of the false edges are set to be a small value so as to reduce the false edges in the fusion image. Finally, the output image can be obtained by inverse nonsubsampled contourlet transform. The experimental results show that the fused DR image brings more detailed information, and the structure of the component can be seen clearly, so it is useful to the fast and accurate quality judgements of the component.
Ellmauthaler, Andreas; Pagliari, Carla L; da Silva, Eduardo A B
2013-03-01
Multiscale transforms are among the most popular techniques in the field of pixel-level image fusion. However, the fusion performance of these methods often deteriorates for images derived from different sensor modalities. In this paper, we demonstrate that for such images, results can be improved using a novel undecimated wavelet transform (UWT)-based fusion scheme, which splits the image decomposition process into two successive filtering operations using spectral factorization of the analysis filters. The actual fusion takes place after convolution with the first filter pair. Its significantly smaller support size leads to the minimization of the unwanted spreading of coefficient values around overlapping image singularities. This usually complicates the feature selection process and may lead to the introduction of reconstruction errors in the fused image. Moreover, we will show that the nonsubsampled nature of the UWT allows the design of nonorthogonal filter banks, which are more robust to artifacts introduced during fusion, additionally improving the obtained results. The combination of these techniques leads to a fusion framework, which provides clear advantages over traditional multiscale fusion approaches, independent of the underlying fusion rule, and reduces unwanted side effects such as ringing artifacts in the fused reconstruction.
Bautista, Pinky A; Yagi, Yukako
2012-05-01
Hematoxylin and eosin (H&E) stain is currently the most popular for routine histopathology staining. Special and/or immuno-histochemical (IHC) staining is often requested to further corroborate the initial diagnosis on H&E stained tissue sections. Digital simulation of staining (or digital staining) can be a very valuable tool to produce the desired stained images from the H&E stained tissue sections instantaneously. We present an approach to digital staining of histopathology multispectral images by combining the effects of spectral enhancement and spectral transformation. Spectral enhancement is accomplished by shifting the N-band original spectrum of the multispectral pixel with the weighted difference between the pixel's original and estimated spectrum; the spectrum is estimated using M transformed to the spectral configuration associated to its reaction to a specific stain by utilizing an N × N transformation matrix, which is derived through application of least mean squares method to the enhanced and target spectral transmittance samples of the different tissue components found in the image. Results of our experiments on the digital conversion of an H&E stained multispectral image to its Masson's trichrome stained equivalent show the viability of the method.
Natural majorization of the Quantum Fourier Transformation in phase-estimation algorithms
Orus, R; Martín-Delgado, M A; Orus, Roman; Latorre, Jose I.; Martin-Delgado, Miguel A.
2002-01-01
We prove that majorization relations hold step by step in the Quantum Fourier Transformation (QFT) for phase-estimation algorithms considered in the canonical decomposition. Our result relies on the fact that states which are mixed by Hadamard operators at any stage of the computation only differ by a phase. This property is a consequence of the structure of the initial state and of the QFT, based on controlled-phase operators and a single action of a Hadamard gate per qubit. As a consequence, Hadamard gates order the probability distribution associated to the quantum state, whereas controlled-phase operators carry all the entanglement but are immaterial to majorization. We also prove that majorization in phase-estimation algorithms follows in a most natural way from unitary evolution, unlike its counterpart in Grover's algorithm.
Li, Xiaosong; Li, Huafeng; Yu, Zhengtao; Kong, Yingchun
2015-07-01
An efficient multifocus image fusion scheme in nonsubsampled contourlet transform (NSCT) domain is proposed. Based on the property of optical imaging and the theory of defocused image, we present a selection principle for lowpass frequency coefficients and also investigate the connection between a low-frequency image and the defocused image. Generally, the NSCT algorithm decomposes detail image information indwells in different scales and different directions in the bandpass subband coefficient. In order to correctly pick out the prefused bandpass directional coefficients, we introduce multiscale curvature, which not only inherits the advantages of windows with different sizes, but also correctly recognizes the focused pixels from source images, and then develop a new fusion scheme of the bandpass subband coefficients. The fused image can be obtained by inverse NSCT with the different fused coefficients. Several multifocus image fusion methods are compared with the proposed scheme. The experimental results clearly indicate the validity and superiority of the proposed scheme in terms of both the visual qualities and the quantitative evaluation.
Study on Soil Gleization in Subtropic Region of China Using LBV Transformed Landsat Images
Institute of Scientific and Technical Information of China (English)
ZENGZHIYUAN; PANXIANZHANG
1997-01-01
This paper describes a new type of transformed Landsat images (LBV images) and their application in discriminating soil gleization in subtropic region of China,LBV transformaition was worked out by the present author for extracting useful information from original landsat images.Using this method three black and white images,L image ,B image and V image ,were computer generated from original bans of a Landsat scene,which covers a large area of 34 528 km2 in Hubei and Hunan province in south China.Then a Color composite was produced by these three images .This kind of black-and-white and color images contained rich and definite geographic in formation.By a field work ,the relationship between the colors on the composite and the land use/cover categories on the graound wa established.37 composite colors and 70 ground feature categories an be discriminated altogether,Finally,17 land use/cover categories and 10 subregions suffering from soil gleization were detemined ,and the gleiztion area for the study area was estimated to be 731.3 km2.
Fast algorithm of byte-to-byte wavelet transform for image compression applications
Pogrebnyak, Oleksiy B.; Sossa Azuela, Juan H.; Ramirez, Pablo M.
2002-11-01
A new fast algorithm of 2D DWT transform is presented. The algorithm operates on byte represented images and performs image transformation with the Cohen-Daubechies-Feauveau wavelet of the second order. It uses the lifting scheme for the calculations. The proposed algorithm is based on the "checkerboard" computation scheme for non-separable 2D wavelet. The problem of data extension near the image borders is resolved computing 1D Haar wavelet in the vicinity of the borders. With the checkerboard splitting, at each level of decomposition only one detail image is produced that simplify the further analysis for data compression. The calculations are rather simple, without any floating point operation allowing the implementation of the designed algorithm in fixed point DSP processors for fast, near real time processing. The proposed algorithm does not possesses perfect restoration of the processed data because of rounding that is introduced at each level of decomposition/restoration to perform operations with byte represented data. The designed algorithm was tested on different images. The criterion to estimate quantitatively the quality of the restored images was the well known PSNR. For the visual quality estimation the error maps between original and restored images were calculated. The obtained simulation results show that the visual and quantitative quality of the restored images is degraded with number of decomposition level increasing but is sufficiently high even after 6 levels. The introduced distortion are concentrated in the vicinity of high spatial activity details and are absent in the homogeneous regions. The designed algorithm can be used for image lossy compression and in noise suppression applications.
Design and Implementation of Fast- Lifting Based Wavelet Transform for Image Compression
Directory of Open Access Journals (Sweden)
Lokesh B.S
2014-06-01
Full Text Available The digital data can be compressed and retrieved using Discrete Wavelet Transform (DWT and Inverse Discrete wavelet Transform (IDWT. The medical images need to be compressed and retrieved without loosing of information. The Discrete Wavelet Transform (DWT is based on time-scale representation which provides efficient multi-resolution. This paper mainly describes the lifting based scheme gives lossless mode of information. The lifting based DWT and IDWT are having lower computational complexity and reduced memory requirement. Conventional convolution based DWT and IDWT are area and power hungry. These drawbacks can be overcome by using the lifting based scheme. This system adopts lifting based scheme DWT and IDWT which gives the lossless information of the data, reduces the complexity and optimized in area and power. In this research the DWT and IDWT are simulated and the design of hardware model is carried out using RTL level coding.
Casero, Ramón; Siedlecka, Urszula; Jones, Elizabeth S; Gruscheski, Lena; Gibb, Matthew; Schneider, Jürgen E; Kohl, Peter; Grau, Vicente
2017-05-01
Traditional histology is the gold standard for tissue studies, but it is intrinsically reliant on two-dimensional (2D) images. Study of volumetric tissue samples such as whole hearts produces a stack of misaligned and distorted 2D images that need to be reconstructed to recover a congruent volume with the original sample's shape. In this paper, we develop a mathematical framework called Transformation Diffusion (TD) for stack alignment refinement as a solution to the heat diffusion equation. This general framework does not require contour segmentation, is independent of the registration method used, and is trivially parallelizable. After the first stack sweep, we also replace registration operations by operations in the space of transformations, several orders of magnitude faster and less memory-consuming. Implementing TD with operations in the space of transformations produces our Transformation Diffusion Reconstruction (TDR) algorithm, applicable to general transformations that are closed under inversion and composition. In particular, we provide formulas for translation and affine transformations. We also propose an Approximated TDR (ATDR) algorithm that extends the same principles to tensor-product B-spline transformations. Using TDR and ATDR, we reconstruct a full mouse heart at pixel size 0.92µm×0.92µm, cut 10µm thick, spaced 20µm (84G). Our algorithms employ only local information from transformations between neighboring slices, but the TD framework allows theoretical analysis of the refinement as applying a global Gaussian low-pass filter to the unknown stack misalignments. We also show that reconstruction without an external reference produces large shape artifacts in a cardiac specimen while still optimizing slice-to-slice alignment. To overcome this problem, we use a pre-cutting blockface imaging process previously developed by our group that takes advantage of Brewster's angle and a polarizer to capture the outline of only the topmost layer of wax
Zarella, Mark D; Breen, David E; Plagov, Andrei; Garcia, Fernando U
2015-01-01
Hematoxylin and eosin (H&E) staining is ubiquitous in pathology practice and research. As digital pathology has evolved, the reliance of quantitative methods that make use of H&E images has similarly expanded. For example, cell counting and nuclear morphometry rely on the accurate demarcation of nuclei from other structures and each other. One of the major obstacles to quantitative analysis of H&E images is the high degree of variability observed between different samples and different laboratories. In an effort to characterize this variability, as well as to provide a substrate that can potentially mitigate this factor in quantitative image analysis, we developed a technique to project H&E images into an optimized space more appropriate for many image analysis procedures. We used a decision tree-based support vector machine learning algorithm to classify 44 H&E stained whole slide images of resected breast tumors according to the histological structures that are present. This procedure takes an H&E image as an input and produces a classification map of the image that predicts the likelihood of a pixel belonging to any one of a set of user-defined structures (e.g., cytoplasm, stroma). By reducing these maps into their constituent pixels in color space, an optimal reference vector is obtained for each structure, which identifies the color attributes that maximally distinguish one structure from other elements in the image. We show that tissue structures can be identified using this semi-automated technique. By comparing structure centroids across different images, we obtained a quantitative depiction of H&E variability for each structure. This measurement can potentially be utilized in the laboratory to help calibrate daily staining or identify troublesome slides. Moreover, by aligning reference vectors derived from this technique, images can be transformed in a way that standardizes their color properties and makes them more amenable to image processing.
Watermarked cardiac CT image segmentation using deformable models and the Hermite transform
Gomez-Coronel, Sandra L.; Moya-Albor, Ernesto; Escalante-Ramírez, Boris; Brieva, Jorge
2015-01-01
Medical image watermarking is an open area for research and is a solution for the protection of copyright and intellectual property. One of the main challenges of this problem is that the marked images should not differ perceptually from the original images allowing a correct diagnosis and authentication. Furthermore, we also aim at obtaining watermarked images with very little numerical distortion so that computer vision tasks such as segmentation of important anatomical structures do not be impaired or affected. We propose a preliminary watermarking application in cardiac CT images based on a perceptive approach that includes a brightness model to generate a perceptive mask and identify the image regions where the watermark detection becomes a difficult task for the human eye. We propose a normalization scheme of the image in order to improve robustness against geometric attacks. We follow a spread spectrum technique to insert an alphanumeric code, such as patient's information, within the watermark. The watermark scheme is based on the Hermite transform as a bio-inspired image representation model. In order to evaluate the numerical integrity of the image data after watermarking, we perform a segmentation task based on deformable models. The segmentation technique is based on a vector-value level sets method such that, given a curve in a specific image, and subject to some constraints, the curve can evolve in order to detect objects. In order to stimulate the curve evolution we introduce simultaneously some image features like the gray level and the steered Hermite coefficients as texture descriptors. Segmentation performance was assessed by means of the Dice index and the Hausdorff distance. We tested different mark sizes and different insertion schemes on images that were later segmented either automatic or manual by physicians.
Mohamed, M. A.; Li, Hongzuo
2013-09-01
In this paper we follow the concept of the track before detect (TBD) category in order to perform a simple, fast and adaptive detection and tracking processes of dim pixel size moving targets in IR images sequence. We present two new algorithms based on an image frames transformation, the first algorithm is a recursive algorithm to measure the image background Baseline which help in assigning an adaptive threshold, while the second is an adaptive recursive statistical spatio-temporal algorithm for detecting and tracking the target. The results of applying the proposed algorithms on a set of frames having a simple single pixel target performing a linear motion shows a high efficiency and validity in the detecting of the motion, and the measurement of the background baseline.
Directory of Open Access Journals (Sweden)
Chin-Chen Chang
2009-03-01
Full Text Available In this paper, a new oblivious fragile watermarking using discrete cosine transform is proposed. It is inspired by Wong's public key watermarking scheme proposed in 1998 and aims to improve its vulnerability towards possible attacks indicated by Barreto and Holliman. Instead of making use of contextual information and making it an inter-block dependent scheme, as suggested by Barreto, we adopt another approach to retain its blockwise independent property. Our scheme can avoid the conditions necessary for such attacks to befeasible. Furthermore, our scheme extracts the inherent image features and embeds them into this image as the watermark. This relieves users from having to maintain a database of watermarks from various sources. Experimental results show that the watermark insertion procedure has little effect on the visual quality of the watermarked image. They also show our scheme can locate the modifications made to the watermarked image, including imagescaling, cropping, geometric distortion, pixel value changes, etc.
An adaptive 3-D discrete cosine transform coder for medical image compression.
Tai, S C; Wu, Y G; Lin, C W
2000-09-01
In this communication, a new three-dimensional (3-D) discrete cosine transform (DCT) coder for medical images is presented. In the proposed method, a segmentation technique based on the local energy magnitude is used to segment subblocks of the image into different energy levels. Then, those subblocks with the same energy level are gathered to form a 3-D cuboid. Finally, 3-D DCT is employed to compress the 3-D cuboid individually. Simulation results show that the reconstructed images achieve a bit rate lower than 0.25 bit per pixel even when the compression ratios are higher than 35. As compared with the results by JPEG and other strategies, it is found that the proposed method achieves better qualities of decoded images than by JPEG and the other strategies.
Lossless compression of medical images using Burrows-Wheeler Transformation with Inversion Coder.
Preston, Collin; Arnavut, Ziya; Koc, Basar
2015-08-01
Medical imaging is a quickly growing industry where the need for highly efficient lossless compression algorithms is necessary in order to reduce storage space and transmission rates for the large, high resolution, medical images. Due to the fact that medical imagining cannot utilize lossy compression, in the event that vital information may be lost, it is imperative that lossless compression be used. While several authors have investigated lossless compression of medical images, the Burrows-Wheeler Transformation with an Inversion Coder (BWIC) has not been examined. Our investigation shows that BWIC runs in linear time and yields better compression rates than well-known image coders, such as JPEG-LS and JPEG-2000.
ISAR Imaging of Maneuvering Targets Based on the Modified Discrete Polynomial-Phase Transform
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Yong Wang
2015-09-01
Full Text Available Inverse synthetic aperture radar (ISAR imaging of a maneuvering target is a challenging task in the field of radar signal processing. The azimuth echo can be characterized as a multi-component polynomial phase signal (PPS after the translational compensation, and the high quality ISAR images can be obtained by the parameters estimation of it combined with the Range-Instantaneous-Doppler (RID technique. In this paper, a novel parameters estimation algorithm of the multi-component PPS with order three (cubic phase signal-CPS based on the modified discrete polynomial-phase transform (MDPT is proposed, and the corresponding new ISAR imaging algorithm is presented consequently. This algorithm is efficient and accurate to generate a focused ISAR image, and the results of real data demonstrate the effectiveness of it.
Automatic Scheme for Fused Medical Image Segmentation with Nonsubsampled Contourlet Transform
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Ch.Hima Bindu
2012-10-01
Full Text Available Medical image segmentation has become an essential technique in clinical and research- oriented applications. Because manual segmentation methods are tedious, and semi-automatic segmentation lacks the flexibility, fully-automatic methods have become the preferred type of medical image segmentation. This work proposes a robust fully automatic segmentation scheme based on the modified contouring technique. The entire scheme consists of three stages. In the first stage, the Nonsubsampled Contourlet Transform (NSCT of image is computed. This is followed by the fusion of coefficients using fusion method. For that fused image local threshold is computed. This is followed by the second stage in which the initial points are determined by computation of global threshold. Finally, in the third stage, searching procedure is started from each initial point to obtain closed-loop contours. The whole process is fully automatic. This avoids the disadvantages of semi-automatic schemes such as manually selecting the initial contours and points.
Study on adaptive thresholding technique of image denoising based on wavelet transform
Zhu, Xi'an; Xie, Xiao
2011-05-01
It is studied in the paper that an adaptive soft and hard thresholding image denoising method, in which image pyramid decomposing is realized by wavelet transform, and the mean value, mid-value and root mean square value of different sub bands are calculated as thresholding. The image is added into different kinds and different intensities noise, and processed by different wavelet decomposing levels and thresholding selected algorithms, the total 27 kinds of thresholding combination schemes are completed in the research process. The SNR (signal noise ratio) and PSNR (peak signal noise ratio) of denoised image are compared and analyzed and benefited results are achieved. Furthermore, the algorithm in reference is realized by MATLAB program, the results of reference are compared with that of the paper to demonstrate the significance and correctness of the results in the paper.
An Improved DC Recovery Method from AC Coefficients of DCT-Transformed Images
Li, Shujun; Saupe, Dietmar; Kuo, C -C Jay
2010-01-01
Motivated by the work of Uehara et al. [1], an improved method to recover DC coefficients from AC coefficients of DCT-transformed images is investigated in this work, which finds applications in cryptanalysis of selective multimedia encryption. The proposed under/over-flow rate minimization (FRM) method employs an optimization process to get a statistically more accurate estimation of unknown DC coefficients, thus achieving a better recovery performance. It was shown by experimental results based on 200 test images that the proposed DC recovery method significantly improves the quality of most recovered images in terms of the PSNR values and several state-of-the-art objective image quality assessment (IQA) metrics such as SSIM and MS-SSIM.
Huck-Pezzei, V A; Pallua, J D; Pezzei, C; Bittner, L K; Schönbichler, S A; Abel, G; Popp, M; Bonn, G K; Huck, C W
2012-10-01
In the present study, Fourier transform infrared (FTIR) imaging and data analysis methods were combined to study morphological and molecular patterns of St. John's wort (Hypericum perforatum) in detail. For interpretation, FTIR imaging results were correlated with histological information gained from light microscopy (LM). Additionally, we tested several evaluation processes and optimized the methodology for use of complex FTIR microscopic images to monitor molecular patterns. It is demonstrated that the combination of the used spectroscopic method with LM enables a more distinct picture, concerning morphology and distribution of active ingredients, to be gained. We were able to obtain high-quality FTIR microscopic imaging results and to distinguish different tissue types with their chemical ingredients.
AN APPLIED RESEARCH ON APPROACH OF DYADIC WAVELET TRANSFORM FOR REMOTE SENSING IMAGE EDGE DETECTION
Institute of Scientific and Technical Information of China (English)
Fu Wei; Xing Guangzhong; Hou Lantian; Qin Qiming; Wang Wenjun
2006-01-01
In the edge detection of Remote Sensing (RS) image, the useful detail losing and the spurious edge often appear. To solve the problem, the authors uses the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, the RS image of a certain appropriate scale is obtained, and the edge data of the plane and the upright directions are respectively figured out, then the gradient vector module of the surface features is worked out. By tracing them, the authors get the edge data of the object, therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of an RS image which obtains an airport, the authors certificate the feasibility of the application of dyadic wavelet in the object edge detection.
3D Modeling of Transformer Substation Based on Mapping and 2D Images
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Lei Sun
2016-01-01
Full Text Available A new method for building 3D models of transformer substation based on mapping and 2D images is proposed in this paper. This method segments objects of equipment in 2D images by using k-means algorithm in determining the cluster centers dynamically to segment different shapes and then extracts feature parameters from the divided objects by using FFT and retrieves the similar objects from 3D databases and then builds 3D models by computing the mapping data. The method proposed in this paper can avoid the complex data collection and big workload by using 3D laser scanner. The example analysis shows the method can build coarse 3D models efficiently which can meet the requirements for hazardous area classification and constructions representations of transformer substation.
Sarty, Gordon E.; Atkins, M. Stella; Olatunbosun, Femi; Chizen, Donna; Loewy, John; Kendall, Edward J.; Pierson, Roger A.
1999-10-01
A new numerical wavelet transform, the discrete torus wavelet transform, is described and an application is given to the denoising of abdominal magnetic resonance imaging (MRI) data. The discrete tori wavelet transform is an undecimated wavelet transform which is computed using a discrete Fourier transform and multiplication instead of by direct convolution in the image domain. This approach leads to a decomposition of the image onto frames in the space of square summable functions on the discrete torus, l2(T2). The new transform was compared to the traditional decimated wavelet transform in its ability to denoise MRI data. By using denoised images as the basis for the computation of a nuclear magnetic resonance spin-spin relaxation-time map through least squares curve fitting, an error map was generated that was used to assess the performance of the denoising algorithms. The discrete torus wavelet transform outperformed the traditional wavelet transform in 88% of the T2 error map denoising tests with phantoms and gynecologic MRI images.
Chu, Ying; Mou, Xuanqin; Fu, Hong; Ji, Zhen
2015-11-01
We present a general purpose blind image quality assessment (IQA) method using the statistical independence hidden in the joint distributions of divisive normalization transform (DNT) representations for natural images. The DNT simulates the redundancy reduction process of the human visual system and has good statistical independence for natural undistorted images; meanwhile, this statistical independence changes as the images suffer from distortion. Inspired by this, we investigate the changes in statistical independence between neighboring DNT outputs across the space and scale for distorted images and propose an independence uncertainty index as a blind IQA (BIQA) feature to measure the image changes. The extracted features are then fed into a regression model to predict the image quality. The proposed BIQA metric is called statistical independence (STAIND). We evaluated STAIND on five public databases: LIVE, CSIQ, TID2013, IRCCyN/IVC Art IQA, and intentionally blurred background images. The performances are relatively high for both single- and cross-database experiments. When compared with the state-of-the-art BIQA algorithms, as well as representative full-reference IQA metrics, such as SSIM, STAIND shows fairly good performance in terms of quality prediction accuracy, stability, robustness, and computational costs.
A NOVEL BIOMETRICS TRIGGERED WATERMARKING OF IMAGES BASED ON WAVELET BASED CONTOURLET TRANSFORM
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Elakkiya Soundar
2013-01-01
Full Text Available The rapid development of network and digital technology has led to several issues to the digital content. The technical solution to provide law enforcement and copyright protection is achieved by digital watermarking Digital watermarking is the process of embedding information into a digital image in a way that is difficult to remove. The proposed method contains following phases (i Pre-processing of biometric image (ii key generation from the biometrics of the owner/user and randomization of the host image using Speeded-Up Robust Features (SURF (iii Wavelet-Based Contourlet Transform (WBCT is applied on the host image. The WBCT can give the anisotropy optimal representation of the edges and contours in the image by virtue of the characteristics of multi-scale framework and multi-directionality (iv Singular Value Decomposition (SVD is enforced over the watermark image (v Embedding of the host image with the watermark image. The comparative analysis confirms the efficiency and robustness of the proposed system Index Terms— Digital Watermarking, copyright, Pre-processing, wavelet, Speeded-Up Robust Features.