Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

Science.gov (United States)

Turpie, Kevin R.; Eplee, Robert E., Jr.; Franz, Bryan A.; Del Castillo, Carlos

2014-01-01

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume IV: Inherent Optical Properties: Instruments, Characterizations, Field Measurements and Data Analysis Protocols

Science.gov (United States)

Mueller, J. L.; Fargion, G. S.; McClain, C. R. (Editor); Pegau, S.; Zanefeld, J. R. V.; Mitchell, B. G.; Kahru, M.; Wieland, J.; Stramska, M.

2003-01-01

This document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparision and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. The document is organized into 6 separate volumes as Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4. Volume I: Introduction, Background, and Conventions; Volume II: Instrument Specifications, Characterization and Calibration; Volume III: Radiometric Measurements and Data Analysis Methods; Volume IV: Inherent Optical Properties: Instruments, Characterization, Field Measurements and Data Analysis Protocols; Volume V: Biogeochemical and Bio-Optical Measurements and Data Analysis Methods; Volume VI: Special Topics in Ocean Optics Protocols and Appendices. The earlier version of Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 3 is entirely superseded by the six volumes of Revision 4 listed above.

Ocean Color and Earth Science Data Records

Science.gov (United States)

Maritorena, S.

2014-12-01

The development of consistent, high quality time series of biogeochemical products from a single ocean color sensor is a difficult task that involves many aspects related to pre- and post-launch instrument calibration and characterization, stability monitoring and the removal of the contribution of the atmosphere which represents most of the signal measured at the sensor. It is even more challenging to build Climate Data Records (CDRs) or Earth Science Data Records (ESDRs) from multiple sensors as design, technology and methodologies (bands, spectral/spatial resolution, Cal/Val, algorithms) differ from sensor to sensor. NASA MEaSUREs, ESA Climate Change Initiative (CCI) and IOCCG Virtual Constellation are some of the underway efforts that investigate or produce ocean color CDRs or ESDRs from the recent and current global missions (SeaWiFS, MODIS, MERIS). These studies look at key aspects of the development of unified data records from multiple sensors, e.g. the concatenation of the "best" individual records vs. the merging of multiple records or band homogenization vs. spectral diversity. The pros and cons of the different approaches are closely dependent upon the overall science purpose of the data record and its temporal resolution. While monthly data are generally adequate for biogeochemical modeling or to assess decadal trends, higher temporal resolution data records are required to look into changes in phenology or the dynamics of phytoplankton blooms. Similarly, short temporal resolution (daily to weekly) time series may benefit more from being built through the merging of data from multiple sensors while a simple concatenation of data from individual sensors might be better suited for longer temporal resolution (e.g. monthly time series). Several Ocean Color ESDRs were developed as part of the NASA MEaSUREs project. Some of these time series are built by merging the reflectance data from SeaWiFS, MODIS-Aqua and Envisat-MERIS in a semi-analytical ocean color

OW NASA MODIS Aqua Ocean Color

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface ocean color (chlorophyll-a) measurements collected by means of the Moderate Resolution Imaging Spectroradiometer...

Diurnal changes in ocean color sensed in satellite imagery

Science.gov (United States)

Arnone, Robert; Vandermuelen, Ryan; Soto, Inia; Ladner, Sherwin; Ondrusek, Michael; Yang, Haoping

2017-07-01

Measurements of diurnal changes in ocean color in turbid coastal regions in the Gulf of Mexico were characterized using above water spectral radiometry from a National Aeronautics and Space Administration (aerosol robotic network-WaveCIS CSI-06) site that can provide 8 to 10 observations per day. Satellite capability to detect diurnal changes in ocean color was characterized using hourly overlapping afternoon orbits of the visual infrared imaging radiometer suite (VIIRS) Suomi National Polar-orbiting Partnership ocean color sensor and validated with in situ observations. The monthly cycle of diurnal changes was investigated for different water masses using VIIRS overlaps. Results showed the capability of satellite observations to monitor hourly color changes in coastal regions that can be impacted by vertical movement of optical layers, in response to tides, resuspension, and river plume dispersion. The spatial variability of VIIRS diurnal changes showed the occurrence and displacement of phytoplankton blooming and decaying processes. The diurnal change in ocean color was above 20%, which represents a 30% change in chlorophyll-a. Seasonal changes in diurnal ocean color for different water masses suggest differences in summer and winter responses to surface processes. The diurnal changes observed using satellite ocean color can be used to define the following: surface processes associated with biological activity, vertical changes in optical depth, and advection of water masses.

OW NASA SeaWIFS Ocean Color

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface ocean color (chlorophyll-a) measurements collected by means of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)...

Phytoplankton phenology indices in coral reef ecosystems: Application to ocean-color observations in the Red Sea

KAUST Repository

Racault, Marie-Fanny; Raitsos, Dionysios E.; Berumen, Michael L.; Brewin, Robert J.W.; Platt, Trevor; Sathyendranath, Shubha; Hoteit, Ibrahim

2015-01-01

Initiative project (OC-CCI) in the entire Red Sea basin. The OC-CCI product, comprising merged and bias-corrected observations from three independent ocean-color sensors (SeaWiFS, MODIS and MERIS), and processed using the POLYMER algorithm (MERIS period

The use of a MODIS band-ratio algorithm versus a new hybrid approach for estimating colored dissolved organic matter (CDOM)

Science.gov (United States)

Satellite remote sensing offers synoptic and frequent monitoring of optical water quality parameters, such as chlorophyll-a, turbidity, and colored dissolved organic matter (CDOM). While traditional satellite algorithms were developed for the open ocean, these algorithms often do...

Chlorophyll-a Algorithms for Oligotrophic Oceans: A Novel Approach Based on Three-Band Reflectance Difference

Science.gov (United States)

Hu, Chuanmin; Lee, Zhongping; Franz, Bryan

2011-01-01

A new empirical algorithm is proposed to estimate surface chlorophyll-a concentrations (Chl) in the global ocean for Chl less than or equal to 0.25 milligrams per cubic meters (approximately 77% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote sensing reflectance (R(sub rs), sr(sup -1) in the green and a reference formed linearly between R(sub rs) in the blue and red. For low Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band-ratios and Chl, which was further validated using global data collected concurrently by ship-borne and SeaWiFS satellite instruments. Model simulations showed that for low Chl waters, compared with the band-ratio algorithm, the CI-based algorithm (CIA) was more tolerant to changes in chlorophyll-specific backscattering coefficient, and performed similarly for different relative contributions of non-phytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band-ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time-series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over MERIS and CZCS data indicate that the new approach should be generally applicable to all existing and future ocean color instruments.

Near Real Time Operational Satellite Ocean Color Products From NOAA OSPO CoastWatch Okeanos System:: Status and Challenges

Science.gov (United States)

Banghua Yan, B.

2016-02-01

Near real-time (NRT) ocean color (OC) satellite operation products are generated and distributed in NOAA Okeanos Operational Product System, by using the CWAPS including the Multi-Sensor Level (MSL) 12 and the chlorophyll-a frontal algorithms. Current OC operational products include daily chlorophyll concentration (anomaly), water turbidity, remote sensing reflectance and chlorophyll frontal products from Moderate-resolution Imaging Spectroradiometer (MODIS)/Aqua. The products have been widely applied to USA local and state ecosystem research, ecosystem observations, and fisheries managements for coastal and regional forecasting of ocean water quality, phytoplankton concentrations, and primary production. Users of the products have the National Ocean Service, National Marine Fisheries Service, National Weather Service, and Oceanic and Atmospheric Research. Recently, the OC products are being extended to S-NPP VIIRS to provide global NRT ocean color products to user community suh as National Weatrher Service for application for Global Data Assimilation System and Real-Time Ocean Forecast System. However, there remain some challenges in application of the products due to certain product quality and coverage issues. Recent efforts were made to provide a comprehensive web-based Quality Assurance (QA) tool for monitoring OC products quality in near real time mode, referring to http://www.ospo.noaa.gov/Products/ocean/color_new/color.htm. The new QA monitoring tool includes but not limited to the following advanced features applicable for MODIS/Aqua and NPP/VIIRS OC products: 1) Monitoring product quality in NRT mode; 2) Monitoring the availability and quality of OC products with time; 3) Detecting anomalous OC products due to low valid pixels and other quality issues. As an example, potential application and challenges of the ocean color products to oceanic oil spill detection are investigated. It is thus expected that the Okeanos ocean color operational system in

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

Science.gov (United States)

Pahlevan, Nima; Sarkar, Sudipta; Franz, Bryan A.

2016-01-01

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for

Biases in ocean color over a Secchi disk

NARCIS (Netherlands)

Pitarch, J.

2017-01-01

The oldest record of ocean color measurements consists of visual comparisonsto a standardized color scale, the Forel-Ule scale (FU). Analysis of FU archived dataallows the construction of a century-long time series. In situ protocols of FUmeasurements require the perceived color to be estimated over

An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing

Science.gov (United States)

Werdell, P. Jeremy; McKinna, Lachlan I. W.; Boss, Emmanuel; Ackleson, Steven G.; Craig, Susanne E.; Gregg, Watson W.; Lee, Zhongping; Maritorena, Stéphane; Roesler, Collin S.; Rousseaux, Cécile S.; Stramski, Dariusz; Sullivan, James M.; Twardowski, Michael S.; Tzortziou, Maria; Zhang, Xiaodong

2018-01-01

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

Science.gov (United States)

Singh, Rakesh Kumar; Shanmugam, Palanisamy

2018-06-01

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water

Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate.

Science.gov (United States)

Dierssen, Heidi M

2010-10-05

Phytoplankton biomass and productivity have been continuously monitored from ocean color satellites for over a decade. Yet, the most widely used empirical approach for estimating chlorophyll a (Chl) from satellites can be in error by a factor of 5 or more. Such variability is due to differences in absorption and backscattering properties of phytoplankton and related concentrations of colored-dissolved organic matter (CDOM) and minerals. The empirical algorithms have built-in assumptions that follow the basic precept of biological oceanography--namely, oligotrophic regions with low phytoplankton biomass are populated with small phytoplankton, whereas more productive regions contain larger bloom-forming phytoplankton. With a changing world ocean, phytoplankton composition may shift in response to altered environmental forcing, and CDOM and mineral concentrations may become uncoupled from phytoplankton stocks, creating further uncertainty and error in the empirical approaches. Hence, caution is warranted when using empirically derived Chl to infer climate-related changes in ocean biology. The Southern Ocean is already experiencing climatic shifts and shows substantial errors in satellite-derived Chl for different phytoplankton assemblages. Accurate global assessments of phytoplankton will require improved technology and modeling, enhanced field observations, and ongoing validation of our "eyes in space."

Satellite Ocean Color Sensor Design Concepts and Performance Requirements

Science.gov (United States)

McClain, Charles R.; Meister, Gerhard; Monosmith, Bryan

2014-01-01

In late 1978, the National Aeronautics and Space Administration (NASA) launched the Nimbus-7 satellite with the Coastal Zone Color Scanner (CZCS) and several other sensors, all of which provided major advances in Earth remote sensing. The inspiration for the CZCS is usually attributed to an article in Science by Clarke et al. who demonstrated that large changes in open ocean spectral reflectance are correlated to chlorophyll-a concentrations. Chlorophyll-a is the primary photosynthetic pigment in green plants (marine and terrestrial) and is used in estimating primary production, i.e., the amount of carbon fixed into organic matter during photosynthesis. Thus, accurate estimates of global and regional primary production are key to studies of the earth's carbon cycle. Because the investigators used an airborne radiometer, they were able to demonstrate the increased radiance contribution of the atmosphere with altitude that would be a major issue for spaceborne measurements. Since 1978, there has been much progress in satellite ocean color remote sensing such that the technique is well established and is used for climate change science and routine operational environmental monitoring. Also, the science objectives and accompanying methodologies have expanded and evolved through a succession of global missions, e.g., the Ocean Color and Temperature Sensor (OCTS), the Seaviewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Medium Resolution Imaging Spectrometer (MERIS), and the Global Imager (GLI). With each advance in science objectives, new and more stringent requirements for sensor capabilities (e.g., spectral coverage) and performance (e.g., signal-to-noise ratio, SNR) are established. The CZCS had four bands for chlorophyll and aerosol corrections. The Ocean Color Imager (OCI) recommended for the NASA Pre-Aerosol, Cloud, and Ocean Ecosystems (PACE) mission includes 5 nanometers hyperspectral coverage from 350 to

Estimating absorption coefficients of colored dissolved organic matter (CDOM) using a semi-analytical algorithm for southern Beaufort Sea waters: application to deriving concentrations of dissolved organic carbon from space

Science.gov (United States)

Matsuoka, A.; Hooker, S. B.; Bricaud, A.; Gentili, B.; Babin, M.

2013-02-01

A series of papers have suggested that freshwater discharge, including a large amount of dissolved organic matter (DOM), has increased since the middle of the 20th century. In this study, a semi-analytical algorithm for estimating light absorption coefficients of the colored fraction of DOM (CDOM) was developed for southern Beaufort Sea waters using remote sensing reflectance at six wavelengths in the visible spectral domain corresponding to MODIS ocean color sensor. This algorithm allows the separation of colored detrital matter (CDM) into CDOM and non-algal particles (NAP) through the determination of NAP absorption using an empirical relationship between NAP absorption and particle backscattering coefficients. Evaluation using independent datasets, which were not used for developing the algorithm, showed that CDOM absorption can be estimated accurately to within an uncertainty of 35% and 50% for oceanic and coastal waters, respectively. A previous paper (Matsuoka et al., 2012) showed that dissolved organic carbon (DOC) concentrations were tightly correlated with CDOM absorption in our study area (r2 = 0.97). By combining the CDOM absorption algorithm together with the DOC versus CDOM relationship, it is now possible to estimate DOC concentrations in the near-surface layer of the southern Beaufort Sea using satellite ocean color data. DOC concentrations in the surface waters were estimated using MODIS ocean color data, and the estimates showed reasonable values compared to in situ measurements. We propose a routine and near real-time method for deriving DOC concentrations from space, which may open the way to an estimate of DOC budgets for Arctic coastal waters.

Estimating absorption coefficients of colored dissolved organic matter (CDOM) using a semi-analytical algorithm for Southern Beaufort Sea (Canadian Arctic) waters: application to deriving concentrations of dissolved organic carbon from space

Science.gov (United States)

Matsuoka, A.; Hooker, S. B.; Bricaud, A.; Gentili, B.; Babin, M.

2012-10-01

A series of papers have suggested that freshwater discharge, including a large amount of dissolved organic matter (DOM), has increased since the middle of the 20th century. In this study, a semi-analytical algorithm for estimating light absorption coefficients of the colored fraction of DOM (CDOM) was developed for Southern Beaufort Sea waters using remote sensing reflectance at six wavelengths in the visible spectral domain corresponding to MODIS ocean color sensor. This algorithm allows to separate colored detrital matter (CDM) into CDOM and non-algal particles (NAP) by determining NAP absorption using an empirical relationship between NAP absorption and particle backscattering coefficients. Evaluation using independent datasets, that were not used for developing the algorithm, showed that CDOM absorption can be estimated accurately to within an uncertainty of 35% and 50% for oceanic and turbid waters, respectively. In situ measurements showed that dissolved organic carbon (DOC) concentrations were tightly correlated with CDOM absorption (r2 = 0.97). By combining the CDOM absorption algorithm together with the DOC versus CDOM relationship, it is now possible to estimate DOC concentrations in the near-surface layer of the Southern Beaufort Sea using satellite ocean color data. DOC concentrations in the surface waters were estimated using MODIS ocean color data, and the estimates showed reasonable values compared to in situ measurements. We propose a routine and near real-time method for deriving DOC concentrations from space, which may open the way to an estimate of DOC budgets for Arctic coastal waters.

[An automatic color correction algorithm for digital human body sections].

Science.gov (United States)

Zhuge, Bin; Zhou, He-qin; Tang, Lei; Lang, Wen-hui; Feng, Huan-qing

2005-06-01

To find a new approach to improve the uniformity of color parameters for images data of the serial sections of the human body. An auto-color correction algorithm in the RGB color space based on a standard CMYK color chart was proposed. The gray part of the color chart was auto-segmented from every original image, and fifteen gray values were attained. The transformation function between the measured gray value and the standard gray value of the color chart and the lookup table were obtained. In RGB color space, the colors of images were corrected according to the lookup table. The color of original Chinese Digital Human Girl No. 1 (CDH-G1) database was corrected by using the algorithm with Matlab 6.5, and it took 13.475 s to deal with one picture on a personal computer. Using the algorithm, the color of the original database is corrected automatically and quickly. The uniformity of color parameters for corrected dataset is improved.

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

Science.gov (United States)

Stamnes, S; Hostetler, C; Ferrare, R; Burton, S; Liu, X; Hair, J; Hu, Y; Wasilewski, A; Martin, W; van Diedenhoven, B; Chowdhary, J; Cetinić, I; Berg, L K; Stamnes, K; Cairns, B

2018-04-01

We present an optimal-estimation-based retrieval framework, the microphysical aerosol properties from polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular total and polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High-Spectral-Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355 and 532 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ångstrøm exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio-Optical Research (SABOR) campaign. For the SABOR campaign, 73% RSP MAPP retrievals fall within ±0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.933 and root-mean-square deviation of 0.0372. For the TCAP campaign, 53% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.927 and root-mean-square deviation of 0.0673. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.959 and a root-mean-square deviation of 0.0694. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar + polarimeter retrieval using both HSRL and RSP measurements.

Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

Directory of Open Access Journals (Sweden)

R. V. V. Krishna

2016-10-01

Full Text Available This paper proposes a hybrid of differential evolution and genetic algorithms to solve the color image segmentation problem. Clustering based color image segmentation algorithms segment an image by clustering the features of color and texture, thereby obtaining accurate prototype cluster centers. In the proposed algorithm, the color features are obtained using the homogeneity model. A new texture feature named Power Law Descriptor (PLD which is a modification of Weber Local Descriptor (WLD is proposed and further used as a texture feature for clustering. Genetic algorithms are competent in handling binary variables, while differential evolution on the other hand is more efficient in handling real parameters. The obtained texture feature is binary in nature and the color feature is a real value, which suits very well the hybrid cluster center optimization problem in image segmentation. Thus in the proposed algorithm, the optimum texture feature centers are evolved using genetic algorithms, whereas the optimum color feature centers are evolved using differential evolution.

A review of ocean chlorophyll algorithms and primary production models

Science.gov (United States)

Li, Jingwen; Zhou, Song; Lv, Nan

2015-12-01

This paper mainly introduces the five ocean chlorophyll concentration inversion algorithm and 3 main models for computing ocean primary production based on ocean chlorophyll concentration. Through the comparison of five ocean chlorophyll inversion algorithm, sums up the advantages and disadvantages of these algorithm,and briefly analyzes the trend of ocean primary production model.

Estimating absorption coefficients of colored dissolved organic matter (CDOM using a semi-analytical algorithm for southern Beaufort Sea waters: application to deriving concentrations of dissolved organic carbon from space

Directory of Open Access Journals (Sweden)

A. Matsuoka

2013-02-01

Full Text Available A series of papers have suggested that freshwater discharge, including a large amount of dissolved organic matter (DOM, has increased since the middle of the 20th century. In this study, a semi-analytical algorithm for estimating light absorption coefficients of the colored fraction of DOM (CDOM was developed for southern Beaufort Sea waters using remote sensing reflectance at six wavelengths in the visible spectral domain corresponding to MODIS ocean color sensor. This algorithm allows the separation of colored detrital matter (CDM into CDOM and non-algal particles (NAP through the determination of NAP absorption using an empirical relationship between NAP absorption and particle backscattering coefficients. Evaluation using independent datasets, which were not used for developing the algorithm, showed that CDOM absorption can be estimated accurately to within an uncertainty of 35% and 50% for oceanic and coastal waters, respectively. A previous paper (Matsuoka et al., 2012 showed that dissolved organic carbon (DOC concentrations were tightly correlated with CDOM absorption in our study area (r² = 0.97. By combining the CDOM absorption algorithm together with the DOC versus CDOM relationship, it is now possible to estimate DOC concentrations in the near-surface layer of the southern Beaufort Sea using satellite ocean color data. DOC concentrations in the surface waters were estimated using MODIS ocean color data, and the estimates showed reasonable values compared to in situ measurements. We propose a routine and near real-time method for deriving DOC concentrations from space, which may open the way to an estimate of DOC budgets for Arctic coastal waters.

Dazzled by ice and snow: improving medium ocean color images in Arctic waters

Science.gov (United States)

Babin, M.; Goyens, C.; Belanger, S.

2016-02-01

The importance of phytoplankton blooms for the Arctic marine ecosystem is well recognized but studies disagree as the consequences of sea ice melt on the phytoplankton distribution and growth. This limited understanding in actual and future Arctic phytoplankton dynamics mostly results from a lack of accurate data at the receding ice-edges where phytoplankton blooms are known to occur. Ocean color sensors on-board satellites represent therefore a crucial tool providing a synoptic view of the ocean systems over broad spatio-temporal scales. However, today the use of ocean color data in Arctic environments remains strongly compromised due to, among others, sea ice contamination. Indeed, medium ocean color data along the receding ice edge are "dazzled" by nearby and/or sub-pixel highly reflective ice floes. Standard ocean color data methods ignore ice-contamination during data processing which deteriorates the quality of the radiometric data and subsequent satellite derived bio-geochemical products. Moreover, since Arctic phytoplankton spring blooms typically develop along the receding ice-edges, ignoring ice-contaminated pixels may lead to wrong interpretation of satellite data. The present study shows how adjacent and sub-pixel sea-ice floes affect the retrieved ocean color data. A correction approach is also suggested to improve the "dazzled" ocean color pixels along the receding ice edge in the aim to provide additional support to better understand current and future trends in phytoplankton dynamics.

Surface roughness considerations for atmospheric correction of ocean color sensors. I - The Rayleigh-scattering component. II - Error in the retrieved water-leaving radiance

Science.gov (United States)

Gordon, Howard R.; Wang, Menghua

1992-01-01

The first step in the Coastal Zone Color Scanner (CZCS) atmospheric-correction algorithm is the computation of the Rayleigh-scattering (RS) contribution, L sub r, to the radiance leaving the top of the atmosphere over the ocean. In the present algorithm, L sub r is computed by assuming that the ocean surface is flat. Calculations of the radiance leaving an RS atmosphere overlying a rough Fresnel-reflecting ocean are presented to evaluate the radiance error caused by the flat-ocean assumption. Simulations are carried out to evaluate the error incurred when the CZCS-type algorithm is applied to a realistic ocean in which the surface is roughened by the wind. In situations where there is no direct sun glitter, it is concluded that the error induced by ignoring the Rayleigh-aerosol interaction is usually larger than that caused by ignoring the surface roughness. This suggests that, in refining algorithms for future sensors, more effort should be focused on dealing with the Rayleigh-aerosol interaction than on the roughness of the sea surface.

Intersatellite comparisons and evaluations of three ocean color products along the Zhejiang coast, eastern China

Science.gov (United States)

Cui, Qiyuan; Wang, Difeng; Gong, Fang; Pan, Delu; Hao, Zengzhou; Wang, Tianyu; Zhu, Qiankun

2017-10-01

With its broad spatial coverage and fine temporal resolution, ocean color remote sensing data represents an effective tool for monitoring large areas of ocean, and has the potential to provide crucial information in coastal waters where routine monitoring is either lacking or unsatisfactory. The semi-analytical or empirical algorithms that work well in Case 1 waters encounter many problems in offshore areas where the water is often optically complex and presents difficulties for atmospheric correction. Zhejiang is one of the most developed provinces in eastern China, and its adjacent seas have been greatly affected by recent rapid economic development. Various islands and semi-closed bays along the Zhejiang coast promote the formation of muddy tidal flats. Moreover, large quantities of terrestrial substances coming down with the Yangtze River and other local rivers also have a great impact on the coastal waters of the province. MODIS, VIIRS and GOCI are three commonly used ocean color sensors covering the East China Sea. Several ocean color products such as remote-sensing reflectance (Rrs) and the concentrations of chlorophyll a (Chl-a) and total suspended matter (TSM) of the above three sensors on the Zhejiang coast have been evaluated. Cloud-free satellite images with synchronous field measurements taken between 2012 and 2015 were used for comparison. It is shown that there is a good correlation between the MODIS and GOCI spectral data, while some outliers were found in the VIIRS images. The low signal-to-noise ratio at short wavelengths in highly turbid waters also reduced the correlation between different sensors. In addition, it was possible to obtain more valid data with GOCI in shallow waters because of the use of an appropriate atmospheric correction algorithm. The standard Chl-a and TSM products of the three satellites were also evaluated, and it was found that the Chl-a and TSM concentrations calculated by the OC3G and Case 2 algorithms, respectively

Validation of ocean color sensors using a profiling hyperspectral radiometer

Science.gov (United States)

Ondrusek, M. E.; Stengel, E.; Rella, M. A.; Goode, W.; Ladner, S.; Feinholz, M.

2014-05-01

Validation measurements of satellite ocean color sensors require in situ measurements that are accurate, repeatable and traceable enough to distinguish variability between in situ measurements and variability in the signal being observed on orbit. The utility of using a Satlantic Profiler II equipped with HyperOCR radiometers (Hyperpro) for validating ocean color sensors is tested by assessing the stability of the calibration coefficients and by comparing Hyperpro in situ measurements to other instruments and between different Hyperpros in a variety of water types. Calibration and characterization of the NOAA Satlantic Hyperpro instrument is described and concurrent measurements of water-leaving radiances conducted during cruises are presented between this profiling instrument and other profiling, above-water and moored instruments. The moored optical instruments are the US operated Marine Optical BuoY (MOBY) and the French operated Boussole Buoy. In addition, Satlantic processing versions are described in terms of accuracy and consistency. A new multi-cast approach is compared to the most commonly used single cast method. Analysis comparisons are conducted in turbid and blue water conditions. Examples of validation matchups with VIIRS ocean color data are presented. With careful data collection and analysis, the Satlantic Hyperpro profiling radiometer has proven to be a reliable and consistent tool for satellite ocean color validation.

Seahawk: An Advanced Cubesat Mission for Sustained Ocean Color Monitoring

Science.gov (United States)

Morrison, John M.; Jeffrey, Hazel; Gorter, Hessel; Anderson, Pamela; Clark, Craig; Holmes, Alan; Feldman, Gene C.; Pratt, Frederick S.

2016-01-01

Sustained ocean color monitoring is vital to understanding the marine ecosystem. It has been identified as an Essential Climate Variable (ECV) and is a vital parameter in understanding long-term climate change. Furthermore, observations can be beneficial in observing oil spills, harmful algal blooms and the health of fisheries. Space-based remote sensing, through MERIS, SeaWiFS and MODIS instruments, have provided a means of observing the vast area covered by the ocean which would otherwise be impossible using ships alone. However, the large pixel size makes measurements of lakes, rivers, estuaries and coastal zones difficult. Furthermore, retirement of a number of widely used and relied upon ocean observation instruments, particularly MERIS and SeaWiFS, leaves a significant gap in ocean color observation opportunities. This paper presents an overview of the SeaHawk mission, a collaborative effort between Clyde Space Ltd., the University of North Carolina Wilmington, Cloudland Instruments, and Goddard Spaceflight Center, funded by the Gordon and Betty Moore Foundation. The goal of the project is to enhance the ability to observe ocean color in high temporal and spatial resolution through use of a low-cost, next-generation ocean color sensor flown aboard a CubeSat. The final product will be 530 times smaller (0.0034 vs 1.81cu m) and 115 time less massive (3.4 vs 390.0 kg) but with a ground resolution 10 times better whilst maintaining a signal/noise ratio 50 that of SeaWiFs. This paper will describe the objectives of the mission, outline the payload specification and the spacecraft platform to support it.

Cross-media color reproduction using the frequency-based spatial gamut mapping algorithm based on human color vision

Science.gov (United States)

Wu, Guangyuan; Niu, Shijun; Li, Xiaozhou; Hu, Guichun

2018-04-01

Due to the increasing globalization of printing industry, remoting proofing will become the inevitable development trend. Cross-media color reproduction will occur in different color gamuts using remote proofing technologies, which usually leads to the problem of incompatible color gamut. In this paper, to achieve equivalent color reproduction between a monitor and a printer, a frequency-based spatial gamut mapping algorithm is proposed for decreasing the loss of visual color information. The design of algorithm is based on the contrast sensitivity functions (CSF), which exploited CSF spatial filter to preserve luminance of the high spatial frequencies and chrominance of the low frequencies. First we show a general framework for how to apply CSF spatial filter in retention of relevant visual information. Then we compare the proposed framework with HPMINDE, CUSP, Bala's algorithm. The psychophysical experimental results indicated the good performance of the proposed algorithm.

Color segmentation in the HSI color space using the K-means algorithm

Science.gov (United States)

Weeks, Arthur R.; Hague, G. Eric

1997-04-01

Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue

A locally adaptive algorithm for shadow correction in color images

Science.gov (United States)

Karnaukhov, Victor; Kober, Vitaly

2017-09-01

The paper deals with correction of color images distorted by spatially nonuniform illumination. A serious distortion occurs in real conditions when a part of the scene containing 3D objects close to a directed light source is illuminated much brighter than the rest of the scene. A locally-adaptive algorithm for correction of shadow regions in color images is proposed. The algorithm consists of segmentation of shadow areas with rank-order statistics followed by correction of nonuniform illumination with human visual perception approach. The performance of the proposed algorithm is compared to that of common algorithms for correction of color images containing shadow regions.

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

Science.gov (United States)

Mannino, Antonio

2008-01-01

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

Science.gov (United States)

Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

Petri nets SM-cover-based on heuristic coloring algorithm

Science.gov (United States)

Tkacz, Jacek; Doligalski, Michał

2015-09-01

In the paper, coloring heuristic algorithm of interpreted Petri nets is presented. Coloring is used to determine the State Machines (SM) subnets. The present algorithm reduces the Petri net in order to reduce the computational complexity and finds one of its possible State Machines cover. The proposed algorithm uses elements of interpretation of Petri nets. The obtained result may not be the best, but it is sufficient for use in rapid prototyping of logic controllers. Found SM-cover will be also used in the development of algorithms for decomposition, and modular synthesis and implementation of parallel logic controllers. Correctness developed heuristic algorithm was verified using Gentzen formal reasoning system.

Demosaicking algorithm for the Kodak-RGBW color filter array

Science.gov (United States)

Rafinazari, M.; Dubois, E.

2015-01-01

Digital cameras capture images through different Color Filter Arrays and then reconstruct the full color image. Each CFA pixel only captures one primary color component; the other primary components will be estimated using information from neighboring pixels. During the demosaicking algorithm, the two unknown color components will be estimated at each pixel location. Most of the demosaicking algorithms use the RGB Bayer CFA pattern with Red, Green and Blue filters. The least-Squares Luma-Chroma demultiplexing method is a state of the art demosaicking method for the Bayer CFA. In this paper we develop a new demosaicking algorithm using the Kodak-RGBW CFA. This particular CFA reduces noise and improves the quality of the reconstructed images by adding white pixels. We have applied non-adaptive and adaptive demosaicking method using the Kodak-RGBW CFA on the standard Kodak image dataset and the results have been compared with previous work.

Estimating the marine signal in the near infrared for atmospheric correction of satellite ocean-color imagery over turbid waters

Science.gov (United States)

Bourdet, Alice; Frouin, Robert J.

2014-11-01

The classic atmospheric correction algorithm, routinely applied to second-generation ocean-color sensors such as SeaWiFS, MODIS, and MERIS, consists of (i) estimating the aerosol reflectance in the red and near infrared (NIR) where the ocean is considered black (i.e., totally absorbing), and (ii) extrapolating the estimated aerosol reflectance to shorter wavelengths. The marine reflectance is then retrieved by subtraction. Variants and improvements have been made over the years to deal with non-null reflectance in the red and near infrared, a general situation in estuaries and the coastal zone, but the solutions proposed so far still suffer some limitations, due to uncertainties in marine reflectance modeling in the near infrared or difficulty to extrapolate the aerosol signal to the blue when using observations in the shortwave infrared (SWIR), a spectral range far from the ocean-color wavelengths. To estimate the marine signal (i.e., the product of marine reflectance and atmospheric transmittance) in the near infrared, the proposed approach is to decompose the aerosol reflectance in the near infrared to shortwave infrared into principal components. Since aerosol scattering is smooth spectrally, a few components are generally sufficient to represent the perturbing signal, i.e., the aerosol reflectance in the near infrared can be determined from measurements in the shortwave infrared where the ocean is black. This gives access to the marine signal in the near infrared, which can then be used in the classic atmospheric correction algorithm. The methodology is evaluated theoretically from simulations of the top-of-atmosphere reflectance for a wide range of geophysical conditions and angular geometries and applied to actual MODIS imagery acquired over the Gulf of Mexico. The number of discarded pixels is reduced by over 80% using the PC modeling to determine the marine signal in the near infrared prior to applying the classic atmospheric correction algorithm.

Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes

Directory of Open Access Journals (Sweden)

Dilip K. Prasad

2016-03-01

Full Text Available We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds. The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS, moderate-resolution imaging spectroradiometer (MODIS, sea-viewing wide field-of-view sensor (SeaWiFS, coastal zone color scanner (CZCS, ocean and land colour instrument (OLCI, and visible infrared imaging radiometer suite (VIIRS sensors. Results are also shown for CIMEL’s SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

A new efficient RLF-like algorithm for the vertex coloring problem

Directory of Open Access Journals (Sweden)

Adegbindin Mourchid

2016-01-01

Full Text Available The Recursive Largest First (RLF algorithm is one of the most popular greedy heuristics for the vertex coloring problem. It sequentially builds color classes on the basis of greedy choices. In particular, the first vertex placed in a color class C is one with a maximum number of uncolored neighbors, and the next vertices placed in C are chosen so that they have as many uncolored neighbors which cannot be placed in C. These greedy choices can have a significant impact on the performance of the algorithm, which explains why we propose alternative selection rules. Computational experiments on 63 difficult DIMACS instances show that the resulting new RLF-like algorithm, when compared with the standard RLF, allows to obtain a reduction of more than 50% of the gap between the number of colors used and the best known upper bound on the chromatic number. The new greedy algorithm even competes with basic metaheuristics for the vertex coloring problem.

Specificity of Atmospheric Correction of Satellite Data on Ocean Color in the Far East

Science.gov (United States)

Aleksanin, A. I.; Kachur, V. A.

2017-12-01

Calculation errors in ocean-brightness coefficients in the Far Eastern are analyzed for two atmospheric correction algorithms (NIR and MUMM). The daylight measurements in different water types show that the main error component is systematic and has a simple dependence on the magnitudes of the coefficients. The causes of the error behavior are considered. The most probable explanation for the large errors in ocean-color parameters in the Far East is a high concentration of continental aerosol absorbing light. A comparison between satellite and in situ measurements at AERONET stations in the United States and South Korea has been made. It is shown the errors in these two regions differ by up to 10 times upon close water turbidity and relatively high aerosol optical-depth computation precision in the case of using the NIR correction of the atmospheric effect.

Regional impacts of ocean color on tropical Pacific variability

OpenAIRE

W. Anderson; A. Gnanadesikan; A. Wittenberg

2009-01-01

The role of the penetration length scale of shortwave radiation into the surface ocean and its impact on tropical Pacific variability is investigated with a fully coupled ocean, atmosphere, land and ice model. Previous work has shown that removal of all ocean color results in a system that tends strongly towards an El Niño state. Results from a suite of surface chlorophyll perturbation experiments show that the mean state and variability of the tropical Pacific is highly se...

Encoding color information for visual tracking: Algorithms and benchmark.

Science.gov (United States)

Liang, Pengpeng; Blasch, Erik; Ling, Haibin

2015-12-01

While color information is known to provide rich discriminative clues for visual inference, most modern visual trackers limit themselves to the grayscale realm. Despite recent efforts to integrate color in tracking, there is a lack of comprehensive understanding of the role color information can play. In this paper, we attack this problem by conducting a systematic study from both the algorithm and benchmark perspectives. On the algorithm side, we comprehensively encode 10 chromatic models into 16 carefully selected state-of-the-art visual trackers. On the benchmark side, we compile a large set of 128 color sequences with ground truth and challenge factor annotations (e.g., occlusion). A thorough evaluation is conducted by running all the color-encoded trackers, together with two recently proposed color trackers. A further validation is conducted on an RGBD tracking benchmark. The results clearly show the benefit of encoding color information for tracking. We also perform detailed analysis on several issues, including the behavior of various combinations between color model and visual tracker, the degree of difficulty of each sequence for tracking, and how different challenge factors affect the tracking performance. We expect the study to provide the guidance, motivation, and benchmark for future work on encoding color in visual tracking.

Generalized Ocean Color Inversion Model for Retrieving Marine Inherent Optical Properties

Science.gov (United States)

Werdell, P. Jeremy; Franz, Bryan A.; Bailey, Sean W.; Feldman, Gene C.; Boss, Emmanuel; Brando, Vittorio E.; Dowell, Mark; Hirata, Takafumi; Lavender, Samantha J.; Lee, ZhongPing;

Evaluating VIIRS ocean color products for west coast and Hawaiian waters

KAUST Repository

Davis, Curtiss O.; Tufillaro, Nicholas; Nahorniak, Jasmine; Jones, Burton; Arnone, Robert

2013-01-01

Automated match ups allow us to maintain and improve the ocean color products of current satellite instruments MODIS, and since February 2012 the Visible Infrared Imaging Radiometer Suite (VIIRS). As part of the VIIRS mission Ocean Calibration

Use of satellite ocean color observations to refine understanding of global geochemical cycles

Science.gov (United States)

Walsh, J. J.; Dieterle, D. A.

1985-01-01

In October 1978, the first satellite-borne color sensor, the Coastal Zone Color Scanner (CZCS), was launched aboard Nimbus-7 with four visible and two infrared bands, permitting a sensitivity about 60 times that of the Landsat-1 multispectral scanner. The CZCS radiance data can be utilized to estimate ocean chlorophyll concentrations by detecting shifts in sea color, particularly in oceanic waters. The obtained data can be used in studies regarding problems of overfishing, and, in addition, in investigations concerning the consequences of man's accelerated extraction of nitrogen from the atmosphere and addition of carbon to the atmosphere. The satellite data base is considered along with a simulation analysis, and ships providing ground-truth chlorophyll measurements in the ocean.

Ocean Color Measurements from Landsat-8 OLI using SeaDAS

Science.gov (United States)

Franz, Bryan Alden; Bailey, Sean W.; Kuring, Norman; Werdell, P. Jeremy

2014-01-01

The Operational Land Imager (OLI) is a multi-spectral radiometer hosted on the recently launched Landsat-8 satellite. OLI includes a suite of relatively narrow spectral bands at 30-meter spatial resolution in the visible to shortwave infrared that make it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in SeaDAS, which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of satellite-based multi-spectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote-sensing reflectance (Rrs; sr exp 1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents such as the concentration of the phytoplankton pigment chlorophyll a.

A deblocking algorithm based on color psychology for display quality enhancement

Science.gov (United States)

Yeh, Chia-Hung; Tseng, Wen-Yu; Huang, Kai-Lin

2012-12-01

This article proposes a post-processing deblocking filter to reduce blocking effects. The proposed algorithm detects blocking effects by fusing the results of Sobel edge detector and wavelet-based edge detector. The filtering stage provides four filter modes to eliminate blocking effects at different color regions according to human color vision and color psychology analysis. Experimental results show that the proposed algorithm has better subjective and objective qualities for H.264/AVC reconstructed videos when compared to several existing methods.

Multi-Working Modes Product-Color Planning Based on Evolutionary Algorithms and Swarm Intelligence

Directory of Open Access Journals (Sweden)

Man Ding

2010-01-01

Full Text Available In order to assist designer in color planning during product development, a novel synthesized evaluation method is presented to evaluate color-combination schemes of multi-working modes products (MMPs. The proposed evaluation method considers color-combination images in different working modes as evaluating attributes, to which the corresponding weights are assigned for synthesized evaluation. Then a mathematical model is developed to search for optimal color-combination schemes of MMP based on the proposed evaluation method and two powerful search techniques known as Evolution Algorithms (EAs and Swarm Intelligence (SI. In the experiments, we present a comparative study for two EAs, namely, Genetic Algorithm (GA and Difference Evolution (DE, and one SI algorithm, namely, Particle Swarm Optimization (PSO, on searching for color-combination schemes of MMP problem. All of the algorithms are evaluated against a test scenario, namely, an Arm-type aerial work platform, which has two working modes. The results show that the DE obtains the superior solution than the other two algorithms for color-combination scheme searching problem in terms of optimization accuracy and computation robustness. Simulation results demonstrate that the proposed method is feasible and efficient.

In-Orbit Vicarious Calibration for Ocean Color and Aerosol Products

National Research Council Canada - National Science Library

Wang, Menghua

2005-01-01

It is well known that, to accurately retrieve the spectrum of the water-leaving radiance and derive the ocean color products from satellite sensors, a vicarious calibration procedure, which performs...

Color reproduction and processing algorithm based on real-time mapping for endoscopic images.

Science.gov (United States)

Khan, Tareq H; Mohammed, Shahed K; Imtiaz, Mohammad S; Wahid, Khan A

2016-01-01

In this paper, we present a real-time preprocessing algorithm for image enhancement for endoscopic images. A novel dictionary based color mapping algorithm is used for reproducing the color information from a theme image. The theme image is selected from a nearby anatomical location. A database of color endoscopy image for different location is prepared for this purpose. The color map is dynamic as its contents change with the change of the theme image. This method is used on low contrast grayscale white light images and raw narrow band images to highlight the vascular and mucosa structures and to colorize the images. It can also be applied to enhance the tone of color images. The statistic visual representation and universal image quality measures show that the proposed method can highlight the mucosa structure compared to other methods. The color similarity has been verified using Delta E color difference, structure similarity index, mean structure similarity index and structure and hue similarity. The color enhancement was measured using color enhancement factor that shows considerable improvements. The proposed algorithm has low and linear time complexity, which results in higher execution speed than other related works.

Algorithms for Coastal-Zone Color-Scanner Data

Science.gov (United States)

1986-01-01

Software for Nimbus-7 Coastal-Zone Color-Scanner (CZCS) derived products consists of set of scientific algorithms for extracting information from CZCS-gathered data. Software uses CZCS-generated Calibrated RadianceTemperature (CRT) tape as input and outputs computer-compatible tape and film product.

Retrospective satellite ocean color analysis of purposeful and natural ocean iron fertilization

Science.gov (United States)

Westberry, Toby K.; Behrenfeld, Michael J.; Milligan, Allen J.; Doney, Scott C.

2013-03-01

Significant effort has been invested in understanding the role of iron in marine ecosystems over the past few decades. What began as shipboard amendment experiments quickly grew into a succession of in situ, mesoscale ocean iron fertilization (OIF) experiments carried out in all three high nutrient low chlorophyll (HNLC) regions of the world ocean. Dedicated process studies have also looked at regions of the ocean that are seasonally exposed to iron-replete conditions as natural OIF experiments. However, one problem common to many OIF experiments is determination of biological response beyond the duration of the experiment (typicallyfloristic shifts in the phytoplankton community. Further, a consistent pattern of decreased satellite fluorescence efficiency (FLH:Chl or ϕf) following OIF is observed that is in agreement with current understanding of phytoplankton physiological responses to relief from iron stress. The current study extends our ability to retrieve phytoplankton physiology from space-based sensors, strengthens the link between satellite fluorescence and iron availability, and shows that satellite ocean color analyses provide a unique tool for monitoring OIF experiments.

A HYBRID ALGORITHM FOR THE ROBUST GRAPH COLORING PROBLEM

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Román Anselmo Mora Gutiérrez

2016-08-01

Full Text Available A hybridalgorithm which combines mathematical programming techniques (Kruskal’s algorithm and the strategy of maintaining arc consistency to solve constraint satisfaction problem “CSP” and heuristic methods (musical composition method and DSATUR to resolve the robust graph coloring problem (RGCP is proposed in this paper. Experimental result shows that this algorithm is better than the other algorithms presented on the literature.

Regional ocean-colour chlorophyll algorithms for the Red Sea

KAUST Repository

Brewin, Robert J.W.

2015-05-18

The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing.

Object tracking system using a VSW algorithm based on color and point features

Directory of Open Access Journals (Sweden)

Lim Hye-Youn

2011-01-01

Full Text Available Abstract An object tracking system using a variable search window (VSW algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects; however, a disadvantage is that it is sensitive to non-specific color objects due to illumination and noise. Therefore, to offset this weakness, it presents the VSW algorithm based on robust feature points for the accurate tracking of moving objects. The proposed method extracts the feature points of a detected object which is the region of interest (ROI, and generates a VSW using the given information which is the positions of extracted feature points. The goal of this paper is to achieve an efficient and effective object tracking system that meets the accurate tracking of moving objects. Through experiments, the object tracking system is implemented that it performs more precisely than existing techniques.

Suspended sediment concentration and optical property observations of mixed-turbidity, coastal waters through multispectral ocean color inversion

Science.gov (United States)

Multispectral satellite ocean color data from high-turbidity areas of the coastal ocean contain information about the surface concentrations and optical properties of suspended sediments and colored dissolved organic matter (CDOM). Empirical and semi-analytical inversion algorit...

Equitable Coloring of Graphs. Recent Theoretical Results and New Practical Algorithms

Directory of Open Access Journals (Sweden)

Furmańczyk Hanna

2016-09-01

Full Text Available In many applications in sequencing and scheduling it is desirable to have an underlaying graph as equitably colored as possible. In this paper we survey recent theoretical results concerning conditions for equitable colorability of some graphs and recent theoretical results concerning the complexity of equitable coloring problem. Next, since the general coloring problem is strongly NP-hard, we report on practical experiments with some efficient polynomial-time algorithms for approximate equitable coloring of general graphs.

Global Ocean Phytoplankton

Science.gov (United States)

Franz, B. A.; Behrenfeld, M. J.; Siegel, D. A.; Werdell, P. J.

2014-01-01

Marine phytoplankton are responsible for roughly half the net primary production (NPP) on Earth, fixing atmospheric CO2 into food that fuels global ocean ecosystems and drives the ocean's biogeochemical cycles. Phytoplankton growth is highly sensitive to variations in ocean physical properties, such as upper ocean stratification and light availability within this mixed layer. Satellite ocean color sensors, such as the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; McClain 2009) and Moderate Resolution Imaging Spectroradiometer (MODIS; Esaias 1998), provide observations of sufficient frequency and geographic coverage to globally monitor physically-driven changes in phytoplankton distributions. In practice, ocean color sensors retrieve the spectral distribution of visible solar radiation reflected upward from beneath the ocean surface, which can then be related to changes in the photosynthetic phytoplankton pigment, chlorophyll- a (Chla; measured in mg m-3). Here, global Chla data for 2013 are evaluated within the context of the 16-year continuous record provided through the combined observations of SeaWiFS (1997-2010) and MODIS on Aqua (MODISA; 2002-present). Ocean color measurements from the recently launched Visible and Infrared Imaging Radiometer Suite (VIIRS; 2011-present) are also considered, but results suggest that the temporal calibration of the VIIRS sensor is not yet sufficiently stable for quantitative global change studies. All MODISA (version 2013.1), SeaWiFS (version 2010.0), and VIIRS (version 2013.1) data presented here were produced by NASA using consistent Chla algorithms.

Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations

Science.gov (United States)

Ciavatta, S.; Brewin, R. J. W.; Skákala, J.; Polimene, L.; de Mora, L.; Artioli, Y.; Allen, J. I.

2018-02-01

We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998-2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems.

Some Insights of Spectral Optimization in Ocean Color Inversion

Science.gov (United States)

Lee, Zhongping; Franz, Bryan; Shang, Shaoling; Dong, Qiang; Arnone, Robert

2011-01-01

In the past decades various algorithms have been developed for the retrieval of water constituents from the measurement of ocean color radiometry, and one of the approaches is spectral optimization. This approach defines an error target (or error function) between the input remote sensing reflectance and the output remote sensing reflectance, with the latter modeled with a few variables that represent the optically active properties (such as the absorption coefficient of phytoplankton and the backscattering coefficient of particles). The values of the variables when the error reach a minimum (optimization is achieved) are considered the properties that form the input remote sensing reflectance; or in other words, the equations are solved numerically. The applications of this approach implicitly assume that the error is a monotonic function of the various variables. Here, with data from numerical simulation and field measurements, we show the shape of the error surface, in a way to justify the possibility of finding a solution of the various variables. In addition, because the spectral properties could be modeled differently, impacts of such differences on the error surface as well as on the retrievals are also presented.

Seasonal estimates of DOC standing stocks in Apalachicola Bay estuary: Towards a better understanding using field, ocean color and model data

Science.gov (United States)

D'Sa, E. J.; Joshi, I.; Osburn, C. L.; Bianchi, T. S.; Ko, D. S.; Oviedo-Vargas, D.; Arellano, A.; Ward, N.

2016-12-01

Apalachicola Bay, a semi-enclosed estuary located in Florida's panhandle, is well known for its water quality and oyster yields. We present the use of combined field and ocean color satellite observations and the outputs of a high-resolution hydrodynamic model to study the influence of physical processes on the distribution and the transport of terrestrially derived CDOM and DOC to shelf waters during the spring and fall of 2015. Determination of DOC stocks were based on the development of a CDOM algorithm (R2 = 0.87, N = 9) for the VIIRS ocean color sensor, and the assessment of CDOM - DOC relationships (R2 = 0.88, N = 13 in March; R2 = 0.83, N = 24 in November) for the Apalachicola Bay. Satellite-derived CDOM and DOC maps together with model-based salinity distributions revealed their spatial extent, sources and transport to the shelf water. Furthermore, strong seasonal influence on DOM distribution in the bay was associated with inputs from Apalachicola and Carrabelle Rivers and the surrounding marshes. Estimates of DOC standing stocks in the bay obtained using ocean color data and high-resolution bathymetry showed relatively higher stocks in November ( 3.71 × 106 kg C, 560 km2) than in March ( 4.07 × 106 kg C, 560 km2) despite lower river discharge in dry season. Results of DOC flux estimates from the bay to coastal waters will also be presented.

A robust color image watermarking algorithm against rotation attacks

Science.gov (United States)

Han, Shao-cheng; Yang, Jin-feng; Wang, Rui; Jia, Gui-min

2018-01-01

A robust digital watermarking algorithm is proposed based on quaternion wavelet transform (QWT) and discrete cosine transform (DCT) for copyright protection of color images. The luminance component Y of a host color image in YIQ space is decomposed by QWT, and then the coefficients of four low-frequency subbands are transformed by DCT. An original binary watermark scrambled by Arnold map and iterated sine chaotic system is embedded into the mid-frequency DCT coefficients of the subbands. In order to improve the performance of the proposed algorithm against rotation attacks, a rotation detection scheme is implemented before watermark extracting. The experimental results demonstrate that the proposed watermarking scheme shows strong robustness not only against common image processing attacks but also against arbitrary rotation attacks.

Polarization-based enhancement of ocean color signal for estimating suspended particulate matter: radiative transfer simulations and laboratory measurements.

Science.gov (United States)

Liu, Jia; He, Xianqiang; Liu, Jiahang; Bai, Yan; Wang, Difeng; Chen, Tieqiao; Wang, Yihao; Zhu, Feng

2017-04-17

Absorption and scattering by molecules, aerosols and hydrosols, and the reflection and transmission over the sea surface can modify the original polarization state of sunlight. However, water-leaving radiance polarization, containing embedded water constituent information, has largely been neglected. Here, the efficiency of the parallel polarization radiance (PPR) for enhancing ocean color signal of suspended particulate matter is examined via vector radiative transfer simulations and laboratory experiments. The simulation results demonstrate that the PPR has a slightly higher ocean color signal at the top-of-atmosphere as compared with that of the total radiance. Moreover, both the simulations and laboratory measurements reveal that, compared with total radiance, PPR can effectively enhance the normalized ocean color signal for a large range of observation geometries, wavelengths, and suspended particle concentrations. Thus, PPR has great potential for improving the ocean color signal detection from satellite.

Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic.

Science.gov (United States)

Kampel, Milton; Lorenzzetti, João A; Bentz, Cristina M; Nunes, Raul A; Paranhos, Rodolfo; Rudorff, Frederico M; Politano, Alexandre T

2009-01-01

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3M(RAD)), Ocean Chlorophyll 4 bands (OC4v4(RAD)), and Ocean Chlorophyll 2 bands (OC2v4(RAD)). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3M(SAT), and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01(SAT)), and Carder(SAT). In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m(3). In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m(3) (OC2v4(RAD)). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m(3)) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m(3), respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm

Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic

Directory of Open Access Journals (Sweden)

Cristina M. Bentz

2009-01-01

Full Text Available Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3MRAD, Ocean Chlorophyll 4 bands (OC4v4RAD, and Ocean Chlorophyll 2 bands (OC2v4RAD. The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3MSAT, and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01SAT, and CarderSAT. In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg·m-3. In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m3 (OC2v4RAD. The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m3 than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m3, respectively. We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of RRS by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed

Detection of Coccolithophore Blooms in Ocean Color Satellite Imagery: a Generalized Approach for Use with Multiple Sensors

Science.gov (United States)

Moore, Timothy; Dowell, Mark; Franz, Bryan A.

2012-01-01

A generalized coccolithophore bloom classifier has been developed for use with ocean color imagery. The bloom classifier was developed using extracted satellite reflectance data from SeaWiFS images screened by the default bloom detection mask. In the current application, we extend the optical water type (OWT) classification scheme by adding a new coccolithophore bloom class formed from these extracted reflectances. Based on an in situ coccolithophore data set from the North Atlantic, the detection levels with the new scheme were between 1,500 and 1,800 coccolithophore cellsmL and 43,000 and 78,000 lithsmL. The detected bloom area using the OWT method was an average of 1.75 times greater than the default bloom detector based on a collection of SeaWiFS 1 km imagery. The versatility of the scheme is shown with SeaWiFS, MODIS Aqua, CZCS and MERIS imagery at the 1 km scale. The OWT scheme was applied to the daily global SeaWiFS imagery mission data set (years 19972010). Based on our results, average annual coccolithophore bloom area was more than two times greater in the southern hemisphere compared to the northern hemi- sphere with values of 2.00 106 km2 and 0.75 106 km2, respectively. The new algorithm detects larger bloom areas in the Southern Ocean compared to the default algorithm, and our revised global annual average of 2.75106 km2 is dominated by contributions from the Southern Ocean.

Use of ocean color scanner data in water quality mapping

Science.gov (United States)

Khorram, S.

1981-01-01

Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

Quantum Color Image Encryption Algorithm Based on A Hyper-Chaotic System and Quantum Fourier Transform

Science.gov (United States)

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.

Satellite Ocean Biology: Past, Present, Future

Science.gov (United States)

McClain, Charles R.

2012-01-01

Since 1978 when the first satellite ocean color proof-of-concept sensor, the Nimbus-7 Coastal Zone Color Scanner, was launched, much progress has been made in refining the basic measurement concept and expanding the research applications of global satellite time series of biological and optical properties such as chlorophyll-a concentrations. The seminar will review the fundamentals of satellite ocean color measurements (sensor design considerations, on-orbit calibration, atmospheric corrections, and bio-optical algorithms), scientific results from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate resolution Imaging Spectroradiometer (MODIS) missions, and the goals of future NASA missions such as PACE, the Aerosol, Cloud, Ecology (ACE), and Geostationary Coastal and Air Pollution Events (GeoCAPE) missions.

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

Science.gov (United States)

Li, Yonghong; Angal, Amit; Wu, Aisheng; Geng, Xu; Link, Daniel; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Evaluating VIIRS ocean color products for west coast and Hawaiian waters

KAUST Repository

Davis, Curtiss O.

2013-06-03

Automated match ups allow us to maintain and improve the ocean color products of current satellite instruments MODIS, and since February 2012 the Visible Infrared Imaging Radiometer Suite (VIIRS). As part of the VIIRS mission Ocean Calibration and Validation Team, we have created a web-based automated match up tool that provides access to searchable fields for date, site, and products, and creates matchups between satellites (MODIS, VIIRS), and in-situ measurements (HyperPRO and SeaPRISM). The goal is to evaluate the standard VIIRS ocean color products produced by the IDPS and available through NOAA’s CLASS data system. Comparisons are made with MODIS data for the same location, and VIIRS data processed using the NRL Automated Processing System (APS) used to produce operational products for the Navy. Results are shown for the first year of VIIRS data matching the satellite data with the data from Platform Eureka SeaPRISM off L. A. Harbor in the Southern California Bight, and HyperPRO data from Station ALOHA near Hawaii. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Regional impacts of ocean color on tropical Pacific variability

Science.gov (United States)

Anderson, W.; Gnanadesikan, A.; Wittenberg, A.

2009-08-01

The role of the penetration length scale of shortwave radiation into the surface ocean and its impact on tropical Pacific variability is investigated with a fully coupled ocean, atmosphere, land and ice model. Previous work has shown that removal of all ocean color results in a system that tends strongly towards an El Niño state. Results from a suite of surface chlorophyll perturbation experiments show that the mean state and variability of the tropical Pacific is highly sensitive to the concentration and distribution of ocean chlorophyll. Setting the near-oligotrophic regions to contain optically pure water warms the mean state and suppresses variability in the western tropical Pacific. Doing the same above the shadow zones of the tropical Pacific also warms the mean state but enhances the variability. It is shown that increasing penetration can both deepen the pycnocline (which tends to damp El Niño) while shifting the mean circulation so that the wind response to temperature changes is altered. Depending on what region is involved this change in the wind stress can either strengthen or weaken ENSO variability.

Bio-optical profiling floats as new observational tools for biogeochemical and ecosystem studies: Potential synergies with ocean color remote sensing

Energy Technology Data Exchange (ETDEWEB)

Claustre, H.; Bishop, J.; Boss, E.; Bernard, S.; Berthon, J.-F.; Coatanoan, C.; Johnson, K.; Lotiker, A.; Ulloa, O.; Perry, M.J.; D' Ortenzio, F.; D' andon, O.H.F.; Uitz, J.

2009-10-01

Profiling floats now represent a mature technology. In parallel with their emergence, the field of miniature, low power bio-optical and biogeochemical sensors is rapidly evolving. Over recent years, the bio-geochemical and bio-optical community has begun to benefit from the increase in observational capacities by developing profiling floats that allow the measurement of key biooptical variables and subsequent products of biogeochemical and ecosystem relevance like Chlorophyll a (Chla), optical backscattering or attenuation coefficients which are proxies of Particulate Organic Carbon (POC), Colored Dissolved Organic Matter (CDOM). Thanks to recent algorithmic improvements, new bio-optical variables such as backscattering coefficient or absorption by CDOM, at present can also be extracted from space observations of ocean color. In the future, an intensification of in situ measurements by bio-optical profiling floats would permit the elaboration of unique 3D/4D bio-optical climatologies, linking surface (remotely detected) properties to their vertical distribution (measured by autonomous platforms), with which key questions in the role of the ocean in climate could be addressed. In this context, the objective of the IOCCG (International Ocean Color Coordinating Group) BIO-Argo working group is to elaborate recommendations in view of a future use of bio-optical profiling floats as part of a network that would include a global array that could be 'Argo-relevant', and specific arrays that would have more focused objectives or regional targets. The overall network, realizing true multi-scale sustained observations of global marine biogeochemistry and biooptics, should satisfy the requirements for validation of ocean color remote sensing as well as the needs of a wider community investigating the impact of global change on biogeochemical cycles and ecosystems. Regarding the global profiling float array, the recommendation is that Chla as well as POC should be the

A design study for an advanced ocean color scanner system. [spaceborne equipment

Science.gov (United States)

Kim, H. H.; Fraser, R. S.; Thompson, L. L.; Bahethi, O.

1980-01-01

Along with a colorimetric data analysis scheme, the instrumental parameters which need to be optimized in future spaceborne ocean color scanner systems are outlined. With regard to assessing atmospheric effects from ocean colorimetry, attention is given to computing size parameters of the aerosols in the atmosphere, total optical depth measurement, and the aerosol optical thickness. It is suggested that sensors based on the use of linear array technology will meet hardware objectives.

Objectness Supervised Merging Algorithm for Color Image Segmentation

Directory of Open Access Journals (Sweden)

Haifeng Sima

2016-01-01

Full Text Available Ideal color image segmentation needs both low-level cues and high-level semantic features. This paper proposes a two-hierarchy segmentation model based on merging homogeneous superpixels. First, a region growing strategy is designed for producing homogenous and compact superpixels in different partitions. Total variation smoothing features are adopted in the growing procedure for locating real boundaries. Before merging, we define a combined color-texture histogram feature for superpixels description and, meanwhile, a novel objectness feature is proposed to supervise the region merging procedure for reliable segmentation. Both color-texture histograms and objectness are computed to measure regional similarities between region pairs, and the mixed standard deviation of the union features is exploited to make stop criteria for merging process. Experimental results on the popular benchmark dataset demonstrate the better segmentation performance of the proposed model compared to other well-known segmentation algorithms.

Regional impacts of ocean color on tropical Pacific variability

Directory of Open Access Journals (Sweden)

W. Anderson

2009-08-01

Full Text Available The role of the penetration length scale of shortwave radiation into the surface ocean and its impact on tropical Pacific variability is investigated with a fully coupled ocean, atmosphere, land and ice model. Previous work has shown that removal of all ocean color results in a system that tends strongly towards an El Niño state. Results from a suite of surface chlorophyll perturbation experiments show that the mean state and variability of the tropical Pacific is highly sensitive to the concentration and distribution of ocean chlorophyll. Setting the near-oligotrophic regions to contain optically pure water warms the mean state and suppresses variability in the western tropical Pacific. Doing the same above the shadow zones of the tropical Pacific also warms the mean state but enhances the variability. It is shown that increasing penetration can both deepen the pycnocline (which tends to damp El Niño while shifting the mean circulation so that the wind response to temperature changes is altered. Depending on what region is involved this change in the wind stress can either strengthen or weaken ENSO variability.

a New Graduation Algorithm for Color Balance of Remote Sensing Image

Science.gov (United States)

Zhou, G.; Liu, X.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Pan, Q.

2018-05-01

In order to expand the field of view to obtain more data and information when doing research on remote sensing image, workers always need to mosaicking images together. However, the image after mosaic always has the large color differences and produces the gap line. This paper based on the graduation algorithm of tarigonometric function proposed a new algorithm of Two Quarter-rounds Curves (TQC). The paper uses the Gaussian filter to solve the program about the image color noise and the gap line. The paper used one of Greenland compiled data acquired in 1963 from Declassified Intelligence Photography Project (DISP) by ARGON KH-5 satellite, and used the photography of North Gulf, China, by Landsat satellite to experiment. The experimental results show that the proposed method has improved the accuracy of the results in two parts: on the one hand, for the large color differences remote sensing image will become more balanced. On the other hands, the remote sensing image will achieve more smooth transition.

Enhance field water-color measurements with a Secchi disk and its implication for fusion of active and passive ocean-color remote sensing.

Science.gov (United States)

Lee, Zhongping; Shang, Shaoling; Du, Keping; Liu, Bingyi; Lin, Gong; Wei, Jianwei; Li, Xiaolong

2018-05-01

Inversion of the total absorption (a) and backscattering coefficients of bulk water through a fusion of remote sensing reflectance (R rs ) and Secchi disk depth (Z SD ) is developed. An application of such a system to a synthesized wide-range dataset shows a reduction of ∼3 folds in the uncertainties of inverted a(λ) (in a range of ∼0.01-6.8  m -1 ) from R rs (λ) for the 350-560 nm range. Such a fusion is further proposed to process concurrent active (ocean LiDAR) and passive (ocean-color) measurements, which can lead to nearly "exact" analytical inversion of an R rs spectrum. With such a fusion, it is found that the uncertainty in the inverted total a in the 350-560 nm range could be reduced to ∼2% for the synthesized data, which can thus significantly improve the derivation of a coefficients of other varying components. Although the inclusion of Z SD places an extra constraint in the inversion of R rs , no apparent improvement over the quasi-analytical algorithm (QAA) was found when the fusion of Z SD and R rs was applied to a field dataset, which calls for more accurate determination of the absorption coefficients from water samples.

EFFICIENT ADAPTIVE STEGANOGRAPHY FOR COLOR IMAGESBASED ON LSBMR ALGORITHM

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B. Sharmila

2012-02-01

Full Text Available Steganography is the art of hiding the fact that communication is taking place, by hiding information in other medium. Many different carrier file formats can be used, but digital images are the most popular because of their frequent use on the Internet. For hiding secret information in images, there exists a large variety of steganographic techniques. The Least Significant Bit (LSB based approach is a simplest type of steganographic algorithm. In all the existing approaches, the decision of choosing the region within a cover image is performed without considering the relationship between image content and the size of secret message. Thus, the plain regions in the cover will be ruin after data hiding even at a low data rate. Hence choosing the edge region for data hiding will be a solution. Many algorithms are deal with edges in images for data hiding. The Paper 'Edge adaptive image steganography based on LSBMR algorithm' is a LSB steganography presented the results of algorithms on gray-scale images only. This paper presents the results of analyzing the performance of edge adaptive steganography for colored images (JPEG. The algorithms have been slightly modified for colored image implementation and are compared on the basis of evaluation parameters like peak signal noise ratio (PSNR and mean square error (MSE. This method can select the edge region depending on the length of secret message and difference between two consecutive bits in the cover image. For length of message is short, only small edge regions are utilized while on leaving other region as such. When the data rate increases, more regions can be used adaptively for data hiding by adjusting the parameters. Besides this, the message is encrypted using efficient cryptographic algorithm which further increases the security.

A novel hybrid color image encryption algorithm using two complex chaotic systems

Science.gov (United States)

Wang, Leyuan; Song, Hongjun; Liu, Ping

2016-02-01

Based on complex Chen and complex Lorenz systems, a novel color image encryption algorithm is proposed. The larger chaotic ranges and more complex behaviors of complex chaotic systems, which compared with real chaotic systems could additionally enhance the security and enlarge key space of color image encryption. The encryption algorithm is comprised of three step processes. In the permutation process, the pixels of plain image are scrambled via two-dimensional and one-dimensional permutation processes among RGB channels individually. In the diffusion process, the exclusive-or (XOR for short) operation is employed to conceal pixels information. Finally, the mixing RGB channels are used to achieve a multilevel encryption. The security analysis and experimental simulations demonstrate that the proposed algorithm is large enough to resist the brute-force attack and has excellent encryption performance.

Variability of the reflectance coefficient of skylight from the ocean surface and its implications to ocean color.

Science.gov (United States)

Gilerson, Alexander; Carrizo, Carlos; Foster, Robert; Harmel, Tristan

2018-04-16

The value and spectral dependence of the reflectance coefficient (ρ) of skylight from wind-roughened ocean surfaces is critical for determining accurate water leaving radiance and remote sensing reflectances from shipborne, AERONET-Ocean Color and satellite observations. Using a vector radiative transfer code, spectra of the reflectance coefficient and corresponding radiances near the ocean surface and at the top of the atmosphere (TOA) are simulated for a broad range of parameters including flat and windy ocean surfaces with wind speeds up to 15 m/s, aerosol optical thicknesses of 0-1 at 440nm, wavelengths of 400-900 nm, and variable Sun and viewing zenith angles. Results revealed a profound impact of the aerosol load and type on the spectral values of ρ. Such impacts, not included yet in standard processing, may produce significant inaccuracies in the reflectance spectra retrieved from above-water radiometry and satellite observations. Implications for satellite cal/val activities as well as potential changes in measurement and data processing schemes are discussed.

A synthesis of light absorption properties of the Arctic Ocean: application to semianalytical estimates of dissolved organic carbon concentrations from space

Science.gov (United States)

Matsuoka, A.; Babin, M.; Doxaran, D.; Hooker, S. B.; Mitchell, B. G.; Bélanger, S.; Bricaud, A.

2014-06-01

In addition to scattering coefficients, the light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean (e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012), the data sets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database of the Arctic Ocean by pooling the majority of published data sets and merging new data sets. Our results show that the total nonwater absorption coefficients measured in the eastern Arctic Ocean (EAO; Siberian side) are significantly higher than in the western Arctic Ocean (WAO; North American side). This higher absorption is explained by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off North America. In contrast, the relationship between the phytoplankton absorption (aϕ(λ)) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semianalytical CDOM absorption algorithm is based on chl a-specific aϕ(λ) values (Matsuoka et al., 2013), this result indirectly suggests that CDOM absorption can be appropriately derived not only for the WAO but also for the EAO using ocean color data. Based on statistics, derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semianalytical algorithm for estimating DOC concentrations for river-influenced coastal waters of the Arctic Ocean is presented and applied to satellite

Surface currents in the Bohai Sea derived from the Korean Geostationary Ocean Color Imager (GOCI)

Science.gov (United States)

Jiang, L.; Wang, M.

2016-02-01

The first geostationary ocean color satellite sensor, the Geostationary Ocean Color Imager (GOCI) onboard the Korean Communication, Ocean, and Meteorological Satellite can monitor and measure ocean phenomena over an area of 2500 × 2500 km2 around the western Pacific region centered at 36°N and 130°E. Hourly measurements during the day around 9:00 to 16:00 local time are a unique capability of GOCI to monitor ocean features of higher temporal variability. In this presentation, we show some recent results of GOCI-derived ocean surface currents in the Bohai Sea using the Maximum Cross-Correlation (MCC) feature tracking method and compare the results with altimetry-inversed tidal current observations produced from Oregon State University (OSU) Tidal Inversion Software (OTIS). The performance of the GOCI-based MCC method is assessed and the discrepancies between the GOCI- and OTIS-derived currents are evaluated. A series of sensitivity studies are conducted with images from various satellite products and of various time differences, MCC adjustable parameters, and influence from other forcings such as wind, to find the best setups for optimal MCC performance. Our results demonstrate that GOCI can effectively provide real-time monitoring of not only water optical, biological, and biogeochemical variability, but also the physical dynamics in the region.

Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms

Directory of Open Access Journals (Sweden)

Iyad Abu Doush

2017-10-01

Full Text Available Banknote recognition means classifying the currency (coin and paper to the correct class. In this paper, we developed a dataset for Jordanian currency. After that we applied automatic mobile recognition system using a smartphone on the dataset using scale-invariant feature transform (SIFT algorithm. This is the first attempt, to the best of the authors knowledge, to recognize both coins and paper banknotes on a smartphone using SIFT algorithm. SIFT has been developed to be the most robust and efficient local invariant feature descriptor. Color provides significant information and important values in the object description process and matching tasks. Many objects cannot be classified correctly without their color features. We compared between two approaches colored local invariant feature descriptor (color SIFT approach and gray image local invariant feature descriptor (gray SIFT approach. The evaluation results show that the color SIFT approach outperforms the gray SIFT approach in terms of processing time and accuracy.

A kind of color image segmentation algorithm based on super-pixel and PCNN

Science.gov (United States)

Xu, GuangZhu; Wang, YaWen; Zhang, Liu; Zhao, JingJing; Fu, YunXia; Lei, BangJun

2018-04-01

Image segmentation is a very important step in the low-level visual computing. Although image segmentation has been studied for many years, there are still many problems. PCNN (Pulse Coupled Neural network) has biological background, when it is applied to image segmentation it can be viewed as a region-based method, but due to the dynamics properties of PCNN, many connectionless neurons will pulse at the same time, so it is necessary to identify different regions for further processing. The existing PCNN image segmentation algorithm based on region growing is used for grayscale image segmentation, cannot be directly used for color image segmentation. In addition, the super-pixel can better reserve the edges of images, and reduce the influences resulted from the individual difference between the pixels on image segmentation at the same time. Therefore, on the basis of the super-pixel, the original PCNN algorithm based on region growing is improved by this paper. First, the color super-pixel image was transformed into grayscale super-pixel image which was used to seek seeds among the neurons that hadn't been fired. And then it determined whether to stop growing by comparing the average of each color channel of all the pixels in the corresponding regions of the color super-pixel image. Experiment results show that the proposed algorithm for the color image segmentation is fast and effective, and has a certain effect and accuracy.

How ocean color can steer Pacific tropical cyclones

Science.gov (United States)

Gnanadesikan, Anand; Emanuel, Kerry; Vecchi, Gabriel A.; Anderson, Whit G.; Hallberg, Robert

2010-09-01

Because ocean color alters the absorption of sunlight, it can produce changes in sea surface temperatures with further impacts on atmospheric circulation. These changes can project onto fields previously recognized to alter the distribution of tropical cyclones. If the North Pacific subtropical gyre contained no absorbing and scattering materials, the result would be to reduce subtropical cyclone activity in the subtropical Northwest Pacific by 2/3, while concentrating cyclone tracks along the equator. Predicting tropical cyclone activity using coupled models may thus require consideration of the details of how heat moves into the upper thermocline as well as biogeochemical cycling.

Use of Real Time Satellite Infrared and Ocean Color to Produce Ocean Products

Science.gov (United States)

Roffer, M. A.; Muller-Karger, F. E.; Westhaver, D.; Gawlikowski, G.; Upton, M.; Hall, C.

2014-12-01

Real-time data products derived from infrared and ocean color satellites are useful for several types of users around the world. Highly relevant applications include recreational and commercial fisheries, commercial towing vessel and other maritime and navigation operations, and other scientific and applied marine research. Uses of the data include developing sampling strategies for research programs, tracking of water masses and ocean fronts, optimizing ship routes, evaluating water quality conditions (coastal, estuarine, oceanic), and developing fisheries and essential fish habitat indices. Important considerations for users are data access and delivery mechanisms, and data formats. At this time, the data are being generated in formats increasingly available on mobile computing platforms, and are delivered through popular interfaces including social media (Facebook, Linkedin, Twitter and others), Google Earth and other online Geographical Information Systems, or are simply distributed via subscription by email. We review 30 years of applications and describe how we develop customized products and delivery mechanisms working directly with users. We review benefits and issues of access to government databases (NOAA, NASA, ESA), standard data products, and the conversion to tailored products for our users. We discuss advantages of different product formats and of the platforms used to display and to manipulate the data.

Validation of Ocean Color Sensors Using a Profiling Hyperspectral Radiometer

Science.gov (United States)

2014-01-01

Chesapeake Bay, South Florida, Hawaii, and the Gulf of Mexico . Typical data collected for each station include Hyperpro in-water measurements, ASD above...K., Demer, K., Fishe,r K.M., Davis, E., Urizar, C, and Merlini, R., "Assessment of the Eastern Gulf of Mexico Harmful Algal Bloom Operational...conducted in turbid and blue water conditions. Examples of validation matchups with VIIRS ocean color data are presented. With careful data collection

A Moving Object Detection Algorithm Based on Color Information

International Nuclear Information System (INIS)

Fang, X H; Xiong, W; Hu, B J; Wang, L T

2006-01-01

This paper designed a new algorithm of moving object detection for the aim of quick moving object detection and orientation, which used a pixel and its neighbors as an image vector to represent that pixel and modeled different chrominance component pixel as a mixture of Gaussians, and set up different mixture model of Gauss for different YUV chrominance components. In order to make full use of the spatial information, color segmentation and background model were combined. Simulation results show that the algorithm can detect intact moving objects even when the foreground has low contrast with background

Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

Science.gov (United States)

Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

2018-04-01

Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Ocean Color/Chlorophyll (OCC) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Ocean Color/Chlorophyll (OCC) from the Visible Infrared Imaging Radiometer Suite...

An optimized digital watermarking algorithm in wavelet domain based on differential evolution for color image.

Science.gov (United States)

Cui, Xinchun; Niu, Yuying; Zheng, Xiangwei; Han, Yingshuai

2018-01-01

In this paper, a new color watermarking algorithm based on differential evolution is proposed. A color host image is first converted from RGB space to YIQ space, which is more suitable for the human visual system. Then, apply three-level discrete wavelet transformation to luminance component Y and generate four different frequency sub-bands. After that, perform singular value decomposition on these sub-bands. In the watermark embedding process, apply discrete wavelet transformation to a watermark image after the scrambling encryption processing. Our new algorithm uses differential evolution algorithm with adaptive optimization to choose the right scaling factors. Experimental results show that the proposed algorithm has a better performance in terms of invisibility and robustness.

Empirical algorithms to estimate water column pH in the Southern Ocean

Science.gov (United States)

Williams, N. L.; Juranek, L. W.; Johnson, K. S.; Feely, R. A.; Riser, S. C.; Talley, L. D.; Russell, J. L.; Sarmiento, J. L.; Wanninkhof, R.

2016-04-01

Empirical algorithms are developed using high-quality GO-SHIP hydrographic measurements of commonly measured parameters (temperature, salinity, pressure, nitrate, and oxygen) that estimate pH in the Pacific sector of the Southern Ocean. The coefficients of determination, R2, are 0.98 for pH from nitrate (pHN) and 0.97 for pH from oxygen (pHOx) with RMS errors of 0.010 and 0.008, respectively. These algorithms are applied to Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemical profiling floats, which include novel sensors (pH, nitrate, oxygen, fluorescence, and backscatter). These algorithms are used to estimate pH on floats with no pH sensors and to validate and adjust pH sensor data from floats with pH sensors. The adjusted float data provide, for the first time, seasonal cycles in surface pH on weekly resolution that range from 0.05 to 0.08 on weekly resolution for the Pacific sector of the Southern Ocean.

UNIFICATION AND APPLICATIONS OF MODERN OCEANIC/ATMOSPHERIC DATA ASSIMILATION ALGORITHMS

Institute of Scientific and Technical Information of China (English)

QIAO Fang-li; ZHANG Shao-qing; YUAN Ye-li

2004-01-01

The key mathematics and applications of various modern atmospheric/oceanic data assimilation methods including Optimal Interpolation(OI),4-dimensional variational approach(4D-Var)and filters were systematically reviewed and classified.Based on the data assimilation philosophy,I.e.,using model dynamics to extract the observational information,the common character of the problem,such as the probabilistic nature of the evolution of the atmospheric/oceanic system,noisy and irregularly spaced observations,and the advantages and disadvantages of these data assimilation algorithms,were discussed.In the filtering framework,all modern data assimilation algorithms were unified: OI/3D-Var is a stationary filter,4D-Var is a linear(Kalman)filter and an ensemble of Kalman filters is able to construct a nonlinear filter.The nonlinear filter such as the Ensemble Kalman Filter(ENKF),Ensemble Adjustment Kalman Filter(EAKF)and Ensemble Transformation Kalman Filter(ETKF)can,to some extent,account for the non-Gaussian information of the prior distribution from the model.The flow-dependent covariance estimated by an ensemble filter may be introduced to OI and 4D-Var to improve these traditional algorithms.In practice,the performance of algorithms may depend on the specific numerical model and the choice of algorithm may depend on the specific problem.However,the unification of algorithms allows us to establish a unified test system to evaluate these algorithms,which provides more insights into data assimilation philosophies and helps improve data assimilation techniques.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 2; Revised

Science.gov (United States)

Mueller, James L. (Editor); Fargion, Giulietta S. (Editor); Trees, C.; Austin, R. W.; Pietras, C. (Editor); Hooker, S.; Holben, B.; McClain, Charles R.; Clark, D. K.; Yuen, M.

2002-01-01

This document stipulates protocols for measuring bio-optical and radiometric data for the SIMBIOS Project. It supersedes the earlier version, and is organized into four parts: Introductory Background, Instrument Characteristics, Field Measurements and Data Analysis, Data Reporting and Archival. Changes in this revision include the addition of three new chapters: (1) Fundamental Definitions, Relationships and Conventions; (2) MOBY, A Radiometric Buoy for Performance Monitoring and Vicarious Calibration of Satellite Ocean Color Sensors: Measurement and Data Analysis Protocols; and (3) Normalized Water-Leaving Radiance and Remote Sensing Reflectance: Bidirectional Reflectance and Other Factors. Although the present document represents another significant, incremental improvement in the ocean optics protocols, there are several protocols that have either been overtaken by recent technological progress, or have been otherwise identified as inadequate. Revision 4 is scheduled for completion sometime in 2003. This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational Project. The contributions are published as submitted, after only minor editing to correct obvious grammatical or clerical errors.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 1; Revised

Science.gov (United States)

Mueller, James L. (Editor); Fargion, Giulietta (Editor); Mueller, J. L.; Trees, C.; Austin, R. W.; Pietras, C.; Hooker, S.; Holben, B.; McClain, Charles R.; Clark, D. K.;

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance.

Science.gov (United States)

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2016-03-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), S cdm (units: nm -1 ), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving S cdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360-500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of S cdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors.

Penetration of UV-visible solar radiation in the global oceans: Insights from ocean color remote sensing

Science.gov (United States)

Lee, Zhongping; Hu, Chuanmin; Shang, Shaoling; Du, Keping; Lewis, Marlon; Arnone, Robert; Brewin, Robert

2013-09-01

Penetration of solar radiation in the ocean is determined by the attenuation coefficient (Kd(λ)). Following radiative transfer theory, Kd is a function of angular distribution of incident light and water's absorption and backscattering coefficients. Because these optical products are now generated routinely from satellite measurements, it is logical to evolve the empirical Kd to a semianalytical Kd that is not only spectrally flexible, but also the sun-angle effect is accounted for explicitly. Here, the semianalytical model developed in Lee et al. (2005b) is revised to account for the shift of phase function between molecular and particulate scattering from the short to long wavelengths. Further, using field data collected independently from oligotrophic ocean to coastal waters covering >99% of the Kd range for the global oceans, the semianalytically derived Kd was evaluated and found to agree with measured data within ˜7-26%. The updated processing system was applied to MODIS measurements to reveal the penetration of UVA-visible radiation in the global oceans, where an empirical procedure to correct Raman effect was also included. The results indicated that the penetration of the blue-green radiation for most oceanic waters is ˜30-40% deeper than the commonly used euphotic zone depth; and confirmed that at a depth of 50-70 m there is still ˜10% of the surface UVA radiation (at 360 nm) in most oligotrophic waters. The results suggest a necessity to modify or expand the light attenuation product from satellite ocean-color measurements in order to be more applicable for studies of ocean physics and biogeochemistry.

Sea Surface Temperature and Ocean Color Variability in the South China Sea

Science.gov (United States)

Conaty, A. P.

2001-12-01

The South China Sea is a marginal sea in the Southeast Asian region whose surface circulation is driven by monsoons and whose surface currents have complex seasonal patterns. Its rich natural resources and strategic location have made its small islands areas of political dispute among the neighboring nations. This study aims to show the seasonal and interannual variability of sea surface temperature and ocean color in South China Sea. It makes use of NOAA's Advanced Very High Resolution Radiometer (AVHRR) satellite data sets on sea surface temperature for the period 1981-2000 and NASA's Nimbus-7 Coastal Zone Color Scanner (CZCS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite data sets on pigment concentration (ocean color) for the period 1981-1996 and 1997-2000, respectively. Transect lines were drawn along several potential hotspot areas to show the variability in sea surface temperature and pigment concentration through time. In-situ data on sea surface temperature along South China Sea were likewise plotted to see the variability with time. Higher seasonal variability in sea surface temperature was seen at higher latitudes. Interannual variability was within 1-3 Kelvin. In most areas, pigment concentration was higher during northern hemisphere winter and autumn, after the monsoon rains, with a maximum of 30 milligrams per cubic meter.

A new parallelization algorithm of ocean model with explicit scheme

Science.gov (United States)

Fu, X. D.

2017-08-01

This paper will focus on the parallelization of ocean model with explicit scheme which is one of the most commonly used schemes in the discretization of governing equation of ocean model. The characteristic of explicit schema is that calculation is simple, and that the value of the given grid point of ocean model depends on the grid point at the previous time step, which means that one doesn’t need to solve sparse linear equations in the process of solving the governing equation of the ocean model. Aiming at characteristics of the explicit scheme, this paper designs a parallel algorithm named halo cells update with tiny modification of original ocean model and little change of space step and time step of the original ocean model, which can parallelize ocean model by designing transmission module between sub-domains. This paper takes the GRGO for an example to implement the parallelization of GRGO (Global Reduced Gravity Ocean model) with halo update. The result demonstrates that the higher speedup can be achieved at different problem size.

Color-SIFT model: a robust and an accurate shot boundary detection algorithm

Science.gov (United States)

Sharmila Kumari, M.; Shekar, B. H.

2010-02-01

In this paper, a new technique called color-SIFT model is devised for shot boundary detection. Unlike scale invariant feature transform model that uses only grayscale information and misses important visual information regarding color, here we have adopted different color planes to extract keypoints which are subsequently used to detect shot boundaries. The basic SIFT model has four stages namely scale-space peak selection, keypoint localization, orientation assignment and keypoint descriptor and all these four stages were employed to extract key descriptors in each color plane. The proposed model works on three different color planes and a fusion has been made to take a decision on number of keypoint matches for shot boundary identification and hence is different from the color global scale invariant feature transform that works on quantized images. In addition, the proposed algorithm possess invariance to linear transformation and robust to occlusion and noisy environment. Experiments have been conducted on the standard TRECVID video database to reveal the performance of the proposed model.

VIIRS Ocean Color Reprocessed Science Quality Environmental Data Record (EDR) Level 3 products from 2012-01 to the present

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains VIIRS Ocean Color Reprocessed Environmental Data Record (EDR) Level 3 products produced by the NESDIS Center for Satellite Applications and...

VIIRS Ocean Color Reprocessed Science Quality Environmental Data Record (EDR) Level 2 products from 2012-01 to the present

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains VIIRS Ocean Color Reprocessed Environmental Data Record (EDR) Level 2 products produced by the NESDIS Center for Satellite Applications and...

Marine mammal distribution in the open ocean: a comparison of ocean color data products and levant time scales

Science.gov (United States)

Ohern, J.

2016-02-01

Marine mammals are generally located in areas of enhanced surface primary productivity, though they may forage much deeper within the water column and higher on the food chain. Numerous studies over the past several decades have utilized ocean color data from remote sensing instruments (CZCS, MODIS, and others) to asses both the quantity and time scales over which surface primary productivity relates to marine mammal distribution. In areas of sustained upwelling, primary productivity may essentially grow in the secondary levels of productivity (the zooplankton and nektonic species on which marine mammals forage). However, in many open ocean habitats a simple trophic cascade does not explain relatively short time lags between enhanced surface productivity and marine mammal presence. Other dynamic features that entrain prey or attract marine mammals may be responsible for the correlations between marine mammals and ocean color. In order to investigate these features, two MODIS (moderate imaging spectroradiometer) data products, the concentration as well as the standard deviation of surface chlorophyll were used in conjunction with marine mammal sightings collected within Ecuadorian waters. Time lags between enhanced surface chlorophyll and marine mammal presence were on the order of 2-4 weeks, however correlations were much stronger when the standard deviation of spatially binned images was used, rather than the chlorophyll concentrations. Time lags also varied between Balaenopterid and Odontocete cetaceans. Overall, the standard deviation of surface chlorophyll proved a useful tool for assessing potential relationships between marine mammal sightings and surface chlorophyll.

Influence of CDOM and particle composition on ocean color of the Eastern New Caledonia Lagoon during the CALIOPE cruises

Science.gov (United States)

Dupouy, Cécile; Röttgers, Rüdiger; Tedetti, Marc; Martias, Chloe; Murakami, Hiroshi; Doxaran, David; Lantoine, Francois; Rodier, Martine; Favareto, Luciane; Kampel, Milton; Goutx, Madeleine; Frouin, Robert J.

2014-11-01

Ocean color of tropical lagoons is dependent on bathymetry and bottom type, as well as input of coastal living and mineral particles and chromophoric dissolved organic matter (CDOM). The New Caledonia lagoon lies in the Southwestern Tropical Pacific around 21° 30'S and 166° 30'E, with a great marine biodiversity in UNESCO Heritage coral reefs, benthic sea grass, and benthic communities. They are largely connected to the open ocean in the southern and eastern parts, but only by narrow passes in the southwest part. The trophic state is linked to spatial variations in flushing times. High run offs due to rain carrying abundant chromophoric dissolved organic matter (CDOM) and particle loads may greatly impact the functioning of ecosystems while rivers and sewage effluents may induce localized impacts. Two oceanographic cruises (CALIOPE 1 in 2011 and CALIOPE 2 in 2014) were carried out off the Eastern Coast of New Caledonia during a calm dry period and during high winds, respectively. Multi- and hyper-spectral marine reflectance was measured with a SIMBADA instrument and a TRIOS radiometer system, together with inherent optical properties (total and CDOM absorption coefficients with a PSICAM, in situ absorption and scattering with an AC9, backscattering with a Hydroscat-6). Fluorescence of CDOM (EEM/PARAFAC) was measured on collected 0.2 μm filtered samples. In 2014, Satlantic and FieldSpec hyper-spectral radiometers were available for in-water profiling of upwelling radiance and downwelling irradiance and above-water reflectance measurements, respectively. Inherent and apparent optical data from the two cruises are compared and used to estimate ocean color algorithms performance and evaluate a Linear Matrix Inversion method, providing tools for remote sensing on this highly under-sampled coastal region of New Caledonia.

Performance metrics for the assessment of satellite data products: an ocean color case study

Science.gov (United States)

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coeffic...

A Synthesis of Light Absorption Properties of the Arctic Ocean: Application to Semi-analytical Estimates of Dissolved Organic Carbon Concentrations from Space

Science.gov (United States)

Matsuoka, A.; Babin, M.; Doxaran, D.; Hooker, S. B.; Mitchell, B. G.; Belanger, S.; Bricaud, A.

2014-01-01

The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean [e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012], the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher 74 than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained 75 by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian 76 side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off 77 North America. In contrast, the relationship between the phytoplankton absorption (a()) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific a() values [Matsuoka et al., 2013], this result indirectly suggests that CDOM absorption can be appropriately erived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

Color Image Secret Watermarking Erase and Write Algorithm Based on SIFT

Science.gov (United States)

Qu, Jubao

The use of adaptive characteristics of SIFT, image features, the implementation of the write, erase operations on Extraction and color image hidden watermarking. From the experimental results, this algorithm has better imperceptibility and at the same time, is robust against geometric attacks and common signal processing.

Parameterization of typhoon-induced ocean cooling using temperature equation and machine learning algorithms: an example of typhoon Soulik (2013)

Science.gov (United States)

Wei, Jun; Jiang, Guo-Qing; Liu, Xin

2017-09-01

This study proposed three algorithms that can potentially be used to provide sea surface temperature (SST) conditions for typhoon prediction models. Different from traditional data assimilation approaches, which provide prescribed initial/boundary conditions, our proposed algorithms aim to resolve a flow-dependent SST feedback between growing typhoons and oceans in the future time. Two of these algorithms are based on linear temperature equations (TE-based), and the other is based on an innovative technique involving machine learning (ML-based). The algorithms are then implemented into a Weather Research and Forecasting model for the simulation of typhoon to assess their effectiveness, and the results show significant improvement in simulated storm intensities by including ocean cooling feedback. The TE-based algorithm I considers wind-induced ocean vertical mixing and upwelling processes only, and thus obtained a synoptic and relatively smooth sea surface temperature cooling. The TE-based algorithm II incorporates not only typhoon winds but also ocean information, and thus resolves more cooling features. The ML-based algorithm is based on a neural network, consisting of multiple layers of input variables and neurons, and produces the best estimate of the cooling structure, in terms of its amplitude and position. Sensitivity analysis indicated that the typhoon-induced ocean cooling is a nonlinear process involving interactions of multiple atmospheric and oceanic variables. Therefore, with an appropriate selection of input variables and neuron sizes, the ML-based algorithm appears to be more efficient in prognosing the typhoon-induced ocean cooling and in predicting typhoon intensity than those algorithms based on linear regression methods.

A synthesis of light absorption properties of the Pan-Arctic Ocean: application to semi-analytical estimates of dissolved organic carbon concentrations from space

Science.gov (United States)

Matsuoka, A.; Babin, M.; Doxaran, D.; Hooker, S. B.; Mitchell, B. G.; Bélanger, S.; Bricaud, A.

2013-11-01

The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean (e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012), the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off North America. In contrast, the relationship between the phytoplankton absorption (aφ(λ)) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific aφ(λ) values (Matsuoka et al., 2013), this result indirectly suggests that CDOM absorption can be appropriately derived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC vs. CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

Coastal Zone Color Scanner atmospheric correction algorithm - Multiple scattering effects

Science.gov (United States)

Gordon, Howard R.; Castano, Diego J.

1987-01-01

Errors due to multiple scattering which are expected to be encountered in application of the current Coastal Zone Color Scanner (CZCS) atmospheric correction algorithm are analyzed. The analysis is based on radiative transfer computations in model atmospheres, in which the aerosols and molecules are distributed vertically in an exponential manner, with most of the aerosol scattering located below the molecular scattering. A unique feature of the analysis is that it is carried out in scan coordinates rather than typical earth-sun coordinates, making it possible to determine the errors along typical CZCS scan lines. Information provided by the analysis makes it possible to judge the efficacy of the current algorithm with the current sensor and to estimate the impact of the algorithm-induced errors on a variety of applications.

A True-Color Sensor and Suitable Evaluation Algorithm for Plant Recognition.

Science.gov (United States)

Schmittmann, Oliver; Schulze Lammers, Peter

2017-08-08

Plant-specific herbicide application requires sensor systems for plant recognition and differentiation. A literature review reveals a lack of sensor systems capable of recognizing small weeds in early stages of development (in the two- or four-leaf stage) and crop plants, of making spraying decisions in real time and, in addition, are that are inexpensive and ready for practical use in sprayers. The system described in this work is based on free cascadable and programmable true-color sensors for real-time recognition and identification of individual weed and crop plants. The application of this type of sensor is suitable for municipal areas and farmland with and without crops to perform the site-specific application of herbicides. Initially, databases with reflection properties of plants, natural and artificial backgrounds were created. Crop and weed plants should be recognized by the use of mathematical algorithms and decision models based on these data. They include the characteristic color spectrum, as well as the reflectance characteristics of unvegetated areas and areas with organic material. The CIE-Lab color-space was chosen for color matching because it contains information not only about coloration (a- and b-channel), but also about luminance (L-channel), thus increasing accuracy. Four different decision making algorithms based on different parameters are explained: (i) color similarity (ΔE); (ii) color similarity split in ΔL, Δa and Δb; (iii) a virtual channel 'd' and (iv) statistical distribution of the differences of reflection backgrounds and plants. Afterwards, the detection success of the recognition system is described. Furthermore, the minimum weed/plant coverage of the measuring spot was calculated by a mathematical model. Plants with a size of 1-5% of the spot can be recognized, and weeds in the two-leaf stage can be identified with a measuring spot size of 5 cm. By choosing a decision model previously, the detection quality can be increased

FUNCTIONALITY ASSESSMENT OF ALGORITHMS FOR THE COLORING OF IMAGES IN TERMS OF INCREASING RADIOMETRIC VALUES OF AERIAL PHOTOGRAPHS ARCHIVES

Directory of Open Access Journals (Sweden)

Ewiak Ireneusz

2016-12-01

Full Text Available Available on the commercial market are a number of algorithms that enable assigning to pixels of a monochrome digital image suitable colors according to a strictly defined schedule. These algorithms have been recently used by professional film studios involved in the coloring of archival productions. This article provides an overview on the functionality of coloring algorithms in terms of their use to improve the interpretation quality of historical, black - and - white aerial photographs. The analysis covered intuitive (Recolored programs, as well as more advanced (Adobe After Effect, DaVinci Resolve programs. The use of their full functionality was limited by the too large information capacity of aerial photograph images. Black - and - white historical aerial photographs, which interpretation quality in many cases does not meet the criteria posed on photogrammetric developments, require an increase of their readability. The solution in this regard may be the process of coloring images. The authors of this article conducted studies aimed to determine to what extent the tested coloring algorithms enable an automatic detection of land cover elements on historical aerial photographs and provide color close to the natural. Used in the studies were archival black - and - white aerial photographs of the western part of Warsaw district made available by the Main Centre of Geodetic and Cartographic Documentation , the selection of which was associated with the presence in this area of various elements of land cover, such as water, forests, crops, exposed soils and also anthropogenic objects. In the analysis of different algorithms are included: format and size of the image, degree of automation of the process, degree of compliance of the result and processing time. The accuracy of the coloring process was different for each class of objects mapped on the photograph. The main limitation of the coloring process created shadows of anthropogenic objects

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

Science.gov (United States)

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-06-28

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

Remote sensing estimation of terrestrially derived colored dissolved organic matterinput to the Arctic Ocean

Science.gov (United States)

Li, J.; Yu, Q.; Tian, Y. Q.

2017-12-01

The DOC flux from land to the Arctic Ocean has remarkable implication on the carbon cycle, biogeochemical & ecological processes in the Arctic. This lateral carbon flux is required to be monitored with high spatial & temporal resolution. However, the current studies in the Arctic regions were obstructed by the factors of the low spatial coverages. The remote sensing could provide an alternative bio-optical approach to field sampling for DOC dynamics monitoring through the observation of the colored dissolved organic matter (CDOM). The DOC and CDOM were found highly correlated based on the analysis of the field sampling data from the Arctic-GRO. These provide the solid foundation of the remote sensing observation. In this study, six major Arctic Rivers (Yukon, Kolyma, Lena, Mackenzie, Ob', Yenisey) were selected to derive the CDOM dynamics along four years. Our newly developed SBOP algorithm was applied to the large Landsat-8 OLI image data (nearly 100 images) for getting the high spatial resolution results. The SBOP algorithm is the first approach developing for the Shallow Water Bio-optical properties estimation. The CDOM absorption derived from the satellite images were verified with the field sampling results with high accuracy (R2 = 0.87). The distinct CDOM dynamics were found in different Rivers. The CDOM absorptions were found highly related to the hydrological activities and the terrestrially environmental dynamics. Our study helps to build the reliable system for studying the carbon cycle at Arctic regions.

Predicting minimum uncertainties in the inversion of ocean color geophysical parameters based on Cramer-Rao bounds.

Science.gov (United States)

Jay, Sylvain; Guillaume, Mireille; Chami, Malik; Minghelli, Audrey; Deville, Yannick; Lafrance, Bruno; Serfaty, Véronique

2018-01-22

We present an analytical approach based on Cramer-Rao Bounds (CRBs) to investigate the uncertainties in estimated ocean color parameters resulting from the propagation of uncertainties in the bio-optical reflectance modeling through the inversion process. Based on given bio-optical and noise probabilistic models, CRBs can be computed efficiently for any set of ocean color parameters and any sensor configuration, directly providing the minimum estimation variance that can be possibly attained by any unbiased estimator of any targeted parameter. Here, CRBs are explicitly developed using (1) two water reflectance models corresponding to deep and shallow waters, resp., and (2) four probabilistic models describing the environmental noises observed within four Sentinel-2 MSI, HICO, Sentinel-3 OLCI and MODIS images, resp. For both deep and shallow waters, CRBs are shown to be consistent with the experimental estimation variances obtained using two published remote-sensing methods, while not requiring one to perform any inversion. CRBs are also used to investigate to what extent perfect a priori knowledge on one or several geophysical parameters can improve the estimation of remaining unknown parameters. For example, using pre-existing knowledge of bathymetry (e.g., derived from LiDAR) within the inversion is shown to greatly improve the retrieval of bottom cover for shallow waters. Finally, CRBs are shown to provide valuable information on the best estimation performances that may be achieved with the MSI, HICO, OLCI and MODIS configurations for a variety of oceanic, coastal and inland waters. CRBs are thus demonstrated to be an informative and efficient tool to characterize minimum uncertainties in inverted ocean color geophysical parameters.

Preliminary results of algorithms to determine horizontal and vertical underwater visibilities of coastal waters

Digital Repository Service at National Institute of Oceanography (India)

Suresh, T.; Joshi, Shreya; Talaulikar, M.; Desa, E.J.

the underwater average cosine. These algorithms for vertical and horizontal visibilities have been validated for the coastal waters of Goa with the measured and those derived from the ocean color data of OCM-2 and MODIS...

Application of in situ observations, high frequency radars, and ocean color, to study suspended matter, particulate carbon, and dissolved organic carbon fluxes in coastal waters of the Barents Sea - the NORDFLUX project

Science.gov (United States)

Stramska, Malgorzata; Yngve Børsheim, Knut; Białogrodzka, Jagoda; Cieszyńska, Agata; Ficek, Dariusz; Wereszka, Marzena

2016-04-01

There is still a limited knowledge about suspended and dissolved matter fluxes transported from coastal regions into the open sea regions in the Arctic. The land/sea interface is environmentally important and sensitive to climate change. Important biogeochemical material entering the oceans (including carbon) passes through this interface, but too little is known about the efficiency of this transport. Our goal in the NORDFLUX program is to improve quantitative understanding of the environmental feedbacks involved in these processes through an interdisciplinary study with innovative in situ observations. Completed work includes two in situ experiments in the Norwegian fiord (Porsangerfjorden) in the summers of 2014 and 2015. Experiments used research boat for collection of water samples and in situ bio-optical data, an autonomous glider, mooring with T S sensors, and a high frequency radar system. We have used these data to derive spatial maps of water temperature, salinity, surface currents, chlorophyll fluorescence, dissolved organic matter (DOM) fluorescence, and inherent optical properties (IOPs) of the water. The interpretation of these data in terms of suspended matter concentration and composition is possible by in situ 'calibrations' using water samples from discrete hydrographic stations. Total suspended matter (TSM), particulate carbon (POC and PIC), and dissolved organic carbon (DOC) concentrations together with measured water currents will allow us to estimate reservoirs and fluxes. Concentrations and fluxes will be related to physical conditions and meteorological data. An important aspect of this project is the work on regional ocean color algorithms. Global ocean color (OC) algorithms currently used by NASA do not perform sufficiently well in coastal Case 2 waters. Our data sets will allow us to derive such local algorithms. We will then use these algorithms for interpretation of OC data in terms of TSM concentrations and composition and DOC. After

Spatially Resolving Ocean Color and Sediment Dispersion in River Plumes, Coastal Systems, and Continental Shelf Waters

Science.gov (United States)

Aurin, Dirk Alexander; Mannino, Antonio; Franz, Bryan

2013-01-01

Satellite remote sensing of ocean color in dynamic coastal, inland, and nearshorewaters is impeded by high variability in optical constituents, demands specialized atmospheric correction, and is limited by instrument sensitivity. To accurately detect dispersion of bio-optical properties, remote sensors require ample signal-to-noise ratio (SNR) to sense small variations in ocean color without saturating over bright pixels, an atmospheric correction that can accommodate significantwater-leaving radiance in the near infrared (NIR), and spatial and temporal resolution that coincides with the scales of variability in the environment. Several current and historic space-borne sensors have met these requirements with success in the open ocean, but are not optimized for highly red-reflective and heterogeneous waters such as those found near river outflows or in the presence of sediment resuspension. Here we apply analytical approaches for determining optimal spatial resolution, dominant spatial scales of variability ("patches"), and proportions of patch variability that can be resolved from four river plumes around the world between 2008 and 2011. An offshore region in the Sargasso Sea is analyzed for comparison. A method is presented for processing Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra imagery including cloud detection, stray lightmasking, faulty detector avoidance, and dynamic aerosol correction using short-wave- and near-infrared wavebands in extremely turbid regions which pose distinct optical and technical challenges. Results showthat a pixel size of approx. 520 mor smaller is generally required to resolve spatial heterogeneity in ocean color and total suspended materials in river plumes. Optimal pixel size increases with distance from shore to approx. 630 m in nearshore regions, approx 750 m on the continental shelf, and approx. 1350 m in the open ocean. Greater than 90% of the optical variability within plume regions is resolvable with

Characteristic vector analysis of inflection ratio spectra: New technique for analysis of ocean color data

Science.gov (United States)

Grew, G. W.

1985-01-01

Characteristic vector analysis applied to inflection ratio spectra is a new approach to analyzing spectral data. The technique applied to remote data collected with the multichannel ocean color sensor (MOCS), a passive sensor, simultaneously maps the distribution of two different phytopigments, chlorophyll alpha and phycoerythrin, the ocean. The data set presented is from a series of warm core ring missions conducted during 1982. The data compare favorably with a theoretical model and with data collected on the same mission by an active sensor, the airborne oceanographic lidar (AOL).

Coastal Zone Color Scanner

Science.gov (United States)

Johnson, B.

1988-01-01

The Coastal Zone Color Scanner (CZCS) spacecraft ocean color instrument is capable of measuring and mapping global ocean surface chlorophyll concentration. It is a scanning radiometer with multiband capability. With new electronics and some mechanical, and optical re-work, it probably can be made flight worthy. Some additional components of a second flight model are also available. An engineering study and further tests are necessary to determine exactly what effort is required to properly prepare the instrument for spaceflight and the nature of interfaces to prospective spacecraft. The CZCS provides operational instrument capability for monitoring of ocean productivity and currents. It could be a simple, low cost alternative to developing new instruments for ocean color imaging. Researchers have determined that with global ocean color data they can: specify quantitatively the role of oceans in the global carbon cycle and other major biogeochemical cycles; determine the magnitude and variability of annual primary production by marine phytoplankton on a global scale; understand the fate of fluvial nutrients and their possible affect on carbon budgets; elucidate the coupling mechanism between upwelling and large scale patterns in ocean basins; answer questions concerning the large scale distribution and timing of spring blooms in the global ocean; acquire a better understanding of the processes associated with mixing along the edge of eddies, coastal currents, western boundary currents, etc., and acquire global data on marine optical properties.

Ocean color remote sensing using polarization properties of reflected sunlight

Science.gov (United States)

Frouin, R.; Pouliquen, E.; Breon, F.-M.

1994-01-01

The effects of the atmosphere and surface on sunlight backscattered to space by the ocean may be substantially reduced by using the unpolarized component of reflectance instead of total reflectance. At 450 nm, a wavelength of interest in ocean color remote sensing, and for typical conditions, 45% of the unpolarized reflectance may originate from the water body instead of 20% of the total reflectance, which represents a gain of a factor 2.2 in useful signal for water composition retrieval. The best viewing geometries are adjacent to the glitter region; they correspond to scattering angles around 100 deg, but they may change slightly depending on the polarization characteristics of the aerosols. As aerosol optical thickness increases, the atmosphere becomes less efficient at polarizing sunlight, and the enhancement of the water body contribution to unpolarized reflectance is reduced. Since the perturbing effects are smaller on unpolarized reflectance, at least for some viewing geometries, they may be more easily corrected, leading to a more accurate water-leaving signal and, therefore, more accurate estimates of phytoplankton pigment concentration.

Shedding light on the Global Ocean microbiome with algorithms and data collection

Science.gov (United States)

Lauro, F.; Ostrowski, M.; Chénard, C.; Acerbi, E.; Paulsen, I.; Jensen, R.

2016-02-01

In the Global Oceans, the marine microbiome plays a critical role in biogeochemical cycling of nutrients, but surveying marine microbial communities requires ship time for sample collection, economically constraining the number of samples collected. An integrative understanding of the microbiome's activity and performance requires the collection of high-density data, both temporally and spatially in a cost-effective way. We have overcome this bottleneck by crowdsourcing the data collection to vessels of opportunity, including bluewater sailing yachts. Sailors know the oceans, and experience first-hand the declines in ocean productivity and the effects of pollution and climate change. Moreover, simply the ability to sample a microbial community during anomalous or inclement weather conditions is a major advance in sampling strategy. Our approach inherently incorporates the benefit of outreach and participation of people in scientific research, gaining positive media attention for sailors, scientists and concerned citizens alike. We have tested the basic methods during a 2013 Indian Ocean Concept Cruise, from Cape Town to Singapore, performing experimental work and reaching sampling locations inaccessible to traditional Oceanographic Vessels. At the same time we developed a small, yacht-adapted automated sampling device that takes a variety of biological and chemical measurements. In 2015 our first beta-cruisers sampled the Pacific Ocean in the first ever citizen-oceanography transect at high and low latitudes in both hemispheres. The collected samples were characterized with next-gen sequencing technology and analysed with a combination of novel algorithmic approaches. With big data management, machine learning algorithms and agent-based models we show that it is possible to deconvolute the complexity of the Ocean Microbiome for the scientific management of fisheries, marine protected areas and preservation of the oceans and seas for generations to come.

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

Science.gov (United States)

Palacios, Sherry L.; Schafer, Chris; Broughton, Jennifer; Guild, Liane S.; Kudela, Raphael M.

2013-01-01

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in

CDOM-DOC relationship in contrasted coastal waters : implication for DOC retrieval from ocean color remote sensing observation

OpenAIRE

Vantrepotte, V.; Danhiez, F. P.; Loisel, Hubert; Ouillon, Sylvain; Meriaux, X.; Cauvin, A.; Dessailly, D.

2015-01-01

Increasing our knowledge on dissolved organic carbon (DOC) spatio-temporal distribution in the coastal ocean represents a crucial challenge for better understanding the role of these ecosystems in the global oceanic carbon cycle. The assessment of DOC concentration from the absorption properties of the colored part of the dissolved organic matter (a(cdom)) was investigated from an extensive data set covering a variety of coastal environments. Our results confirmed that variation in the acdom(...

Phytoplankton phenology indices in coral reef ecosystems: Application to ocean-color observations in the Red Sea

KAUST Repository

Racault, Marie-Fanny

2015-02-18

Phytoplankton, at the base of the marine food web, represent a fundamental food source in coral reef ecosystems. The timing (phenology) and magnitude of the phytoplankton biomass are major determinants of trophic interactions. The Red Sea is one of the warmest and most saline basins in the world, characterized by an arid tropical climate regulated by the monsoon. These extreme conditions are particularly challenging for marine life. Phytoplankton phenological indices provide objective and quantitative metrics to characterize phytoplankton seasonality. The indices i.e. timings of initiation, peak, termination and duration are estimated here using 15 years (1997–2012) of remote sensing ocean-color data from the European Space Agency (ESA) Climate Change Initiative project (OC-CCI) in the entire Red Sea basin. The OC-CCI product, comprising merged and bias-corrected observations from three independent ocean-color sensors (SeaWiFS, MODIS and MERIS), and processed using the POLYMER algorithm (MERIS period), shows a significant increase in chlorophyll data coverage, especially in the southern Red Sea during the months of summer NW monsoon. In open and reef-bound coastal waters, the performance of OC-CCI chlorophyll data is shown to be comparable with the performance of other standard chlorophyll products for the global oceans. These features have permitted us to investigate phytoplankton phenology in the entire Red Sea basin, and during both winter SE monsoon and summer NW monsoon periods. The phenological indices are estimated in the four open water provinces of the basin, and further examined at six coral reef complexes of particular socio-economic importance in the Red Sea, including Siyal Islands, Sharm El Sheikh, Al Wajh bank, Thuwal reefs, Al Lith reefs and Farasan Islands. Most of the open and deeper waters of the basin show an apparent higher chlorophyll concentration and longer duration of phytoplankton growth during the winter period (relative to the summer

A fast color image enhancement algorithm based on Max Intensity Channel

Science.gov (United States)

Sun, Wei; Han, Long; Guo, Baolong; Jia, Wenyan; Sun, Mingui

2014-03-01

In this paper, we extend image enhancement techniques based on the retinex theory imitating human visual perception of scenes containing high illumination variations. This extension achieves simultaneous dynamic range modification, color consistency, and lightness rendition without multi-scale Gaussian filtering which has a certain halo effect. The reflection component is analyzed based on the illumination and reflection imaging model. A new prior named Max Intensity Channel (MIC) is implemented assuming that the reflections of some points in the scene are very high in at least one color channel. Using this prior, the illumination of the scene is obtained directly by performing a gray-scale closing operation and a fast cross-bilateral filtering on the MIC of the input color image. Consequently, the reflection component of each RGB color channel can be determined from the illumination and reflection imaging model. The proposed algorithm estimates the illumination component which is relatively smooth and maintains the edge details in different regions. A satisfactory color rendition is achieved for a class of images that do not satisfy the gray-world assumption implicit to the theoretical foundation of the retinex. Experiments are carried out to compare the new method with several spatial and transform domain methods. Our results indicate that the new method is superior in enhancement applications, improves computation speed, and performs well for images with high illumination variations than other methods. Further comparisons of images from National Aeronautics and Space Administration and a wearable camera eButton have shown a high performance of the new method with better color restoration and preservation of image details.

A Deep Learning Algorithm of Neural Network for the Parameterization of Typhoon-Ocean Feedback in Typhoon Forecast Models

Science.gov (United States)

Jiang, Guo-Qing; Xu, Jing; Wei, Jun

2018-04-01

Two algorithms based on machine learning neural networks are proposed—the shallow learning (S-L) and deep learning (D-L) algorithms—that can potentially be used in atmosphere-only typhoon forecast models to provide flow-dependent typhoon-induced sea surface temperature cooling (SSTC) for improving typhoon predictions. The major challenge of existing SSTC algorithms in forecast models is how to accurately predict SSTC induced by an upcoming typhoon, which requires information not only from historical data but more importantly also from the target typhoon itself. The S-L algorithm composes of a single layer of neurons with mixed atmospheric and oceanic factors. Such a structure is found to be unable to represent correctly the physical typhoon-ocean interaction. It tends to produce an unstable SSTC distribution, for which any perturbations may lead to changes in both SSTC pattern and strength. The D-L algorithm extends the neural network to a 4 × 5 neuron matrix with atmospheric and oceanic factors being separated in different layers of neurons, so that the machine learning can determine the roles of atmospheric and oceanic factors in shaping the SSTC. Therefore, it produces a stable crescent-shaped SSTC distribution, with its large-scale pattern determined mainly by atmospheric factors (e.g., winds) and small-scale features by oceanic factors (e.g., eddies). Sensitivity experiments reveal that the D-L algorithms improve maximum wind intensity errors by 60-70% for four case study simulations, compared to their atmosphere-only model runs.

Specificity of Atmosphere Correction of Satellite Ocean Color Data in Far-Eastern Region

Science.gov (United States)

Trusenkova, O.; Kachur, V.; Aleksanin, A. I.

2016-02-01

It was carried out an error analysis of satellite reflectance coefficients (Rrs) of MODIS/AQUA colour data for two atmospheric correction algorithms (NIR, MUMM) in the Far-Eastern region. Some sets of unique data of in situ and satellite measurements have been analysed. A set has some measurements with ASD spectroradiometer for each satellite pass. The measurement allocations were selected so the Chlorophyll-a concentration has high variability. Analysis of arbitrary set demonstrated that the main error component is systematic error, and it has simple relations on Rrs values. The reasons of such error behavior are considered. The most probable explanation of the large errors of oceanic color parameters in the Far-Eastern region is the ability of high concentrations of continental aerosol. A comparison of satellite and in situ measurements at AERONET stations of USA and South Korea regions has been made. It was shown that for NIR-correction of the atmosphere influence the error values in these two regions have differences up to 10 times for almost the same water turbidity and relatively good accuracy of computation of aerosol optical thickness. The study was supported by grant Russian Scientific Foundation No. 14-50-00034, by grant of Russian Foundation of Basic Research No.15-35-21032-mol-a-ved, and by Program of Basic Research "Far East" of Far Eastern Branch of Russian Academy of Sciences.

Illuminant color estimation based on pigmentation separation from human skin color

Science.gov (United States)

Tanaka, Satomi; Kakinuma, Akihiro; Kamijo, Naohiro; Takahashi, Hiroshi; Tsumura, Norimichi

2015-03-01

Human has the visual system called "color constancy" that maintains the perceptive colors of same object across various light sources. The effective method of color constancy algorithm was proposed to use the human facial color in a digital color image, however, this method has wrong estimation results by the difference of individual facial colors. In this paper, we present the novel color constancy algorithm based on skin color analysis. The skin color analysis is the method to separate the skin color into the components of melanin, hemoglobin and shading. We use the stationary property of Japanese facial color, and this property is calculated from the components of melanin and hemoglobin. As a result, we achieve to propose the method to use subject's facial color in image and not depend on the individual difference among Japanese facial color.

Coastal Zone Color Scanner (CZCS): Imagery of near-surface phytoplankton pigment concentrations from the first coastal ocean dynamics experiment (CODE-1), March - July 1981

Science.gov (United States)

Abbott, M. R.; Zion, P. M.

1984-01-01

As part of the first Coastal Ocean Dynamics Experiment, images of ocean color were collected from late March until late July, 1981, by the Coastal Zone Color Scanner aboard Nimbus-7. Images that had sufficient cloud-free area to be of interest were processed to yield near-surface phytoplankton pigment concentrations. These images were then remapped to a fixed equal-area grid. This report contains photographs of the digital images and a brief description of the processing methods.

Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea

Directory of Open Access Journals (Sweden)

Anne-Hélène Rêve-Lamarche

2017-12-01

Full Text Available Over the past years, a large number of new approaches in the domain of ocean-color have been developed, leading to a variety of innovative descriptors for phytoplankton communities. One of these methods, named PHYSAT, currently allows for the qualitative detection of five main phytoplankton groups from ocean-color measurements. Even though PHYSAT products are widely used in various applications and projects, the approach is limited by the fact it identifies only dominant phytoplankton groups. This current limitation is due to the use of biomarker pigment ratios for establishing empirical relationships between in-situ information and specific ocean-color radiance anomalies in open ocean waters. However, theoretical explanations of PHYSAT suggests that it could be possible to detect more than dominance cases but move more toward phytoplanktonic assemblage detection. Thus, to evaluate the potential of PHYSAT for the detection of phytoplankton assemblages, we took advantage of the Continuous Plankton Recorder (CPR survey, collected in both the English Channel and the North Sea. The available CPR dataset contains information on diatom abundance in two large areas of the North Sea for the period 1998-2010. Using this unique dataset, recurrent diatom assemblages were retrieved based on classification of CPR samples. Six diatom assemblages were identified in-situ, each having indicators taxa or species. Once this first step was completed, the in-situ analysis was used to empirically associate the diatom assemblages with specific PHYSAT spectral anomalies. This step was facilitated by the use of previous classifications of regional radiance anomalies in terms of shape and amplitude, coupled with phenological tools. Through a matchup exercise, three CPR assemblages were associated with specific radiance anomalies. The maps of detection of these specific radiances anomalies are in close agreement with current in-situ ecological knowledge.

Empirical algorithm to estimate the average cosine of underwater light field at 490 nm

Digital Repository Service at National Institute of Oceanography (India)

Talaulikar, M.; Suresh, T.; Desa, E.; Matondkar, S.G.P.; Kumar, T.S.; Lotliker, A.; Inamdar, A.

optical properties from water color, a multi-band quasi-analytical algorithm for optically deep waters. Applied Optic, 41, pp. 5755– 5772. MCCORMIC, N. J., 1995, Mathematical models for the mean cosine of irradiance and the diffuse attenuation... parameter to determine μ(490) from the measured data and from the ocean color satellite data is discussed. Absorption coefficients of water derived using μ(490) were also evaluated comparing with the synthetic data and in-situ measured data from other...

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Revised

Science.gov (United States)

Fargion, Giulietta S.; Mueller, James L.

2000-01-01

The document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. This document supersedes the earlier version (Mueller and Austin 1995) published as Volume 25 in the SeaWiFS Technical Report Series. This document marks a significant departure from, and improvement on, theformat and content of Mueller and Austin (1995). The authorship of the protocols has been greatly broadened to include experts specializing in some key areas. New chapters have been added to provide detailed and comprehensive protocols for stability monitoring of radiometers using portable sources, abovewater measurements of remote-sensing reflectance, spectral absorption measurements for discrete water samples, HPLC pigment analysis and fluorometric pigment analysis. Protocols were included in Mueller and Austin (1995) for each of these areas, but the new treatment makes significant advances in each topic area. There are also new chapters prescribing protocols for calibration of sun photometers and sky radiance sensors, sun photometer and sky radiance measurements and analysis, and data archival. These topic areas were barely mentioned in Mueller and Austin (1995).

完全图的点可区别强全染色算法%Strong Vertex-distinguishing Total Coloring Algorithm of Complete Graph

Institute of Scientific and Technical Information of China (English)

赵焕平; 刘平; 李敬文

2012-01-01

According to the definition of strong vertex-distinguishing total coloring, this paper combines with the symmetry of complete graph, proposes a new strong vertex-distinguishing total coloring algorithm. The algorithm divides the filled colors into two parts: overcolor and propercolor. At the premise of getting the coloring number and the coloring frequency, it uses colored at first to enhance its convergence. Experimental results show that this algorithm has a lower time complexity.%根据图的点可区别全染色的定义,结合完全图的对称性,提出一种新的点可区别强全染色算法.该算法将需要填充的颜色分为超色数和正常色数2个部分,在得到染色数量和染色次数的前提下,对超色数进行染色以增强算法收敛性.实验结果表明,该算法具有较低的时间复杂度.

GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 Campaign

Science.gov (United States)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.;

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

Science.gov (United States)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.; Song, Chul H.; Lim, Jae-Hyun; Song, Chang-Keun

2016-04-01

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better

Variability in global ocean phytoplankton distribution over 1979-2007

Science.gov (United States)

Masotti, I.; Alvain, S.; Moulin, C.; Antoine, D.

2009-04-01

Recently, reanalysis of long-term ocean color data (CZCS and SeaWiFS; Antoine et al., 2005) has shown that world ocean average phytoplankton chlorophyll levels show an increase of 20% over the last two decades. It is however unknown whether this increase is associated with a change in the distribution of phytoplankton groups or if it simply corresponds to an increase of the productivity. Within the framework of the GLOBPHY project, the distribution of the phytoplankton groups was monitored by applying the PHYSAT method (Alvain et al., 2005) to the historical ocean color data series from CZCS, OCTS and SeaWiFS sensors. The PHYSAT algorithm allows identification of several phytoplankton, like nanoeucaryotes, prochlorococcus, synechococcus and diatoms. Because both sensors (OCTS-SeaWiFS) are very similar, OCTS data were processed with the standard PHYSAT algorithm to cover the 1996-1997 period during which a large El Niño event occurred, just before the SeaWiFS era. Our analysis of this dataset (1996-2006) evidences a strong variability in the distribution of phytoplankton groups at both regional and global scales. In the equatorial region (0°-5°S), a three-fold increase of nanoeucaryotes frequency was detected in opposition to a two-fold decrease of synechococcus during the early stages of El Niño conditions (May-June 1997, OCTS). The impact of this El Niño is however not confined to the Equatorial Pacific and has affected the global ocean. The processing of CZCS data with PHYSAT has required several adaptations of this algorithm due to the lower performances and the reduced number of spectral bands of the sensor. Despites higher uncertainties, the phytoplankton groups distribution obtained with CZCS is globally consistent with that of SeaWiFS. A comparison of variability in global phytoplankton distribution between 1979-1982 (CZCS) and 1999-2002 (SeaWiFS) suggests an increase in nanoeucaryotes at high latitudes (>40°) and in the equatorial region (10°S-10�

Assimilation of satellite color observations in a coupled ocean GCM-ecosystem model

Science.gov (United States)

Sarmiento, Jorge L.

1992-01-01

Monthly average coastal zone color scanner (CZCS) estimates of chlorophyll concentration were assimilated into an ocean global circulation model(GCM) containing a simple model of the pelagic ecosystem. The assimilation was performed in the simplest possible manner, to allow the assessment of whether there were major problems with the ecosystem model or with the assimilation procedure. The current ecosystem model performed well in some regions, but failed in others to assimilate chlorophyll estimates without disrupting important ecosystem properties. This experiment gave insight into those properties of the ecosystem model that must be changed to allow data assimilation to be generally successful, while raising other important issues about the assimilation procedure.

A Machine-Learning Algorithm Toward Color Analysis for Chronic Liver Disease Classification, Employing Ultrasound Shear Wave Elastography.

Science.gov (United States)

Gatos, Ilias; Tsantis, Stavros; Spiliopoulos, Stavros; Karnabatidis, Dimitris; Theotokas, Ioannis; Zoumpoulis, Pavlos; Loupas, Thanasis; Hazle, John D; Kagadis, George C

2017-09-01

The purpose of the present study was to employ a computer-aided diagnosis system that classifies chronic liver disease (CLD) using ultrasound shear wave elastography (SWE) imaging, with a stiffness value-clustering and machine-learning algorithm. A clinical data set of 126 patients (56 healthy controls, 70 with CLD) was analyzed. First, an RGB-to-stiffness inverse mapping technique was employed. A five-cluster segmentation was then performed associating corresponding different-color regions with certain stiffness value ranges acquired from the SWE manufacturer-provided color bar. Subsequently, 35 features (7 for each cluster), indicative of physical characteristics existing within the SWE image, were extracted. A stepwise regression analysis toward feature reduction was used to derive a reduced feature subset that was fed into the support vector machine classification algorithm to classify CLD from healthy cases. The highest accuracy in classification of healthy to CLD subject discrimination from the support vector machine model was 87.3% with sensitivity and specificity values of 93.5% and 81.2%, respectively. Receiver operating characteristic curve analysis gave an area under the curve value of 0.87 (confidence interval: 0.77-0.92). A machine-learning algorithm that quantifies color information in terms of stiffness values from SWE images and discriminates CLD from healthy cases is introduced. New objective parameters and criteria for CLD diagnosis employing SWE images provided by the present study can be considered an important step toward color-based interpretation, and could assist radiologists' diagnostic performance on a daily basis after being installed in a PC and employed retrospectively, immediately after the examination. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Automated ocean color product validation for the Southern California Bight

Science.gov (United States)

Davis, Curtiss O.; Tufillaro, Nicholas; Jones, Burt; Arnone, Robert

2012-06-01

Automated match ups allow us to maintain and improve the products of current satellite ocean color sensors (MODIS, MERIS), and new sensors (VIIRS). As part of the VIIRS mission preparation, we have created a web based automated match up tool that provides access to searchable fields for date, site, and products, and creates match-ups between satellite (MODIS, MERIS, VIIRS), and in-situ measurements (HyperPRO and SeaPRISM). The back end of the system is a 'mySQL' database, and the front end is a `php' web portal with pull down menus for searchable fields. Based on selections, graphics are generated showing match-ups and statistics, and ascii files are created for downloads for the matchup data. Examples are shown for matching the satellite data with the data from Platform Eureka SeaPRISM off L.A. Harbor in the Southern California Bight.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

Science.gov (United States)

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

SeaWinds - Oceans, Land, Polar Regions

Science.gov (United States)

1999-01-01

The SeaWinds scatterometer on the QuikScat satellite makes global radar measurements -- day and night, in clear sky and through clouds. The radar data over the oceans provide scientists and weather forecasters with information on surface wind speed and direction. Scientists also use the radar measurements directly to learn about changes in vegetation and ice extent over land and polar regions.This false-color image is based entirely on SeaWinds measurements obtained over oceans, land, and polar regions. Over the ocean, colors indicate wind speed with orange as the fastest wind speeds and blue as the slowest. White streamlines indicate the wind direction. The ocean winds in this image were measured by SeaWinds on September 20, 1999. The large storm in the Atlantic off the coast of Florida is Hurricane Gert. Tropical storm Harvey is evident as a high wind region in the Gulf of Mexico, while farther west in the Pacific is tropical storm Hilary. An extensive storm is also present in the South Atlantic Ocean near Antarctica.The land image was made from four days of SeaWinds data with the aid of a resolution enhancement algorithm developed by Dr. David Long at Brigham Young University. The lightest green areas correspond to the highest radar backscatter. Note the bright Amazon and Congo rainforests compared to the dark Sahara desert. The Amazon River is visible as a dark line running horizontally though the bright South American rain forest. Cities appear as bright spots on the images, especially in the U.S. and Europe.The image of Greenland and the north polar ice cap was generated from data acquired by SeaWinds on a single day. In the polar region portion of the image, white corresponds to the largest radar return, while purple is the lowest. The variations in color in Greenland and the polar ice cap reveal information about the ice and snow conditions present.NASA's Earth Science Enterprise is a long-term research and technology program designed to examine Earth

The Potential of Autonomous Ship-Borne Hyperspectral Radiometers for the Validation of Ocean Color Radiometry Data

Directory of Open Access Journals (Sweden)

Vittorio E. Brando

2016-02-01

Full Text Available Calibration and validation of satellite observations are essential and on-going tasks to ensure compliance with mission accuracy requirements. An automated above water hyperspectral radiometer significantly augmented Australia’s ability to contribute to global and regional ocean color validation and algorithm design activities. The hyperspectral data can be re-sampled for comparison with current and future sensor wavebands. The continuous spectral acquisition along the ship track enables spatial resampling to match satellite footprint. This study reports spectral comparisons of the radiometer data with Visible Infrared Imaging Radiometer Suite (VIIRS and Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua for contrasting water types in tropical waters off northern Australia based on the standard NIR atmospheric correction implemented in SeaDAS. Consistent match-ups are shown for transects of up to 50 km over a range of reflectance values. The MODIS and VIIRS satellite reflectance data consistently underestimated the in situ spectra in the blue with a bias relative to the “dynamic above water radiance and irradiance collector” (DALEC at 443 nm ranging from 9.8 × 10−4 to 3.1 × 10−3 sr−1. Automated acquisition has produced good quality data under standard operating and maintenance procedures. A sensitivity analysis explored the effects of some assumptions in the data reduction methods, indicating the need for a comprehensive investigation and quantification of each source of uncertainty in the estimate of the DALEC reflectances. Deployment on a Research Vessel provides the potential for the radiometric data to be combined with other sampling and observational activities to contribute to algorithm development in the wider bio-optical research community.

Arctic-COLORS (Coastal Land Ocean Interactions in the Arctic) - a NASA field campaign scoping study to examine land-ocean interactions in the Arctic

Science.gov (United States)

Hernes, P.; Tzortziou, M.; Salisbury, J.; Mannino, A.; Matrai, P.; Friedrichs, M. A.; Del Castillo, C. E.

2014-12-01

The Arctic region is warming faster than anywhere else on the planet, triggering rapid social and economic changes and impacting both terrestrial and marine ecosystems. Yet our understanding of critical processes and interactions along the Arctic land-ocean interface is limited. Arctic-COLORS is a Field Campaign Scoping Study funded by NASA's Ocean Biology and Biogeochemistry Program that aims to improve understanding and prediction of land-ocean interactions in a rapidly changing Arctic coastal zone, and assess vulnerability, response, feedbacks and resilience of coastal ecosystems, communities and natural resources to current and future pressures. Specific science objectives include: - Quantify lateral fluxes to the arctic inner shelf from (i) rivers and (ii) the outer shelf/basin that affect biology, biodiversity, biogeochemistry (i.e. organic matter, nutrients, suspended sediment), and the processing rates of these constituents in coastal waters. - Evaluate the impact of the thawing of Arctic permafrost within the river basins on coastal biology, biodiversity and biogeochemistry, including various rates of community production and the role these may play in the health of regional economies. - Assess the impact of changing Arctic landfast ice and coastal sea ice dynamics. - Establish a baseline for comparison to future change, and use state-of-the-art models to assess impacts of environmental change on coastal biology, biodiversity and biogeochemistry. A key component of Arctic-COLORS will be the integration of satellite and field observations with coupled physical-biogeochemical models for predicting impacts of future pressures on Arctic, coastal ocean, biological processes and biogeochemical cycles. Through interagency and international collaborations, and through the organization of dedicated workshops, town hall meetings and presentations at international conferences, the scoping study engages the broader scientific community and invites participation of

Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

Directory of Open Access Journals (Sweden)

Behnam Barzegar

2012-01-01

Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.

Color constancy by characterization of illumination chromaticity

Science.gov (United States)

Nikkanen, Jarno T.

2011-05-01

Computational color constancy algorithms play a key role in achieving desired color reproduction in digital cameras. Failure to estimate illumination chromaticity correctly will result in invalid overall colour cast in the image that will be easily detected by human observers. A new algorithm is presented for computational color constancy. Low computational complexity and low memory requirement make the algorithm suitable for resource-limited camera devices, such as consumer digital cameras and camera phones. Operation of the algorithm relies on characterization of the range of possible illumination chromaticities in terms of camera sensor response. The fact that only illumination chromaticity is characterized instead of the full color gamut, for example, increases robustness against variations in sensor characteristics and against failure of diagonal model of illumination change. Multiple databases are used in order to demonstrate the good performance of the algorithm in comparison to the state-of-the-art color constancy algorithms.

Diurnal variability in carbon and nitrogen pools within Chesapeake Bay and northern Gulf of Mexico: implications for future ocean color satellite sensors

Science.gov (United States)

Mannino, A.; Novak, M. G.; Tzortziou, M.; Salisbury, J.

2016-02-01

Relative to their areal extent, estuaries and coastal ocean ecosystems contribute disproportionately more to global biogeochemical cycling of carbon, nitrogen and other elements compared to the open ocean. Applying ocean color satellite data to study biological and biogeochemical processes within coastal ecosystems is challenging due to the complex mixtures of aquatic constituents derived from terrestrial, anthropogenic, and marine sources, human-impacted atmospheric properties, presence of clouds during satellite overpass, fine-scale spatial gradients, and time-varying processes on diurnal scales that cannot be resolved with current sensors. On diurnal scales, biological, photochemical, and biogeochemical processes are regulated by the variation in solar radiation. Other physical factors, such as tides, river discharge, estuarine and coastal ocean circulation, wind-driven mixing, etc., impart further variability on biological and biogeochemical processes on diurnal to multi-day time scales. Efforts to determine the temporal frequency required from a NASA GEO-CAPE ocean color satellite sensor to discern diurnal variability C and N stocks, fluxes and productivity culminated in field campaigns in the Chesapeake Bay and northern Gulf of Mexico. Near-surface drogues were released and tracked in quasi-lagrangian space to monitor hourly changes in community production, C and N stocks, and optical properties. While only small diurnal changes were observed in dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM) absorption in Chesapeake Bay, substantial variation in particulate organic carbon (POC) and nitrogen (PN), chlorophyll-a, and inorganic nitrogen (DIN) were measured. Similar or greater diurnal changes in POC, PN, chlorophyll-a and DIN were found in Gulf of Mexico nearshore and offshore sites. These results suggest that satellite observations at hourly frequency are desirable to capture diurnal variability in carbon and nitrogen stocks, fluxes

Infuence of Averaging Method on the Evaluation of a Coastal Ocean Color Event on the U.S. Northeast Coast

Science.gov (United States)

Acker, James G.; Uz, Stephanie Schollaert; Shen, Suhung; Leptoukh, Gregory G.

2010-01-01

Application of appropriate spatial averaging techniques is crucial to correct evaluation of ocean color radiometric data, due to the common log-normal or mixed log-normal distribution of these data. Averaging method is particularly crucial for data acquired in coastal regions. The effect of averaging method was markedly demonstrated for a precipitation-driven event on the U.S. Northeast coast in October-November 2005, which resulted in export of high concentrations of riverine colored dissolved organic matter (CDOM) to New York and New Jersey coastal waters over a period of several days. Use of the arithmetic mean averaging method created an inaccurate representation of the magnitude of this event in SeaWiFS global mapped chl a data, causing it to be visualized as a very large chl a anomaly. The apparent chl a anomaly was enhanced by the known incomplete discrimination of CDOM and phytoplankton chlorophyll in SeaWiFS data; other data sources enable an improved characterization. Analysis using the geometric mean averaging method did not indicate this event to be statistically anomalous. Our results predicate the necessity of providing the geometric mean averaging method for ocean color radiometric data in the Goddard Earth Sciences DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni).

An objective algorithm for reconstructing the three-dimensional ocean temperature field based on Argo profiles and SST data

Science.gov (United States)

Zhou, Chaojie; Ding, Xiaohua; Zhang, Jie; Yang, Jungang; Ma, Qiang

2017-12-01

While global oceanic surface information with large-scale, real-time, high-resolution data is collected by satellite remote sensing instrumentation, three-dimensional (3D) observations are usually obtained from in situ measurements, but with minimal coverage and spatial resolution. To meet the needs of 3D ocean investigations, we have developed a new algorithm to reconstruct the 3D ocean temperature field based on the Array for Real-time Geostrophic Oceanography (Argo) profiles and sea surface temperature (SST) data. The Argo temperature profiles are first optimally fitted to generate a series of temperature functions of depth, with the vertical temperature structure represented continuously. By calculating the derivatives of the fitted functions, the calculation of the vertical temperature gradient of the Argo profiles at an arbitrary depth is accomplished. A gridded 3D temperature gradient field is then found by applying inverse distance weighting interpolation in the horizontal direction. Combined with the processed SST, the 3D temperature field reconstruction is realized below the surface using the gridded temperature gradient. Finally, to confirm the effectiveness of the algorithm, an experiment in the Pacific Ocean south of Japan is conducted, for which a 3D temperature field is generated. Compared with other similar gridded products, the reconstructed 3D temperature field derived by the proposed algorithm achieves satisfactory accuracy, with correlation coefficients of 0.99 obtained, including a higher spatial resolution (0.25° × 0.25°), resulting in the capture of smaller-scale characteristics. Finally, both the accuracy and the superiority of the algorithm are validated.

Towards representation of a perceptual color manifold using associative memory for color constancy.

Science.gov (United States)

Seow, Ming-Jung; Asari, Vijayan K

2009-01-01

In this paper, we propose the concept of a manifold of color perception through empirical observation that the center-surround properties of images in a perceptually similar environment define a manifold in the high dimensional space. Such a manifold representation can be learned using a novel recurrent neural network based learning algorithm. Unlike the conventional recurrent neural network model in which the memory is stored in an attractive fixed point at discrete locations in the state space, the dynamics of the proposed learning algorithm represent memory as a nonlinear line of attraction. The region of convergence around the nonlinear line is defined by the statistical characteristics of the training data. This learned manifold can then be used as a basis for color correction of the images having different color perception to the learned color perception. Experimental results show that the proposed recurrent neural network learning algorithm is capable of color balance the lighting variations in images captured in different environments successfully.

Microradiometers Reveal Ocean Health, Climate Change

Science.gov (United States)

2013-01-01

When NASA researcher Stanford Hooker is in the field, he pays close attention to color. For Hooker, being in the field means being at sea. On one such research trip to the frigid waters of the Arctic, with a Coast Guard icebreaker looming nearby and the snow-crusted ice shelf a few feet away, Hooker leaned over the edge of his small boat and lowered a tethered device into the bright turquoise water, a new product devised by a NASA partner and enabled by a promising technology for oceanographers and atmospheric scientists alike. Color is a function of light. Pure water is clear, but the variation in color observed during a visit to the beach or a flight along a coastline depends on the water s depth and the constituents in it, how far down the light penetrates and how it is absorbed and scattered by dissolved and suspended material. Hooker cares about ocean color because of what it can reveal about the health of the ocean, and in turn, the health of our planet. "The main thing we are interested in is the productivity of the water," Hooker says. The seawater contains phytoplankton, microscopic plants, which are the food base for the ocean s ecosystems. Changes in the water s properties, whether due to natural seasonal effects or human influence, can lead to problems for delicate ecosystems such as coral reefs. Ocean color can inform researchers about the quantities and distribution of phytoplankton and other materials, providing clues as to how the world ocean is changing. NASA s Coastal Zone Color Scanner, launched in 1978, was the first ocean color instrument flown on a spacecraft. Since then, the Agency s ocean color research capabilities have become increasingly sophisticated with the launch of the SeaWiFS instrument in 1997 and the twin MODIS instruments carried into orbit on NASA s Terra (1999) and Aqua (2002) satellites. The technology provides sweeping, global information on ocean color on a scale unattainable by any other means. One issue that arises from

A Study of Color Transformation on Website Images for the Color Blind

OpenAIRE

Siew-Li Ching; Maziani Sabudin

2010-01-01

In this paper, we study on color transformation method on website images for the color blind. The most common category of color blindness is red-green color blindness which is viewed as beige color. By transforming the colors of the images, the color blind can improve their color visibility. They can have a better view when browsing through the websites. To transform colors on the website images, we study on two algorithms which are the conversion techniques from RGB colo...

CFA-aware features for steganalysis of color images

Science.gov (United States)

Goljan, Miroslav; Fridrich, Jessica

2015-03-01

Color interpolation is a form of upsampling, which introduces constraints on the relationship between neighboring pixels in a color image. These constraints can be utilized to substantially boost the accuracy of steganography detectors. In this paper, we introduce a rich model formed by 3D co-occurrences of color noise residuals split according to the structure of the Bayer color filter array to further improve detection. Some color interpolation algorithms, AHD and PPG, impose pixel constraints so tight that extremely accurate detection becomes possible with merely eight features eliminating the need for model richification. We carry out experiments on non-adaptive LSB matching and the content-adaptive algorithm WOW on five different color interpolation algorithms. In contrast to grayscale images, in color images that exhibit traces of color interpolation the security of WOW is significantly lower and, depending on the interpolation algorithm, may even be lower than non-adaptive LSB matching.

Shot Boundary Detection in Soccer Video using Twin-comparison Algorithm and Dominant Color Region

Directory of Open Access Journals (Sweden)

Matko Šarić

2008-06-01

Full Text Available The first step in generic video processing is temporal segmentation, i.e. shot boundary detection. Camera shot transitions can be either abrupt (e.g. cuts or gradual (e.g. fades, dissolves, wipes. Sports video is one of the most challenging domains for robust shot boundary detection. We proposed a shot boundary detection algorithm for soccer video based on the twin-comparison method and the absolute difference between frames in their ratios of dominant colored pixels to total number of pixels. With this approach the detection of gradual transitions is improved by decreasing the number of false positives caused by some camera operations. We also compared performances of our algorithm and the standard twin-comparison method.

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

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Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

2017-12-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

CDOM-DOC relationship in contrasted coastal waters: implication for DOC retrieval from ocean color remote sensing observation.

Science.gov (United States)

Vantrepotte, Vincent; Danhiez, François-Pierre; Loisel, Hubert; Ouillon, Sylvain; Mériaux, Xavier; Cauvin, Arnaud; Dessailly, David

2015-01-12

Increasing our knowledge on dissolved organic carbon (DOC) spatio-temporal distribution in the coastal ocean represents a crucial challenge for better understanding the role of these ecosystems in the global oceanic carbon cycle. The assessment of DOC concentration from the absorption properties of the colored part of the dissolved organic matter (a(cdom)) was investigated from an extensive data set covering a variety of coastal environments. Our results confirmed that variation in the a(cdom)(412) to DOC ratio (a*(cdom)(412)) can be depicted from the CDOM spectral slope in the UV domain (S(275-295)). They also evidenced that regional first order variation in both a*(cdom)(412) and S(275-295) are highly correlated to variation in a(cdom)(412). From these observations, generalized relationships for estimating a*(cdom)(412) from S(275-295) or a(cdom)(412) were parameterized from our development sites (N = 158; English Channel, French Guiana, Hai Phong Bay) and tested against an independent data set covering others coastal regions (N = 223; French Polynesia, Rhone River estuary, Gulf of Maine, Chesapeake Bay, Southern Middle Atlantic Bight) demonstrating the possibility to derive DOC estimates from in situ CDOM optical properties with an average accuracy of ~16% over very contrasted coastal environments (with DOC ranging from 50 to 250 µmol.L(-1)). The applicability of these generalized approaches was evaluated in the context of ocean color remote sensing observation emphasizing the limits of S(275-295)-based formulations and the potential for a(cdom)-based approaches to represent a compelling alternative for assessing synoptic DOC distribution.

Investigating preferences for color-shape combinations with gaze driven optimization method based on evolutionary algorithms.

Science.gov (United States)

Holmes, Tim; Zanker, Johannes M

2013-01-01

Studying aesthetic preference is notoriously difficult because it targets individual experience. Eye movements provide a rich source of behavioral measures that directly reflect subjective choice. To determine individual preferences for simple composition rules we here use fixation duration as the fitness measure in a Gaze Driven Evolutionary Algorithm (GDEA), which has been demonstrated as a tool to identify aesthetic preferences (Holmes and Zanker, 2012). In the present study, the GDEA was used to investigate the preferred combination of color and shape which have been promoted in the Bauhaus arts school. We used the same three shapes (square, circle, triangle) used by Kandinsky (1923), with the three color palette from the original experiment (A), an extended seven color palette (B), and eight different shape orientation (C). Participants were instructed to look for their preferred circle, triangle or square in displays with eight stimuli of different shapes, colors and rotations, in an attempt to test for a strong preference for red squares, yellow triangles and blue circles in such an unbiased experimental design and with an extended set of possible combinations. We Tested six participants extensively on the different conditions and found consistent preferences for color-shape combinations for individuals, but little evidence at the group level for clear color/shape preference consistent with Kandinsky's claims, apart from some weak link between yellow and triangles. Our findings suggest substantial inter-individual differences in the presence of stable individual associations of color and shapes, but also that these associations are robust within a single individual. These individual differences go some way toward challenging the claims of the universal preference for color/shape combinations proposed by Kandinsky, but also indicate that a much larger sample size would be needed to confidently reject that hypothesis. Moreover, these experiments highlight the

Sensor-centric calibration and characterization of the VIIRS Ocean Color bands using Suomi NPP operational data

Science.gov (United States)

Pratt, P.

2012-12-01

Ocean color bands on VIIRS span the visible spectrum and include two NIR bands. There are sixteen detectors per band and two HAM (Half-angle mirror) sides giving a total of thirty two independent systems. For each scan, thirty two hundred pixels are collected and each has a fixed specific optical path and a dynamic position relative to the earth geoid. For a given calibration target where scene variation is minimized, sensor characteristics can be observed. This gives insight into the performance and calibration of the instrument from a sensor-centric perspective. Calibration of the blue bands is especially challenging since there are few blue targets on land. An ocean region called the South Pacific Gyre (SPG) was chosen for its known stability and large area to serve as a calibration target for this investigation. Thousands of pixels from every granule that views the SPG are collected daily through an automated system and tabulated along with the detector, HAM and scan position. These are then collated and organized in a sensor-centric set of tables. The data are then analyzed by slicing by each variable and then plotted in a number of ways over time. Trends in the data show that the VIIRS sensor is largely behaving as expected according to heritage data and also reveals weaknesses where additional characterization of the sensor is possible. This work by Northrop Grumman NPP CalVal Team is supporting the VIIRS on-orbit calibration and validation teams for the sensor and ocean color as well as providing scientists interested in performing ground truth with results that show which detectors and scan angles are the most reliable over time. This novel approach offers a comprehensive sensor-centric on-orbit characterization of the VIIRS instrument on the NASA Suomi NPP mission.

Atmospheric correction of SeaWiFS ocean color imagery in the presence of absorbing aerosols off the Indian coast using a neuro-variational method

Science.gov (United States)

Brajard, J.; Moulin, C.; Thiria, S.

2008-10-01

This paper presents a comparison of the atmospheric correction accuracy between the standard sea-viewing wide field-of-view sensor (SeaWiFS) algorithm and the NeuroVaria algorithm for the ocean off the Indian coast in March 1999. NeuroVaria is a general method developed to retrieve aerosol optical properties and water-leaving reflectances for all types of aerosols, including absorbing ones. It has been applied to SeaWiFS images of March 1999, during an episode of transport of absorbing aerosols coming from pollutant sources in India. Water-leaving reflectances and aerosol optical thickness estimated by the two methods were extracted along a transect across the aerosol plume for three days. The comparison showed that NeuroVaria allows the retrieval of oceanic properties in the presence of absorbing aerosols with a better spatial and temporal stability than the standard SeaWiFS algorithm. NeuroVaria was then applied to the available SeaWiFS images over a two-week period. NeuroVaria algorithm retrieves ocean products for a larger number of pixels than the standard one and eliminates most of the discontinuities and artifacts associated with the standard algorithm in presence of absorbing aerosols.

The algorithm to generate color point-cloud with the registration between panoramic image and laser point-cloud

International Nuclear Information System (INIS)

Zeng, Fanyang; Zhong, Ruofei

2014-01-01

Laser point cloud contains only intensity information and it is necessary for visual interpretation to obtain color information from other sensor. Cameras can provide texture, color, and other information of the corresponding object. Points with color information of corresponding pixels in digital images can be used to generate color point-cloud and is conducive to the visualization, classification and modeling of point-cloud. Different types of digital cameras are used in different Mobile Measurement Systems (MMS).the principles and processes for generating color point-cloud in different systems are not the same. The most prominent feature of the panoramic images is the field of 360 degrees view angle in the horizontal direction, to obtain the image information around the camera as much as possible. In this paper, we introduce a method to generate color point-cloud with panoramic image and laser point-cloud, and deduce the equation of the correspondence between points in panoramic images and laser point-clouds. The fusion of panoramic image and laser point-cloud is according to the collinear principle of three points (the center of the omnidirectional multi-camera system, the image point on the sphere, the object point). The experimental results show that the proposed algorithm and formulae in this paper are correct

Bayesian model for matching the radiometric measurements of aerospace and field ocean color sensors.

Science.gov (United States)

Salama, Mhd Suhyb; Su, Zhongbo

2010-01-01

A Bayesian model is developed to match aerospace ocean color observation to field measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R(2) > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors.

Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors

Directory of Open Access Journals (Sweden)

Mhd. Suhyb Salama

2010-08-01

Full Text Available A Bayesian model is developed to match aerospace ocean color observation tofield measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R2 > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors.

Spectral interdependence of remote-sensing reflectance and its implications on the design of ocean color satellite sensors.

Science.gov (United States)

Lee, Zhongping; Shang, Shaoling; Hu, Chuanmin; Zibordi, Giuseppe

2014-05-20

Using 901 remote-sensing reflectance spectra (R(rs)(λ), sr⁻¹, λ from 400 to 700 nm with a 5 nm resolution), we evaluated the correlations of R(rs)(λ) between neighboring spectral bands in order to characterize (1) the spectral interdependence of R(rs)(λ) at different bands and (2) to what extent hyperspectral R(rs)(λ) can be reconstructed from multiband measurements. The 901 R(rs) spectra were measured over a wide variety of aquatic environments in which water color varied from oceanic blue to coastal green or brown, with chlorophyll-a concentrations ranging from ~0.02 to >100  mg  m⁻³, bottom depths from ~1  m to >1000  m, and bottom substrates including sand, coral reef, and seagrass. The correlation coefficient of R(rs)(λ) between neighboring bands at center wavelengths λ(k) and λ(l), r(Δλ)(λ(k), λ(l)), was evaluated systematically, with the spectral gap (Δλ=λ(l)-λ(k)) changing between 5, 10, 15, 20, 25, and 30 nm, respectively. It was found that r(Δλ) decreased with increasing Δλ, but remained >0.97 for Δλ≤20  nm for all spectral bands. Further, using 15 spectral bands between 400 and 710 nm, we reconstructed, via multivariant linear regression, hyperspectral R(rs)(λ) (from 400 to 700 nm with a 5 nm resolution). The percentage difference between measured and reconstructed R(rs) for each band in the 400-700 nm range was generally less than 1%, with a correlation coefficient close to 1.0. The mean absolute error between measured and reconstructed R(rs) was about 0.00002  sr⁻¹ for each band, which is significantly smaller than the R(rs) uncertainties from all past and current ocean color satellite radiometric products. These results echo findings of earlier studies that R(rs) measurements at ~15 spectral bands in the visible domain can provide nearly identical spectral information as with hyperspectral (contiguous bands at 5 nm spectral resolution) measurements. Such results provide insights for data

Multi-color and artistic dithering

OpenAIRE

Ostromoukhov, Victor; Hersch, Roger D.

1999-01-01

A multi-color dithering algorithm is proposed, which converts a barycentric combination of color intensities into a multi-color non-overlapping surface coverage. Multi-color dithering is a generalization of standard bi-level dithering. Combined with tetrahedral color separation, multi-color dithering makes it possible to print images made of a set of non-standard inks. In contrast to most previous color halftoning methods, multi-color dithering ensures by construction that the different selec...

Two-component wind fields over ocean waves using atmospheric lidar and motion estimation algorithms

Science.gov (United States)

Mayor, S. D.

2016-02-01

Numerical models, such as large eddy simulations, are capable of providing stunning visualizations of the air-sea interface. One reason for this is the inherent spatial nature of such models. As compute power grows, models are able to provide higher resolution visualizations over larger domains revealing intricate details of the interactions of ocean waves and the airflow over them. Spatial observations on the other hand, which are necessary to validate the simulations, appear to lag behind models. The rough ocean environment of the real world is an additional challenge. One method of providing spatial observations of fluid flow is that of particle image velocimetry (PIV). PIV has been successfully applied to many problems in engineering and the geosciences. This presentation will show recent research results that demonstate that a PIV-style approach using pulsed-fiber atmospheric elastic backscatter lidar hardware and wavelet-based optical flow motion estimation software can reveal two-component wind fields over rough ocean surfaces. Namely, a recently-developed compact lidar was deployed for 10 days in March of 2015 in the Eureka, California area. It scanned over the ocean. Imagery reveal that breaking ocean waves provide copius amounts of particulate matter for the lidar to detect and for the motion estimation algorithms to retrieve wind vectors from. The image below shows two examples of results from the experiment. The left panel shows the elastic backscatter intensity (copper shades) under a field of vectors that was retrieved by the wavelet-based optical flow algorithm from two scans that took about 15 s each to acquire. The vectors, that reveal offshore flow toward the NW, were decimated for clarity. The bright aerosol features along the right edge of the sector scan were caused by ocean waves breaking on the beach. The right panel is the result of scanning over the ocean on a day when wave amplitudes ranged from 8-12 feet and whitecaps offshore beyond the

Using Remote Sensing and Field Observations of Colored Dissolved Organic Material (CDOM) to Improve Understanding of Carbon Dynamics at the Land-Ocean Interface

Science.gov (United States)

Lai, L.; Tzortziou, M.; Gilerson, A.; Foster, R.

2013-12-01

Dissolved Organic Matter (DOM) and its colored component, (CDOM) are sensitive indicators of environmental pollution, nutrient enrichment, water quality and plays a key role in a broad range of processes and climate-related biogeochemical cycles in estuarine and coastal ecosystems. Because of its strong influence on how ocean color is viewed, CDOM can provide an invaluable optical tool for coastal zone environmental assessment and from space. There is a continuous cycle of sources and sinks of CDOM from terrestrial sources to the wetlands to the estuaries and to the ocean waters. Terrestrial inputs from natural processes, anthropogenic activities, exchanges with the atmosphere, rich biodiversity and high primary productivity, physical, photochemical and microbial processes affect not only the amount but also the quality and optical signature of CDOM in near-shore waters. In this study, new measurements are presented of the optical characteristics of CDOM collected from the Chesapeake Bay estuarine environment. Measured parameters include absorption spectra, estimated spectral slopes, slope ratios, DOC-specific CDOM absorption as well as 3D CDOM fluorescence emission-excitation matrices. Such results will provide insight of the measured CDOM in this complex environment and the complex process that affect CDOM quality and amount during transport to the estuary and coastal ocean. New field campaigns will be conducted in August and September in the Chesapeake Bay estuary and the coast of the Gulf of Mexico to collect more samples for analysis of CDOM dynamics and link field observations and measurements to satellite ocean color retrievals of estuarine biogeochemical processes. In addition, advanced satellite CDOM data distribution and usage is discussed as it has considerable operational value and practical application beyond the scientific community and research. Keywords: CDOM, carbon dynamics, estuaries, coastal ecosystems, optical properties, satellite applications

Retrieval of Oceanic Constituents from Ocean Color Using Simulated Annealing

National Research Council Canada - National Science Library

Kempeneers, Pieter; Sterckx, Sindy; Debruyn, Walter; De Backer, Steve; Scheunders, Paul; Park, Youngje; Ruddick, Kevin

2005-01-01

...), phytoplankton pigments such as chlorophyll (CHL) and colored dissolved organic matter (CDOM). Reversely, optical sensors that measure the water-leaving reflectance spectra allow us to calculate the desired concentration products...

End User Perceptual Distorted Scenes Enhancement Algorithm Using Partition-Based Local Color Values for QoE-Guaranteed IPTV

Science.gov (United States)

Kim, Jinsul

In this letter, we propose distorted scenes enhancement algorithm in order to provide end user perceptual QoE-guaranteed IPTV service. The block edge detection with weight factor and partition-based local color values method can be applied for the degraded video frames which are affected by network transmission errors such as out of order, jitter, and packet loss to improve QoE efficiently. Based on the result of quality metric after using the distorted scenes enhancement algorithm, the distorted scenes have been restored better than others.

Oceanographic applications of laser technology

Science.gov (United States)

Hoge, F. E.

1988-01-01

Oceanographic activities with the Airborne Oceanographic Lidar (AOL) for the past several years have primarily been focussed on using active (laser induced pigment fluorescence) and concurrent passive ocean color spectra to improve existing ocean color algorithms for estimating primary production in the world's oceans. The most significant results were the development of a technique for selecting optimal passive wavelengths for recovering phytoplankton photopigment concentration and the application of this technique, termed active-passive correlation spectroscopy (APCS), to various forms of passive ocean color algorithms. Included in this activity is use of airborne laser and passive ocean color for development of advanced satellite ocean color sensors. Promising on-wavelength subsurface scattering layer measurements were recently obtained. A partial summary of these results are shown.

Algorithming the Algorithm

DEFF Research Database (Denmark)

Mahnke, Martina; Uprichard, Emma

2014-01-01

Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...

Decadal Changes in Global Ocean Annual Primary Production

Science.gov (United States)

Gregg, Watson; Conkright, Margarita E.; Behrenfeld, Michael J.; Ginoux, Paul; Casey, Nancy W.; Koblinsky, Chester J. (Technical Monitor)

2002-01-01

The Sea-viewing Wide Field-of-View Sensor (SeaWiFS) has produced the first multi-year time series of global ocean chlorophyll observations since the demise of the Coastal Zone Color Scanner (CZCS) in 1986. Global observations from 1997-present from SeaWiFS combined with observations from 1979-1986 from the CZCS should in principle provide an opportunity to observe decadal changes in global ocean annual primary production, since chlorophyll is the primary driver for estimates of primary production. However, incompatibilities between algorithms have so far precluded quantitative analysis. We have developed and applied compatible processing methods for the CZCS, using modern advances in atmospheric correction and consistent bio-optical algorithms to advance the CZCS archive to comparable quality with SeaWiFS. We applied blending methodologies, where in situ data observations are incorporated into the CZCS and SeaWiFS data records, to provide improvement of the residuals. These re-analyzed, blended data records provide maximum compatibility and permit, for the first time, a quantitative analysis of the changes in global ocean primary production in the early-to-mid 1980's and the present, using synoptic satellite observations. An intercomparison of the global and regional primary production from these blended satellite observations is important to understand global climate change and the effects on ocean biota. Photosynthesis by chlorophyll-containing phytoplankton is responsible for biotic uptake of carbon in the oceans and potentially ultimately from the atmosphere. Global ocean annual primary decreased from the CZCS record to SeaWiFS, by nearly 6% from the early 1980s to the present. Annual primary production in the high latitudes was responsible for most of the decadal change. Conversely, primary production in the low latitudes generally increased, with the exception of the tropical Pacific. The differences and similarities of the two data records provide evidence

Analyses of multi-color plant-growth light sources in achieving maximum photosynthesis efficiencies with enhanced color qualities.

Science.gov (United States)

Wu, Tingzhu; Lin, Yue; Zheng, Lili; Guo, Ziquan; Xu, Jianxing; Liang, Shijie; Liu, Zhuguagn; Lu, Yijun; Shih, Tien-Mo; Chen, Zhong

2018-02-19

An optimal design of light-emitting diode (LED) lighting that benefits both the photosynthesis performance for plants and the visional health for human eyes has drawn considerable attention. In the present study, we have developed a multi-color driving algorithm that serves as a liaison between desired spectral power distributions and pulse-width-modulation duty cycles. With the aid of this algorithm, our multi-color plant-growth light sources can optimize correlated-color temperature (CCT) and color rendering index (CRI) such that photosynthetic luminous efficacy of radiation (PLER) is maximized regardless of the number of LEDs and the type of photosynthetic action spectrum (PAS). In order to illustrate the accuracies of the proposed algorithm and the practicalities of our plant-growth light sources, we choose six color LEDs and German PAS for experiments. Finally, our study can help provide a useful guide to improve light qualities in plant factories, in which long-term co-inhabitance of plants and human beings is required.

Region-Based Color Image Indexing and Retrieval

DEFF Research Database (Denmark)

Kompatsiaris, Ioannis; Triantafyllou, Evangelia; Strintzis, Michael G.

2001-01-01

In this paper a region-based color image indexing and retrieval algorithm is presented. As a basis for the indexing, a novel K-Means segmentation algorithm is used, modified so as to take into account the coherence of the regions. A new color distance is also defined for this algorithm. Based on ....... Experimental results demonstrate the performance of the algorithm. The development of an intelligent image content-based search engine for the World Wide Web is also presented, as a direct application of the presented algorithm....

Color-to-grayscale conversion through weighted multiresolution channel fusion

NARCIS (Netherlands)

Wu, T.; Toet, A.

2014-01-01

We present a color-to-gray conversion algorithm that retains both the overall appearance and the discriminability of details of the input color image. The algorithm employs a weighted pyramid image fusion scheme to blend the R, G, and B color channels of the input image into a single grayscale

1-Colored Archetypal Permutations and Strings of Degree n

Directory of Open Access Journals (Sweden)

Gheorghe Eduard Tara

2012-10-01

Full Text Available New notions related to permutations are introduced here. We present the string of a 1-colored permutation as a closed planar curve, the fundamental 1-colored permutation as an equivalence class related to the equivalence in strings of the 1-colored permutations. We give formulas for the number of the 1-colored archetypal permutations of degree n. We establish an algorithm to identify the 1- colored archetypal permutations of degree n and we present the atlas of the 1-colored archetypal strings of degree n, n ≤ 7, based on this algorithm.

Categorization and Searching of Color Images Using Mean Shift Algorithm

Directory of Open Access Journals (Sweden)

Prakash PANDEY

2009-07-01

Full Text Available Now a day’s Image Searching is still a challenging problem in content based image retrieval (CBIR system. Most CBIR system operates on all images without pre-sorting the images. The image search result contains many unrelated image. The aim of this research is to propose a new object based indexing system Based on extracting salient region representative from the image, categorizing the image into different types and search images that are similar to given query images.In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique, Dominant objects are obtained by performing region grouping of segmented thumbnails. The category for an image is generated automatically by analyzing the image for the presence of a dominant object. The images in the database are clustered based on region feature similarity using Euclidian distance. Placing an image into a category can help the user to navigate retrieval results more effectively. Extensive experimental results illustrate excellent performance.

Ocean Color and the Equatorial Annual Cycle in the Pacific

Science.gov (United States)

Hammann, A. C.; Gnanadesikan, A.

2012-12-01

The presence of chlorophyll, colored dissolved organic matter (CDOM) and other scatterers in ocean surface waters affect the flux divergence of solar radiation and thus the vertical distribution of radiant heating of the ocean. While this may directly alter the local mixed-layer depth and temperature (Martin 1985; Strutton & Chavez 2004), non-local changes are propagated through advection (Manizza et al. 2005; Murtugudde et al. 2002; Nakamoto et al. 2001; Sweeny et al. 2005). In and coupled feedbacks (Lengaigne et al. 2007; Marzeion & Timmermann 2005). Anderson et al. (2007), Anderson et al. (2009) and Gnanadesikan & Anderson (2009) have performed a series of experiments with a fully coupled climate model which parameterizes the e-folding depth of solar irradiance in terms of surface chlorophyll-a concentration. The results have so far been discussed with respect to the climatic mean state and ENSO variability in the tropical Pacific. We extend the discussion here to the Pacific equatorial annual cycle. The focus of the coupled experiments has been the sensitivity of the coupled system to regional differences in chlorophyll concentration. While runs have been completed with realistic SeaWiFS-derived monthly composite chlorophyll ('green') and with a globally chlorophyll-free ocean ('blue'), the concentrations in two additional runs have been selectively set to zero in specific regions: the oligotrophic subtropical gyres ('gyre') in one case and the mesotrophic gyre margins ('margin') in the other. The annual cycle of ocean temperatures exhibits distinctly reduced amplitudes in the 'blue' and 'margin' experiments, and a slight reduction in 'gyre' (while ENSO variability almost vanishes in 'blue' and 'gyre', but amplifies in 'margin' - thus the frequently quoted inverse correlation between ENSO and annual amplitudes holds only for the 'green' / 'margin' comparison). It is well-known that on annual time scales, the anomalous divergence of surface currents and vertical

High-dynamic range imaging techniques based on both color-separation algorithms used in conventional graphic arts and the human visual perception modeling

Science.gov (United States)

Lo, Mei-Chun; Hsieh, Tsung-Hsien; Perng, Ruey-Kuen; Chen, Jiong-Qiao

2010-01-01

The aim of this research is to derive illuminant-independent type of HDR imaging modules which can optimally multispectrally reconstruct of every color concerned in high-dynamic-range of original images for preferable cross-media color reproduction applications. Each module, based on either of broadband and multispectral approach, would be incorporated models of perceptual HDR tone-mapping, device characterization. In this study, an xvYCC format of HDR digital camera was used to capture HDR scene images for test. A tone-mapping module was derived based on a multiscale representation of the human visual system and used equations similar to a photoreceptor adaptation equation, proposed by Michaelis-Menten. Additionally, an adaptive bilateral type of gamut mapping algorithm, using approach of a multiple conversing-points (previously derived), was incorporated with or without adaptive Un-sharp Masking (USM) to carry out the optimization of HDR image rendering. An LCD with standard color space of Adobe RGB (D65) was used as a soft-proofing platform to display/represent HDR original RGB images, and also evaluate both renditionquality and prediction-performance of modules derived. Also, another LCD with standard color space of sRGB was used to test gamut-mapping algorithms, used to be integrated with tone-mapping module derived.

Impulsive noise removal from color video with morphological filtering

Science.gov (United States)

Ruchay, Alexey; Kober, Vitaly

2017-09-01

This paper deals with impulse noise removal from color video. The proposed noise removal algorithm employs a switching filtering for denoising of color video; that is, detection of corrupted pixels by means of a novel morphological filtering followed by removal of the detected pixels on the base of estimation of uncorrupted pixels in the previous scenes. With the help of computer simulation we show that the proposed algorithm is able to well remove impulse noise in color video. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.

Hourly changes in sea surface salinity in coastal waters recorded by Geostationary Ocean Color Imager

Science.gov (United States)

Liu, Rongjie; Zhang, Jie; Yao, Haiyan; Cui, Tingwei; Wang, Ning; Zhang, Yi; Wu, Lingjuan; An, Jubai

2017-09-01

In this study, we monitored hourly changes in sea surface salinity (SSS) in turbid coastal waters from geostationary satellite ocean color images for the first time, using the Bohai Sea as a case study. We developed a simple multi-linear statistical regression model to retrieve SSS data from Geostationary Ocean Color Imager (GOCI) based on an in situ satellite matched-up dataset (R2 = 0.795; N = 41; Range: 26.4 to 31.9 psμ). The model was then validated using independent continuous SSS measurements from buoys, with the average percentage difference of 0.65%. The model was applied to GOCI images from the dry season during an astronomical tide to characterize hourly changes in SSS in the Bohai Sea. We found that the model provided reasonable estimates of the hourly changes in SSS and that trends in the modeled and measured data were similar in magnitude and direction (0.43 vs 0.33 psμ, R2 = 0.51). There were clear diurnal variations in the SSS of the Bohai Sea, with a regional average of 0.455 ± 0.079 psμ (0.02-3.77 psμ). The magnitude of the diurnal variations in SSS varied spatially, with large diurnal variability in the nearshore, particularly in the estuary, and small variability in the offshore area. The model for the riverine area was based on the inverse correlation between SSS and CDOM absorption. In the offshore area, the water mass of the North Yellow Sea, characterized by high SSS and low CDOM concentrations, dominated. Analysis of the driving mechanisms showed that the tidal current was the main control on hourly changes in SSS in the Bohai Sea.

Finding text in color images

Science.gov (United States)

Zhou, Jiangying; Lopresti, Daniel P.; Tasdizen, Tolga

1998-04-01

In this paper, we consider the problem of locating and extracting text from WWW images. A previous algorithm based on color clustering and connected components analysis works well as long as the color of each character is relatively uniform and the typography is fairly simple. It breaks down quickly, however, when these assumptions are violated. In this paper, we describe more robust techniques for dealing with this challenging problem. We present an improved color clustering algorithm that measures similarity based on both RGB and spatial proximity. Layout analysis is also incorporated to handle more complex typography. THese changes significantly enhance the performance of our text detection procedure.

Riemann Geometric Color-Weak Compensationfor Individual Observers

OpenAIRE

Kojima, Takanori; Mochizuki, Rika; Lenz, Reiner; Chao, Jinhui

2014-01-01

We extend a method for color weak compensation based on the criterion of preservation of subjective color differences between color normal and color weak observers presented in [2]. We introduce a new algorithm for color weak compensation using local affine maps between color spaces of color normal and color weak observers. We show howto estimate the local affine map and how to determine correspondences between the origins of local coordinates in color spaces of color normal and color weak ob...

Underway Sampling of Marine Inherent Optical Properties on the Tara Oceans Expedition as a Novel Resource for Ocean Color Satellite Data Product Validation

Science.gov (United States)

Werdell, P. Jeremy; Proctor, Christopher W.; Boss, Emmanuel; Leeuw, Thomas; Ouhssain, Mustapha

2013-01-01

Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate-the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

How Ocean Color Influences the Interplay Between Annual and Interannual Tropical Pacific Variability

Science.gov (United States)

Hammann, A. C.; Gnanadesikan, A.

2010-12-01

While the basic mechanisms responsible for ENSO have long been known, many details still evade our understanding. Since the behavior of the real climate system appears to be highly sensitive to such details, however, our ability to model, let alone predict it with any confidence has so far been rather restricted. Not only can small perturbations in many state variables lead to strongly amplified responses, but also do spatial and temporal scales of variability rarely occur in isolation from each other. Both points are born out in the study by Anderson et al. (2009), who removed surface chlorophyll in different regions of the tropical (but mostly off-equatorial) Pacific in a coupled ocean-atmosphere-land-ice model. Different removal patterns lead to large differences in the amplitudes of both ENSO and the equatorial annual cycle. Anderson et al.’s analysis focuses on ENSO and reveals that the transmission of off-equatorial perturbations to the equator happens mainly through a changed atmospheric response to SST anomalies. Here, we analyze the same data with respect to the annual cycle and how it interacts with ENSO. Guilyardi (2006) reports that observations and models alike show a zero-sum-type behavior of annual and ENSO-scale variability; increased spectral power in the annual band means decreased power in the ENSO band and vice versa. This is not the case for the different patterns of chlorophyll removal in our model, and hence it appears that this removal changes a fundamental part of its mean state. The dynamics of the annual cycle are likely influenced by oceanic meridional temperature advection, which provides another possible route for off-to-equatorial signal propagation. A common aspect of the tropical annual cycle in most coupled climate models is the presence of a double ITCZ instead of a single north-shifted one. Even though this appears to be unrelated to (albeit influenced by) the changes in ocean color, our model exhibits a much improved

Enriching text with images and colored light

Science.gov (United States)

Sekulovski, Dragan; Geleijnse, Gijs; Kater, Bram; Korst, Jan; Pauws, Steffen; Clout, Ramon

2008-01-01

We present an unsupervised method to enrich textual applications with relevant images and colors. The images are collected by querying large image repositories and subsequently the colors are computed using image processing. A prototype system based on this method is presented where the method is applied to song lyrics. In combination with a lyrics synchronization algorithm the system produces a rich multimedia experience. In order to identify terms within the text that may be associated with images and colors, we select noun phrases using a part of speech tagger. Large image repositories are queried with these terms. Per term representative colors are extracted using the collected images. Hereto, we either use a histogram-based or a mean shift-based algorithm. The representative color extraction uses the non-uniform distribution of the colors found in the large repositories. The images that are ranked best by the search engine are displayed on a screen, while the extracted representative colors are rendered on controllable lighting devices in the living room. We evaluate our method by comparing the computed colors to standard color representations of a set of English color terms. A second evaluation focuses on the distance in color between a queried term in English and its translation in a foreign language. Based on results from three sets of terms, a measure of suitability of a term for color extraction based on KL Divergence is proposed. Finally, we compare the performance of the algorithm using either the automatically indexed repository of Google Images and the manually annotated Flickr.com. Based on the results of these experiments, we conclude that using the presented method we can compute the relevant color for a term using a large image repository and image processing.

Design of an Image Motion Compenstaion (IMC Algorithm for Image Registration of the Communication, Ocean, Meteorolotical Satellite (COMS-1

Directory of Open Access Journals (Sweden)

Taek Seo Jung

2006-03-01

Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.

Improved Algorithms for Accurate Retrieval of UV - Visible Diffuse Attenuation Coefficients in Optically Complex, Inshore Waters

Science.gov (United States)

Cao, Fang; Fichot, Cedric G.; Hooker, Stanford B.; Miller, William L.

2014-01-01

Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This

Empirical Algorithms to Predict pH and Aragonite Saturation State on SOCCOM Biogeochemical Argo Floats in the Pacific Sector of the Southern Ocean

Science.gov (United States)

Williams, N. L.; Juranek, L. W.; Feely, R. A.; Johnson, K. S.; Russell, J. L.

2016-02-01

The Southern Ocean plays a major role in the global uptake, transport, and storage of both heat and carbon, yet it remains one of the least-sampled regions of the ocean. The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project aims to fill the observational gaps by deploying over 200 autonomous profiling floats in the Southern Ocean over the next several years. Initial float deployments have greatly expanded our observational capability to include wintertime measurements as well as under-ice measurements, and many of these floats include novel biogeochemical sensors (pH, nitrate, oxygen). Here we present empirical algorithms that can be used to predict pH and ΩAragonite from other float-measured parameters (temperature, salinity, pressure, nitrate, oxygen). These algorithms were trained using bottle measurements from high-quality repeat hydrographic GO-SHIP cruises. We obtained R2 values of 0.98 (pH) and 0.99 (ΩAragonite) and RMS errors of 0.007 (pH) and 0.052 (ΩAragonite) for data between 100-1500 m. These algorithms will allow us to both validate pH data from these sensors, as well as predict ΩAragonite and pH on floats that do not have pH sensors. Here we present estimated pH and ΩAragonite over 20 months of deployment for several SOCCOM floats in the Pacific Sector of the Southern Ocean. The results show seasonal ranges in surface pH and ΩAragonite of 0.05 and 0.1, respectively.

Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM)

Science.gov (United States)

Halliwell, George R.

Vertical coordinate and vertical mixing algorithms included in the HYbrid Coordinate Ocean Model (HYCOM) are evaluated in low-resolution climatological simulations of the Atlantic Ocean. The hybrid vertical coordinates are isopycnic in the deep ocean interior, but smoothly transition to level (pressure) coordinates near the ocean surface, to sigma coordinates in shallow water regions, and back again to level coordinates in very shallow water. By comparing simulations to climatology, the best model performance is realized using hybrid coordinates in conjunction with one of the three available differential vertical mixing models: the nonlocal K-Profile Parameterization, the NASA GISS level 2 turbulence closure, and the Mellor-Yamada level 2.5 turbulence closure. Good performance is also achieved using the quasi-slab Price-Weller-Pinkel dynamical instability model. Differences among these simulations are too small relative to other errors and biases to identify the "best" vertical mixing model for low-resolution climate simulations. Model performance deteriorates slightly when the Kraus-Turner slab mixed layer model is used with hybrid coordinates. This deterioration is smallest when solar radiation penetrates beneath the mixed layer and when shear instability mixing is included. A simulation performed using isopycnic coordinates to emulate the Miami Isopycnic Coordinate Ocean Model (MICOM), which uses Kraus-Turner mixing without penetrating shortwave radiation and shear instability mixing, demonstrates that the advantages of switching from isopycnic to hybrid coordinates and including more sophisticated turbulence closures outweigh the negative numerical effects of maintaining hybrid vertical coordinates.

Application of an optimization algorithm to satellite ocean color imagery: A case study in Southwest Florida coastal waters

Science.gov (United States)

Hu, Chuanmin; Lee, Zhongping; Muller-Karger, Frank E.; Carder, Kendall L.

2003-05-01

A spectra-matching optimization algorithm, designed for hyperspectral sensors, has been implemented to process SeaWiFS-derived multi-spectral water-leaving radiance data. The algorithm has been tested over Southwest Florida coastal waters. The total spectral absorption and backscattering coefficients can be well partitioned with the inversion algorithm, resulting in RMS errors generally less than 5% in the modeled spectra. For extremely turbid waters that come from either river runoff or sediment resuspension, the RMS error is in the range of 5-15%. The bio-optical parameters derived in this optically complex environment agree well with those obtained in situ. Further, the ability to separate backscattering (a proxy for turbidity) from the satellite signal makes it possible to trace water movement patterns, as indicated by the total absorption imagery. The derived patterns agree with those from concurrent surface drifters. For waters where CDOM overwhelmingly dominates the optical signal, however, the procedure tends to regard CDOM as the sole source of absorption, implying the need for better atmospheric correction and for adjustment of some model coefficients for this particular region.

Combining fine texture and coarse color features for color texture classification

Science.gov (United States)

Wang, Junmin; Fan, Yangyu; Li, Ning

2017-11-01

Color texture classification plays an important role in computer vision applications because texture and color are two fundamental visual features. To classify the color texture via extracting discriminative color texture features in real time, we present an approach of combining the fine texture and coarse color features for color texture classification. First, the input image is transformed from RGB to HSV color space to separate texture and color information. Second, the scale-selective completed local binary count (CLBC) algorithm is introduced to extract the fine texture feature from the V component in HSV color space. Third, both H and S components are quantized at an optimal coarse level. Furthermore, the joint histogram of H and S components is calculated, which is considered as the coarse color feature. Finally, the fine texture and coarse color features are combined as the final descriptor and the nearest subspace classifier is used for classification. Experimental results on CUReT, KTH-TIPS, and New-BarkTex databases demonstrate that the proposed method achieves state-of-the-art classification performance. Moreover, the proposed method is fast enough for real-time applications.

COLORS OF A SECOND EARTH: ESTIMATING THE FRACTIONAL AREAS OF OCEAN, LAND, AND VEGETATION OF EARTH-LIKE EXOPLANETS

International Nuclear Information System (INIS)

Fujii, Yuka; Kawahara, Hajime; Suto, Yasushi; Taruya, Atsushi; Fukuda, Satoru; Nakajima, Teruyuki; Turner, Edwin L.

2010-01-01

Characterizing the surfaces of rocky exoplanets via their scattered light will be an essential challenge in investigating their habitability and the possible existence of life on their surfaces. We present a reconstruction method for fractional areas of different surface types from the colors of an Earth-like exoplanet. We create mock light curves for Earth without clouds using empirical data. These light curves are fitted to an isotropic scattering model consisting of four surface types: ocean, soil, snow, and vegetation. In an idealized situation where the photometric errors are only photon shot noise, we are able to reproduce the fractional areas of those components fairly well. The results offer some hope for detection of vegetation via the distinct spectral feature of photosynthesis on Earth, known as the red edge. In our reconstruction method, Rayleigh scattering due to the atmosphere plays an important role, and for terrestrial exoplanets with an atmosphere similar to our Earth, it is possible to estimate the presence of oceans and an atmosphere simultaneously.

Improved NAMK Color Images Representation Algorithm%改进的NAMK彩色图像表示算法

Institute of Scientific and Technical Information of China (English)

郑运平

2011-01-01

By taking advantages of the characteristic of Gray code that can extend or remain the block character of binary images, this paper proposes an improved Non-symmetry and Anti-packing Model with K-lines(NAMK) representation algorithm for color images, which is called NAMKG algorithm.The description of NAMKG algorithm is presented and the storage structure and the total data amount of the algorithm are analyzed.Theoretical and experimental results show that, compared with NAMK and Linear Quadtree(LQT), NAMKG can effectively reduce the number of subpatterns and reduce the storage room.%利用格雷码可以扩展或保持二值图像块状性的特点,提出一种改进的NAMK彩色图像表示算法NAMKG,给出算法的形式化描述及其存储结构,对其总数据量进行分析.理论分析和实验结果表明,相比NAMK算法和线性四元树算法,NAMKG可以有效减少子模式数,减小存储空间.

A Simple Encryption Algorithm for Quantum Color Image

Science.gov (United States)

Li, Panchi; Zhao, Ya

2017-06-01

In this paper, a simple encryption scheme for quantum color image is proposed. Firstly, a color image is transformed into a quantum superposition state by employing NEQR (novel enhanced quantum representation), where the R,G,B values of every pixel in a 24-bit RGB true color image are represented by 24 single-qubit basic states, and each value has 8 qubits. Then, these 24 qubits are respectively transformed from a basic state into a balanced superposition state by employed the controlled rotation gates. At this time, the gray-scale values of R, G, B of every pixel are in a balanced superposition of 224 multi-qubits basic states. After measuring, the whole image is an uniform white noise, which does not provide any information. Decryption is the reverse process of encryption. The experimental results on the classical computer show that the proposed encryption scheme has better security.

Computational Ocean Acoustics

CERN Document Server

Jensen, Finn B; Porter, Michael B; Schmidt, Henrik

2011-01-01

Since the mid-1970s, the computer has played an increasingly pivotal role in the field of ocean acoustics. Faster and less expensive than actual ocean experiments, and capable of accommodating the full complexity of the acoustic problem, numerical models are now standard research tools in ocean laboratories. The progress made in computational ocean acoustics over the last thirty years is summed up in this authoritative and innovatively illustrated new text. Written by some of the field's pioneers, all Fellows of the Acoustical Society of America, Computational Ocean Acoustics presents the latest numerical techniques for solving the wave equation in heterogeneous fluid–solid media. The authors discuss various computational schemes in detail, emphasizing the importance of theoretical foundations that lead directly to numerical implementations for real ocean environments. To further clarify the presentation, the fundamental propagation features of the techniques are illustrated in color. Computational Ocean A...

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

Science.gov (United States)

Mannino, Antonio; Novak, Michael G.; Hooker, Stanford B.; Hyde, Kimberly; Aurin, Dick

2014-01-01

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than

Biodiversity of Pigmented Fungi Isolated from Marine Environment in La Réunion Island, Indian Ocean: New Resources for Colored Metabolites

Directory of Open Access Journals (Sweden)

Mireille Fouillaud

2017-07-01

Full Text Available Marine ecosystems cover about 70% of the planet surface and are still an underexploited source of useful metabolites. Among microbes, filamentous fungi are captivating organisms used for the production of many chemical classes of secondary metabolites bound to be used in various fields of industrial application. The present study was focused on the collection, isolation, screening and genotyping of pigmented filamentous fungi isolated from tropical marine environments around La Réunion Island, Indian Ocean. About 150 micromycetes were revived and isolated from 14 marine samples (sediments, living corals, coral rubble, sea water and hard substrates collected in four different locations. Forty-two colored fungal isolates belonging to 16 families, 25 genera and 31 species were further studied depending on their ability to produce pigments and thus subjected to molecular identification. From gene sequence analysis, the most frequently identified colored fungi belong to the widespread Penicillium, Talaromyces and Aspergillus genera in the family Trichocomaceae (11 species, then followed by the family Hypocreaceae (three species. This study demonstrates that marine biotopes in La Réunion Island, Indian Ocean, from coral reefs to underwater slopes of this volcanic island, shelter numerous species of micromycetes, from common or uncommon genera. This unstudied biodiversity comes along with the ability for some fungal marine inhabitants, to produce a range of pigments and hues.

Clustering of color map pixels: an interactive approach

Science.gov (United States)

Moon, Yiu Sang; Luk, Franklin T.; Yuen, K. N.; Yeung, Hoi Wo

2003-12-01

The demand for digital maps continues to arise as mobile electronic devices become more popular nowadays. Instead of creating the entire map from void, we may convert a scanned paper map into a digital one. Color clustering is the very first step of the conversion process. Currently, most of the existing clustering algorithms are fully automatic. They are fast and efficient but may not work well in map conversion because of the numerous ambiguous issues associated with printed maps. Here we introduce two interactive approaches for color clustering on the map: color clustering with pre-calculated index colors (PCIC) and color clustering with pre-calculated color ranges (PCCR). We also introduce a memory model that could enhance and integrate different image processing techniques for fine-tuning the clustering results. Problems and examples of the algorithms are discussed in the paper.

A framework for interactive image color editing

KAUST Repository

Musialski, Przemyslaw

2012-11-08

We propose a new method for interactive image color replacement that creates smooth and naturally looking results with minimal user interaction. Our system expects as input a source image and rawly scribbled target color values and generates high quality results in interactive rates. To achieve this goal we introduce an algorithm that preserves pairwise distances of the signatures in the original image and simultaneously maps the color to the user defined target values. We propose efficient sub-sampling in order to reduce the computational load and adapt semi-supervised locally linear embedding to optimize the constraints in one objective function. We show the application of the algorithm on typical photographs and compare the results to other color replacement methods. © 2012 Springer-Verlag Berlin Heidelberg.

Color correction for chromatic distortion in a multi-wavelength digital holographic system

International Nuclear Information System (INIS)

Lin, Li-Chien; Huang, Yi-Lun; Tu, Han-Yen; Lai, Xin-Ji; Cheng, Chau-Jern

2011-01-01

A multi-wavelength digital holographic (MWDH) system has been developed to record and reconstruct color images. In comparison to working with digital cameras, however, high-quality color reproduction is difficult to achieve, because of the imperfections from the light sources, optical components, optical recording devices and recording processes. Thus, we face the problem of correcting the colors altered during the digital holographic process. We therefore propose a color correction scheme to correct the chromatic distortion caused by the MWDH system. The scheme consists of two steps: (1) creating a color correction profile and (2) applying it to the correction of the distorted colors. To create the color correction profile, we generate two algorithms: the sequential algorithm and the integrated algorithm. The ColorChecker is used to generate the distorted colors and their desired corrected colors. The relationship between these two color patches is fixed into a specific mathematical model, the parameters of which are estimated, creating the profile. Next, the profile is used to correct the color distortion of images, capturing and preserving the original vibrancy of the reproduced colors for different reconstructed images

VIIRS Product Evaluation at the Ocean PEATE

Science.gov (United States)

Patt, Frederick S.; Feldman, Gene C.

2010-01-01

The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) mission will support the continuation of climate records generated from NASA missions. The NASA Science Data Segment (SDS) relies upon discipline-specific centers of expertise to evaluate the NPP data products for suitability as climate data records, The Ocean Product Evaluation and Analysis Tool Element (PEATE) will build upon Well established NASA capabilities within the Ocean Color program in order to evaluate the NPP Visible and Infrared Imager/Radiometer Suite (VIIRS) Ocean Color and Chlorophyll data products. The specific evaluation methods will support not only the evaluation of product quality but also the sources of differences with existing data records.

Retrieval of aerosol properties and water-leaving reflectance from multi-angular polarimetric measurements over coastal waters.

Science.gov (United States)

Gao, Meng; Zhai, Peng-Wang; Franz, Bryan; Hu, Yongxiang; Knobelspiesse, Kirk; Werdell, P Jeremy; Ibrahim, Amir; Xu, Feng; Cairns, Brian

2018-04-02

Ocean color remote sensing is an important tool to monitor water quality and biogeochemical conditions of ocean. Atmospheric correction, which obtains water-leaving radiance from the total radiance measured by satellite-borne or airborne sensors, remains a challenging task for coastal waters due to the complex optical properties of aerosols and ocean waters. In this paper, we report a research algorithm on aerosol and ocean color retrieval with emphasis on coastal waters, which uses coupled atmosphere and ocean radiative transfer model to fit polarized radiance measurements at multiple viewing angles and multiple wavelengths. Ocean optical properties are characterized by a generalized bio-optical model with direct accounting for the absorption and scattering of phytoplankton, colored dissolved organic matter (CDOM) and non-algal particles (NAP). Our retrieval algorithm can accurately determine the water-leaving radiance and aerosol properties for coastal waters, and may be used to improve the atmospheric correction when apply to a hyperspectral ocean color instrument.

Seasonality and flux estimates of dissolved organic carbon in tidal wetlands and estuaries in the U.S. Mid- Atlantic Bight and Gulf of Mexico from ocean color

Science.gov (United States)

Cao, F.; Tzortziou, M.; Hu, C.; Najjar, R.

2016-02-01

Tidal wetlands and estuaries are dynamic features of coastal ocean and play critical roles in the global carbon cycle. Exchanges of dissolved organic carbon (DOC) between tidal wetlands and adjacent estuaries have important implications for carbon sequestration in tidal wetlands as well as biogeochemical cycling of wetlands derived material in the coastal zones. Recent studies demonstrated that the absorption coefficients of chromophoric dissolved organic matter at λ= 275 and 295 nm, which can be derived from satellite ocean color observations, can be used to accurately retrieve dissolved organic carbon (DOC) in some coastal waters. Based on a synthesis of existing field observations collected covering wide spatial and temporal variability in the Mid-Atlantic Bight and the Gulf of Mexico, here we developed and validated new empirical models to estimate coastal DOC from remotely sensed bio-optical properties of the surface water. We focused on the interfaces between tidal wetland-estuary and estuary-shelf water domains. The DOC algorithms were applied to SeaWiFs and MODIS observations to generate long-term climatological DOC distributions from 1998 to 2014. Empirical orthogonal function analysis revealed strong seasonality and spatial gradients in the satellite retrieved DOC in the tidal wetlands and estuaries. Combined with field observations and biogeochemical models, satellite retrievals can be used to scale up carbon fluxes from individual marshes and sub-estuaries to the whole estuarine system, and improve understanding of biogeochemical exchanges between terrestrial and aquatic ecosystems.

A new parameterization for surface ocean light attenuation in Earth System Models: assessing the impact of light absorption by colored detrital material

OpenAIRE

G. E. Kim; M.-A. Pradal; A. Gnanadesikan

2015-01-01

Light limitation can affect the distribution of biota and nutrients in the ocean. Light absorption by colored detrital material (CDM) was included in a fully coupled Earth System Model using a new parameterization for shortwave attenuation. Two model runs were conducted, with and without light attenuation by CDM. In a global average sense, greater light limitation associated with CDM increased surface chlorophyll, biomass and nutrients together. These changes can be attribut...

Separation of irradiance and reflectance from observed color images by logarithmical nonlinear diffusion process

Science.gov (United States)

Saito, Takahiro; Takahashi, Hiromi; Komatsu, Takashi

2006-02-01

The Retinex theory was first proposed by Land, and deals with separation of irradiance from reflectance in an observed image. The separation problem is an ill-posed problem. Land and others proposed various Retinex separation algorithms. Recently, Kimmel and others proposed a variational framework that unifies the previous Retinex algorithms such as the Poisson-equation-type Retinex algorithms developed by Horn and others, and presented a Retinex separation algorithm with the time-evolution of a linear diffusion process. However, the Kimmel's separation algorithm cannot achieve physically rational separation, if true irradiance varies among color channels. To cope with this problem, we introduce a nonlinear diffusion process into the time-evolution. Moreover, as to its extension to color images, we present two approaches to treat color channels: the independent approach to treat each color channel separately and the collective approach to treat all color channels collectively. The latter approach outperforms the former. Furthermore, we apply our separation algorithm to a high quality chroma key in which before combining a foreground frame and a background frame into an output image a color of each pixel in the foreground frame are spatially adaptively corrected through transformation of the separated irradiance. Experiments demonstrate superiority of our separation algorithm over the Kimmel's separation algorithm.

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance.

Science.gov (United States)

Zeng, Chen; Xu, Huiping; Fischer, Andrew M

2016-12-07

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy.

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance

Directory of Open Access Journals (Sweden)

Chen Zeng

2016-12-01

Full Text Available Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO. However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution, simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy.

Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines

Directory of Open Access Journals (Sweden)

Ayşegül Uçar

2014-01-01

Full Text Available This paper presents a novel color face recognition algorithm by means of fusing color and local information. The proposed algorithm fuses the multiple features derived from different color spaces. Multiorientation and multiscale information relating to the color face features are extracted by applying Steerable Pyramid Transform (SPT to the local face regions. In this paper, the new three hybrid color spaces, YSCr, ZnSCr, and BnSCr, are firstly constructed using the Cb and Cr component images of the YCbCr color space, the S color component of the HSV color spaces, and the Zn and Bn color components of the normalized XYZ color space. Secondly, the color component face images are partitioned into the local patches. Thirdly, SPT is applied to local face regions and some statistical features are extracted. Fourthly, all features are fused according to decision fusion frame and the combinations of Extreme Learning Machines classifiers are applied to achieve color face recognition with fast and high correctness. The experiments show that the proposed Local Color Steerable Pyramid Transform (LCSPT face recognition algorithm improves seriously face recognition performance by using the new color spaces compared to the conventional and some hybrid ones. Furthermore, it achieves faster recognition compared with state-of-the-art studies.

Retrieval of aerosol properties and water leaving radiance from multi-angle spectro-polarimetric measurement over coastal waters

Science.gov (United States)

Gao, M.; Zhai, P.; Franz, B. A.; Hu, Y.; Knobelspiesse, K. D.; Xu, F.; Ibrahim, A.

2017-12-01

Ocean color remote sensing in coastal waters remains a challenging task due to the complex optical properties of aerosols and ocean water properties. It is highly desirable to develop an advanced ocean color and aerosol retrieval algorithm for coastal waters, to advance our capabilities in monitoring water quality, improve our understanding of coastal carbon cycle dynamics, and allow for the development of more accurate circulation models. However, distinguishing the dissolved and suspended material from absorbing aerosols over coastal waters is challenging as they share similar absorption spectrum within the deep blue to UV range. In this paper we report a research algorithm on aerosol and ocean color retrieval with emphasis on coastal waters. The main features of our algorithm include: 1) combining co-located measurements from a hyperspectral ocean color instrument (OCI) and a multi-angle polarimeter (MAP); 2) using the radiative transfer model for coupled atmosphere and ocean system (CAOS), which is based on the highly accurate and efficient successive order of scattering method; and 3) incorporating a generalized bio-optical model with direct accounting of the total absorption of phytoplankton, CDOM and non-algal particles(NAP), and the total scattering of phytoplankton and NAP for improved description of ocean light scattering. The non-linear least square fitting algorithm is used to optimize the bio-optical model parameters and the aerosol optical and microphysical properties including refractive indices and size distributions for both fine and coarse modes. The retrieved aerosol information is used to calculate the atmospheric path radiance, which is then subtracted from the OCI observations to obtain the water leaving radiance contribution. Our work aims to maximize the use of available information from the co-located dataset and conduct the atmospheric correction with minimal assumptions. The algorithm will contribute to the success of current MAP

Coloring geographical threshold graphs

Energy Technology Data Exchange (ETDEWEB)

Bradonjic, Milan [Los Alamos National Laboratory; Percus, Allon [Los Alamos National Laboratory; Muller, Tobias [EINDHOVEN UNIV. OF TECH

2008-01-01

We propose a coloring algorithm for sparse random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Here, we analyze the GTG coloring algorithm together with the graph's clique number, showing formally that in spite of the differences in structure between GTG and RGG, the asymptotic behavior of the chromatic number is identical: {chi}1n 1n n / 1n n (1 + {omicron}(1)). Finally, we consider the leading corrections to this expression, again using the coloring algorithm and clique number to provide bounds on the chromatic number. We show that the gap between the lower and upper bound is within C 1n n / (1n 1n n){sup 2}, and specify the constant C.

New Triangular and Rectangular NAM Representation Algorithm for Color Images%一种新的TRNAM彩色图像表示算法

Institute of Scientific and Technical Information of China (English)

郑运平

2011-01-01

The Non-symmetry and Anti-packing Model (NAM) is suitable for representations of image pattern, audio pattern, video pattern, and text pattern, and it is a general pattern representation model. Inspired by the idea of representing the pixels by the Gray code, a new triangular and rectangular NAM representation algorithm for color images, which is called the NTRNAM algorithm, is proposed. The principium and the description of the NTRNAM algorithm are presented and the storage structure, the total data a-mount, and the time and space complexities of the proposed algorithm are analyzed. The theoretical and experimental results show that the NTRNAM algorithm can greatly reduce the number of subpatterns and simultaneously save the storage room, and therefore it is an effective algorithm for color image representation.%非对称逆布局模型(NAM)适用于图像模式、语音模式、文本模式、视频模式的表示,是一个通用型的模式表示模型.借助于格雷码表示图像像素的思想,提出了一种新的三角形和矩形NAM彩色图像表示算法(简称NTRNAM算法).给出了算法的原理及形式化描述,并对其存储结构、总数据量和时空复杂性进行了分析.理论分析和实验结果表明:NTRNAM算法能够显著降低子模式数和存储空间,是一种有效的彩色图像表示算法.

A new bio-optical algorithm for the remote sensing of algal blooms in complex ocean waters

Science.gov (United States)

Shanmugam, Palanisamy

2011-04-01

A new bio-optical algorithm has been developed to provide accurate assessments of chlorophyll a (Chl a) concentration for detection and mapping of algal blooms from satellite data in optically complex waters, where the presence of suspended sediments and dissolved substances can interfere with phytoplankton signal and thus confound conventional band ratio algorithms. A global data set of concurrent measurements of pigment concentration and radiometric reflectance was compiled and used to develop this algorithm that uses the normalized water-leaving radiance ratios along with an algal bloom index (ABI) between three visible bands to determine Chl a concentrations. The algorithm is derived using Sea-viewing Wide Field-of-view Sensor bands, and it is subsequently tuned to be applicable to Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua data. When compared with large in situ data sets and satellite matchups in a variety of coastal and ocean waters the present algorithm makes good retrievals of the Chl a concentration and shows statistically significant improvement over current global algorithms (e.g., OC3 and OC4v4). An examination of the performance of these algorithms on several MODIS/Aqua images in complex waters of the Arabian Sea and west Florida shelf shows that the new algorithm provides a better means for detecting and differentiating algal blooms from other turbid features, whereas the OC3 algorithm has significant errors although yielding relatively consistent results in clear waters. These findings imply that, provided that an accurate atmospheric correction scheme is available to deal with complex waters, the current MODIS/Aqua, MERIS and OCM data could be extensively used for quantitative and operational monitoring of algal blooms in various regional and global waters.

A Novel Algorithm for Color Space Conversion Model from CMYK to LAB

OpenAIRE

Juan-li Hu; Jia-bing Deng; Shan-shan Zou

2010-01-01

Color space conversion has become a very important role in the image acquisition, display and the transmission of the color information in the replication. Printers and Image setter express color by CMYK space. But if color is edited and corrected in the CMYK space, it will cause a greater loss of color, and the Computing of computer will also be slowed down. So it often needs to be converted to a LAB uniform color space. Among the previous conversion methods, there is a widespread problem th...

Regression analysis for LED color detection of visual-MIMO system

Science.gov (United States)

Banik, Partha Pratim; Saha, Rappy; Kim, Ki-Doo

2018-04-01

Color detection from a light emitting diode (LED) array using a smartphone camera is very difficult in a visual multiple-input multiple-output (visual-MIMO) system. In this paper, we propose a method to determine the LED color using a smartphone camera by applying regression analysis. We employ a multivariate regression model to identify the LED color. After taking a picture of an LED array, we select the LED array region, and detect the LED using an image processing algorithm. We then apply the k-means clustering algorithm to determine the number of potential colors for feature extraction of each LED. Finally, we apply the multivariate regression model to predict the color of the transmitted LEDs. In this paper, we show our results for three types of environmental light condition: room environmental light, low environmental light (560 lux), and strong environmental light (2450 lux). We compare the results of our proposed algorithm from the analysis of training and test R-Square (%) values, percentage of closeness of transmitted and predicted colors, and we also mention about the number of distorted test data points from the analysis of distortion bar graph in CIE1931 color space.

Digital image processing an algorithmic approach with Matlab

CERN Document Server

Qidwai, Uvais

2009-01-01

Introduction to Image Processing and the MATLAB EnvironmentIntroduction Digital Image Definitions: Theoretical Account Image Properties MATLAB Algorithmic Account MATLAB CodeImage Acquisition, Types, and File I/OImage Acquisition Image Types and File I/O Basics of Color Images Other Color Spaces Algorithmic Account MATLAB CodeImage ArithmeticIntroduction Operator Basics Theoretical TreatmentAlgorithmic Treatment Coding ExamplesAffine and Logical Operations, Distortions, and Noise in ImagesIntroduction Affine Operations Logical Operators Noise in Images Distortions in ImagesAlgorithmic Account

Investigating Rhône River plume (Gulf of Lions, France) dynamics using metrics analysis from the MERIS 300m Ocean Color archive (2002-2012)

Science.gov (United States)

Gangloff, Aurélien; Verney, Romaric; Doxaran, David; Ody, Anouck; Estournel, Claude

2017-07-01

In coastal environments, river plumes are major transport mechanisms for particulate matter, nutriments and pollutants. Ocean color satellite imagery is a valuable tool to explore river turbid plume characteristics, providing observations at high temporal and spatial resolutions of suspended particulate matter (SPM) concentration over a long time period, covering a wide range of hydro-meteorological conditions. We propose here to use the MERIS-FR (300m) Ocean Color archive (2002-2012) in order to investigate Rhône River turbid plume patterns generated by the two main forcings acting on the north-eastern part of the Gulf of Lions (France): wind and river freshwater discharge. Results are exposed considering plume metrics (area of extension, south-east-westernmost points, shape, centroid, SPM concentrations) extracted from satellite data using an automated image-processing tool. Rhône River turbid plume SPM concentrations and area of extension are shown to be mainly driven by the river outflow while wind direction acts on its shape and orientation. This paper also presents the region of influence of the Rhône River turbid plume over monthly and annual periods, and highlights its interannual variability.

Fast and robust wavelet-based dynamic range compression and contrast enhancement model with color restoration

Science.gov (United States)

Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur

2009-05-01

Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.

Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

Directory of Open Access Journals (Sweden)

Dayong Zhou

2008-12-01

Full Text Available Tsatsanis and Xu have applied the constrained minimum output variance (CMOV principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.

INVESTIGATION THE BEHAVIOR OF MODIS OCEAN COLOR PRODUCTS UNDER THE 2008 RED TIDE IN THE EASTERN PERSIAN GULF

Directory of Open Access Journals (Sweden)

M. Ghanea

2015-12-01

Full Text Available Biophysical properties of water undergo serious variations under red tide (RT outbreak. During RT conditions, algal blooms spread out in the estuarine, marine and fresh waters due to different triggering factors such as nutrient loading, marine currents, and monsoonal winds. The Persian Gulf (PG was a talent region subjected to different RTs in recent decade. A massive RT started from the Strait of Hormuz in October 2008 and extended towards the northern parts of the PG covering more than 1200 km of coastlines. The bloom of microorganism C. Polykrikoides was the main specie that generated large fish mortalities, and hampered marine industries, and water desalination appliances. Ocean color satellite data have many advantages to monitor and alarm RT occurrences, such as wide and continuous extent, short time of imagery, high accessibility, and appropriate estimation of ocean color parameters. Since 1999, MODerate Resolution Imaging Spectroradiometer (MODIS satellite sensor has estimated satellite derived chlorophyll-a (Chl-a, normalized fluorescence line height (nFLH, and diffuse attenuation coefficient at 490nm (kd490. It provides a capability to study the behavior of these parameters during RT and normal conditions. This study monitors variations in satellite derived Chl-a, nFLH, and kd490 under both RT and normal conditions of the PG between 2002 and 2008. Up to now, daily and monthly variations in these products were no synchronously investigated under RT conditions in the PG. In doing so, the MODIS L1B products were provided from NASA data archive. They were corrected for Rayleigh scattering and gaseous absorption, and atmospheric interference in turbid coastal waters, and then converted to level 2 data. In addition, Enhanced Red Green Blue (ERGB image was used to illustrate better water variations. ERGB image was built with three normalized leaving water radiance between 443 to 560nm. All the above data processes were applied by SeaDAS 7

Incident Light Frequency-Based Image Defogging Algorithm

Directory of Open Access Journals (Sweden)

Wenbo Zhang

2017-01-01

Full Text Available To solve the color distortion problem produced by the dark channel prior algorithm, an improved method for calculating transmittance of all channels, respectively, was proposed in this paper. Based on the Beer-Lambert Law, the influence between the frequency of the incident light and the transmittance was analyzed, and the ratios between each channel’s transmittance were derived. Then, in order to increase efficiency, the input image was resized to a smaller size before acquiring the refined transmittance which will be resized to the same size of original image. Finally, all the transmittances were obtained with the help of the proportion between each color channel, and then they were used to restore the defogging image. Experiments suggest that the improved algorithm can produce a much more natural result image in comparison with original algorithm, which means the problem of high color saturation was eliminated. What is more, the improved algorithm speeds up by four to nine times compared to the original algorithm.

Advancing Atmosphere-Ocean Remote Sensing with Spaceborne High Spectral Resolution Lidar

Science.gov (United States)

Hostetler, C. A.; Behrenfeld, M. J.; Chepfer, H.; Hu, Y.; Hair, J. W.; Trepte, C. R.; Winker, D. M.; Ferrare, R. A.; Burton, S. P.; Scarino, A. J.; Powell, K. A.; Michaud, J.

2016-12-01

More than 1600 publications employing observations from the CALIOP lidar on CALIPSO testify to the value of spaceborne lidar for aerosol and cloud remote sensing. Recent publications have shown the value of CALIOP data for retrievals of key ocean carbon cycle stocks. In this presentation we focus on the advantages of a more advanced technique, High Spectral Resolution Lidar (HSRL), for aerosol, cloud, and ocean remote sensing. An atmosphere-ocean optimized HSRL achieves greater accuracy over the standard backscatter lidar technique for retrievals of aerosol and cloud extinction and backscatter profiles, provides additional capability to retrieve aerosol and cloud microphysical parameters, and enables vertically-resolved characterization of scattering and absorption properties of suspended and dissolved materials in the ocean. Numerous publications highlight the synergy of coincident CALIOP and passive A-train observations for studies of aerosol-cloud radiative effects and cloud-climate feedback. Less appreciated is the complementarity that would exist between an optimized spaceborne lidar and passive ocean color. An optimized HSRL flown in formation with the Plankton, Aerosol, and ocean Ecosystem (PACE) mission would provide phytoplankton vertical distribution, which is needed for accurately estimating net primary productivity but absent in the PACE ocean color data. The HSRL would also provide data needed to improve atmospheric correction schemes in ocean color retrievals. Because lidar provides measurements both night and day, through tenuous clouds and aerosol layers, and in holes between clouds, the sampling achieved is highly complementary to passive radiometry, providing data in important high latitude regions where ocean color data are sparse or nonexistent. In this presentation we will discuss 1) relevant aerosol, cloud, and ocean retrievals from airborne HSRL field missions; 2) the advantages of an optimized spaceborne HSRL for aerosol, cloud, and ocean

A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography.

Science.gov (United States)

Grassmann, Felix; Mengelkamp, Judith; Brandl, Caroline; Harsch, Sebastian; Zimmermann, Martina E; Linkohr, Birgit; Peters, Annette; Heid, Iris M; Palm, Christoph; Weber, Bernhard H F

2018-04-10

Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these require in-depth and time-consuming analysis of fundus images. Herein, we present an automated computer-based classification algorithm. Algorithm development for AMD classification based on a large collection of color fundus images. Validation is performed on a cross-sectional, population-based study. We included 120 656 manually graded color fundus images from 3654 Age-Related Eye Disease Study (AREDS) participants. AREDS participants were >55 years of age, and non-AMD sight-threatening diseases were excluded at recruitment. In addition, performance of our algorithm was evaluated in 5555 fundus images from the population-based Kooperative Gesundheitsforschung in der Region Augsburg (KORA; Cooperative Health Research in the Region of Augsburg) study. We defined 13 classes (9 AREDS steps, 3 late AMD stages, and 1 for ungradable images) and trained several convolution deep learning architectures. An ensemble of network architectures improved prediction accuracy. An independent dataset was used to evaluate the performance of our algorithm in a population-based study. κ Statistics and accuracy to evaluate the concordance between predicted and expert human grader classification. A network ensemble of 6 different neural net architectures predicted the 13 classes in the AREDS test set with a quadratic weighted κ of 92% (95% confidence interval, 89%-92%) and an overall accuracy of 63.3%. In the independent KORA dataset, images wrongly classified as AMD were mainly the result of a macular reflex observed in young individuals. By restricting the KORA analysis to individuals >55 years of age and prior exclusion of other retinopathies, the weighted and unweighted κ increased to 50% and 63%, respectively. Importantly, the algorithm

A Color Image Watermarking Scheme Resistant against Geometrical Attacks

Directory of Open Access Journals (Sweden)

Y. Xing

2010-04-01

Full Text Available The geometrical attacks are still a problem for many digital watermarking algorithms at present. In this paper, we propose a watermarking algorithm for color images resistant to geometrical distortions (rotation and scaling. The singular value decomposition is used for watermark embedding and extraction. The log-polar map- ping (LPM and phase correlation method are used to register the position of geometrical distortion suffered by the watermarked image. Experiments with different kinds of color images and watermarks demonstrate that the watermarking algorithm is robust to common image processing attacks, especially geometrical attacks.

Southern Ocean Predicted Seafloor Topography Poster - MGG9

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This 36 by 48 inch full color poster is MGG Report 9. In many areas of the global ocean, the depth of the seafloor is not well known because survey lines by ships...

Compressed Subsequence Matching and Packed Tree Coloring

DEFF Research Database (Denmark)

Bille, Philip; Cording, Patrick Hagge; Gørtz, Inge Li

2017-01-01

We present a new algorithm for subsequence matching in grammar compressed strings. Given a grammar of size n compressing a string of size N and a pattern string of size m over an alphabet of size \\(\\sigma \\), our algorithm uses \\(O(n+\\frac{n\\sigma }{w})\\) space and \\(O(n+\\frac{n\\sigma }{w}+m\\log N\\log...... w\\cdot occ)\\) or \\(O(n+\\frac{n\\sigma }{w}\\log w+m\\log N\\cdot occ)\\) time. Here w is the word size and occ is the number of minimal occurrences of the pattern. Our algorithm uses less space than previous algorithms and is also faster for \\(occ=o(\\frac{n}{\\log N})\\) occurrences. The algorithm uses...... a new data structure that allows us to efficiently find the next occurrence of a given character after a given position in a compressed string. This data structure in turn is based on a new data structure for the tree color problem, where the node colors are packed in bit strings....

Three-coloring graphs with no induced seven-vertex path II : using a triangle

OpenAIRE

Chudnovsky, Maria; Maceli, Peter; Zhong, Mingxian

2015-01-01

In this paper, we give a polynomial time algorithm which determines if a given graph containing a triangle and no induced seven-vertex path is 3-colorable, and gives an explicit coloring if one exists. In previous work, we gave a polynomial time algorithm for three-coloring triangle-free graphs with no induced seven-vertex path. Combined, our work shows that three-coloring a graph with no induced seven-vertex path can be done in polynomial time.

Contourlet domain multiband deblurring based on color correlation for fluid lens cameras.

Science.gov (United States)

Tzeng, Jack; Liu, Chun-Chen; Nguyen, Truong Q

2010-10-01

Due to the novel fluid optics, unique image processing challenges are presented by the fluidic lens camera system. Developed for surgical applications, unique properties, such as no moving parts while zooming and better miniaturization than traditional glass optics, are advantages of the fluid lens. Despite these abilities, sharp color planes and blurred color planes are created by the nonuniform reaction of the liquid lens to different color wavelengths. Severe axial color aberrations are caused by this reaction. In order to deblur color images without estimating a point spread function, a contourlet filter bank system is proposed. Information from sharp color planes is used by this multiband deblurring method to improve blurred color planes. Compared to traditional Lucy-Richardson and Wiener deconvolution algorithms, significantly improved sharpness and reduced ghosting artifacts are produced by a previous wavelet-based method. Directional filtering is used by the proposed contourlet-based system to adjust to the contours of the image. An image is produced by the proposed method which has a similar level of sharpness to the previous wavelet-based method and has fewer ghosting artifacts. Conditions for when this algorithm will reduce the mean squared error are analyzed. While improving the blue color plane by using information from the green color plane is the primary focus of this paper, these methods could be adjusted to improve the red color plane. Many multiband systems such as global mapping, infrared imaging, and computer assisted surgery are natural extensions of this work. This information sharing algorithm is beneficial to any image set with high edge correlation. Improved results in the areas of deblurring, noise reduction, and resolution enhancement can be produced by the proposed algorithm.

Deciding the On-line Chromatic Number of a Graph with Pre-coloring is PSPACE-complete

DEFF Research Database (Denmark)

Kudahl, Christian

2015-01-01

In an on-line coloring, the vertices of a graph are revealed one by one. An algorithm assigns a color to each vertex after it is revealed. When a vertex is revealed, it is also revealed which of the previous vertices it is adjacent to. The on-line chromatic number of a graph, G, is the smallest...... number of colors an algorithm will need when on-line-coloring G. The algorithm may know G, but not the order in which the vertices are revealed. The problem of determining if the on-line chromatic number of a graph is less than or equal to k, given a pre-coloring, is shown to be PSPACE-complete....

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

Science.gov (United States)

Brewin, Robert J.W.; Sathyendranath, Shubha; Muller, Dagmar; Brockmann, Carsten; Deschamps, Pierre-Yves; Devred, Emmanuel; Doerffer, Roland; Fomferra, Norman; Franz, Bryan; Grant, Mike;

Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS

Directory of Open Access Journals (Sweden)

Tara Blakey

2016-10-01

Full Text Available This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning.

Airborne Ocean Color Imager Experiment Data 1988 - 1991

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic and fisheries data were collected during 1988 through 1991 through a multiagency research project to develop a remote sensing system to provide near...

Estimators of primary production for interpretation of remotely sensed data on ocean color

Science.gov (United States)

Platt, Trevor; Sathyendranath, Shubha

1993-01-01

The theoretical basis is explained for some commonly used estimators of daily primary production in a vertically uniform water column. These models are recast into a canonical form, with dimensionless arguments, to facilitate comparison with each other and with an analytic solution. The limitations of each model are examined. The values of the photoadaptation parameter I(k) observed in the ocean are analyzed, and I(k) is used as a scale to normalize the surface irradiance. The range of this scaled irradiance is presented. An equation is given for estimation of I(k) from recent light history. It is shown how the models for water column production can be adapted for estimation of the production in finite layers. The distinctions between model formulation, model implementation and model evaluation are discussed. Recommendations are given on the choice of algorithm for computation of daily production according to the degree of approximation acceptable in the result.

Gravity Field Over the S.Ocean - Poster, MGG-6

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This is a full color 24 by 36 inch poster. In many areas of the global ocean, the depth of the seafloor is not well known because survey lines by ships are hundreds...

Regional ocean-colour chlorophyll algorithms for the Red Sea

KAUST Repository

Brewin, Robert J.W.; Raitsos, Dionysios E.; Dall'Olmo, Giorgio; Zarokanellos, Nikolaos; Jackson, Thomas; Racault, Marie-Fanny; Boss, Emmanuel S.; Sathyendranath, Shubha; Jones, Burton; Hoteit, Ibrahim

2015-01-01

an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll

The study of the ocean from space

Energy Technology Data Exchange (ETDEWEB)

Novogrudskii, B V; Skliarov, V E; Fedorov, K N; Shifrin, K S

1978-01-01

The application of earth satellites and manned spacecraft to the study of the world's oceans is reviewed. Attention is given to the atmospheric transfer function in the visible, near-IR, middle-IR and microwave regions and the use of satellites in ocean data acquisition and transmission systems. The measurement of sea level and the topography of the ocean surface by means of orbital radar altimeters is discussed, together with IR and microwave measurements of ocean surface temperature and the study of surface roughness, surface evidence of internal waves, oil pollution and ice fields. Consideration is also given to the determination of ocean chlorophyll content and color distribution, coastal region characteristics, ocean salinity and other biological parameters from space.

Color-weak compensation using local affine isometry based on discrimination threshold matching

OpenAIRE

Mochizuki, Rika; Kojima, Takanori; Lenz, Reiner; Chao, Jinhui

2015-01-01

We develop algorithms for color-weak compensation and color-weak simulation based on Riemannian geometry models of color spaces. The objective function introduced measures the match of color discrimination thresholds of average normal observers and a color-weak observer. The developed matching process makes use of local affine maps between color spaces of color-normal and color-weak observers. The method can be used to generate displays of images that provide color-normal and color-weak obser...

Hyperspectral Imager for the Coastal Ocean (HICO): Overview, Operational Updates, and Coastal Ocean Applications

Science.gov (United States)

Davis, Curtiss O.; Kappus, Mary E.; Bowles, Jeffrey H.; Evans, Cynthia A.; Stefanov, William L.

2014-01-01

The Hyperspectral Imager for the Coastal Ocean (HICO) was built to measure in-water properties of complex coastal regions. HICO enables synoptic coverage; 100-meter spatial resolution for sampling the variability and spatial irregularity of coastal waters; and high spectral resolution to untangle the signals from chlorophyll, colored dissolved organic matter, suspended sediments and varying bottom types. HICO was built by the Naval Research Laboratory, installed on the International Space Station (ISS) in September 2009, and operated for ONR for the first three years. In 2013, NASA assumed sponsorship of operations in order to leverage HICO's ability to address their Earth monitoring mission. This has opened up access of HICO data to the broad research community. Over 8000 images are now available on NASA's Ocean Color Website (http://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=hi). Oregon State University's HICO website (http://hico.coas.oregonstate.edu) remains the portal for researchers to request new collections and access their requested data. We will present updates on HICO's calibration and improvements in geolocation and show examples of the use of HICO data to address issues in the coastal ocean and Great Lakes.

The Hyperspectral Imager for the Coastal Ocean (HICO): Sensor and Data Processing Overview

Science.gov (United States)

2010-01-20

backscattering coefficients, and others. Several of these software modules will be developed within the Automated Processing System (APS), a data... Automated Processing System (APS) NRL developed APS, which processes satellite data into ocean color data products. APS is a collection of methods...used for ocean color processing which provide the tools for the automated processing of satellite imagery [1]. These tools are in the process of

Frog: Asynchronous Graph Processing on GPU with Hybrid Coloring Model

Energy Technology Data Exchange (ETDEWEB)

Shi, Xuanhua; Luo, Xuan; Liang, Junling; Zhao, Peng; Di, Sheng; He, Bingsheng; Jin, Hai

2018-01-01

GPUs have been increasingly used to accelerate graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or atomic operations, leading to significant penalties/overheads when implemented on GPUs. As such, coloring algorithm is adopted to separate the vertices with potential updating conflicts, guaranteeing the consistency/correctness of the parallel processing. Common coloring algorithms, however, may suffer from low parallelism because of a large number of colors generally required for processing a large-scale graph with billions of vertices. We propose a light-weight asynchronous processing framework called Frog with a preprocessing/hybrid coloring model. The fundamental idea is based on Pareto principle (or 80-20 rule) about coloring algorithms as we observed through masses of realworld graph coloring cases. We find that a majority of vertices (about 80%) are colored with only a few colors, such that they can be read and updated in a very high degree of parallelism without violating the sequential consistency. Accordingly, our solution separates the processing of the vertices based on the distribution of colors. In this work, we mainly answer three questions: (1) how to partition the vertices in a sparse graph with maximized parallelism, (2) how to process large-scale graphs that cannot fit into GPU memory, and (3) how to reduce the overhead of data transfers on PCIe while processing each partition. We conduct experiments on real-world data (Amazon, DBLP, YouTube, RoadNet-CA, WikiTalk and Twitter) to evaluate our approach and make comparisons with well-known non-preprocessed (such as Totem, Medusa, MapGraph and Gunrock) and preprocessed (Cusha) approaches, by testing four classical algorithms (BFS, PageRank, SSSP and CC). On all the tested applications and

Modelling ocean-colour-derived chlorophyll a

Directory of Open Access Journals (Sweden)

S. Dutkiewicz

2018-01-01

Full Text Available This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called derived Chl a in this paper. We compare the derived Chl a to the actual model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that region-specific algorithms provide a significant improvement, at least in the annual mean. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter. The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation

Harmonious colors: from alchemy to science

Science.gov (United States)

Beretta, Giordano B.; Moroney, Nathan M.

2012-01-01

There is a very long tradition in designing color palettes for various applications, going back to at least the Upanishad. Although color palettes have been influenced by the available colorants, starting with the advent of aniline dyes in the late 1850s there have been few physical limits on the choice of individual colors. This abundance of choices exacerbates the problem of limiting the number of colors in a palette, i.e., in keeping them into a manageable quantity. For example, it is not practical for a car company to offer each model in hundreds of colors. Instead, for each model year a small number of color palettes is offered, each containing the colors for the body, trim, interior, etc. Another example is the fashion industry, where in addition to solid colors there are also patterns, leading to a huge variety of combinations that would be impossible to stock. The traditional solution is that of "color forecasting." Color consultants assess the sentiment or affective state of a target customer class and compare it with new colorants offered by the industry. They assemble a limited color palette, name the colors according to the sentiment, and publish their result. Textile manufacturers will produce fabrics in these colors and fashion designers will design clothes, accessories, and furniture based on these fabrics. Eventually, the media will communicate these forecasts to the consumers, who will be admired by their cohorts when they choose colors from the forecast palette, which by then is widely diffused. The color forecasting business is very labor intensive and difficult, thus for years computer engineers have tried to come up with algorithms to design harmonious color palettes, alas with little commercial success. For example, Johannes Itten's color theory has been implemented many times, but despite Itten's success in the Bauhaus artifacts, the computer tools have been of little utility. Indeed, contrary to the auditory sense, there is no known

A color based face detection system using multiple templates

Institute of Scientific and Technical Information of China (English)

王涛; 卜佳俊; 陈纯

2003-01-01

A color based system using multiple templates was developed and implemented for detecting human faces in color images. The algorithm consists of three image processing steps. The first step is human skin color statistics. Then it separates skin regions from non-skin regions. After that, it locates the frontal human face(s) within the skin regions. In the first step, 250 skin samples from persons of different ethnicities are used to determine the color distribution of human skin in chromatic color space in order to get a chroma chart showing likelihoods of skin colors. This chroma chart is used to generate, from the original color image, a gray scale image whose gray value at a pixel shows its likelihood of representing the skin. The algorithm uses an adaptive thresholding process to achieve the optimal threshold value for dividing the gray scale image into separate skin regions from non skin regions. Finally, multiple face templates matching is used to determine if a given skin region represents a frontal human face or not. Test of the system with more than 400 color images showed that the resulting detection rate was 83%, which is better than most color-based face detection systems. The average speed for face detection is 0.8 second/image (400×300 pixels) on a Pentium 3 (800MHz) PC.

Ocean Bottom Pressure Seasonal Cycles and Decadal Trends from GRACE Release-05: Ocean Circulation Implications

Science.gov (United States)

Johnson, G. C.; Chambers, D. P.

2013-12-01

Ocean mass variations are important for diagnosing sea level budgets, the hydrological cycle and global energy budget, as well as ocean circulation variability. Here seasonal cycles and decadal trends of ocean mass from January 2003 to December 2012, both global and regional, are analyzed using GRACE Release 05 data. The trend of global flux of mass into the ocean approaches 2 cm decade-1 in equivalent sea level rise. Regional trends are of similar magnitude, with the North Pacific, South Atlantic, and South Indian oceans generally gaining mass and other regions losing mass. These trends suggest a spin-down of the North Pacific western boundary current extension and the Antarctic Circumpolar Current in the South Atlantic and South Indian oceans. The global average seasonal cycle of ocean mass is about 1 cm in amplitude, with a maximum in early October and volume fluxes in and out of the ocean reaching 0.5 Sv (1 Sv = 1 × 106 m3 s-1) when integrated over the area analyzed here. Regional patterns of seasonal ocean mass change have typical amplitudes of 1-4 cm, and include maxima in the subtropics and minima in the subpolar regions in hemispheric winters. The subtropical mass gains and subpolar mass losses in the winter spin up both subtropical and subpolar gyres, hence the western boundary current extensions. Seasonal variations in these currents are order 10 Sv, but since the associated depth-averaged current variations are only order 0.1 cm s-1, they would be difficult to detect using in situ oceanographic instruments. a) Amplitude (colors, in cm) and b) phase (colors, in months of the year) of an annual harmonic fit to monthly GRACE Release 05 CSR 500 km smoothed maps (concurrently with a trend and the semiannual harmonic). The 97.5% confidence interval for difference from zero is also indicated (solid black line). Data within 300 km of coastlines are not considered.

Guided color consistency optimization for image mosaicking

Science.gov (United States)

Xie, Renping; Xia, Menghan; Yao, Jian; Li, Li

2018-01-01

This paper studies the problem of color consistency correction for sequential images with diverse color characteristics. Existing algorithms try to adjust all images to minimize color differences among images under a unified energy framework, however, the results are prone to presenting a consistent but unnatural appearance when the color difference between images is large and diverse. In our approach, this problem is addressed effectively by providing a guided initial solution for the global consistency optimization, which avoids converging to a meaningless integrated solution. First of all, to obtain the reliable intensity correspondences in overlapping regions between image pairs, we creatively propose the histogram extreme point matching algorithm which is robust to image geometrical misalignment to some extents. In the absence of the extra reference information, the guided initial solution is learned from the major tone of the original images by searching some image subset as the reference, whose color characteristics will be transferred to the others via the paths of graph analysis. Thus, the final results via global adjustment will take on a consistent color similar to the appearance of the reference image subset. Several groups of convincing experiments on both the synthetic dataset and the challenging real ones sufficiently demonstrate that the proposed approach can achieve as good or even better results compared with the state-of-the-art approaches.

Applications of color machine vision in the agricultural and food industries

Science.gov (United States)

Zhang, Min; Ludas, Laszlo I.; Morgan, Mark T.; Krutz, Gary W.; Precetti, Cyrille J.

1999-01-01

Color is an important factor in Agricultural and the Food Industry. Agricultural or prepared food products are often grade by producers and consumers using color parameters. Color is used to estimate maturity, sort produce for defects, but also perform genetic screenings or make an aesthetic judgement. The task of sorting produce following a color scale is very complex, requires special illumination and training. Also, this task cannot be performed for long durations without fatigue and loss of accuracy. This paper describes a machine vision system designed to perform color classification in real-time. Applications for sorting a variety of agricultural products are included: e.g. seeds, meat, baked goods, plant and wood.FIrst the theory of color classification of agricultural and biological materials is introduced. Then, some tools for classifier development are presented. Finally, the implementation of the algorithm on real-time image processing hardware and example applications for industry is described. This paper also presented an image analysis algorithm and a prototype machine vision system which was developed for industry. This system will automatically locate the surface of some plants using digital camera and predict information such as size, potential value and type of this plant. The algorithm developed will be feasible for real-time identification in an industrial environment.

A robust embedded vision system feasible white balance algorithm

Science.gov (United States)

Wang, Yuan; Yu, Feihong

2018-01-01

White balance is a very important part of the color image processing pipeline. In order to meet the need of efficiency and accuracy in embedded machine vision processing system, an efficient and robust white balance algorithm combining several classical ones is proposed. The proposed algorithm mainly has three parts. Firstly, in order to guarantee higher efficiency, an initial parameter calculated from the statistics of R, G and B components from raw data is used to initialize the following iterative method. After that, the bilinear interpolation algorithm is utilized to implement demosaicing procedure. Finally, an adaptive step adjustable scheme is introduced to ensure the controllability and robustness of the algorithm. In order to verify the proposed algorithm's performance on embedded vision system, a smart camera based on IMX6 DualLite, IMX291 and XC6130 is designed. Extensive experiments on a large amount of images under different color temperatures and exposure conditions illustrate that the proposed white balance algorithm avoids color deviation problem effectively, achieves a good balance between efficiency and quality, and is suitable for embedded machine vision processing system.

Comparing objective and subjective error measures for color constancy

NARCIS (Netherlands)

Lucassen, M.P.; Gijsenij, A.; Gevers, T.

2008-01-01

We compare an objective and a subjective performance measure for color constancy algorithms. Eight hyper-spectral images were rendered under a neutral reference illuminant and four chromatic illuminants (Red, Green, Yellow, Blue). The scenes rendered under the chromatic illuminants were color

Segmentation and Classification of Burn Color Images

National Research Council Canada - National Science Library

Acha, Begonya

2001-01-01

.... In the classification part, we take advantage of color information by clustering, with a vector quantization algorithm, the color centroids of small squares, taken from the burnt segmented part of the image, in the (V1, V2) plane into two possible groups, where V1 and V2 are the two chrominance components of the CIE Lab representation.

Tests of numerical simulation algorithms for the Kubo oscillator

International Nuclear Information System (INIS)

Fox, R.F.; Roy, R.; Yu, A.W.

1987-01-01

Numerical simulation algorithms for multiplicative noise (white or colored) are tested for accuracy against closed-form expressions for the Kubo oscillator. Direct white noise simulations lead to spurious decay of the modulus of the oscillator amplitude. A straightforward colored noise algorithm greatly reduces this decay and also provides highly accurate results in the white noise limit

Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA

Directory of Open Access Journals (Sweden)

John P. Ryan

2014-01-01

Full Text Available As a demonstrator for technologies for the next generation of ocean color sensors, the Hyperspectral Imager for the Coastal Ocean (HICO provides enhanced spatial and spectral resolution that is required to understand optically complex aquatic environments. In this study we apply HICO, along with satellite remote sensing and in situ observations, to studies of phytoplankton ecology in a dynamic coastal upwelling environment—Monterey Bay, CA, USA. From a spring 2011 study, we examine HICO-detected spatial patterns in phytoplankton optical properties along an environmental gradient defined by upwelling flow patterns and along a temporal gradient of upwelling intensification. From a fall 2011 study, we use HICO’s enhanced spatial and spectral resolution to distinguish a small-scale “red tide” bloom, and we examine bloom expansion and its supporting processes using other remote sensing and in situ data. From a spectacular HICO image of the Monterey Bay region acquired during fall of 2012, we present a suite of algorithm results for characterization of phytoplankton, and we examine the strengths, limitations, and distinctions of each algorithm in the context of the enhanced spatial and spectral resolution.

SeaHawk: an advanced CubeSat mission for sustained ocean colour monitoring

Science.gov (United States)

Morrison, John M.; Jeffrey, Hazel; Gorter, Hessel; Anderson, Pamela; Clark, Craig; Holmes, Alan; Feldman, Gene C.; Patt, Frederick S.

2016-10-01

Sustained ocean color monitoring is vital to understanding the marine ecosystem. It has been identified as an Essential Climate Variable (ECV) and is a vital parameter in understanding long-term climate change. Furthermore, observations can be beneficial in observing oil spills, harmful algal blooms and the health of fisheries. Space-based remote sensing, through MERIS, SeaWiFS and MODIS instruments, have provided a means of observing the vast area covered by the ocean which would otherwise be impossible using ships alone. However, the large pixel size makes measurements of lakes, rivers, estuaries and coastal zones difficult. Furthermore, retirement of a number of widely used and relied upon ocean observation instruments, particularly MERIS and SeaWiFS, leaves a significant gap in ocean color observation opportunities This paper presents an overview of the SeaHawk mission, a collaborative effort between Clyde Space Ltd., the University of North Carolina Wilmington, Cloudland Instruments, and Goddard Spaceflight Center, funded by the Gordon and Betty Moore Foundation. The goal of the project is to enhance the ability to observe ocean color in high temporal and spatial resolution through use of a low-cost, next-generation ocean color sensor flown aboard a CubeSat. The final product will be 530 times smaller (0.0034 vs 1.81m3) and 115 time less massive (3.4 vs 390.0kg) but with a ground resolution 10 times better whilst maintaining a signal/noise ratio 50% that of SeaWiFs. This paper will describe the objectives of the mission, outline the payload specification and the spacecraft platform to support it.

Dichromatic Gray Pixel for Camera-agnostic Color Constancy

OpenAIRE

Qian, Yanlin; Chen, Ke; Nikkanen, Jarno; Kämäräinen, Joni-Kristian; Matas, Jiri

2018-01-01

We propose a novel statistical color constancy method, especially suitable for the Camera-agnostic Color Constancy, i.e. the scenario where nothing is known a priori about the capturing devices. The method, called Dichromatic Gray Pixel, or DGP, relies on a novel gray pixel detection algorithm derived using the Dichromatic Reflection Model. DGP is suitable for camera-agnostic color constancy since varying devices are set to make achromatic pixels look gray under standard neutral illumination....

Geometric approximation algorithms

CERN Document Server

Har-Peled, Sariel

2011-01-01

Exact algorithms for dealing with geometric objects are complicated, hard to implement in practice, and slow. Over the last 20 years a theory of geometric approximation algorithms has emerged. These algorithms tend to be simple, fast, and more robust than their exact counterparts. This book is the first to cover geometric approximation algorithms in detail. In addition, more traditional computational geometry techniques that are widely used in developing such algorithms, like sampling, linear programming, etc., are also surveyed. Other topics covered include approximate nearest-neighbor search, shape approximation, coresets, dimension reduction, and embeddings. The topics covered are relatively independent and are supplemented by exercises. Close to 200 color figures are included in the text to illustrate proofs and ideas.

Live texturing of augmented reality characters from colored drawings.

Science.gov (United States)

Magnenat, Stéphane; Ngo, Dat Tien; Zünd, Fabio; Ryffel, Mattia; Noris, Gioacchino; Rothlin, Gerhard; Marra, Alessia; Nitti, Maurizio; Fua, Pascal; Gross, Markus; Sumner, Robert W

2015-11-01

Coloring books capture the imagination of children and provide them with one of their earliest opportunities for creative expression. However, given the proliferation and popularity of digital devices, real-world activities like coloring can seem unexciting, and children become less engaged in them. Augmented reality holds unique potential to impact this situation by providing a bridge between real-world activities and digital enhancements. In this paper, we present an augmented reality coloring book App in which children color characters in a printed coloring book and inspect their work using a mobile device. The drawing is detected and tracked, and the video stream is augmented with an animated 3-D version of the character that is textured according to the child's coloring. This is possible thanks to several novel technical contributions. We present a texturing process that applies the captured texture from a 2-D colored drawing to both the visible and occluded regions of a 3-D character in real time. We develop a deformable surface tracking method designed for colored drawings that uses a new outlier rejection algorithm for real-time tracking and surface deformation recovery. We present a content creation pipeline to efficiently create the 2-D and 3-D content. And, finally, we validate our work with two user studies that examine the quality of our texturing algorithm and the overall App experience.

A color based face detection system using multiple templates

Institute of Scientific and Technical Information of China (English)

王涛; 卜佳酸; 陈纯

2003-01-01

A color based system using multiple templates was developed and implemented for detecting hu-man faces in color images.The algorithm comsists of three image processing steps.The first step is human skin color statistics.Then it separates skin regions from non-skin regions.After that,it locates the frontal human face(s) within the skin regions.In the first step,250 skin samples from persons of different ethnicities are used to determine the color distribution of human skin in chromatic color space in order to get a chroma chart showing likelihoods of skin colors.This chroma chart is used to generate,from the original color image,a gray scale image whose gray value at a pixel shows its likelihood of representing the shin,The algorithm uses an adaptive thresholding process to achieve the optimal threshold value for dividing the gray scale image into sep-arate skin regions from non skin regions.Finally,multiple face templates matching is used to determine if a given skin region represents a frontal human face or not.Test of the system with more than 400 color images showed that the resulting detection rate was 83%,which is better than most colou-based face detection sys-tems.The average speed for face detection is 0.8 second/image(400×300pixels) on a Pentium 3(800MHz) PC.

A Linear Criterion to sort Color Components in Images

Directory of Open Access Journals (Sweden)

Leonardo Barriga Rodriguez

2017-01-01

Full Text Available The color and its representation play a basic role in Image Analysis process. Several methods can be beneficial whenever they have a correct representation of wave-length variations used to represent scenes with a camera. A wide variety of spaces and color representations is founded in specialized literature. Each one is useful in concrete circumstances and others may offer redundant color information (for instance, all RGB components are high correlated. This work deals with the task of identifying and sorting which component from several color representations offers the majority of information about the scene. This approach is based on analyzing linear dependences among each color component, by the implementation of a new sorting algorithm based on entropy. The proposal is tested in several outdoor/indoor scenes with different light conditions. Repeatability and stability are tested in order to guarantee its use in several image analysis applications. Finally, the results of this work have been used to enhance an external algorithm to compensate the camera random vibrations.

Dynamics of the transition zone in coastal zone color scanner-sensed ocean color in the North Pacific during oceanographic spring

Science.gov (United States)

Glover, David M.; Wroblewski, J. S.; Mcclain, Charles R.

1994-01-01

A transition zone in phytoplankton concentration running across the North Pacific basin at 30 deg to 40 deg north latitude corresponds to a basin-wide front in surface chlorophyll observed in a composite of coastal zone color scanner (CZCS) images for May, June, and July 1979-1986. This transition zone with low chlorophyll to the south and higher chlorophyll to the north can be simulated by a simple model of the concentration of phytoplankton, zooplankton, and dissolved nutrient (nitrate) in the surface mixed layer of the ocean applied to the North Pacific basin for the climatological conditions during oceanographic springtime (May, June, and July). The model is initialized with a 1 deg x 1 deg gridded estimate of wintertime (February, March, and April) mixed layer nitrate concentrations calculated from an extensive nutrient database and a similarly gridded mixed layer depth data set. Comparison of model predictions with CZCS data provides a means of evaluating the dynamics of the transition zone. We conclude that in the North Pacific, away from major boundary currents and coastal upwelling zones, wintertime vertical mixing determines the total nutrient available to the plankton ecosystem in the spring. The transition zone seen in basin-scale CZCS images is a reflection of the geographic variation in the wintertime mixed layer depth and the nitracline, leading to a latitudinal gradient in phytoplankton chlorophyll.

A robust human face detection algorithm

Science.gov (United States)

Raviteja, Thaluru; Karanam, Srikrishna; Yeduguru, Dinesh Reddy V.

2012-01-01

Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.

Imaging tristimulus colorimeter for the evaluation of color in printed textiles

Science.gov (United States)

Hunt, Martin A.; Goddard, James S., Jr.; Hylton, Kathy W.; Karnowski, Thomas P.; Richards, Roger K.; Simpson, Marc L.; Tobin, Kenneth W., Jr.; Treece, Dale A.

1999-03-01

The high-speed production of textiles with complicated printed patterns presents a difficult problem for a colorimetric measurement system. Accurate assessment of product quality requires a repeatable measurement using a standard color space, such as CIELAB, and the use of a perceptually based color difference formula, e.g. (Delta) ECMC color difference formula. Image based color sensors used for on-line measurement are not colorimetric by nature and require a non-linear transformation of the component colors based on the spectral properties of the incident illumination, imaging sensor, and the actual textile color. This research and development effort describes a benchtop, proof-of-principle system that implements a projection onto convex sets (POCS) algorithm for mapping component color measurements to standard tristimulus values and incorporates structural and color based segmentation for improved precision and accuracy. The POCS algorithm consists of determining the closed convex sets that describe the constraints on the reconstruction of the true tristimulus values based on the measured imperfect values. We show that using a simulated D65 standard illuminant, commercial filters and a CCD camera, accurate (under perceptibility limits) per-region based (Delta) ECMC values can be measured on real textile samples.

Forward looking anomaly detection via fusion of infrared and color imagery

Science.gov (United States)

Stone, K.; Keller, J. M.; Popescu, M.; Havens, T. C.; Ho, K. C.

2010-04-01

This paper develops algorithms for the detection of interesting and abnormal objects in color and infrared imagery taken from cameras mounted on a moving vehicle, observing a fixed scene. The primary purpose of detection is to cue a human-in-the-loop detection system. Algorithms for direct detection and change detection are investigated, as well as fusion of the two. Both methods use temporal information to reduce the number of false alarms. The direct detection algorithm uses image self-similarity computed between local neighborhoods to determine interesting, or unique, parts of an image. Neighborhood similarity is computed using Euclidean distance in CIELAB color space for the color imagery, and Euclidean distance between grey levels in the infrared imagery. The change detection algorithm uses the affine scale-invariant feature transform (ASIFT) to transform multiple background frames into the current image space. Each transformed image is then compared to the current image, and the multiple outputs are fused to produce a single difference image. Changes in lighting and contrast between the background run and the current run are adjusted for in both color and infrared imagery. Frame-to-frame motion is modeled using a perspective transformation, the parameters of which are computed using scale-invariant feature transform (SIFT) keypoint correspondences. This information is used to perform temporal accumulation of single frame detections for both the direct detection and change detection algorithms. Performance of the proposed algorithms is evaluated on multiple lanes from a data collection at a US Army test site.

Predicting the usefulness and naturalness of color reproductions

NARCIS (Netherlands)

Janssen, T.J.W.M.; Blommaert, F.J.J.

2000-01-01

We present algorithms for predicting the usefulness and naturalness of color reproductions of natural scenes. The algorithms are based on a computational model of the stages that lead to an observer's impression of the usefulness and naturalness of an image. These stages are (1) the perception, or

A Fuzzy Logic-Based Video Subtitle and Caption Coloring System

Directory of Open Access Journals (Sweden)

Mohsen Davoudi

2012-01-01

Full Text Available An approach has been proposed for automatic adaptive subtitle coloring using fuzzy logic-based algorithm. This system changes the color of the video subtitle/caption to “pleasant” color according to color harmony and the visual perception of the image background colors. In the fuzzy analyzer unit, using RGB histograms of background image, the R, G, and B values for the color of the subtitle/caption are computed using fixed fuzzy IF-THEN rules fully driven from the color harmony theories to satisfy complementary color and subtitle-background color harmony conditions. A real-time hardware structure has been proposed for implementation of the front-end processing unit as well as the fuzzy analyzer unit.

Color Segmentation of Homogeneous Areas on Colposcopical Images

Directory of Open Access Journals (Sweden)

Kosteley Yana

2016-01-01

Full Text Available The article provides an analysis of image processing and color segmentation applied to the problem of selection of homogeneous regions in the parameters of the color model. Methods of image processing such as Gaussian filter, median filter, histogram equalization and mathematical morphology are considered. The segmentation algorithm with the parameters of color components is presented, followed by isolation of the resulting connected component of a binary segmentation mask. Analysis of methods performed on images colposcopic research.

A Demosaicking Algorithm with Adaptive Inter-Channel Correlation

Directory of Open Access Journals (Sweden)

Joan Duran

2015-12-01

Full Text Available Most common cameras use a CCD sensor device measuring a single color per pixel. Demosaicking is the interpolation process by which one can infer a full color image from such a matrix of values, thus interpolating the two missing components per pixel. Most demosaicking methods take advantage of inter-channel correlation locally selecting the best interpolation direction. The obtained results look convincing except when local geometry cannot be inferred from neighboring pixels or channel correlation is low. In these cases, these algorithms create interpolation artifacts such as zipper effect or color aliasing. This paper discusses the implementation details of the algorithm proposed in [J. Duran, A. Buades, ``Self-Similarity and Spectral Correlation Adaptive Algorithm for Color Demosaicking'', IEEE Transactions on Image Processing, 23(9, pp. 4031--4040, 2014]. The proposed method involves nonlocal image self-similarity in order to reduce interpolation artifacts when local geometry is ambiguous. It further introduces a clear and intuitive manner of balancing how much channel-correlation must be taken advantage of.

Efficient Color-Dressed Calculation of Virtual Corrections

CERN Document Server

Giele, Walter; Winter, Jan

2010-01-01

With the advent of generalized unitarity and parametric integration techniques, the construction of a generic Next-to-Leading Order Monte Carlo becomes feasible. Such a generator will entail the treatment of QCD color in the amplitudes. We extend the concept of color dressing to one-loop amplitudes, resulting in the formulation of an explicit algorithmic solution for the calculation of arbitrary scattering processes at Next-to-Leading order. The resulting algorithm is of exponential complexity, that is the numerical evaluation time of the virtual corrections grows by a constant multiplicative factor as the number of external partons is increased. To study the properties of the method, we calculate the virtual corrections to $n$-gluon scattering.

STAR Algorithm Integration Team - Facilitating operational algorithm development

Science.gov (United States)

Mikles, V. J.

2015-12-01

The NOAA/NESDIS Center for Satellite Research and Applications (STAR) provides technical support of the Joint Polar Satellite System (JPSS) algorithm development and integration tasks. Utilizing data from the S-NPP satellite, JPSS generates over thirty Environmental Data Records (EDRs) and Intermediate Products (IPs) spanning atmospheric, ocean, cryosphere, and land weather disciplines. The Algorithm Integration Team (AIT) brings technical expertise and support to product algorithms, specifically in testing and validating science algorithms in a pre-operational environment. The AIT verifies that new and updated algorithms function in the development environment, enforces established software development standards, and ensures that delivered packages are functional and complete. AIT facilitates the development of new JPSS-1 algorithms by implementing a review approach based on the Enterprise Product Lifecycle (EPL) process. Building on relationships established during the S-NPP algorithm development process and coordinating directly with science algorithm developers, the AIT has implemented structured reviews with self-contained document suites. The process has supported algorithm improvements for products such as ozone, active fire, vegetation index, and temperature and moisture profiles.

MATHEMATICA APPLICATION FOR GRAPH COLORING AT THE INTERSECTION OF JALAN PANGERAN ANTASARI JAKARTA

Directory of Open Access Journals (Sweden)

Suwarno Suwarno

2017-12-01

Full Text Available This research examines about graph coloring using Welch-Powell algorithm. This research begins by trying to understand about graph coloring and its algorithm. The case study was conducted at the intersection of Pangeran Antasari Street. In the formation of graph obtained 12 vertices as traffic flow and 16 edges as traffic path. The results of this study obtained 4 chromatic numbers which describes 4 stages of traffic light arrangement. This paper also explains the application of Mathematica software in graph coloring.

Color quality management in advanced flat panel display engines

Science.gov (United States)

Lebowsky, Fritz; Neugebauer, Charles F.; Marnatti, David M.

2003-01-01

During recent years color reproduction systems for consumer needs have experienced various difficulties. In particular, flat panels and printers could not reach a satisfactory color match. The RGB image stored on an Internet server of a retailer did not show the desired colors on a consumer display device or printer device. STMicroelectronics addresses this important color reproduction issue inside their advanced display engines using novel algorithms targeted for low cost consumer flat panels. Using a new and genuine RGB color space transformation, which combines a gamma correction Look-Up-Table, tetrahedrization, and linear interpolation, we satisfy market demands.

Image processing algorithm for robot tracking in reactor vessel

International Nuclear Information System (INIS)

Kim, Tae Won; Choi, Young Soo; Lee, Sung Uk; Jeong, Kyung Min; Kim, Nam Kyun

2011-01-01

In this paper, we proposed an image processing algorithm to find the position of an underwater robot in the reactor vessel. Proposed algorithm is composed of Modified SURF(Speeded Up Robust Feature) based on Mean-Shift and CAMSHIFT(Continuously Adaptive Mean Shift Algorithm) based on color tracking algorithm. Noise filtering using luminosity blend method and color clipping are preprocessed. Initial tracking area for the CAMSHIFT is determined by using modified SURF. And then extracting the contour and corner points in the area of target tracked by CAMSHIFT method. Experiments are performed at the reactor vessel mockup and verified to use in the control of robot by visual tracking

Color image digitization and analysis for drum inspection

International Nuclear Information System (INIS)

Muller, R.C.; Armstrong, G.A.; Burks, B.L.; Kress, R.L.; Heckendorn, F.M.; Ward, C.R.

1993-01-01

A rust inspection system that uses color analysis to find rust spots on drums has been developed. The system is composed of high-resolution color video equipment that permits the inspection of rust spots on the order of 0.25 cm (0.1-in.) in diameter. Because of the modular nature of the system design, the use of open systems software (X11, etc.), the inspection system can be easily integrated into other environmental restoration and waste management programs. The inspection system represents an excellent platform for the integration of other color inspection and color image processing algorithms

Factors challenging our ability to detect long-term trends in ocean chlorophyll

Directory of Open Access Journals (Sweden)

C. Beaulieu

2013-04-01

Full Text Available Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multidecadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, which failed in December 2010. The Moderate Resolution Imaging Spectroradiometer (MODIS ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS instrument, or successful launch of the Ocean and Land Colour Instrument (OLCI expected in 2014 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies.

Accurately Measuring the Color of the Ocean on Earth and from Space: Uncertainties Revisited and A Report from the Community-Led Spectral Absorption Workshop to Update and Revise the NASA Inherent Optical Properties Protocol

Science.gov (United States)

Neeley, Aimee Renee

2014-01-01

The color of the ocean (apparent optical properties or AOPs) is determined by the spectral scattering and absorption of light by its dissolved and particulate constituents.The absorption and scattering properties of the water column are the so-called inherent optical properties.

Approximation and hardness results for the maximum edge q-coloring problem

DEFF Research Database (Denmark)

Adamaszek, Anna Maria; Popa, Alexandru

2016-01-01

We consider the problem of coloring edges of a graph subject to the following constraints: for every vertex v, all the edges incident with v have to be colored with at most q colors. The goal is to find a coloring satisfying the above constraints and using the maximum number of colors. Notice...... ϵ>0 and any q≥2 assuming the unique games conjecture (UGC), or 1+−ϵ for any ϵ>0 and any q≥3 (≈1.19 for q=2) assuming P≠NP. These results hold even when the considered graphs are bipartite. On the algorithmic side, we restrict to the case q=2, since this is the most important in practice and we show...... a 5/3-approximation algorithm for graphs which have a perfect matching....

Characterization of Optical Attenuation by Colored Dissolved Organic Matter (CDOM) in the Red Sea

KAUST Repository

Tiwari, Surya Prakash

2016-02-01

Optical properties of colored dissolved organic matter (CDOM) control the downward irradiance in the ultraviolet and visible range of the electromagnetic radiation. CDOM is a strong absorber in shorter wavelengths (ultraviolet light) with steeper spectral slopes in the open ocean. Despite the importance of CDOM in understanding physical and biogeochemical processes in the marine environment, in situ measurements of optical properties in the Red Sea are sparse. This study comprises CDOM absorption from two different instruments (i.e. a spectrophotometer and WET Labs ac-s sensor), and assesses the variations in optical properties of CDOM in the Red Sea using data collected in 2014 and 2015. Three global inversion algorithms (Garver-Siegel-Maritorena model - GSM, Quasi-Analytical Algorithm - QAA, and the Constrained Linear-Matrix inversion model - CLM) were applied to recent data collected in the Red Sea, providing the comparison at five key selected wavelengths (412, 443, 490, 510, and 555 nm) demonstrated that in situ aCDOM values were higher than the values predicted from the three inversion algorithms and leads to underestimating in situ measurements. This finding is consistent with the conclusion of Brewin et al. (2015) that overestimation of chlorophyll in the Red Sea could be due to excessive CDOM.

Is Ocean Reflectance Acquired by Citizen Scientists Robust for Science Applications?

Directory of Open Access Journals (Sweden)

Yuyan Yang

2018-05-01

Full Text Available Monitoring the dynamics of the productivity of ocean water and how it affects fisheries is essential for management. It requires data on proper spatial and temporal scales, which can be provided by operational ocean colour satellites. However, accurate productivity data from ocean colour imagery is only possible with proper validation of, for instance, the atmospheric correction applied to the images. In situ water reflectance data are of great value due to the requirements for validation and reflectance is traditionally measured with the Surface Acquisition System (SAS solar tracker system. Recently, an application for mobile devices, “HydroColor”, was developed to acquire water reflectance data. We examined the accuracy of the water reflectance measures acquired by HydroColor with the help of both trained and untrained citizens, under different environmental conditions. We used water reflectance data acquired by SAS solar tracker and by HydroColor onboard the BC ferry Queen of Oak Bay from July to September 2016. Monte Carlo permutation F tests were used to assess whether the differences between measurements collected by SAS solar tracker and HydroColor with citizens were significant. Results showed that citizen HydroColor measurements were accurate in red, green, and blue bands, as well as red/green and red/blue ratios under different environmental conditions. In addition, we found that a trained citizen obtained higher quality HydroColor data especially under clear skies at noon.

Comparison of primary productivity estimates in the Baltic Sea based on the DESAMBEM algorithm with estimates based on other similar algorithms

Directory of Open Access Journals (Sweden)

Małgorzata Stramska

2013-02-01

Full Text Available The quasi-synoptic view available from satellites has been broadly used in recent years to observe in near-real time the large-scale dynamics of marine ecosystems and to estimate primary productivity in the world ocean. However, the standard global NASA ocean colour algorithms generally do not produce good results in the Baltic Sea. In this paper, we compare the ability of seven algorithms to estimate depth-integrated daily primary production (PP, mg C m-2 in the Baltic Sea. All the algorithms use surface chlorophyll concentration, sea surface temperature, photosynthetic available radiation, latitude, longitude and day of the year as input data. Algorithm-derived PP is then compared with PP estimates obtained from 14C uptake measurements. The results indicate that the best agreement between the modelled and measured PP in the Baltic Sea is obtained with the DESAMBEM algorithm. This result supports the notion that a regional approach should be used in the interpretation of ocean colour satellite data in the Baltic Sea.

Phase recovering algorithms for extended objects encoded in digitally recorded holograms

Directory of Open Access Journals (Sweden)

Peng Z.

2010-06-01

Full Text Available The paper presents algorithms to recover the optical phase of digitally encoded holograms. Algorithms are based on the use of a numerical spherical reconstructing wave. Proof of the validity of the concept is performed through an experimental off axis digital holographic set-up. Two-color digital holographic reconstruction is also investigated. Application of the color set-up and algorithms concerns the simultaneous two-dimensional deformation measurement of an object submitted to a mechanical loading.

Mapping the low salinity Changjiang Diluted Water using satellite-retrieved colored dissolved organic matter (CDOM) in the East China Sea during high river flow season

Science.gov (United States)

Sasaki, Hiroaki; Siswanto, Eko; Nishiuchi, Kou; Tanaka, Katsuhisa; Hasegawa, Toru; Ishizaka, Joji

2008-02-01

Absorption coefficients of colored dissolved organic matter (CDOM) [a g(λ)] were measured and relationship with salinity was derived in the East China Sea (ECS) during summer when amount of the Changjiang River discharge is large. Low salinity Changjiang Diluted Water (CDW) was observed widely in the shelf region and was considered to be the main origin of CDOM, resulting in a strong relationship between salinity and a g(λ). Error of satellite a g(λ) estimated by the present ocean color algorithm could be corrected by satellite-retrieved chlorophyll data. Satellite-retrieved salinity could be predicted with about +/-1.0 accuracy from satellite a g(λ) and the relation between salinity and a g(λ). Our study suggests that satellite-derived a g(λ) can be an indicator of the low salinity CDW during summer.

A Modified Image Comparison Algorithm Using Histogram Features

OpenAIRE

Al-Oraiqat, Anas M.; Kostyukova, Natalya S.

2018-01-01

This article discuss the problem of color image content comparison. Particularly, methods of image content comparison are analyzed, restrictions of color histogram are described and a modified method of images content comparison is proposed. This method uses the color histograms and considers color locations. Testing and analyzing of based and modified algorithms are performed. The modified method shows 97% average precision for a collection containing about 700 images without loss of the adv...

Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans

Directory of Open Access Journals (Sweden)

D. Stramski

2008-02-01

recommend that these algorithms be implemented for routine processing of ocean color satellite data to produce maps of surface POC with the status of an evaluation data product for continued work on algorithm development and refinements. The two-step algorithms also deserve further attention because they can utilize various models for estimating IOPs from reflectance, offer advantages for developing an understanding of bio-optical variability underlying the algorithms, and provide flexibility for regional or seasonal parameterizations of the algorithms.

Distributed graph coloring fundamentals and recent developments

CERN Document Server

Barenboim, Leonid

2013-01-01

The focus of this monograph is on symmetry breaking problems in the message-passing model of distributed computing. In this model a communication network is represented by a n-vertex graph G = (V,E), whose vertices host autonomous processors. The processors communicate over the edges of G in discrete rounds. The goal is to devise algorithms that use as few rounds as possible.A typical symmetry-breaking problem is the problem of graph coloring. Denote by ? the maximum degree of G. While coloring G with ? + 1 colors is trivial in the centralized setting, the problem becomes much more challenging

Evaluation of downwelling diffuse attenuation coefficient algorithms in the Red Sea

KAUST Repository

Tiwari, Surya Prakash

2016-05-07

Despite the importance of the optical properties such as the downwelling diffuse attenuation coefficient for characterizing the upper water column, until recently no in situ optical measurements were published for the Red Sea. Kirby et al. used observations from the Coastal Zone Color Scanner to characterize the spatial and temporal variability of the diffuse attenuation coefficient (Kd(490)) in the Red Sea. To better understand optical variability and its utility in the Red Sea, it is imperative to comprehend the diffuse attenuation coefficient and its relationship with in situ properties. Two apparent optical properties, spectral remote sensing reflectance (Rrs) and the downwelling diffuse attenuation coefficient (Kd), are calculated from vertical profile measurements of downwelling irradiance (Ed) and upwelling radiance (Lu). Kd characterizes light penetration into water column that is important for understanding both the physical and biogeochemical environment, including water quality and the health of ocean environment. Our study tests the performance of the existing Kd(490) algorithms in the Red Sea and compares them against direct in situ measurements within various subdivisions of the Red Sea. Most standard algorithms either overestimated or underestimated with the measured in situ values of Kd. Consequently, these algorithms provided poor retrieval of Kd(490) for the Red Sea. Random errors were high for all algorithms and the correlation coefficients (r2) with in situ measurements were quite low. Hence, these algorithms may not be suitable for the Red Sea. Overall, statistical analyses of the various algorithms indicated that the existing algorithms are inadequate for the Red Sea. The present study suggests that reparameterizing existing algorithms or developing new regional algorithms is required to improve retrieval of Kd(490) for the Red Sea. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is

Using color histogram normalization for recovering chromatic illumination-changed images.

Science.gov (United States)

Pei, S C; Tseng, C L; Wu, C C

2001-11-01

We propose a novel image-recovery method using the covariance matrix of the red-green-blue (R-G-B) color histogram and tensor theories. The image-recovery method is called the color histogram normalization algorithm. It is known that the color histograms of an image taken under varied illuminations are related by a general affine transformation of the R-G-B coordinates when the illumination is changed. We propose a simplified affine model for application with illumination variation. This simplified affine model considers the effects of only three basic forms of distortion: translation, scaling, and rotation. According to this principle, we can estimate the affine transformation matrix necessary to recover images whose color distributions are varied as a result of illumination changes. We compare the normalized color histogram of the standard image with that of the tested image. By performing some operations of simple linear algebra, we can estimate the matrix of the affine transformation between two images under different illuminations. To demonstrate the performance of the proposed algorithm, we divide the experiments into two parts: computer-simulated images and real images corresponding to illumination changes. Simulation results show that the proposed algorithm is effective for both types of images. We also explain the noise-sensitive skew-rotation estimation that exists in the general affine model and demonstrate that the proposed simplified affine model without the use of skew rotation is better than the general affine model for such applications.

Color image encryption using random transforms, phase retrieval, chaotic maps, and diffusion

Science.gov (United States)

Annaby, M. H.; Rushdi, M. A.; Nehary, E. A.

2018-04-01

The recent tremendous proliferation of color imaging applications has been accompanied by growing research in data encryption to secure color images against adversary attacks. While recent color image encryption techniques perform reasonably well, they still exhibit vulnerabilities and deficiencies in terms of statistical security measures due to image data redundancy and inherent weaknesses. This paper proposes two encryption algorithms that largely treat these deficiencies and boost the security strength through novel integration of the random fractional Fourier transforms, phase retrieval algorithms, as well as chaotic scrambling and diffusion. We show through detailed experiments and statistical analysis that the proposed enhancements significantly improve security measures and immunity to attacks.

CMEIAS color segmentation: an improved computing technology to process color images for quantitative microbial ecology studies at single-cell resolution.

Science.gov (United States)

Gross, Colin A; Reddy, Chandan K; Dazzo, Frank B

2010-02-01

Quantitative microscopy and digital image analysis are underutilized in microbial ecology largely because of the laborious task to segment foreground object pixels from background, especially in complex color micrographs of environmental samples. In this paper, we describe an improved computing technology developed to alleviate this limitation. The system's uniqueness is its ability to edit digital images accurately when presented with the difficult yet commonplace challenge of removing background pixels whose three-dimensional color space overlaps the range that defines foreground objects. Image segmentation is accomplished by utilizing algorithms that address color and spatial relationships of user-selected foreground object pixels. Performance of the color segmentation algorithm evaluated on 26 complex micrographs at single pixel resolution had an overall pixel classification accuracy of 99+%. Several applications illustrate how this improved computing technology can successfully resolve numerous challenges of complex color segmentation in order to produce images from which quantitative information can be accurately extracted, thereby gain new perspectives on the in situ ecology of microorganisms. Examples include improvements in the quantitative analysis of (1) microbial abundance and phylotype diversity of single cells classified by their discriminating color within heterogeneous communities, (2) cell viability, (3) spatial relationships and intensity of bacterial gene expression involved in cellular communication between individual cells within rhizoplane biofilms, and (4) biofilm ecophysiology based on ribotype-differentiated radioactive substrate utilization. The stand-alone executable file plus user manual and tutorial images for this color segmentation computing application are freely available at http://cme.msu.edu/cmeias/ . This improved computing technology opens new opportunities of imaging applications where discriminating colors really matter most

The Hyperspectral Imager for the Coastal Ocean (HICO (trademark)) Provides a New View of the Coastal Ocean

Science.gov (United States)

2012-02-09

The calibrated data are then sent to NRL Stennis Space Center (NRL-SSC) for further processing using the NRL SSC Automated Processing System (APS...hyperspectral sensor in space we have not previously developed automated processing for hyperspectral ocean color data. The hyperspectral processing branch

Robust Color Choice for Small-size League RoboCup Competition

Directory of Open Access Journals (Sweden)

Qiang Zhou

2004-10-01

Full Text Available In this paper, the problem of choosing a set of most separable colors in a given environment is discussed. The proposed method models the process of generating theoretically computed best colors, printing of these colors through a color printer, and imaging the printed colors through a camera into an integrated framework. Thus, it provides a feasible way to generate practically best separable colors for a given environment with a set of given equipment. A real world application (robust color choice for small-size league RoboCup competition is used as an example to illustrate the proposed method. Experimental results on this example show the competitiveness of the colors learned from our algorithm compared to the colors adopted by other teams which are chosen via an extensive trial and error process using standard color papers.

Color correction pipeline optimization for digital cameras

Science.gov (United States)

Bianco, Simone; Bruna, Arcangelo R.; Naccari, Filippo; Schettini, Raimondo

2013-04-01

The processing pipeline of a digital camera converts the RAW image acquired by the sensor to a representation of the original scene that should be as faithful as possible. There are mainly two modules responsible for the color-rendering accuracy of a digital camera: the former is the illuminant estimation and correction module, and the latter is the color matrix transformation aimed to adapt the color response of the sensor to a standard color space. These two modules together form what may be called the color correction pipeline. We design and test new color correction pipelines that exploit different illuminant estimation and correction algorithms that are tuned and automatically selected on the basis of the image content. Since the illuminant estimation is an ill-posed problem, illuminant correction is not error-free. An adaptive color matrix transformation module is optimized, taking into account the behavior of the first module in order to alleviate the amplification of color errors. The proposed pipelines are tested on a publicly available dataset of RAW images. Experimental results show that exploiting the cross-talks between the modules of the pipeline can lead to a higher color-rendition accuracy.

Reading color barcodes using visual snakes.

Energy Technology Data Exchange (ETDEWEB)

Schaub, Hanspeter (ORION International Technologies, Albuquerque, NM)

2004-05-01

Statistical pressure snakes are used to track a mono-color target in an unstructured environment using a video camera. The report discusses an algorithm to extract a bar code signal that is embedded within the target. The target is assumed to be rectangular in shape, with the bar code printed in a slightly different saturation and value in HSV color space. Thus, the visual snake, which primarily weighs hue tracking errors, will not be deterred by the presence of the color bar codes in the target. The bar code is generate with the standard 3 of 9 method. Using this method, the numeric bar codes reveal if the target is right-side-up or up-side-down.

GLAS/ICESat L2 Ocean Altimetry Data V033

Data.gov (United States)

National Aeronautics and Space Administration — GLA15 contains the ocean elevation and small-scale roughness corrected for geodetic and atmospheric affects, calculated from algorithms fine-tuned for ocean returns....

Determination of Primary Bands for Global Ocean-Color Remote Sensing

National Research Council Canada - National Science Library

Lee, ZhongPing; Arnone, Robert; Carder, Kendall; He, MingXia

2007-01-01

...) from remote sensing of its color, a sensor with roughly 17 spectral bands in the 400 - 800 nm range can provide acceptable results compared to a sensor with 81 consecutive bands (in a 5-nm step...

A combination chaotic system and application in color image encryption

Science.gov (United States)

Parvaz, R.; Zarebnia, M.

2018-05-01

In this paper, by using Logistic, Sine and Tent systems we define a combination chaotic system. Some properties of the chaotic system are studied by using figures and numerical results. A color image encryption algorithm is introduced based on new chaotic system. Also this encryption algorithm can be used for gray scale or binary images. The experimental results of the encryption algorithm show that the encryption algorithm is secure and practical.

Image mosaicking based on feature points using color-invariant values

Science.gov (United States)

Lee, Dong-Chang; Kwon, Oh-Seol; Ko, Kyung-Woo; Lee, Ho-Young; Ha, Yeong-Ho

2008-02-01

In the field of computer vision, image mosaicking is achieved using image features, such as textures, colors, and shapes between corresponding images, or local descriptors representing neighborhoods of feature points extracted from corresponding images. However, image mosaicking based on feature points has attracted more recent attention due to the simplicity of the geometric transformation, regardless of distortion and differences in intensity generated by camera motion in consecutive images. Yet, since most feature-point matching algorithms extract feature points using gray values, identifying corresponding points becomes difficult in the case of changing illumination and images with a similar intensity. Accordingly, to solve these problems, this paper proposes a method of image mosaicking based on feature points using color information of images. Essentially, the digital values acquired from a real digital color camera are converted to values of a virtual camera with distinct narrow bands. Values based on the surface reflectance and invariant to the chromaticity of various illuminations are then derived from the virtual camera values and defined as color-invariant values invariant to changing illuminations. The validity of these color-invariant values is verified in a test using a Macbeth Color-Checker under simulated illuminations. The test also compares the proposed method using the color-invariant values with the conventional SIFT algorithm. The accuracy of the matching between the feature points extracted using the proposed method is increased, while image mosaicking using color information is also achieved.

Single underwater image enhancement based on color cast removal and visibility restoration

Science.gov (United States)

Li, Chongyi; Guo, Jichang; Wang, Bo; Cong, Runmin; Zhang, Yan; Wang, Jian

2016-05-01

Images taken under underwater condition usually have color cast and serious loss of contrast and visibility. Degraded underwater images are inconvenient for observation and analysis. In order to address these problems, an underwater image-enhancement method is proposed. A simple yet effective underwater image color cast removal algorithm is first presented based on the optimization theory. Then, based on the minimum information loss principle and inherent relationship of medium transmission maps of three color channels in an underwater image, an effective visibility restoration algorithm is proposed to recover visibility, contrast, and natural appearance of degraded underwater images. To evaluate the performance of the proposed method, qualitative comparison, quantitative comparison, and color accuracy test are conducted. Experimental results demonstrate that the proposed method can effectively remove color cast, improve contrast and visibility, and recover natural appearance of degraded underwater images. Additionally, the proposed method is comparable to and even better than several state-of-the-art methods.

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

Science.gov (United States)

Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

2017-12-01

A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System

Science.gov (United States)

Haidvogel, D.B.; Arango, H.; Budgell, W.P.; Cornuelle, B.D.; Curchitser, E.; Di, Lorenzo E.; Fennel, K.; Geyer, W.R.; Hermann, A.J.; Lanerolle, L.; Levin, J.; McWilliams, J.C.; Miller, A.J.; Moore, A.M.; Powell, T.M.; Shchepetkin, A.F.; Sherwood, C.R.; Signell, R.P.; Warner, J.C.; Wilkin, J.

2008-01-01

Systematic improvements in algorithmic design of regional ocean circulation models have led to significant enhancement in simulation ability across a wide range of space/time scales and marine system types. As an example, we briefly review the Regional Ocean Modeling System, a member of a general class of three-dimensional, free-surface, terrain-following numerical models. Noteworthy characteristics of the ROMS computational kernel include: consistent temporal averaging of the barotropic mode to guarantee both exact conservation and constancy preservation properties for tracers; redefined barotropic pressure-gradient terms to account for local variations in the density field; vertical interpolation performed using conservative parabolic splines; and higher-order, quasi-monotone advection algorithms. Examples of quantitative skill assessment are shown for a tidally driven estuary, an ice-covered high-latitude sea, a wind- and buoyancy-forced continental shelf, and a mid-latitude ocean basin. The combination of moderate-order spatial approximations, enhanced conservation properties, and quasi-monotone advection produces both more robust and accurate, and less diffusive, solutions than those produced in earlier terrain-following ocean models. Together with advanced methods of data assimilation and novel observing system technologies, these capabilities constitute the necessary ingredients for multi-purpose regional ocean prediction systems. 

Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

Science.gov (United States)

Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

2015-02-10

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

Seagrass ecophysiological performance under ocean warming and acidification.

Science.gov (United States)

Repolho, Tiago; Duarte, Bernardo; Dionísio, Gisela; Paula, José Ricardo; Lopes, Ana R; Rosa, Inês C; Grilo, Tiago F; Caçador, Isabel; Calado, Ricardo; Rosa, Rui

2017-02-01

Seagrasses play an essential ecological role within coastal habitats and their worldwide population decline has been linked to different types of anthropogenic forces. We investigated, for the first time, the combined effects of future ocean warming and acidification on fundamental biological processes of Zostera noltii, including shoot density, leaf coloration, photophysiology (electron transport rate, ETR; maximum PSII quantum yield, F v /F m ) and photosynthetic pigments. Shoot density was severely affected under warming conditions, with a concomitant increase in the frequency of brownish colored leaves (seagrass die-off). Warming was responsible for a significant decrease in ETR and F v /F m (particularly under control pH conditions), while promoting the highest ETR variability (among experimental treatments). Warming also elicited a significant increase in pheophytin and carotenoid levels, alongside an increase in carotenoid/chlorophyll ratio and De-Epoxidation State (DES). Acidification significantly affected photosynthetic pigments content (antheraxanthin, β-carotene, violaxanthin and zeaxanthin), with a significant decrease being recorded under the warming scenario. No significant interaction between ocean acidification and warming was observed. Our findings suggest that future ocean warming will be a foremost determinant stressor influencing Z. noltii survival and physiological performance. Additionally, acidification conditions to occur in the future will be unable to counteract deleterious effects posed by ocean warming.

Comparatively Studied Color Correction Methods for Color Calibration of Automated Microscopy Complex of Biomedical Specimens

Directory of Open Access Journals (Sweden)

T. A. Kravtsova

2016-01-01

Full Text Available The paper considers a task of generating the requirements and creating a calibration target for automated microscopy systems (AMS of biomedical specimens to provide the invariance of algorithms and software to the hardware configuration. The required number of color fields of the calibration target and their color coordinates are mostly determined by the color correction method, for which coefficients of the equations are estimated during the calibration process. The paper analyses existing color calibration techniques for digital imaging systems using an optical microscope and shows that there is a lack of published results of comparative studies to demonstrate a particular useful color correction method for microscopic images. A comparative study of ten image color correction methods in RGB space using polynomials and combinations of color coordinate of different orders was carried out. The method of conditioned least squares to estimate the coefficients in the color correction equations using captured images of 217 color fields of the calibration target Kodak Q60-E3 was applied. The regularization parameter in this method was chosen experimentally. It was demonstrated that the best color correction quality characteristics are provided by the method that uses a combination of color coordinates of the 3rd order. The study of the influence of the number and the set of color fields included in calibration target on color correction quality for microscopic images was performed. Six train sets containing 30, 35, 40, 50, 60 and 80 color fields, and test set of 47 color fields not included in any of the train sets were formed. It was found out that the train set of 60 color fields minimizes the color correction error values for both operating modes of digital camera: using "default" color settings and with automatic white balance. At the same time it was established that the use of color fields from the widely used now Kodak Q60-E3 target does not

A vector radiative transfer model for coupled atmosphere and ocean systems with a rough interface

International Nuclear Information System (INIS)

Zhai Pengwang; Hu Yongxiang; Chowdhary, Jacek; Trepte, Charles R.; Lucker, Patricia L.; Josset, Damien B.

2010-01-01

We report on an exact vector (polarized) radiative transfer (VRT) model for coupled atmosphere and ocean systems. This VRT model is based on the successive order of scattering (SOS) method, which virtually takes all the multiple scattering processes into account, including atmospheric scattering, oceanic scattering, reflection and transmission through the rough ocean surface. The isotropic Cox-Munk wave model is used to derive the ref and transmission matrices for the rough ocean surface. Shadowing effects are included by the shadowing function. We validated the SOS results by comparing them with those calculated by two independent codes based on the doubling/adding and Monte Carlo methods. Two error analyses related to the ocean color remote sensing are performed in the coupled atmosphere and ocean systems. One is the scalar error caused by ignoring the polarization in the whole system. The other is the error introduced by ignoring the polarization of the light transmitted through the ocean interface. Both errors are significant for the cases studied. This code fits for the next generation of ocean color study because it converges fast for absorbing medium as, for instance, ocean.

Recommendations on Future Science and Engineering Studies for Ocean Color

Science.gov (United States)

Mannino, Antonio

2015-01-01

The Ocean Health Index measured Ecological Integrity as the relative condition of assessed species in a given location. This was calculated as the weighted sum of the International Union for Conservation of Natures (IUCN) assessments of species. Weights used were based on the level of extinction risk following Butchart et al.2007: EX (extinct) 0.0, CR (critically endangered) 0.2, EN (endangered) 0.5, VU (vulnerable) 0.7, NT (not threatened) 0.9, and LC (least concern) 0.99. For primarily coastal goals, the spatial average of these per pixel scores was based on a 3nmi buffer; for goals derived from all ocean waters, the spatial average was computed for the entire EEZ.

Color constancy in 3D-2D face recognition

Science.gov (United States)

Meyer, Manuel; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis A.

2013-05-01

Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibility and effect of explicitly embedding illuminant color information in face recognition systems. We empirically examine the theoretical maximum gain of including known illuminant color to a 3D-2D face recognition system. We also investigate the impact of using computational color constancy methods for estimating the illuminant color, which is then incorporated into the face recognition framework. Our experiments show that under close-to-ideal illumination estimates, one can improve face recognition rates by 16%. When the illuminant color is algorithmically estimated, the improvement is approximately 5%. These results suggest that color constancy has a positive impact on face recognition, but the accuracy of the illuminant color estimate has a considerable effect on its benefits.

An Innovative Concept for Spacebased Lidar Measurement of Ocean Carbon Biomass

Science.gov (United States)

Hu, Yongxiang; Behrenfeld, Michael; Hostetler, Chris; Pelon, Jacques; Trepte, Charles; Hair, John; Slade, Wayne; Cetinic, Ivona; Vaughan, Mark; Lu, Xiaomei;

Oceanic eddies in synthetic aperture radar images

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

2000) can be carried out in two different ways. The first one is ..... mushroom-like currents forming composite multi- .... eddies. Combination of SAR, IR and color data will ... Fu L-L and Holt B 1982 Seasat views oceans and sea ice with.

Multiobjective generalized extremal optimization algorithm for simulation of daylight illuminants

Science.gov (United States)

Kumar, Srividya Ravindra; Kurian, Ciji Pearl; Gomes-Borges, Marcos Eduardo

2017-10-01

Daylight illuminants are widely used as references for color quality testing and optical vision testing applications. Presently used daylight simulators make use of fluorescent bulbs that are not tunable and occupy more space inside the quality testing chambers. By designing a spectrally tunable LED light source with an optimal number of LEDs, cost, space, and energy can be saved. This paper describes an application of the generalized extremal optimization (GEO) algorithm for selection of the appropriate quantity and quality of LEDs that compose the light source. The multiobjective approach of this algorithm tries to get the best spectral simulation with minimum fitness error toward the target spectrum, correlated color temperature (CCT) the same as the target spectrum, high color rendering index (CRI), and luminous flux as required for testing applications. GEO is a global search algorithm based on phenomena of natural evolution and is especially designed to be used in complex optimization problems. Several simulations have been conducted to validate the performance of the algorithm. The methodology applied to model the LEDs, together with the theoretical basis for CCT and CRI calculation, is presented in this paper. A comparative result analysis of M-GEO evolutionary algorithm with the Levenberg-Marquardt conventional deterministic algorithm is also presented.

RESEARCH ON FOREST FLAME RECOGNITION ALGORITHM BASED ON IMAGE FEATURE

Directory of Open Access Journals (Sweden)

Z. Wang

2017-09-01

Full Text Available In recent years, fire recognition based on image features has become a hotspot in fire monitoring. However, due to the complexity of forest environment, the accuracy of forest fireworks recognition based on image features is low. Based on this, this paper proposes a feature extraction algorithm based on YCrCb color space and K-means clustering. Firstly, the paper prepares and analyzes the color characteristics of a large number of forest fire image samples. Using the K-means clustering algorithm, the forest flame model is obtained by comparing the two commonly used color spaces, and the suspected flame area is discriminated and extracted. The experimental results show that the extraction accuracy of flame area based on YCrCb color model is higher than that of HSI color model, which can be applied in different scene forest fire identification, and it is feasible in practice.

An algorithm for estimating aerosol optical depth from HIMAWARI-8 data over Ocean

Science.gov (United States)

Lee, Kwon Ho

2016-04-01

The paper presents currently developing algorithm for aerosol detection and retrieval over ocean for the next generation geostationary satellite, HIMAWARI-8. Enhanced geostationary remote sensing observations are now enables for aerosol retrieval of dust, smoke, and ash, which began a new era of geostationary aerosol observations. Sixteen channels of the Advanced HIMAWARI Imager (AHI) onboard HIMAWARI-8 offer capabilities for aerosol remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS). Aerosols were estimated in detection processing from visible and infrared channel radiances, and in retrieval processing using the inversion-optimization of satellite-observed radiances with those calculated from radiative transfer model. The retrievals are performed operationally every ten minutes for pixel sizes of ~8 km. The algorithm currently under development uses a multichannel approach to estimate the effective radius, aerosol optical depth (AOD) simultaneously. The instantaneous retrieved AOD is evaluated by the MODIS level 2 operational aerosol products (C006), and the daily retrieved AOD was compared with ground-based measurements from the AERONET databases. The results show that the detection of aerosol and estimated AOD are in good agreement with the MODIS data and ground measurements with a correlation coefficient of ˜0.90 and a bias of 4%. These results suggest that the proposed method applied to the HIMAWARI-8 satellite data can accurately estimate continuous AOD. Acknowledgments This work was supported by "Development of Geostationary Meteorological Satellite Ground Segment(NMSC-2014-01)" program funded by National Meteorological Satellite Centre(NMSC) of Korea Meteorological Administration(KMA).

Principles of image processing in machine vision systems for the color analysis of minerals

Science.gov (United States)

Petukhova, Daria B.; Gorbunova, Elena V.; Chertov, Aleksandr N.; Korotaev, Valery V.

2014-09-01

At the moment color sorting method is one of promising methods of mineral raw materials enrichment. This method is based on registration of color differences between images of analyzed objects. As is generally known the problem with delimitation of close color tints when sorting low-contrast minerals is one of the main disadvantages of color sorting method. It is can be related with wrong choice of a color model and incomplete image processing in machine vision system for realizing color sorting algorithm. Another problem is a necessity of image processing features reconfiguration when changing the type of analyzed minerals. This is due to the fact that optical properties of mineral samples vary from one mineral deposit to another. Therefore searching for values of image processing features is non-trivial task. And this task doesn't always have an acceptable solution. In addition there are no uniform guidelines for determining criteria of mineral samples separation. It is assumed that the process of image processing features reconfiguration had to be made by machine learning. But in practice it's carried out by adjusting the operating parameters which are satisfactory for one specific enrichment task. This approach usually leads to the fact that machine vision system unable to estimate rapidly the concentration rate of analyzed mineral ore by using color sorting method. This paper presents the results of research aimed at addressing mentioned shortcomings in image processing organization for machine vision systems which are used to color sorting of mineral samples. The principles of color analysis for low-contrast minerals by using machine vision systems are also studied. In addition, a special processing algorithm for color images of mineral samples is developed. Mentioned algorithm allows you to determine automatically the criteria of mineral samples separation based on an analysis of representative mineral samples. Experimental studies of the proposed algorithm

Method for numerical simulation of two-term exponentially correlated colored noise

International Nuclear Information System (INIS)

Yilmaz, B.; Ayik, S.; Abe, Y.; Gokalp, A.; Yilmaz, O.

2006-01-01

A method for numerical simulation of two-term exponentially correlated colored noise is proposed. The method is an extension of traditional method for one-term exponentially correlated colored noise. The validity of the algorithm is tested by comparing numerical simulations with analytical results in two physical applications

Ocean bio-geophysical modeling using mixed layer-isopycnal general circulation model coupled with photosynthesis process

Digital Repository Service at National Institute of Oceanography (India)

Nakamoto, S.; Saito, H.; Muneyama, K.; Sato, T.; PrasannaKumar, S.; Kumar, A.; Frouin, R.

-chemical system that supports steady carbon circulation in geological time scale in the world ocean using Mixed Layer-Isopycnal ocean General Circulation model with remotely sensed Coastal Zone Color Scanner (CZCS) chlorophyll pigment concentration....

Algorithms evaluation for fundus images enhancement

International Nuclear Information System (INIS)

Braem, V; Marcos, M; Bizai, G; Drozdowicz, B; Salvatelli, A

2011-01-01

Color images of the retina inherently involve noise and illumination artifacts. In order to improve the diagnostic quality of the images, it is desirable to homogenize the non-uniform illumination and increase contrast while preserving color characteristics. The visual result of different pre-processing techniques can be very dissimilar and it is necessary to make an objective assessment of the techniques in order to select the most suitable. In this article the performance of eight algorithms to correct the non-uniform illumination, contrast modification and color preservation was evaluated. In order to choose the most suitable a general score was proposed. The results got good impression from experts, although some differences suggest that not necessarily the best statistical quality of image is the one of best diagnostic quality to the trained doctor eye. This means that the best pre-processing algorithm for an automatic classification may be different to the most suitable one for visual diagnosis. However, both should result in the same final diagnosis.

Effect of algae and water on water color shift

Science.gov (United States)

Yang, Shengguang; Xia, Daying; Yang, Xiaolong; Zhao, Jun

1991-03-01

This study showed that the combined effect of absorption of planktonic algae and water on water color shift can be simulated approximately by the exponential function: Log( E {100cm/ W }+ E {100cm/ Xch1})=0.002λ-2.5 where E {100/cm W }, E {100cm/ Xchl} are, respectively, extinction coefficients of seawater and chlorophyll—a (concentration is equal to X mg/m3), and λ (nm) is wavelength. This empirical regression equation is very useful for forecasting the relation between water color and biomass in water not affected by terrigenous material. The main factor affecting water color shift in the ocean should be the absorption of blue light by planktonic algae.

Event-Based Color Segmentation With a High Dynamic Range Sensor

Directory of Open Access Journals (Sweden)

Alexandre Marcireau

2018-04-01

Full Text Available This paper introduces a color asynchronous neuromorphic event-based camera and a methodology to process color output from the device to perform color segmentation and tracking at the native temporal resolution of the sensor (down to one microsecond. Our color vision sensor prototype is a combination of three Asynchronous Time-based Image Sensors, sensitive to absolute color information. We devise a color processing algorithm leveraging this information. It is designed to be computationally cheap, thus showing how low level processing benefits from asynchronous acquisition and high temporal resolution data. The resulting color segmentation and tracking performance is assessed both with an indoor controlled scene and two outdoor uncontrolled scenes. The tracking's mean error to the ground truth for the objects of the outdoor scenes ranges from two to twenty pixels.

Real-time Face Detection using Skin Color Model

Institute of Scientific and Technical Information of China (English)

LU Yao-xin; LIU Zhi-Qiang; ZHU Xiang-hua

2004-01-01

This paper presents a new face detection approach to real-time applications, which is based on the skin color model and the morphological filtering. First the non-skin color pixels of the input image are removed based on the skin color model in the YCrCb chrominance space, from which we extract candidate human face regions. Then a mathematical morphological filter is used to remove noisy regions and fill the holes in the candidate skin color regions. We adopt the similarity between the human face features and the candidate face regions to locate the face regions in the original image. We have implemented the algorithm in our smart media system. The experiment results show that this system is effective in real-time applications.

A fuzzy art neural network based color image processing and ...

African Journals Online (AJOL)

To improve the learning process from the input data, a new learning rule was suggested. In this paper, a new method is proposed to deal with the RGB color image pixels, which enables a Fuzzy ART neural network to process the RGB color images. The application of the algorithm was implemented and tested on a set of ...

On the Color of the Orinoco River Plume

Science.gov (United States)

Odriozola, A.; Muller-Karger, F.; Carder, K.; Hu, C.; Varela, R.

2005-05-01

In situ measurements were used to study the bio-optical properties of marine waters within the Gulf of Paria (GOP, Venezuela) and in the Southeastern Caribbean Sea (SEC) as they are affected by the seasonal discharge of the Orinoco River plume. The main purpose of this study was to determine the impact of colored dissolved organic matter (CDOM) (also known as Gelbstoff), phytoplankton, and total suspended matter (TSM) in the color of the Orinoco River plume. This information is essential for regional ocean color algorithms development. Salinity and silica values indicate that the GOP and SEC waters were under the influence of the Orinoco River plume during both seasons. This riverine influence resulted in high values of Gelbstoff absorption, ag(λ), which contributed to up to 90% of the total absorption at 440 nm in both the GOP and SEC regardless of the season. Phytoplankton absorption contributions were normally around 5%, but during the dry season these values reached 20% in the SEC. Ratios of ag(440) to ph(440) were extremely large, with most of the values ranging from 10 to 50. Due to the strong absorption by Gelbstoff, light at the blue wavelengths (412 nm, 440 nm and 490 nm) was attenuated to 1% of the subsurface irradiance in the first 5 m of the water column within the GOP, and in the first 10 m of the water column in the SEC. Furthermore, the absorption by Gelbstoff significantly decreased the water leaving radiance (Lw(λ)) in the blue wavelengths along the Orinoco River plume. As ag(λ) relatively decreased from the GOP to the SEC (mean ~1.6 m-1 and mean ~0.9 m-1, respectively), a shift in the maximum peak of Rrs(λ) spectra (Rrsmax(λ)), towards shorter wavelengths (from ~ 580 nm to ~500 nm) was observed. Similar to Gelbstoff, concentrations of TSM normally decreased from the stations near the Delta to the stations in the SEC. The impact of TSM on the color of the Orinoco plume was represented by a reduction in the magnitude of Rrsmax(λ) of ~50% going

NIMBUS-7 CZCS. Coastal Zone Color Scanner Imagery for Selected Coastal Regions. North America - Europe. South America - Africa - Antarctica. Level 2 Photographic Product

Science.gov (United States)

1984-01-01

The Nimbus-7 Coastal Zone Color Scanner (CZCS) is the first spacecraft instrument devoted to the measurement of ocean color. Although instruments on other satellites have sensed ocean color, their spectral bands, spatial resolution, and dynamic range were optimized for geographical or meteorological use. In the CZCS, every parameter is optimized for use over water to the exclusion of any other type of sensing. The signal-to-noise ratios in the spectral channels sensing reflected solar radiance are higher than those required in the past. These ratios need to be high because the ocean is such a poor reflecting surface that the majority of the signal seen by the reflected energy channels at spacecraft altitudes is backscattered solar radiation from the atmosphere rather than reflected solar energy from the ocean. The CZCS is a conventional multichannel scanning radiometer utilizing a rotating plane mirror at a 45 deg angle to the optic axis of a Cassegrain telescope. The mirror scans 360 deg; however, only 80 deg of data centered on the spacecraft nadir is collected for ocean color measurements. Spatial resolution at spacecraft nadir is 825x825 m with some degradation at the edges of the scan swath. The useful swath width from a spacecraft altitude of 955 km is 1600 km.

Morphological rational multi-scale algorithm for color contrast enhancement

Science.gov (United States)

Peregrina-Barreto, Hayde; Terol-Villalobos, Iván R.

2010-01-01

Contrast enhancement main goal consists on improving the image visual appearance but also it is used for providing a transformed image in order to segment it. In mathematical morphology several works have been derived from the framework theory for contrast enhancement proposed by Meyer and Serra. However, when working with images with a wide range of scene brightness, as for example when strong highlights and deep shadows appear in the same image, the proposed morphological methods do not allow the enhancement. In this work, a rational multi-scale method, which uses a class of morphological connected filters called filters by reconstruction, is proposed. Granulometry is used by finding the more accurate scales for filters and with the aim of avoiding the use of other little significant scales. The CIE-u'v'Y' space was used to introduce our results since it takes into account the Weber's Law and by avoiding the creation of new colors it permits to modify the luminance values without affecting the hue. The luminance component ('Y) is enhanced separately using the proposed method, next it is used for enhancing the chromatic components (u', v') by means of the center of gravity law of color mixing.

Study on the effects of sample selection on spectral reflectance reconstruction based on the algorithm of compressive sensing

International Nuclear Information System (INIS)

Zhang, Leihong; Liang, Dong

2016-01-01

In order to solve the problem that reconstruction efficiency and precision is not high, in this paper different samples are selected to reconstruct spectral reflectance, and a new kind of spectral reflectance reconstruction method based on the algorithm of compressive sensing is provided. Four different color numbers of matte color cards such as the ColorChecker Color Rendition Chart and Color Checker SG, the copperplate paper spot color card of Panton, and the Munsell colors card are chosen as training samples, the spectral image is reconstructed respectively by the algorithm of compressive sensing and pseudo-inverse and Wiener, and the results are compared. These methods of spectral reconstruction are evaluated by root mean square error and color difference accuracy. The experiments show that the cumulative contribution rate and color difference of the Munsell colors card are better than those of the other three numbers of color cards in the same conditions of reconstruction, and the accuracy of the spectral reconstruction will be affected by the training sample of different numbers of color cards. The key technology of reconstruction means that the uniformity and representation of the training sample selection has important significance upon reconstruction. In this paper, the influence of the sample selection on the spectral image reconstruction is studied. The precision of the spectral reconstruction based on the algorithm of compressive sensing is higher than that of the traditional algorithm of spectral reconstruction. By the MATLAB simulation results, it can be seen that the spectral reconstruction precision and efficiency are affected by the different color numbers of the training sample. (paper)

The Chinese FY-1 Meteorological Satellite Application in Observation on Oceanic Environment

Science.gov (United States)

Weimin, S.

meteorological satellite is stated in this paper. exploration of the ocean resources has been a very important question of global strategy in the world. The exploration of the ocean resources includes following items: Making full use of oceanic resources and space, protecting oceanic environment. to observe the ocean is by using of satellite. In 1978, US successfully launched the first ocean observation satellite in the world --- Sea Satellite. It develops ancient oceanography in to advanced space-oceanography. FY-1 B and FY- IC respectively. High quality data were acquired at home and abroad. FY-1 is Chinese meteorological satellite, but with 0.43 ~ 0.48 μm ,0.48 ~ 0.53 μm and 0.53 ~ 0.58 μm three ocean color channels, actually it is a multipurpose remote sensing satellite of meteorology and oceanography. FY-1 satellite's capability of observation on ocean partly, thus the application field is expanded and the value is increased. With the addition of oceanic channels on FY-1, the design of the satellite is changed from the original with meteorological observation as its main purpose into remote sensing satellite possessing capability of observing meteorology and ocean as well. Thus, the social and economic benefit of FY-1 is increased. the social and economic benefit of the development of the satellite is the key technique in the system design of the satellite. technically feasible but also save the funds in researching and manufacturing of the satellite, quicken the tempo of researching and manufacturing satellite. the scanning radiometer for FY-1 is conducted an aviation experiment over Chinese ocean. This experiment was of vital importance to the addition of oceanic observation channel on FY-1. FY-1 oceanic channels design to be correct. detecting ocean color. This is the unique character of Chinese FY-1 meteorological satellite. meteorological remote sensing channel on FY-1 to form detecting capability of three visible channels: red, yellow and blue

Airborne Mission Concept for Coastal Ocean Color and Ecosystems Research

Science.gov (United States)

Guild, Liane S.; Hooker, Stanford B.; Morrow, John H.; Kudela, Raphael M.; Palacios, Sherry L.; Torres Perez, Juan L.; Hayashi, Kendra; Dunagan, Stephen E.

2016-01-01

NASA airborne missions in 2011 and 2013 over Monterey Bay, CA, demonstrated novel above- and in-water calibration and validation measurements supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The resultant airborne data characterize contemporaneous coastal atmospheric and aquatic properties plus sea-truth observations from state-of-the-art instrument systems spanning a next-generation spectral domain (320-875 nm). This airborne instrument suite for calibration, validation, and research flew at the lowest safe altitude (ca. 100 ft or 30 m) as well as higher altitudes (e.g., 6,000 ft or 1,800 m) above the sea surface covering a larger area in a single synoptic sortie than ship-based measurements at a few stations during the same sampling period. Data collection of coincident atmospheric and aquatic properties near the sea surface and at altitude allows the input of relevant variables into atmospheric correction schemes to improve the output of corrected imaging spectrometer data. Specific channels support legacy and next-generation satellite capabilities, and flights are planned to within 30 min of satellite overpass. This concept supports calibration and validation activities of ocean color phenomena (e.g., river plumes, algal blooms) and studies of water quality and coastal ecosystems. The 2011 COAST mission flew at 100 and 6,000 ft on a Twin Otter platform with flight plans accommodating the competing requirements of the sensor suite, which included the Coastal-Airborne In-situ Radiometers (C-AIR) for the first time. C-AIR (Biospherical Instruments Inc.) also flew in the 2013 OCEANIA mission at 100 and 1,000 ft on the Twin Otter below the California airborne simulation of the proposed NASA HyspIRI satellite system comprised of an imaging spectrometer and thermal infrared multispectral imager on the ER-2 at 65,000 ft (20,000 m). For both missions, the Compact-Optical Profiling System (Biospherical

Schwarz-Christoffel Conformal Mapping based Grid Generation for Global Oceanic Circulation Models

Science.gov (United States)

Xu, Shiming

2015-04-01

We propose new grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithm are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the conventional grid design problem of pole relocation, it also addresses more advanced issues of computational efficiency and the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily 10 utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling when complex land-ocean distribution is present.

Voice-Centric LTE Femtocells and Improper Graph Colorings

DEFF Research Database (Denmark)

Garcia, Luis Guilherme Uzeda; Pedersen, Klaus; Mogensen, Preben

2012-01-01

. The investigation revolves around the sensible definition of the underlying graph, i.e. the network model, rather than focusing on the coloring algorithms and their properties. Ultimately, we posit that improper online graph-coloring suffices and is actually preferable. In short, settling for less......This paper addresses carrier-based inter-cell interference coordination (CB-ICIC) among LTE femtocells operating on a single carrier. CB-ICIC is in many ways linked to the widely investigated dynamic channel assignment problem, which is often studied in the context of graph coloring......-than-optimal configurations avoids uncontrolled service interruptions. Such disruptions tend to raise understandable concerns when it comes to fully autonomous selection of operational CCs. Our results dispel such concerns by showing that conservative methods can achieve most of the benefits of unrestricted off-line coloring...

Nimbus 7 Coastal Zone Color Scanner (CZCS). Level 1 data product users' guide

Science.gov (United States)

Williams, S. P.; Szajna, E. F.; Hovis, W. A.

1985-01-01

The coastal zone color scanner (CZCS) is a scanning multispectral radiometer designed specifically for the remote sensing of Ocean Color parameters from an Earth orbiting space platform. A technical manual which is intended for users of NIMBUS 7 CZCS Level 1 data products is presented. It contains information needed by investigators and data processing personnel to operate on the data using digital computers and related equipment.

Assessment of Satellite Ocean Colour Radiometry and Derived Geophysical Products. Chapter 6.1

Science.gov (United States)

Melin, Frederic; Franz, Bryan A.

2014-01-01

Standardization of methods to assess and assign quality metrics to satellite ocean color radiometry and derived geophysical products has become paramount with the inclusion of the marine reflectance and chlorophyll-a concentration (Chla) as essential climate variables (ECV; [1]) and the recognition that optical remote sensing of the oceans can only contribute to climate research if and when a continuous succession of satellite missions can be shown to collectively provide a consistent, long-term record with known uncertainties. In 20 years, the community has made significant advancements toward that objective, but providing a complete uncertainty budget for all products and for all conditions remains a daunting task. In the retrieval of marine water-leaving radiance from observed top-of-atmosphere radiance, the sources of uncertainties include those associated with propagation of sensor noise and radiometric calibration and characterization errors, as well as a multitude of uncertainties associated with the modeling and removal of effects from the atmosphere and sea surface. This chapter describes some common approaches used to assess quality and consistency of ocean color satellite products and reviews the current status of uncertainty quantification in the field. Its focus is on the primary ocean color product, the spectrum of marine reflectance Rrs, but uncertainties in some derived products such as the Chla or inherent optical properties (IOPs) will also be considered.

The application of computer color matching techniques to the matching of target colors in a food substrate: a first step in the development of foods with customized appearance.

Science.gov (United States)

Kim, Sandra; Golding, Matt; Archer, Richard H

2012-06-01

A predictive color matching model based on the colorimetric technique was developed and used to calculate the concentrations of primary food dyes needed in a model food substrate to match a set of standard tile colors. This research is the first stage in the development of novel three-dimensional (3D) foods in which color images or designs can be rapidly reproduced in 3D form. Absorption coefficients were derived for each dye, from a concentration series in the model substrate, a microwave-baked cake. When used in a linear, additive blending model these coefficients were able to predict cake color from selected dye blends to within 3 ΔE*(ab,10) color difference units, or within the limit of a visually acceptable match. Absorption coefficients were converted to pseudo X₁₀, Y₁₀, and Z₁₀ tri-stimulus values (X₁₀(P), Y₁₀(P), Z₁₀(P)) for colorimetric matching. The Allen algorithm was used to calculate dye concentrations to match the X₁₀(P), Y₁₀(P), and Z₁₀(P) values of each tile color. Several recipes for each color were computed with the tile specular component included or excluded, and tested in the cake. Some tile colors proved out-of-gamut, limited by legal dye concentrations; these were scaled to within legal range. Actual differences suggest reasonable visual matches could be achieved for within-gamut tile colors. The Allen algorithm, with appropriate adjustments of concentration outputs, could provide a sufficiently rapid and accurate calculation tool for 3D color food printing. The predictive color matching approach shows potential for use in a novel embodiment of 3D food printing in which a color image or design could be rendered within a food matrix through the selective blending of primary dyes to reproduce each color element. The on-demand nature of this food application requires rapid color outputs which could be provided by the color matching technique, currently used in nonfood industries, rather than by empirical food

Overview of remote sensing of chlorophyll flourescene in ocean waters

African Journals Online (AJOL)

Overview of remote sensing of chlorophyll flourescene in ocean waters. ... Besides empirical algorithms with the blue-green ratio, the algorithms based on ... between fluorescence and chlorophyll concentration and the red shift phenomena.

An optimized Chlorophyll a switching algorithm for MERIS and OLCI in phytoplankton-dominated waters

CSIR Research Space (South Africa)

Smith, Marie E

2018-06-01

Full Text Available complexity for ocean colour applications such as Harmful Algal Bloom (HAB) monitoring. As low and high biomass algorithmic approaches for ocean colour differ, no single algorithm can optimally retrieve accurate Chl a over such a wide range of biomass. We...

Colorant modelling for on-line paper coloring: Evaluations of models and an extension to Kubelka-Munk model

Science.gov (United States)

Shakespeare, Tarja Tuulikki

Traditionally, single constant Kubelka-Munk type colorant formulation algorithms have been used for color control in the paper industry. Tuning data is derived from colored handsheets representing dyeing of a particular color grade, applicable to a substrate of similar properties. Due to furnish variation and changes in the chemical environment, such tuning data is of limited accuracy in practice. Kubelka-Munk approaches have numerous other limitations, in part due to their physically unrealistic assumptions. In particular, they neglect fluorescence phenomena, the interdependence of absorption and scattering, and nonlinearities due to colorant interactions. This thesis addresses those problems. A set of colored handsheets was made, employing several anionic direct dyes and fluorescent colorants, individually and in various combinations. Both a spectrophotometer and a spectrofluorimeter were used for measuring color properties. An extended Langmuir adsorption isotherm was used in modelling the dye-on- fiber in each dyeing. Kubelka-Munk absorption and scattering coefficients were then modelled based on dye- on-fiber, and a number of the limitations of the Kubelka- Munk approach were clearly demonstrated. An extended phenomenological model was derived, incorporating fluorescence and interdependence of absorption and scattering. This model predicts illuminator-independent radiance transfer factors based on dye-on-fiber, from which total radiance factor responses under arbitrary illumination can be computed. It requires spectrofluorometric measurements to characterize the coloring process. A new reflectance factor model, based on the same adsorption isotherm approach, was derived for non- fluorescent colorants. A corresponding total radiance factor model, which is illuminator-dependent, was derived for fluorescent colorants. These models have provision for phenomena such as broadening of absorption and scattering bands, which are encountered in practice. Being based on

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

Directory of Open Access Journals (Sweden)

Stéfani Novoa

2017-01-01

Full Text Available The accurate measurement of suspended particulate matter (SPM concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal (ρw tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i an assessment of existing atmospheric correction (AC algorithms developed for turbid coastal waters; and (ii a switching method that automatically selects the most sensitive SPM vs. ρw relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE with a method based on multi-temporal analyses of atmospheric constituents (MACCS. For the selected scenes, the ACOLITE-MACCS difference was

Modeling human color categorization: Color discrimination and color memory

OpenAIRE

Heskes, T.; van den Broek, Egon; Lucas, P.; Hendriks, Maria A.; Vuurpijl, L.G.; Puts, M.J.H.; Wiegerinck, W.

2003-01-01

Color matching in Content-Based Image Retrieval is done using a color space and measuring distances between colors. Such an approach yields non-intuitive results for the user. We introduce color categories (or focal colors), determine that they are valid, and use them in two experiments. The experiments conducted prove the difference between color categorization by the cognitive processes color discrimination and color memory. In addition, they yield a Color Look-Up Table, which can improve c...

Accelerated one-step generation of full-color holographic videos using a color-tunable novel-look-up-table method for holographic three-dimensional television broadcasting

Science.gov (United States)

Kim, Seung-Cheol; Dong, Xiao-Bin; Kim, Eun-Soo

2015-09-01

A color-tunable novel-look-up-table (CT-NLUT) for fast one-step calculation of full-color computer-generated holograms is proposed. The proposed method is composed of four principal fringe patterns (PFPs) such as a baseline, a depth-compensating and two color-compensating PFPs. CGH patterns for one color are calculated by combined use of baseline-PFP and depth-compensating-PFP and from them, those for two other colors are generated by being multiplied by the corresponding color-compensating-PFPs. color-compensating-PFPs compensate for differences in the wavelength between two colors based on their unique achromatic thin-lens properties, enabling transformation of one-color CGH pattern into those for other colors. This color-conversion property of the proposed method enables simultaneous generation of full color-CGH patterns, resulting in a significant reduction of the full color-CGH calculation time. Experimental results with test scenario show that the full color-CGH calculation time of the proposed CT-NLUT has been reduced by 45.10%, compared to the conventional NLUT. It has been further reduced by 96.01% when a data compression algorithm, called temporal redundancy-based NLUT, was used together, which means 25-fold reduction of its full color-CGH calculation time. Successful computational and optical reconstructions of full color-CGH patterns confirm the feasibility of the proposed method.

Scheduling algorithms for saving energy and balancing load

Energy Technology Data Exchange (ETDEWEB)

Antoniadis, Antonios

2012-08-03

-processor result the competitive factor increases by an additive constant of 1. With respect to load balancing, we consider offline load balancing on identical machines, with the objective of minimizing the current load, for temporary unit-weight jobs. The problem can be seen as coloring n intervals with k colors, such that for each point on the line, the maximal difference between the number of intervals of any two colors is minimal. We prove that a coloring with maximal difference at most one is always possible, and develop a fast polynomial-time algorithm for generating such a coloring. Regarding the online version of the problem, we show that the maximal difference in the size of color classes can become arbitrary high for any online algorithm. Lastly, we prove that two generalizations of the problem are NP-hard. In the first we generalize from intervals to d-dimensional boxes while in the second we consider multiple-intervals, i.e., specific subsets of disjoint intervals must receive the same color.

Equitable Colorings Of Corona Multiproducts Of Graphs

Directory of Open Access Journals (Sweden)

Furmánczyk Hanna

2017-11-01

Full Text Available A graph is equitably k-colorable if its vertices can be partitioned into k independent sets in such a way that the numbers of vertices in any two sets differ by at most one. The smallest k for which such a coloring exists is known as the equitable chromatic number of G and denoted by =(G. It is known that the problem of computation of =(G is NP-hard in general and remains so for corona graphs. In this paper we consider the same model of coloring in the case of corona multiproducts of graphs. In particular, we obtain some results regarding the equitable chromatic number for the l-corona product G ◦l H, where G is an equitably 3- or 4-colorable graph and H is an r-partite graph, a cycle or a complete graph. Our proofs are mostly constructive in that they lead to polynomial algorithms for equitable coloring of such graph products provided that there is given an equitable coloring of G. Moreover, we confirm the Equitable Coloring Conjecture for corona products of such graphs. This paper extends the results from [H. Furmánczyk, K. Kaliraj, M. Kubale and V.J. Vivin, Equitable coloring of corona products of graphs, Adv. Appl. Discrete Math. 11 (2013 103–120].

Color seamlessness in multi-projector displays using constrained gamut morphing.

Science.gov (United States)

Sajadi, Behzad; Lazarov, Maxim; Majumder, Aditi; Gopi, M

2009-01-01

Multi-projector displays show significant spatial variation in 3D color gamut due to variation in the chromaticity gamuts across the projectors, vignetting effect of each projector and also overlap across adjacent projectors. In this paper we present a new constrained gamut morphing algorithm that removes all these variations and results in true color seamlessness across tiled multiprojector displays. Our color morphing algorithm adjusts the intensities of light from each pixel of each projector precisely to achieve a smooth morphing from one projector's gamut to the other's through the overlap region. This morphing is achieved by imposing precise constraints on the perceptual difference between the gamuts of two adjacent pixels. In addition, our gamut morphing assures a C1 continuity yielding visually pleasing appearance across the entire display.We demonstrate our method successfully on a planar and a curved display using both low and high-end projectors. Our approach is completely scalable, efficient and automatic. We also demonstrate the real-time performance of our image correction algorithm on GPUs for interactive applications. To the best of our knowledge, this is the first work that presents a scalable method with a strong foundation in perception and realizes, for the first time, a truly seamless display where the number of projectors cannot be deciphered.

Color Image Evaluation for Small Space Based on FA and GEP

Directory of Open Access Journals (Sweden)

Li Deng

2014-01-01

Full Text Available Aiming at the problem that color image is difficult to quantify, this paper proposes an evaluation method of color image for small space based on factor analysis (FA and gene expression programming (GEP and constructs a correlation model between color image factors and comprehensive color image. The basic color samples of small space and color images are evaluated by semantic differential method (SD method, color image factors are selected via dimension reduction in FA, factor score function is established, and by combining the entropy weight method to determine each factor weights then the comprehensive color image score is calculated finally. The best fitting function between color image factors and comprehensive color image is obtained by GEP algorithm, which can predict the users’ color image values. A color image evaluation system for small space is developed based on this model. The color evaluation of a control room on AC frequency conversion rig is taken as an example, verifying the effectiveness of the proposed method. It also can assist the designers in other color designs and provide a fast evaluation tool for testing users’ color image.

A Robust Color Image Watermarking Scheme Using Entropy and QR Decomposition

Directory of Open Access Journals (Sweden)

L. Laur

2015-12-01

Full Text Available Internet has affected our everyday life drastically. Expansive volumes of information are exchanged over the Internet consistently which causes numerous security concerns. Issues like content identification, document and image security, audience measurement, ownership, copyrights and others can be settled by using digital watermarking. In this work, robust and imperceptible non-blind color image watermarking algorithm is proposed, which benefit from the fact that watermark can be hidden in different color channel which results into further robustness of the proposed technique to attacks. Given method uses some algorithms such as entropy, discrete wavelet transform, Chirp z-transform, orthogonal-triangular decomposition and Singular value decomposition in order to embed the watermark in a color image. Many experiments are performed using well-known signal processing attacks such as histogram equalization, adding noise and compression. Experimental results show that proposed scheme is imperceptible and robust against common signal processing attacks.

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

Science.gov (United States)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

The most oligotrophic subtropical zones of the global ocean: similarities and differences in terms of chlorophyll and yellow substance

OpenAIRE

A. Morel; H. Claustre; B. Gentili

2010-01-01

The cores of the subtropical anticyclonic gyres are characterized by their oligotrophic status and minimal chlorophyll concentration, compared to that of the whole ocean. These zones are unambiguously detected by space borne ocean color sensors thanks to their typical spectral reflectance, which is that of extremely clear and deep blue waters. Not only the low chlorophyll (denoted [Chl]) level, but also a reduced amount of colored dissolved organic matter (CDOM or "yellow substance") account ...

The most oligotrophic subtropical zones of the global ocean: similarities and differences in terms of chlorophyll and yellow substance

OpenAIRE

Morel, A.; Claustre, H.; Gentili, B.

2010-01-01

The cores of the subtropical anticyclonic gyres are characterized by their oligotrophic status and minimal chlorophyll concentration, compared to that of the whole ocean. These zones are unambiguously detected by space borne ocean color sensors thanks to their typical spectral reflectance, which is that of extremely clear and deep blue waters. Not only the low chlorophyll (denoted [Chl]) level, but also a reduced amount of colored dissolved organic matter (CDOM or "yellow substance") acc...

Perceptual approach for unsupervised digital color restoration of cinematographic archives

Science.gov (United States)

Chambah, Majed; Rizzi, Alessandro; Gatta, Carlo; Besserer, Bernard; Marini, Daniele

2003-01-01

The cinematographic archives represent an important part of our collective memory. We present in this paper some advances in automating the color fading restoration process, especially with regard to the automatic color correction technique. The proposed color correction method is based on the ACE model, an unsupervised color equalization algorithm based on a perceptual approach and inspired by some adaptation mechanisms of the human visual system, in particular lightness constancy and color constancy. There are some advantages in a perceptual approach: mainly its robustness and its local filtering properties, that lead to more effective results. The resulting technique, is not just an application of ACE on movie images, but an enhancement of ACE principles to meet the requirements in the digital film restoration field. The presented preliminary results are satisfying and promising.

Optimized universal color palette design for error diffusion

Science.gov (United States)

Kolpatzik, Bernd W.; Bouman, Charles A.

1995-04-01

Currently, many low-cost computers can only simultaneously display a palette of 256 color. However, this palette is usually selectable from a very large gamut of available colors. For many applications, this limited palette size imposes a significant constraint on the achievable image quality. We propose a method for designing an optimized universal color palette for use with halftoning methods such as error diffusion. The advantage of a universal color palette is that it is fixed and therefore allows multiple images to be displayed simultaneously. To design the palette, we employ a new vector quantization method known as sequential scalar quantization (SSQ) to allocate the colors in a visually uniform color space. The SSQ method achieves near-optimal allocation, but may be efficiently implemented using a series of lookup tables. When used with error diffusion, SSQ adds little computational overhead and may be used to minimize the visual error in an opponent color coordinate system. We compare the performance of the optimized algorithm to standard error diffusion by evaluating a visually weighted mean-squared-error measure. Our metric is based on the color difference in CIE L*AL*B*, but also accounts for the lowpass characteristic of human contrast sensitivity.

Coastal Zone Color Scanner studies

Science.gov (United States)

Elrod, J.

1988-01-01

Activities over the past year have included cooperative work with a summer faculty fellow using the Coastal Zone Color Scanner (CZCS) imagery to study the effects of gradients in trophic resources on coral reefs in the Caribbean. Other research included characterization of ocean radiances specific to an acid-waste plume. Other activities include involvement in the quality control of imagery produced in the processing of the global CZCS data set, the collection of various other data global sets, and the subsequent data comparison and analysis.

Autonomous detection of ISO fade point with color laser printers

Science.gov (United States)

Yan, Ni; Maggard, Eric; Fothergill, Roberta; Jessome, Renee J.; Allebach, Jan P.

2015-01-01

Image quality assessment is a very important field in image processing. Human observation is slow and subjective, it also requires strict environment setup for the psychological test 1. Thus developing algorithms to match desired human experiments is always in need. Many studies have focused on detecting the fading phenomenon after the materials are printed, that is to monitor the persistence of the color ink 2-4. However, fading is also a common artifact produced by printing systems when the cartridges run low. We want to develop an automatic system to monitor cartridge life and report fading defects when they appear. In this paper, we first describe a psychological experiment that studies the human perspective on printed fading pages. Then we propose an algorithm based on Color Space Projection and K-means clustering to predict the visibility of fading defects. At last, we integrate the psychological experiment result with our algorithm to give a machine learning tool that monitors cartridge life.

A new parameterization for surface ocean light attenuation in Earth System Models: assessing the impact of light absorption by colored detrital material

Science.gov (United States)

Kim, G. E.; Pradal, M.-A.; Gnanadesikan, A.

2015-03-01

Light limitation can affect the distribution of biota and nutrients in the ocean. Light absorption by colored detrital material (CDM) was included in a fully coupled Earth System Model using a new parameterization for shortwave attenuation. Two model runs were conducted, with and without light attenuation by CDM. In a global average sense, greater light limitation associated with CDM increased surface chlorophyll, biomass and nutrients together. These changes can be attributed to the movement of biological productivity higher up the water column, which increased surface chlorophyll and biomass while simultaneously decreasing total biomass. Meanwhile, the reduction in biomass resulted in greater nutrient availability throughout the water column. Similar results were found on a regional scale in an analysis of the oceans by biome. In coastal regions, surface chlorophyll increased by 35% while total integrated phytoplankton biomass diminished by 18%. The largest relative increases in modeled surface chlorophyll and biomass in the open ocean were found in the equatorial biomes, while largest decreases in depth-integrated biomass and chlorophyll were found in the subpolar and polar biomes. This mismatch of surface and subsurface trends and their regional dependence was analyzed by comparing the competing factors of diminished light availability and increased nutrient availability on phytoplankton growth in the upper 200 m. Overall, increases in surface biomass were expected to accompany greater nutrient uptake and therefore diminish surface nutrients, but changes in light limitation decoupled trends between these two variables. Understanding changes in biological productivity requires both surface and depth-resolved information. Surface trends may be minimal or of the opposite sign to depth-integrated amounts, depending on the vertical structure of phytoplankton abundance.

Ocean surface partitioning strategies using ocean colour remote Sensing: A review

Science.gov (United States)

Krug, Lilian Anne; Platt, Trevor; Sathyendranath, Shubha; Barbosa, Ana B.

2017-06-01

The ocean surface is organized into regions with distinct properties reflecting the complexity of interactions between environmental forcing and biological responses. The delineation of these functional units, each with unique, homogeneous properties and underlying ecosystem structure and dynamics, can be defined as ocean surface partitioning. The main purposes and applications of ocean partitioning include the evaluation of particular marine environments; generation of more accurate satellite ocean colour products; assimilation of data into biogeochemical and climate models; and establishment of ecosystem-based management practices. This paper reviews the diverse approaches implemented for ocean surface partition into functional units, using ocean colour remote sensing (OCRS) data, including their purposes, criteria, methods and scales. OCRS offers a synoptic, high spatial-temporal resolution, multi-decadal coverage of bio-optical properties, relevant to the applications and value of ocean surface partitioning. In combination with other biotic and/or abiotic data, OCRS-derived data (e.g., chlorophyll-a, optical properties) provide a broad and varied source of information that can be analysed using different delineation methods derived from subjective, expert-based to unsupervised learning approaches (e.g., cluster, fuzzy and empirical orthogonal function analyses). Partition schemes are applied at global to mesoscale spatial coverage, with static (time-invariant) or dynamic (time-varying) representations. A case study, the highly heterogeneous area off SW Iberian Peninsula (NE Atlantic), illustrates how the selection of spatial coverage and temporal representation affects the discrimination of distinct environmental drivers of phytoplankton variability. Advances in operational oceanography and in the subject area of satellite ocean colour, including development of new sensors, algorithms and products, are among the potential benefits from extended use, scope and

Research on the Algoritm of Automatic Map Coloring and Its Application%地图自动着色算法研究与实践

Institute of Scientific and Technical Information of China (English)

李晓年; 张国合; 朱翊; 刘晓东

2011-01-01

从四色问题的抽象模型入手,通过对现有的搜索算法——遗传算法、模拟退火算法这两种算法的原理和流程进行了较为细致的分析,总结出它们在地图四色填充实现过程中的优点与不足之处,并进行比较,找出这两种算法的结合点进行算法的改进优化,将模拟退火算法引入遗传算法,使它们结合起来解决地图四色填充问题,从而形成相对优化的算法,以期达到更加优化的效果.%This article firstly introduced the abstract model of four-color problem for map coloring.Then,through the detail analysis on the principle and process of the existing search algorithms that such as genetic algorithm and simulated annealing algorithm,it summarized the advantages and shortcomings of these algorithms when dealing with the four-color problem for map coloring.Based on the comparison,it found the joint point of the two algorithms to improve and optimize them.It introduced the simulated annealing algorithm into the genetic algorithm,and combined the two algorithms to solve the four-color problem for map coloring and achieve more optimized results.

Planar graphs theory and algorithms

CERN Document Server

Nishizeki, T

1988-01-01

Collected in this volume are most of the important theorems and algorithms currently known for planar graphs, together with constructive proofs for the theorems. Many of the algorithms are written in Pidgin PASCAL, and are the best-known ones; the complexities are linear or 0(nlogn). The first two chapters provide the foundations of graph theoretic notions and algorithmic techniques. The remaining chapters discuss the topics of planarity testing, embedding, drawing, vertex- or edge-coloring, maximum independence set, subgraph listing, planar separator theorem, Hamiltonian cycles, and single- or multicommodity flows. Suitable for a course on algorithms, graph theory, or planar graphs, the volume will also be useful for computer scientists and graph theorists at the research level. An extensive reference section is included.

Vector sparse representation of color image using quaternion matrix analysis.

Science.gov (United States)

Xu, Yi; Yu, Licheng; Xu, Hongteng; Zhang, Hao; Nguyen, Truong

2015-04-01

Traditional sparse image models treat color image pixel as a scalar, which represents color channels separately or concatenate color channels as a monochrome image. In this paper, we propose a vector sparse representation model for color images using quaternion matrix analysis. As a new tool for color image representation, its potential applications in several image-processing tasks are presented, including color image reconstruction, denoising, inpainting, and super-resolution. The proposed model represents the color image as a quaternion matrix, where a quaternion-based dictionary learning algorithm is presented using the K-quaternion singular value decomposition (QSVD) (generalized K-means clustering for QSVD) method. It conducts the sparse basis selection in quaternion space, which uniformly transforms the channel images to an orthogonal color space. In this new color space, it is significant that the inherent color structures can be completely preserved during vector reconstruction. Moreover, the proposed sparse model is more efficient comparing with the current sparse models for image restoration tasks due to lower redundancy between the atoms of different color channels. The experimental results demonstrate that the proposed sparse image model avoids the hue bias issue successfully and shows its potential as a general and powerful tool in color image analysis and processing domain.

Nimbus 7 Coastal Zone Color Scanner (CZCS). Level 2 data product users' guide

Science.gov (United States)

Williams, S. P.; Szajna, E. F.; Hovis, W. A.

1985-01-01

The coastal zone color scanner (CZCS) is a scanning multispectral radiometer designed for the remote sensing of ocean color parameters from an earth orbiting space platform. A Technical Manual was designed for users of NIMBUS 7 CZCS Level 2 data products. It contains information which describes how the Level 1 data was process to obtain the Level 2 (derived) product. It contains information needed to operate on the data using digital computers and related equipment.

A REVIEW OF COLOR MEASURMENTS IN THE TEXTILE INDUSTRY

Directory of Open Access Journals (Sweden)

BRAD Raluca

2016-05-01

Full Text Available Color is an important factor in the evaluation of aesthetic appearance and functionality of many products, but especially of textile industry ones. In textiles production process, color can be assessed in different stages: the selection of raw materials, the incoming item tests, the preparation of dyeing ingredients, the crocking resistance testing, the color fastness and in all stages, the quality control. Color evaluation can be done visually or using specialized test instruments such as colorimeters or spectrometers, therefore a high accuracy of measurements must be achieved. Standards describe different procedures and testing techniques depending on the product type and the quality level required by the customer. The paper presents the most common systems of color representation and communication, measurement methods and techniques, and standards that define them. The CIE color representation systems have been reviewed, together with the measurement methods offering the repeatability of the process. Most of the standards have been issued in US, but several European and International are stating the color assessment process. We have also conducted a review of latest published papers in the topic of color measurement, comparison and match. Several image processing applications algorithms offers new opportunities for computer assisted evaluation and control of textile color properties.

Investigation of dynamic of unconsolidated materials using two-color digital holography

Directory of Open Access Journals (Sweden)

Boileau J.-P.

2010-06-01

Full Text Available The paper presents a two-color digital holographic interferometer. The set-up is devoted to the study of the fundamental dynamic of unconsolidated materials. Optical configuration and algorithms to recover the optical phase of two-color digitally encoded holograms are described. The method is based on a spatial-color-multiplexing scheme in which holographic reconstruction is performed using adapted wavelength zero-padding and reconstructing distance. Experimental results are presented in the case of granular media excited in the frequency range 400Hz-3000Hz and exhibits the 3D movement.

A New Binarization Algorithm for Historical Documents

Directory of Open Access Journals (Sweden)

Marcos Almeida

2018-01-01

Full Text Available Monochromatic documents claim for much less computer bandwidth for network transmission and storage space than their color or even grayscale equivalent. The binarization of historical documents is far more complex than recent ones as paper aging, color, texture, translucidity, stains, back-to-front interference, kind and color of ink used in handwriting, printing process, digitalization process, etc. are some of the factors that affect binarization. This article presents a new binarization algorithm for historical documents. The new global filter proposed is performed in four steps: filtering the image using a bilateral filter, splitting image into the RGB components, decision-making for each RGB channel based on an adaptive binarization method inspired by Otsu’s method with a choice of the threshold level, and classification of the binarized images to decide which of the RGB components best preserved the document information in the foreground. The quantitative and qualitative assessment made with 23 binarization algorithms in three sets of “real world” documents showed very good results.

Sensitivity of Ocean Reflectance Inversion Models for Identifying and Discriminating Between Phytoplankton Functional Groups

Science.gov (United States)

Werdell, P. Jeremy; Ooesler, Collin S.

2012-01-01

The daily, synoptic images provided by satellite ocean color instruments provide viable data streams for observing changes in the biogeochemistrY of marine ecosystems. Ocean reflectance inversion models (ORMs) provide a common mechanism for inverting the "color" of the water observed a satellite into marine inherent optical properties (lOPs) through a combination of empiricism and radiative transfer theory. lOPs, namely the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents, describe the contents of the upper ocean, information critical for furthering scientific understanding of biogeochemical oceanic processes. Many recent studies inferred marine particle sizes and discriminated between phytoplankton functional groups using remotely-sensed lOPs. While all demonstrated the viability of their approaches, few described the vertical distributions of the water column constituents under consideration and, thus, failed to report the biophysical conditions under which their model performed (e.g., the depth and thickness of the phytoplankton bloom(s)). We developed an ORM to remotely identifY Noctiluca miliaris and other phytoplankton functional types using satellite ocean color data records collected in the northern Arabian Sea. Here, we present results from analyses designed to evaluate the applicability and sensitivity of the ORM to varied biophysical conditions. Specifically, we: (1) synthesized a series of vertical profiles of spectral inherent optical properties that represent a wide variety of bio-optical conditions for the northern Arabian Sea under aN Miliaris bloom; (2) generated spectral remote-sensing reflectances from these profiles using Hydrolight; and, (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N Miliaris for each example. By comparing the estimates from the inversion model to those from synthesized vertical profiles, we were able to

Integrating biogeochemistry and ecology into ocean data assimilation systems

DEFF Research Database (Denmark)

Brasseur, Pierre; Gruber, Nicolas; Barciela, Rosa

2009-01-01

that are not yet considered essential, such as upper-ocean vertical fluxes that are critically important to biological activity. Further, the observing systems will need to be expanded in terms of in situ platforms (with intensified deployments of sensors for O-2 and chlorophyll, and inclusion of new sensors...... for nutrients, zooplankton, micronekton biomass, and others), satellite missions (e.g., hyperspectral instruments for ocean color, lidar systems for mixed-layer depths, and wide-swath altimeters for coastal sea level), and improved methods to assimilate these new measurements....

How Two Sides of the Atlantic Contributed to Understanding of the Global Oceans: Charles Yentsch and Andre Morel

Science.gov (United States)

Acker, James G.

2013-01-01

In a few short days in September of this year, the ocean color/ocean optics community lost two of the founding members of its Hall of FameCharles Yentsch and Andre Morel. Yentsch passed away at the age of 85 on September 19, and Morel passed away on September 23 at the age of 79. It might sound clich to say that someone was instrumental to the advance of science in a particular field, but in the case of Yentsch and Morel and ocean color instrumentation, such an assessment would likely be accurate. Each mans career complimented that of the other Yentsch was one of the first to make measurements of the light field of the ocean from altitude and to advocate an instrument in space that could observe the spectrum of ocean radiance Morels theoretical underpinnings established a firm foundation for the measurements such an instrument could make, allowing their successful interpretation.

Spatial imaging in color and HDR: prometheus unchained

Science.gov (United States)

McCann, John J.

2013-03-01

The Human Vision and Electronic Imaging Conferences (HVEI) at the IS and T/SPIE Electronic Imaging meetings have brought together research in the fundamentals of both vision and digital technology. This conference has incorporated many color disciplines that have contributed to the theory and practice of today's imaging: color constancy, models of vision, digital output, high-dynamic-range imaging, and the understanding of perceptual mechanisms. Before digital imaging, silver halide color was a pixel-based mechanism. Color films are closely tied to colorimetry, the science of matching pixels in a black surround. The quanta catch of the sensitized silver salts determines the amount of colored dyes in the final print. The rapid expansion of digital imaging over the past 25 years has eliminated the limitations of using small local regions in forming images. Spatial interactions can now generate images more like vision. Since the 1950's, neurophysiology has shown that post-receptor neural processing is based on spatial interactions. These results reinforced the findings of 19th century experimental psychology. This paper reviews the role of HVEI in color, emphasizing the interaction of research on vision and the new algorithms and processes made possible by electronic imaging.

Color image guided depth image super resolution using fusion filter

Science.gov (United States)

He, Jin; Liang, Bin; He, Ying; Yang, Jun

2018-04-01

Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.

Modeling human color categorization: Color discrimination and color memory

NARCIS (Netherlands)

Heskes, T.; van den Broek, Egon; Lucas, P.; Hendriks, Maria A.; Vuurpijl, L.G.; Puts, M.J.H.; Wiegerinck, W.

2003-01-01

Color matching in Content-Based Image Retrieval is done using a color space and measuring distances between colors. Such an approach yields non-intuitive results for the user. We introduce color categories (or focal colors), determine that they are valid, and use them in two experiments. The

Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems

Energy Technology Data Exchange (ETDEWEB)

Scherrer, Chad; Halappanavar, Mahantesh; Tewari, Ambuj; Haglin, David J.

2012-07-03

We present a generic framework for parallel coordinate descent (CD) algorithms that has as special cases the original sequential algorithms of Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm of Bradley et al. We introduce two novel parallel algorithms that are also special cases---Thread-Greedy CD and Coloring-Based CD---and give performance measurements for an OpenMP implementation of these.

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight.

Science.gov (United States)

Guo, Siqiu; Zhang, Tao; Song, Yulong; Qian, Feng

2018-04-23

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios.

Splitting turbulence algorithm for mixing parameterization embedded in the ocean climate model. Examples of data assimilation and Prandtl number variations.

Science.gov (United States)

Moshonkin, Sergey; Gusev, Anatoly; Zalesny, Vladimir; Diansky, Nikolay

2017-04-01

Series of experiments were performed with a three-dimensional, free surface, sigma coordinate eddy-permitting ocean circulation model for Atlantic (from 30°S) - Arctic and Bering sea domain (0.25 degrees resolution, Institute of Numerical Mathematics Ocean Model or INMOM) using vertical grid refinement in the zone of fully developed turbulence (40 sigma-levels). The model variables are horizontal velocity components, potential temperature, and salinity as well as free surface height. For parameterization of viscosity and diffusivity, the original splitting turbulence algorithm (STA) is used when total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF) split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage the analytical solution was obtained for TKE and TDF as functions of the buoyancy and velocity shift frequencies (BF and VSF). The proposed model with STA is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. For mixing simulation in the zone of turbulence decay, the two kind numerical experiments were carried out, as with assimilation of annual mean climatic buoyancy frequency, as with variation of Prandtl number function dependence upon the BF, VSF, TKE and TDF. The CORE-II data for 1948-2009 were used for experiments. Quality of temperature T and salinity S structure simulation is estimated by the comparison of model monthly profiles T and S averaged for 1980-2009, with T and S monthly data from the World Ocean Atlas 2013. Form of coefficients in equations for TKE and TDF on the generation-dissipation stage makes it possible to assimilate annual mean climatic buoyancy frequency in a varying degree that cardinally improves adequacy of model results to climatic data in all analyzed model domain. The numerical experiments with modified

The Research and Application of SURF Algorithm Based on Feature Point Selection Algorithm

Directory of Open Access Journals (Sweden)

Zhang Fang Hu

2014-04-01

Full Text Available As the pixel information of depth image is derived from the distance information, when implementing SURF algorithm with KINECT sensor for static sign language recognition, there can be some mismatched pairs in palm area. This paper proposes a feature point selection algorithm, by filtering the SURF feature points step by step based on the number of feature points within adaptive radius r and the distance between the two points, it not only greatly improves the recognition rate, but also ensures the robustness under the environmental factors, such as skin color, illumination intensity, complex background, angle and scale changes. The experiment results show that the improved SURF algorithm can effectively improve the recognition rate, has a good robustness.

Evolution of pygmy angelfishes: Recent divergences, introgression, and the usefulness of color in taxonomy

KAUST Repository

Gaither, Michelle R.; Schultz, Jennifer K.; Bellwood, David R.; Pyle, Richard L.; DiBattista, Joseph; Rocha, Luiz A.; Bowen, Brian W.

2014-01-01

The pygmy angelfishes (genus Centropyge, family Pomacanthidae) are brightly colored species that occupy reef habitats in every tropical ocean. Some species are rarely observed because they occur below conventional scuba depths. Their striking

Revealing the timing of ocean stratification using remotely sensed ocean fronts

Science.gov (United States)

Miller, Peter I.; Loveday, Benjamin R.

2017-10-01

Stratification is of critical importance to the circulation, mixing and productivity of the ocean, and is expected to be modified by climate change. Stratification is also understood to affect the surface aggregation of pelagic fish and hence the foraging behaviour and distribution of their predators such as seabirds and cetaceans. Hence it would be prudent to monitor the stratification of the global ocean, though this is currently only possible using in situ sampling, profiling buoys or underwater autonomous vehicles. Earth observation (EO) sensors cannot directly detect stratification, but can observe surface features related to the presence of stratification, for example shelf-sea fronts that separate tidally-mixed water from seasonally stratified water. This paper describes a novel algorithm that accumulates evidence for stratification from a sequence of oceanic front maps, and discusses preliminary results in comparison with in situ data and simulations from 3D hydrodynamic models. In certain regions, this method can reveal the timing of the seasonal onset and breakdown of stratification.

Image color reduction method for color-defective observers using a color palette composed of 20 particular colors

Science.gov (United States)

Sakamoto, Takashi

2015-01-01

This study describes a color enhancement method that uses a color palette especially designed for protan and deutan defects, commonly known as red-green color blindness. The proposed color reduction method is based on a simple color mapping. Complicated computation and image processing are not required by using the proposed method, and the method can replace protan and deutan confusion (p/d-confusion) colors with protan and deutan safe (p/d-safe) colors. Color palettes for protan and deutan defects proposed by previous studies are composed of few p/d-safe colors. Thus, the colors contained in these palettes are insufficient for replacing colors in photographs. Recently, Ito et al. proposed a p/dsafe color palette composed of 20 particular colors. The author demonstrated that their p/d-safe color palette could be applied to image color reduction in photographs as a means to replace p/d-confusion colors. This study describes the results of the proposed color reduction in photographs that include typical p/d-confusion colors, which can be replaced. After the reduction process is completed, color-defective observers can distinguish these confusion colors.

CONTROLLED CONDENSATION IN K-NN AND ITS APPLICATION FOR REAL TIME COLOR IDENTIFICATION

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Carmen Villar Patiño

2017-04-01

Full Text Available k-NN algorithms are frequently used in statistical classification. They are accurate and distribution free. Despite these advantages, k-NN algorithms imply a high computational cost. To find efficient ways to implement them is an important challenge in pattern recognition. In this article, an improved version of the k-NN Controlled Condensation algorithm is introduced. Its potential for instantaneous color identification in real time is also analyzed. This algorithm is based on the representation of data in terms of a reduced set of informative prototypes. It includes two parameters to control the balance between speed and precision. This gives us the opportunity to achieve a convenient percentage of condensation without incurring in an important loss of accuracy. We test our proposal in an instantaneous color identification exercise in video images. We achieve the real time identification by using k-NN Controlled Condensation executed through multi-threading programming methods. The results are encouraging.

Ocean Science for Decision-Making: Current Activities of the National Research Council's Ocean Studies Board

Science.gov (United States)

Roberts, S.; Glickson, D.; Mengelt, C.; Forrest, S.; Waddell, K.

2012-12-01

The National Research Council is a private, nonprofit organization chartered by Congress in 1916 as an expansion of the U.S. National Academy of Sciences. Its mission is to improve the use of science in government decision making and public policy, increase public understanding, and promote the acquisition and dissemination of knowledge in matters involving science, engineering, technology, and health. Within the National Research Council, the Ocean Studies Board (OSB) mission is to explore the science, policies, and infrastructure needed to understand, manage, and conserve coastal and marine environments and resources. OSB undertakes studies and workshops on emerging scientific and policy issues at the request of federal agencies, Congress, and others; provides program reviews and guidance; and facilitates communication on oceanographic issues among different sectors. OSB also serves as the U.S. National Committee to the international, nongovernmental Scientific Committee on Oceanic Research (SCOR). OSB has produced reports on a wide range of topics of interest to researchers and educators, the federal government, the non-profit sector, and industry. Recent reports have focused on ecosystem services in the Gulf of Mexico after the Deepwater Horizon oil spill, sea level rise on the U.S. west coast, scientific ocean drilling needs and accomplishments, requirements for sustained ocean color measurements, critical infrastructure for ocean research, tsunami warning and preparedness, ocean acidification, and marine and hydrokinetic power resource assessments. Studies that are currently underway include responding to oil spills in the Arctic, evaluating the effectiveness of fishery stock rebuilding plans, and reviewing the National Ocean Acidification Research Plan. OSB plays an important role in helping create policy decisions and disseminating important information regarding various aspects of ocean science.

Optical Moorings-of-Opportunity for Validation of Ocean Color Satellites

Science.gov (United States)

2008-01-01

at the midpoint of the two depths is given by: K , z d dz lnE , z , , d dλ λ λ λ ( ) = − ( )[ ] ( ) = − ( ) ( ) ( ) 4a 1 z ln E , z E , z 4bd 2 d 1...Biological Oceanography Program ( TD : OCE-9627281, OCE-9730471, OCE-9819477), NASA ( TD : NAS5-97127), the ONR Ocean Engineering and Marine Systems Program

Cartesian product of hypergraphs: properties and algorithms

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Alain Bretto

2009-09-01

Full Text Available Cartesian products of graphs have been studied extensively since the 1960s. They make it possible to decrease the algorithmic complexity of problems by using the factorization of the product. Hypergraphs were introduced as a generalization of graphs and the definition of Cartesian products extends naturally to them. In this paper, we give new properties and algorithms concerning coloring aspects of Cartesian products of hypergraphs. We also extend a classical prime factorization algorithm initially designed for graphs to connected conformal hypergraphs using 2-sections of hypergraphs.

Influence of Surrounding Colors in the Illuminant-Color Mode on Color Constancy

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Kazuho Fukuda

2011-05-01

Full Text Available On color constancy, we showed that brighter surrounding colors had greater influence than dim colors (Uchikawa, Kitazawa, MacLeod, Fukuda, 2010 APCV. Increasing luminance of a stimulus causes the change in appearance from the surface-color to the illuminant-color mode. However it is unknown whether the visual system considers such color appearance mode of surrounding colors to achieve color constancy. We investigated the influence of surrounding colors that appeared illuminant on color constancy. The stimulus was composed of a central test stimulus and surrounding six colors: bright and dim red, green and blue. The observers adjusted the chromaticity of the test stimulus to be appeared as an achromatic surface. The luminance balance of three bright surrounding colors was equalized with that of the optimal colors in three illuminant conditions, then, the luminance of one of the three bright colors was varied in the range beyond the critical luminance of color appearance mode transition. The results showed that increasing luminance of a bright surrounding color shifted the observers' achromatic setting toward its chromaticity, but this effect diminished for the surrounding color in the illuminant-color mode. These results suggest that the visual system considers color appearance mode of surrounding colors to accomplish color constancy.

Whole Genome Phylogenetic Tree Reconstruction using Colored de Bruijn Graphs

OpenAIRE

Lyman, Cole

2017-01-01

We present kleuren, a novel assembly-free method to reconstruct phylogenetic trees using the Colored de Bruijn Graph. kleuren works by constructing the Colored de Bruijn Graph and then traversing it, finding bubble structures in the graph that provide phylogenetic signal. The bubbles are then aligned and concatenated to form a supermatrix, from which a phylogenetic tree is inferred. We introduce the algorithm that kleuren uses to accomplish this task, and show its performance on reconstructin...

Exemplar-based optical neural net classifier for color pattern recognition

Science.gov (United States)

Yu, Francis T. S.; Uang, Chii-Maw; Yang, Xiangyang

1992-10-01

We present a color exemplar-based neural network that can be used as an optimum image classifier or an associative memory. Color decomposition and composition technique is used for constructing the polychromatic interconnection weight matrix (IWM). The Hamming net algorithm is modified to relax the dynamic range requirement of the spatial light modulator and to reduce the number of iteration cycles in the winner-take-all layer. Computer simulation results demonstrated the feasibility of this approach

OceanXtremes: Scalable Anomaly Detection in Oceanographic Time-Series

Science.gov (United States)

Wilson, B. D.; Armstrong, E. M.; Chin, T. M.; Gill, K. M.; Greguska, F. R., III; Huang, T.; Jacob, J. C.; Quach, N.

2016-12-01

The oceanographic community must meet the challenge to rapidly identify features and anomalies in complex and voluminous observations to further science and improve decision support. Given this data-intensive reality, we are developing an anomaly detection system, called OceanXtremes, powered by an intelligent, elastic Cloud-based analytic service backend that enables execution of domain-specific, multi-scale anomaly and feature detection algorithms across the entire archive of 15 to 30-year ocean science datasets.Our parallel analytics engine is extending the NEXUS system and exploits multiple open-source technologies: Apache Cassandra as a distributed spatial "tile" cache, Apache Spark for in-memory parallel computation, and Apache Solr for spatial search and storing pre-computed tile statistics and other metadata. OceanXtremes provides these key capabilities: Parallel generation (Spark on a compute cluster) of 15 to 30-year Ocean Climatologies (e.g. sea surface temperature or SST) in hours or overnight, using simple pixel averages or customizable Gaussian-weighted "smoothing" over latitude, longitude, and time; Parallel pre-computation, tiling, and caching of anomaly fields (daily variables minus a chosen climatology) with pre-computed tile statistics; Parallel detection (over the time-series of tiles) of anomalies or phenomena by regional area-averages exceeding a specified threshold (e.g. high SST in El Nino or SST "blob" regions), or more complex, custom data mining algorithms; Shared discovery and exploration of ocean phenomena and anomalies (facet search using Solr), along with unexpected correlations between key measured variables; Scalable execution for all capabilities on a hybrid Cloud, using our on-premise OpenStack Cloud cluster or at Amazon. The key idea is that the parallel data-mining operations will be run "near" the ocean data archives (a local "network" hop) so that we can efficiently access the thousands of files making up a three decade time

Removal of impulse noise clusters from color images with local order statistics

Science.gov (United States)

Ruchay, Alexey; Kober, Vitaly

2017-09-01

This paper proposes a novel algorithm for restoring images corrupted with clusters of impulse noise. The noise clusters often occur when the probability of impulse noise is very high. The proposed noise removal algorithm consists of detection of bulky impulse noise in three color channels with local order statistics followed by removal of the detected clusters by means of vector median filtering. With the help of computer simulation we show that the proposed algorithm is able to effectively remove clustered impulse noise. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.

Video-to-Video Dynamic Super-Resolution for Grayscale and Color Sequences

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Elad Michael

2006-01-01

Full Text Available We address the dynamic super-resolution (SR problem of reconstructing a high-quality set of monochromatic or color super-resolved images from low-quality monochromatic, color, or mosaiced frames. Our approach includes a joint method for simultaneous SR, deblurring, and demosaicing, this way taking into account practical color measurements encountered in video sequences. For the case of translational motion and common space-invariant blur, the proposed method is based on a very fast and memory efficient approximation of the Kalman filter (KF. Experimental results on both simulated and real data are supplied, demonstrating the presented algorithms, and their strength.

The colors of icebergs

Science.gov (United States)

Warren, S. G.

2017-12-01

Ordinary icebergs of meteoric glacier ice appear bluish-white, i.e. intermediate in color between the white of snow and the blue of pure ice, depending on the bubble content. However, clear dark bubble-free icebergs are occasionally seen in the Antarctic Ocean; they originate from freezing of seawater to the base of ice shelves. On parts of the Amery Ice Shelf, frozen seawater contributes up to one-third of the ice-shelf thickness. Many of the icebergs produced by the Amery are therefore composite icebergs; the upper part consists of meteoric glacier ice from snowfall, but the lower part is frozen seawater ("marine ice"). When these icebergs capsize, the marine ice is exposed to view; it can be accessed for study in springtime when the icebergs are embedded in shorefast sea ice. The marine ice varies in color from blue to green depending on the content of dissolved organic matter. The color is therefore an indicator of biological productivity in the seawater from which the ice froze. To infer processes at the ice-shelf base, these icebergs may be examined and cored for spectral reflectance, hydrogen and oxygen isotopes, organic matter, particles, and distribution of cracks and stripes. Seasonal and interannual variations may be quantified from samples collected along the marine ice-growth trajectory at the meteoric/marine-ice interface. The scale of small turbulent eddies at the ice-shelf base, which govern the transfer of heat between ocean and ice, can be inferred from the size of scallops in the iceberg surface (typically a few centimeters). Dark stripes within meteoric ice result from tension-cracks at the grounding line, forming basal crevasses that fill suddenly with seawater; their width, spacing, and salinity can give clues to processes at the grounding line. Results will be shown from icebergs sampled on Australian expeditions near Davis and Mawson stations. Marine ice is more readily accessed by sampling an iceberg than by drilling through an ice shelf

An Early Fire Detection Algorithm Using IP Cameras