True Color Images Research Articles

Content‐adaptive steganalysis for color images

AbstractSome steganography methods for gray‐scale image can be extended to true RGB color image by treating each of its three color channels as a gray‐scale image. In modern popular steganography, most embedding changes are highly concentrated on those complex textural regions with smaller embedding distortions. However, the existing steganalysis methods for color images directly extract steganalytic features from the whole image. In this paper, we propose a content‐adaptive steganalysis strategy for color images. The new strategy aims to extract spatial rich model features from each color channel and just extract color rich model features from the pixels that may have been modified. In order to locate those suspected pixels, we first calculate the embedding costs of each channel, and then a subset of pixels with smaller embedding costs is selected. Experimental results show that the proposed strategy performs better than the state‐of‐the‐art color image steganalysis method. Copyright © 2017 John Wiley & Sons, Ltd.

Haze Spectral Analysis and Detection Algorithm Using Satellite Remote Sensing Data

Frequent occurring of haze pollution events and high fine particulate matter (PM(2.5)) concentration in China have attracted more and more attention in the world. Satellite remote sensing can be used to characterize the air pollution. However, haze is usually misidentified as fog, thin cloud or bright surface in NASA’s Moderate Resolution Imaging Spectrometer (MODIS) cloud and clear days’ aerosol products, and the retrieval of its optical properties is not included in MODIS cloud detection and dark target algorithm. This approach first studies the spectral characters of cloud, fog, haze, and land cover pixels. Second, following the previous cloud detection and aerosol retrieval literatures, a threshold algorithm is developed to distinguish haze from other pixels based on MODIS multi-band apparent reflectance and brightness temperature. This algorithm is used to detect the haze distribution over North China Plain in 2008 spring and summer. Our result shows a good agreement with the true-color satellite images, which enhances MODIS’s ability to monitor the severe air pollution episodes. In addition, the high AOD data from Beijing and Xiang Aerosol Robotic NETwork (AERONET) sites indicate nearly 80% haze days are detected by our approach. Finally, we analyze the errors and uncertainties in haze detection algorithm, and put forward the potential improvements.

Combined optical coherence tomography and hyperspectral imaging using a double-clad fiber coupler.

This work demonstrates the combination of optical coherence tomography (OCT) and hyperspectral imaging (HSI) using a double-clad optical fiber coupler. The single-mode core of the fiber is used for OCT imaging, while the inner cladding of the double-clad fiber provides an efficient way to capture the reflectance spectrum of the sample. The combination of both methods enables three-dimensional acquisition of the sample morphology with OCT, enhanced with complementary molecular information contained in the hyperspectral image. The HSI data can be used to highlight the presence of specific molecules with characteristic absorption peaks or to produce true color images overlaid on the OCT volume for improved tissue identification by the clinician. Such a system could be implemented in a number of clinical endoscopic applications and could improve the current practice in tissue characterization, diagnosis, and surgical guidance.

A Robust Automated Cataract Detection Algorithm Using Diagnostic Opinion Based Parameter Thresholding for Telemedicine Application

This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images in adult human subjects. Currently, methods available for cataract detection are based on the use of either fundus camera or Digital Single-Lens Reflex (DSLR) camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of an eye. An algorithm is proposed for cataract screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system and later tested on real subjects in an eye clinic. Finally, a tele-ophthamology model using our proposed system has been suggested, which confirms the telemedicine application of the proposed system.

Comparison of Manual Mapping and Automated Object-Based Image Analysis of Non-Submerged Aquatic Vegetation from Very-High-Resolution UAS Images

Aquatic vegetation has important ecological and regulatory functions and should be monitored in order to detect ecosystem changes. Field data collection is often costly and time-consuming; remote sensing with unmanned aircraft systems (UASs) provides aerial images with sub-decimetre resolution and offers a potential data source for vegetation mapping. In a manual mapping approach, UAS true-colour images with 5-cm-resolution pixels allowed for the identification of non-submerged aquatic vegetation at the species level. However, manual mapping is labour-intensive, and while automated classification methods are available, they have rarely been evaluated for aquatic vegetation, particularly at the scale of individual vegetation stands. We evaluated classification accuracy and time-efficiency for mapping non-submerged aquatic vegetation at three levels of detail at five test sites (100 m × 100 m) differing in vegetation complexity. We used object-based image analysis and tested two classification methods (threshold classification and Random Forest) using eCognition®. The automated classification results were compared to results from manual mapping. Using threshold classification, overall accuracy at the five test sites ranged from 93% to 99% for the water-versus-vegetation level and from 62% to 90% for the growth-form level. Using Random Forest classification, overall accuracy ranged from 56% to 94% for the growth-form level and from 52% to 75% for the dominant-taxon level. Overall classification accuracy decreased with increasing vegetation complexity. In test sites with more complex vegetation, automated classification was more time-efficient than manual mapping. This study demonstrated that automated classification of non-submerged aquatic vegetation from true-colour UAS images was feasible, indicating good potential for operative mapping of aquatic vegetation. When choosing the preferred mapping method (manual versus automated) the desired level of thematic detail and the required accuracy for the mapping task needs to be considered.

Utilization of ETM+ Landsat data in geologic mapping of wadi Ghadir-Gabal Zabara area, Central Eastern Desert, Egypt

The Wadi Ghadir area, Central Eastern Desert, Egypt is covered by a sequence of Pan-African basement rocks comprising allochthonous ophiolitic rock assemblage thrust over Gabal Zabara gneiss. The ophiolite sequence comprises layered gabbro, pillowed basalts, island arc metavolcanics and low grade metasediments. These rocks are intruded by syn-to late tectonic intrusions followed by basic and acidic dyke swarms. The processed digital data of Landsat 7 ETM+ covering the study area have been used. Several products of Landsat-7 ETM+ digital data such as true color image (3, 2 and 1 in RGB), false color composite images (7, 4, 2 and 7, 5, 1 in RGB), principal component (PC2, PC1, PC4), band rationing images (5/1, 3/2, 7/2), (5/3, 4/2, 3/1) and (3/1, 4/2, 5/7) are generated. Products of image processing improve lithological discrimination specially of serpentinites talc carbonate rocks and different varieties of intrusive rocks. Supervised and unsupervised classifications have been used to recognize and discriminate between the different rock units.The obvious color contrast of ratio images enabled easier delineation of major structural features characterizing the mapped area. NNW-SSE striking, easterly dipping, thrust faults are located in the western part within the study area. They are associated with asymmetrical folds whose axial planes are parallel to these thrusts. Other NW folds affecting gabbro masses and mélange rocks could easily be delineated and verified during field observations. Two sets of shear zones of NW and NE trends affect the mapped area. Lineament analysis revealed the prevalence of two main structural trends NW-SE and NE-SW.

Efficient quantum inspired meta-heuristics for multi-level true colour image thresholding

Thresholding is a commonly used simple and effective technique for image segmentation. The computational time in multi-level thresholding significantly increases with the level of computation because of exhaustive searching, adding to exponential growth of computational complexity. Hence, in this paper, the features of quantum computing are exploited to introduce four different quantum inspired meta-heuristic techniques to accelerate the execution of multi-level thresholding. The proposed techniques are Quantum Inspired Genetic Algorithm, Quantum Inspired Simulated Annealing, Quantum Inspired Differential Evolution and Quantum Inspired Particle Swarm Optimization. The effectiveness of the proposed techniques is exhibited in comparison with the backtracking search optimization algorithm, the composite DE method, the classical genetic algorithm, the classical simulated annealing, the classical differential evolution and the classical particle swarm optimization for ten real life true colour images. The experimental results are presented in terms of optimal threshold values for each primary colour component, the fitness value and the computational time (in seconds) at different levels. Thereafter, the quality of thresholding is judged in terms of the peak signal-to-noise ratio for each technique. Moreover, statistical test, referred to as Friedman test, and also median based estimation among all techniques, are conducted separately to judge the preeminence of a technique among them. Finally, the performance of each technique is visually judged from convergence plots for all test images, which affirms that the proposed quantum inspired particle swarm optimization technique outperforms other techniques.

Synergistic use of Lagrangian dispersion and radiative transfer modelling with satellite and surface remote sensing measurements for the investigation of volcanic plumes: the Mount Etna eruption of 25–27 October 2013

Abstract. In this paper we combine SO2 and ash plume dispersion modelling with satellite and surface remote sensing observations to study the regional influence of a relatively weak volcanic eruption from Mount Etna on the optical and micro-physical properties of Mediterranean aerosols. We analyse the Mount Etna eruption episode of 25–27 October 2013. The evolution of the plume along the trajectory is investigated by means of the FLEXible PARTicle Lagrangian dispersion (FLEXPART) model. The satellite data set includes true colour images, retrieved values of volcanic SO2 and ash, estimates of SO2 and ash emission rates derived from MODIS (MODerate resolution Imaging Spectroradiometer) observations and estimates of cloud top pressure from SEVIRI (Spinning Enhanced Visible and InfraRed Imager). Surface remote sensing measurements of aerosol and SO2 made at the ENEA Station for Climate Observations (35.52° N, 12.63° E; 50 m a.s.l.) on the island of Lampedusa are used in the analysis. The combination of these different data sets suggests that SO2 and ash, despite the initial injection at about 7.0 km altitude, reached altitudes around 10–12 km and influenced the column average aerosol particle size distribution at a distance of more than 350 km downwind. This study indicates that even a relatively weak volcanic eruption may produce an observable effect on the aerosol properties at the regional scale. The impact of secondary sulfate particles on the aerosol size distribution at Lampedusa is discussed and estimates of the clear-sky direct aerosol radiative forcing are derived. Daily shortwave radiative forcing efficiencies, i.e. radiative forcing per unit AOD (aerosol optical depth), are calculated with the LibRadtran model. They are estimated between −39 and −48 W m−2 AOD−1 at the top of the atmosphere and between −66 and −49 W m−2 AOD−1 at the surface, with the variability in the estimates mainly depending on the aerosol single scattering albedo. These results suggest that sulfate particles played a large role in the transported plume composition and radiative forcing, while the contribution by ash particles was small in the volcanic plume arriving at Lampedusa during this event.

Phenology and vegetation change measurements from true colour digital photography in high Arctic tundra

Manual collection of accurate phenology data is time-consuming and expensive. In this study, we investigate whether repeat colour digital photography can be used (1) to identify phenological patterns, (2) to identify differences in vegetation due to experimental warming and site moisture conditions, and (3) as a proxy for biomass. Pixel values (RGB) were extracted from images taken of permanent plots in long-term warming experiments in three tundra communities at a high Arctic site during one growing season. The Greenness Excess Index (GEI) was calculated from image data at the plot scale (1 × 1 m) as well as for two species, Dryas integrifolia and Salix arctica. GEI values were then compared to corresponding field-based phenology observations. GEI and Normalized Difference Vegetation Index (NDVI) values from a paired set of true colour and infrared images were compared with biomass data. The GEI values followed seasonal phenology at the plot and species scale and correlated well with standardized observations. GEI correlated well with biomass and was able to detect quantitative differences between warmed and control plots and the differences between communities due to site-specific moisture conditions. We conclude that true colour images can be used effectively to monitor phenology and biomass in high Arctic tundra. The simplicity and affordability of the photographic method represents an opportunity to expand observations in tundra ecosystems.

연근해 양식장 주변 적조 모니터링을 위한 무인항공영상 적용 연구

매년 여름 우리나라 양식업에 피해를 입히는 적조를 탐지하기 위한 연구는 대부분 인공위성을 이용하였으나 양식장에 대한 정보는 인공위성으로 산출하기에는 한계를 가진다. 따라서 본 연구에서는 무인항공기를 이용한 연안촬영과 그 산출물을 이용하여 적조를 탐지하는 기법을 제시하였다. 그 결과 높은 해상도를 가진 무인항공영상을 획득 할 수 있었으며 색상을 이용한 무감독 분류와 가시광영역의 세 가지 분광밴드를 이용한 단순 알고리즘을 이용하여 적조를 탐지하였다. 기존의 천연색 영상에 비하여 시각적으로 명확한 해수색의 구분이 가능하였으며 적조의 해수면 분포를 확인할 수 있었다. 이와 같은 방법은 양식장이 설치되어 있는 연안에서 더욱 정확한 적조의 분포 상황을 모니터링 할 수 있을 것으로 판단된다. Red tide, causes aquaculture industry the damages in Korea every summer, was usually detected by using satellite, aquaculture information was difficult to detect by using satellite. Therefore, we suggests the method for detecting the red tide using the coastal observation and the product from the unmanned aerial Vehicle. As a result, we obtained the high resolution unmanned aerial Vehicle images, detected the red tide by using the unsupervised classification from the true color images and the simple algorithm from the RGB color images. Compared the previous color images, unmanned aerial Vehicle images were clearly classified the ocean color, we were able to identify the red tide distribution in sea surface. These methods were determined to accurately monitor the red tide distribution on the aquaculture fields in the coastal waters where is established the aquaculture.

Chromophores from photolyzed ammonia reacting with acetylene: Application to Jupiter's Great Red Spot

The high altitude of Jupiter's Great Red Spot (GRS) may enhance the upward flux of gaseous ammonia (NH3) into the high troposphere, where NH3 molecules can be photodissociated and initiate a chain of chemical reactions with downwelling acetylene molecules (C2H2). These reactions, experimentally studied earlier by (Ferris and Ishikawa [1987] Nature 326, 777-778) and (Ferris and Ishikawa [1988] J. Amer. Chem. Soc. 110, 4306–4312), produce chromophores that absorb in the visible and ultraviolet regions. In this work we photolyzed mixtures of NH3 and C2H2 using ultraviolet radiation with a wavelength of 214nm and measured the spectral transmission of the deposited films in the visible region (400–740nm). From these transmission data we estimated the imaginary indices of refraction. Assuming that ammonia grains at the top of the GRS clouds are coated with this material, we performed layered sphere and radiative transfer calculations to predict GRS reflection spectra. Comparison of those results with observed and previously unreported Cassini visible spectra and with true-color images of the GRS show that the unknown GRS chromophore is spectrally consistent with the coupled NH3–C2H2 photochemical products produced in our laboratory experiments. Using high-resolution mass spectrometry and infrared spectroscopy we infer that the chromophore-containing residue is composed of aliphatic azine, azo, and diazo compounds.

CWS Compression: Cascading of Wavelet difference Reduction and Singular Value Decomposition

People are sharing, transmitting and storing millions of images every day. To store images it may require huge data storage. The compression of images reduces the storage required to store images, also permits the faster transmission. Several works have been carried out in designing compression techniques that reduce image size with higher image quality. True color images take largest part in web pages, hence it is important to make control over image size and their quality to deliver fastest loading. This paper presents a new image compression technique CWS by cascading wavelet difference reduction (WDR) and singular value decomposition(SVD). In the proposed method, an input image is first compressed using WDR and then compressed using SVD. These two techniques are cascaded to boost the performance of WDR. The results are showing that the proposed compression is superior over the aforementioned compression techniques.

Remote-sensing reflectance and true colour produced by a coupled hydrodynamic, optical, sediment, biogeochemical model of the Great Barrier Reef, Australia: Comparison with satellite data

Aquatic biogeochemical models are vital tools in understanding and predicting human impacts on water clarity. In this paper, we develop a spectrally-resolved optical model that produces remote-sensing reflectance as a function of depth-resolved biogeochemical model properties such as phytoplankton biomass, suspended sediment concentrations and benthic reflectance. We compare simulated remote-sensing reflectance from a 4 km resolution coupled hydrodynamic, optical, sediment and biogeochemical model configured for the Great Barrier Reef with observed remote-sensing reflectance from the MODIS sensor at the 8 ocean colour bands. The optical model is sufficiently accurate to capture the remote-sensing reflectance that would arise from a specific biogeochemical state. Thus the mismatch between simulated and observed remote-sensing reflectance provides an excellent metric for model assessment of the coupled biogeochemical model. Finally, we combine simulated remote-sensing reflectance in a red/green/blue colour model to produce simulated true colour images during the passage of Tropical Cyclone Yasi in February 2011.

Tricolor acquisition and true color images fusion method under low illumination condition

Tricolor acquisition and true color images fusion method under low illumination condition

Incoherent ptychography in Fresnel domain with simultaneous multi-wavelength illumination

Single wavelength illumination is used in the traditional ptychography. Even though using multi-wavelength to improve image quality, it takes the scheme of illuminating in turn due to the requirement of coherence. So far, the addition of incoherent modes has been regarded as a nuisance in diffractive imaging. Here we propose a scheme of incoherent ptychography and an algorithm of information multiplexing that uses the multi-wavelength illumination simultaneously, which are demonstrated in experiment and simulation. Compared with the scheme of traditional ptychography, it can recover not only the object well, but also the spectral response of the object, probes of complex value and spectral weight of each wavelength respectively. This method obtains much information about the object and owns the multichannel and multispectral merits. Meanwhile, by means of color image coding, this method can retrieve true color images and enhance the image quality. The proposed algorithm has strong robustness. Besides, we also investigate how many modes can be recovered by this method. The work may open up possibilities for information multiplexing in ptychography and multispectral microscopy imaging over various applications.

Spatial distribution of jovian clouds, hazes and colors from Cassini ISS multi-spectral images

The Cassini spacecraft made a gravity assist flyby of Jupiter in December 2000. The Imaging Science Subsystem (ISS) acquired images of the planet that covered the visual range with filters sensitive to the distribution of clouds and hazes, their altitudes and color. We use a selection of these images to build high-resolution cylindrical maps of the planet in 9 wavelengths. We explore the spatial distribution of the planet reflectivity examining the distribution of color and altitudes of hazes as well as their relation. A variety of analyses is presented: (a) Principal Component Analysis (PCA); (b) color-altitude indices; and (c) chromaticity diagrams (for a quantitative characterization of Jupiter “true” colors as they would be perceived by a human observer). PCA of the full dataset indicates that six components are required to explain the data. These components are likely related to the distribution of cloud opacity at the main cloud, the distribution of two types of hazes, two chromophores or coloring processes and the distribution of convective storms. While the distribution of a single chromophore can explain most of the color variations in the atmosphere, a second coloring agent is required to explain the brownish cyclones in the North Equatorial Belt (NEB). This second colorant could be caused by a different chromophore or by the same chromophore located in structures deeper in the atmosphere. Color indices separate different dynamical regions where cloud color and altitude are correlated from those where they are not. The Great Red Spot (GRS) appears as a well separated region in terms of its position in a global color-altitude scatter diagram and different families of vortices are examined, including the red cyclones which are located deeper in the atmosphere. Finally, a chromaticity diagram of Jupiter nearly true color images quantifies the color variations in Jupiter’s clouds from the perspective of a visual observer and helps to quantify how different are the observed shades of yellow and red. The color analysis also gives additional evidence in favor of a second distinct color in the red brown cyclones of the NEB.

New quantum inspired meta-heuristic techniques for multi-level colour image thresholding

The efficient meta-heuristic techniques, called ant colony optimization, differential evolution and particle swarm optimization, inspired by the fundamental features of quantum systems, are presented in this paper. The proposed techniques are Quantum Inspired Ant Colony Optimization, Quantum Inspired Differential Evolution and Quantum Inspired Particle Swarm Optimization for Multi-level Colour Image Thresholding. These techniques find optimal threshold values at different levels of thresholding for colour images. A minimum cross entropy based thresholding method, called Li's method is employed as an objective (fitness) function for this purpose. The efficiency of the proposed techniques is exhibited computationally and visually on ten real life true colour images. Experiments with the composite DE (CoDE) method, the backtracking search optimization algorithm (BSA), the classical ant colony optimization (ACO), the classical differential evolution (DE) and the classical particle swarm optimization (PSO), have also been conducted subsequently along with the proposed techniques. Experimental results are described in terms of the best threshold value, fitness measure and the computational time (in seconds) for each technique at various levels. Thereafter, the accuracy and stability of the proposed techniques are established by computing the mean and standard deviation of fitness values for each technique. Moreover, the quality of thresholding for each technique is determined by computing the peak signal-to-noise ratio (PSNR) values at different levels. Afterwards, the statistical superiority of the proposed techniques is proved by incorporating Friedman test (statistical test) among different techniques. Finally, convergence curves for different techniques are presented for all test images to show the visual representation of results, which proves that the proposed Quantum Inspired Ant Colony Optimization technique outperforms all the other techniques.

Water Quality of Four Major Lakes in Mississippi, USA: Impacts on Human and Aquatic Ecosystem Health

Harmful algal blooms (HABs), harmful microorganisms (pathogens) and toxic metals represent three major agents of water quality deterioration. Water quality of three northern lakes (Sardis, Enid, and Grenada) and a central lake (Ross Barnett Reservoir) of Mississippi, USA were examined in this study. While all these lakes are heavily used for recreational purposes, the Ross Barnett Reservoir serves additionally as the primary water supply for the City of Jackson, the capital city of Mississippi. The main goal of this study was to comprehensively assess the water quality of these lakes employing field and satellite data, and evaluate the potential human and aquatic health impacts. A time-series of true color images derived from satellite data indicated that algal blooms have been a recurring phenomenon in these lakes. Cyanobacteria, the algal group that predominantly occur in freshwater and form toxic blooms, were always present in these lakes and were most abundant on many occasions. The most toxic cyanotoxin, microcystin-LR, was found in all lakes, and its concentrations exceeded federal drinking water guidelines for children under six years of age many times. Potential bioaccumulation and biomagnification of microcystin-LR may pose serious risk to the aquatic ecosystem and human health including adults. Nutrient measurements indicated that all four lakes were eutrophic. Among bacterial populations, total coliforms and enterococci exceeded guideline values on several occasions. Arsenic, cadmium, chromium, and lead were found in the water of all the lakes, with arsenic exceeding the guideline values at two sites in Ross Barnett Reservoir. While it is apparent from this study that these lakes face many water quality issues, data across all seasons will be required to document potential trends and to devise management strategies. Use of remote sensing technology is recommended to monitor some of the water quality parameters such as suspended particulate matter and algal blooms, especially cyanobacterial blooms.

Encryption function on artificial neural network

Six algorithms that design secrecy keys are used for digital image encryption. The privacy keys generated by stream cipher generators were tested for their randomness applying five tests of randomness. The images generated by applying each algorithm were tested for their regularity and residual intelligibility. The histograms for images ciphered by stream cipher schemes all have approximately flat histogram less information as compared to one-dimensional ciphering algorithms and threshold generator-based image ciphering scheme. Furthermore, the stream cipher schemes were effectively applied to the colored images of 256-color levels of true-color images (24 bit). In this paper, we try to decrypt automatically using artificial neural network by decryption through multilayer perceptron and radial basis function; networks were tested using the interface by calculating the error rates of decrypted images.

True-color real-time imaging and spectroscopy of carbon nanotubes on substrates using enhanced Rayleigh scattering

Single-walled carbon nanotubes (SWCNTs) illuminated by white light should appear colored due to resonance Rayleigh scattering. However, true-color imaging of SWCNTs on substrates has not been reported, because of the extremely low scattering intensity of SWCNTs and the strong substrate scattering. Here we show that Rayleigh scattering can be greatly enhanced by the interface dipole enhancement effect. Consequently colorful SWCNTs on substrates can be directly imaged under an optical microscope by wide field supercontinuum laser illumination, which facilitates high throughput chirality assignment of individual SWCNTs. This approach, termed “Rayleigh imaging microscopy”, is not restricted to SWCNTs, but widely applicable to a variety of nanomaterials, which enables the colorful nanoworld to be explored under optical microscopes.