Sergey Abramov

National Aerospace University “Kharkiv Aviation Institute” · Information-Communication Technologies

Characterization of remote sensing (RS) sensors noise is important for optimization and analysis of potential accuracy of subsequent image processing stages (such as filtering or compression, image registration accuracy or objects classification). Blind noise parameters estimation (BNPE) allows analyzing sensor noise directly from noisy images. BNP...

Green computing is a popular trend nowadays. In this paper, we show a way to incorporate this tendency in lossy image compression by an efficient coder based on discrete cosine transform. We study the case when it is desired to provide distortions characterized by mean square error not worse than a given threshold. In opposite to two-step and itera...

Since the number of acquired images and their size have the tendency to increase, their lossy compression is widely applied for their storage, transfer, and dissemination. Simultaneously with providing a relatively large compression ratio, lossy compression produces distortions that are inevitably introduced and have to be controlled. The propertie...

SALIENCY MAP IN IMAGE VISUAL QUALITY ASSESSMENT AND PROCESSING Images are mainly viewed and analyzed by humans. Because of this, in the characterization of image quality and effectiveness of image processing, it is necessary to take into account the peculiarities of the human vision system and cognition that are very complex. Saliency maps as well...

The possibility of overcoming some hardware limitations resulting in low quality of terahertz images is considered. The set of images obtained at different distances from the source of terahertz radiation at frequency 0.1 THz is studied. It is shown that the noise in these images is of mixed type and has quite high level of spatial correlation. A f...

Image lossy compression is currently widely employed in different fields. Compared to lossless compression, it allows providing a considerably larger compression ratio but distortions are introduced inevitably. Properties of these distortions depend on a used coder, an image subject to compression, and compression parameters. Distortions affect vis...

In this paper, we consider a problem of lossy compression of three-channel or color images with application to remote sensing. The main task of such a compression is to provide a trade-off between compression ratio and quality of compressed data that should be appropriate for solving the basic tasks as classification of sensed terrains, object dete...

Multichannel (multispectral, hyperspectral) remote sensing data may include junk component images which have quality considerably worse than other components. This can be due to intensive noise or low dynamic range of information component in such junk channels (sub-bands). Such component images are sometimes ignored (not used in further processing...

The goal of our studies in 2018–2020 has been design of approaches and methods for automated processing of remote sensing (RS) and other types of data acquired by different existing imaging systems most of which are multichannel.

This paper deals with processing of multichannel remote sensing images for which it is difficult and often impossible to carry out any stage of data processing in an interactive manner and, thus, full or, at least, partial automation is needed. Despite of existence of many methods, it is difficult to choose the best or an appropriate one and/or to...

Many similarity measures (SMs) were proposed to measure the similarity between multimodal remote sensing (RS) images. Each SM is efficient to a different degree in different registration cases (we consider visible-to-infrared, visible-to-radar, visible-to-digital elevation model (DEM), and radar-to-DEM ones), but no SM was shown to outperform all o...

To enhance images, often one has to apply filtering (denoising). However, there are several open issues within denoising. One of them is that sometimes denoising can be not efficient. Another issue regards a selection of an appropriate filter and setting its parameters. As a particular case, we consider 2D DCT-based filter with 8x8 pixel fully over...

Проанализированы эффективность и целесообразность применения фильтрации на основе дискретного косинусного преобразования (ДКП) одномерных сигналов, искаженных белым гауссовым шумом с заранее известной или априорно оцененной дисперсией. Показано, что эффективность изменяется в широких пределах в зависимости от отношения сигнал-шум на входе и степени...

Multispectral remote sensing data may contain component images that are heavily corrupted by noise and the pre-filtering (denoising) procedure is often applied to enhance these component images. To do this, one can use reference images—component images having relatively high quality and that are similar to the image subject to pre-filtering. Here,...

Multispectral remote sensing data may contain component images which are heavily corrupted by noise and pre-filtering (denoising) procedure is often applied to enhance these component images. To do this, one can use reference images – component images having relatively high quality and which are similar to the image subject to pre-filtering. Here w...

Signals acquired by different sensors are often noisy and are subject to filtering aimed to reduce noise and preserve important information. Although a great number of different filters exist, their performance does not always satisfy users. There are practical situations when denoising does not lead to expected positive effect which makes it usele...

A task of template-based detection of similar objects or blocks in images is considered. As a measure of similarity, different similarity metrics (distances) are studied under assumption that noise is present in images or video frames. It is shown that there are metrics that are able to perform sufficiently better than standard Euclidean norm in bo...

Methods for automatic lossy compression of hyperspectral images are considered. Their advantages and drawbacks are discussed. Simulation and real-life results are presented.

Compression is a typical stage in processing of remote sensing images. Here we consider lossy compression of images that contain noise. Then, there are, at least, two approaches – to compress images without pre-filtering and with prefiltering. The second approach is shown to have some advantages but only under certain conditions. Several metrics ch...

Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. In this study, we address the semiblind restoration of the degraded images component-wise, according to a sequential scheme. We propose a new component-wise semi-blind method for estimating effectively and acc...

Рассмотрен метод автоматического оценивания дисперсии помех, основанный на анализе характеристик распределений коэффициентов дискретного косинусного преобразования. Исследована возможность повышения быстродействия данного метода за счет уменьшения числа обрабатываемых блоков изображения. На основании данных численного моделирования, проведенных для...

Remote sensing images are usually subject to compression for their further transmission, storage and dissemination. Because of lossy nature of compression, resulting images appear distorted. Degradations of image quality due to compression depend on noisy input image, a type and intensity of noise, and used image coder. To control image degradation...

It has been demonstrated recently that efficiency of filtering a noisy component image of a multichannel image can be sufficiently improved under condition that the multichannel image has almost noise-free component image(s) that possess high correlated with the noisy component image used as reference. High correlation and practical absence of the...

The paper deals with design and testing a method for determining maximal distance of visual observation detection of unmanned aerial vehicles using their three-dimensional (3D) models. The designed method is briefly described and examples of its use for several UAV models are presented. The method testing by means of visual experiment is carried ou...

A problem of predicting compression ratio (CR) for lossy image compression methods based on discrete cosine transform (DCT) is considered for remote sensing imaging as a main target application. We demonstrate that the noise presence in images leads to specific requirements to lossy image compression as well as to criteria used, and ways to meet th...

Amount and size of remote sensing (RS) images acquired by modern systems are so large that data have to be compressed in order to transfer, save and disseminate them. Lossy compression becomes more popular for aforementioned situations. But lossy compression has to be applied carefully with providing acceptable level of introduced distortions not t...

Data provided by synthetic aperture radar (SAR) of Sentinel satellite can be useful for many applications. However, as for any SAR image, speckle noise is present in acquired images. Speckle properties are important for different operations of SAR image processing as filtering, edge detection, segmentation, classification. Thus, we first carry out...

A modification of blind method for additive noise variance evaluation based on analysis of characteristics of discrete cosine transform coefficients is described. It takes into account inherent inter-channel correlation of multichannel images. Numerical simulation results obtained for a large test image database demonstrate essential increase of es...

This paper analyzes possibilities and recently proposed methodology of performance prediction for denoising and lossy compression of radar images under assumption that they are corrupted by pure multiplicative noise. Methods based on discrete cosine transform in blocks are considered. Characteristics of the noise (speckle) are assumed a priori know...

For many applied problems in agricultural monitoring and food security, it is important to provide reliable crop classification maps. In this paper, we aim to compare performance of different filters available in ESA SNAP toolbox and compare them with our approach with applying to reduce speckle in multitemporal synthetic-aperture radar (SAR) Senti...

Images of different origin contain textures, and textural features in such regions are frequently employed in pattern recognition, image classification, information extraction, etc. Noise often present in analyzed images might prevent a proper solution of basic tasks in the aforementioned applications and is worth suppressing. This is not an easy t...

Some aspects of image lossy compression based on orthogonal transforms including standards JPEG and JPEG200 are considered. The main advantages and drawbacks of these techniques are specified. It is demonstrated that, in fact, most of them have been partly or even fully eliminated. The references to papers are given where approaches for eliminating...

This paper considers specific aspects of lossy compression of noisy remote sensing images. A method based on discrete cosine transform (DCT) in 32x32 pixels blocks is analyzed. Characteristics of noise assumed additive (in original data or after proper variance stabilizing transform), spatially uncorrelated and Gaussian are assumed a priori known....

In this paper, we study a problem of filtering noisy component image of a multichannel image, under assumption that the multichannel data contain almost noise-free component image(s) highly correlated with the noisy one. Our proposed denoising approach is based on three-dimensional (3D) representation of the noisy and reference images. One dimensio...

In this chapter, we consider lossy compression of multichannel images acquired by remote sensing systems. Two main features of such data are taken into account. First, images contain inherent noise that can be of different intensity and type. Second, there can be essential correlation between component images. These features can be exploited in 3D...

assuming that a reference (noise-free) image is available. We propose a denoising approach based on three-dimensional (3D) discrete cosine transform (DCT) applied in blocks. We show that a use of a reference image allows improving the denoising performance (measured by different quality metrics) although it depends on several factors such as a choi...

We propose and study an approach to compression ratio prediction and providing with application to multichannel remote sensing images. DCT-based compression techniques, both 2D applied component-wise and 3D applied to sub-band groups, are considered. It is shown that compression ratio can be predicted for component-wise processing of multichannel i...

Textures are typical elements of natural scene images widely used in pattern recognition and image classification. Noise, often being present in acquired images, deteriorates texture features (characteristics), and it is desirable both to suppress it and to preserve a texture. This task is quite difficult even for the most advanced filters, and the...

It is often needed to compress images with providing certain properties or quality. Wavelet based coders SPIHT and JPEG2000 easily produce a desired compression ratio but not quality especially if one deals with compressing images corrupted by noise for which specific behavior of quality metrics on compression ratio (CR) or bpp might be ob-served....

A novel compression ratio prediction and providing technique applicable to noisy and almost noise�free remote sensing images is proposed. It allows predicting and then providing a desired compression ratio for DCT�based coder in automatical manner. The proposed technique is algorithmically simple and has low computational complexity that allows usi...

The paper deals with considering a problem typical for lossy compression of remote sensing images. While compressing an image under interest by DCT-based coders which are rather efficient it is desirable to predict what CR will be attained for a given quantization step. We show that such prediction is possible and it can be done easily, quickly, an...

In processing of multichannel remote sensing data, there is a need in automation of basic operations as filtering and compression. Automation presumes undertaking a decision on expedience of image filtering. Automation also deals with obtaining of information based on which certain decisions can be undertaken or parameters of processing algorithms...

Several approaches to prediction of denoising efficiency for the DCT-based filters with application to single and multichannel images corrupted by different types of noise have been proposed recently. For all of them, it has been assumed that the noise characteristics are a priori and accurately known. In this paper, we analyze the influence of err...

Для методов сжатия изображений на основе вейвлетных преобразований (SPIHT, JPEG2000) разработана неитеративная процедура сжатия изображений, на которых присутствуют некоррелированные помехи, в окрестности оптимальной рабочей точки. Для достижения такого сжатия предполагается, что дисперсия или другие характеристики помех априорно известны или автом...

We propose and study an approach to compression ratio prediction and providing with application to multichannel remote sensing images. DCT-based compression techniques, both 2D applied component-wise and 3D applied to sub-band groups, are considered. It is shown that compression ratio can be predicted for component-wise processing of multichannel i...

Several approaches to prediction image denoising efficiency for DCT�based filter have been proposed recently. They allow predicting improvement of PSNR (IPSNR) and visual quality metrics as PSNR�HVS�M (IPHVS) for denoised images under condition of noise characteristics known or pre�estimated in advance. Here we apply the prediction approach to pre�...

In practice, acquired color images are inevitably noisy, and filtering/denoising procedure is used to suppress the noise. Although numerous denoising techniques have been proposed, they are not universally efficient in all considered practical situations. There are also contradictory requirements to color image denoising and their priority can be d...

Performance of denoising based on discrete cosine transform applied to multichannel remote sensing images corrupted by additive white Gaussian noise is analyzed. Images obtained by satellite Earth Observing-1 (EO-1) mission using hyperspectral imager instrument (Hyperion) that have high input SNR are taken as test images. Denoising performance is c...

We address lossy compression of noisy remote sensing images, where the noise is supposed to be spatially uncorrelated (white), additive originally or after a proper variancestabilizing transformation (VST). In such situations, the so-called optimal operation point (OOP) might exist. The OOP is associated with the parameter that controls compression...

Statistical characteristics of coefficients of discrete cosine transform (DCT) in 8x8 pixel blocks of grayscale images are analyzed. Robust estimators of distribution scale and tail heaviness are used in analysis since it is shown that the considered distributions are essentially non-Gaussian and they are better described by generalized Gaussian di...

The paper addresses practical aspects of multichannel images compression. Color and multichannel images are commonly characterized by high degree of component correlation. This property can be exploited in 3D-compression techniques for achieving high compression ratio. The main goal of this paper is to show that 3D-compression on basis of discrete...

we consider practical aspects of lossy compression with application to multispectral images provided by Landsat sensor. It is demonstrated that 3D compression using 6techniques based on DCT can provide some benefits but under conditions of proper grouping of sub-band images

A task of blind estimation of multiplicative noise (speckle) variance in multi-look images acquired by radars with synthesized aperture array is considered. It is shown that there are several factors affecting accuracy of such estimation. The main of them are spatial correlation of the speckle, complexity of an analyzed image and peculiarities of a...

Abstract. A task of lossy compression of multichannel images corrupted by additive noise is considered. Three-dimensional (3D) compression based on discrete cosine transform (DCT) is paid main attention. It is shown that optimal operation point (OOP) often exists where OOP relates to such compression parameters when a compressed image is maximally...

A task of lossy compression of multichannel images corrupted by additive noise is considered. Three-dimensional (3D) compression based on discrete cosine transform (DCT) is paid main attention. It is shown that optimal operation point (OOP) often exists where OOP relates to such compression parameters when a compressed image is maximally close to c...