Adaptive wavelet codec for noisy image compression

Bekhtin, Yury S.

doi:10.1109/ewdts.2011.6116587

Cited by 12 publications

(3 citation statements)

References 9 publications

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“…In particular, there are standard means for this purpose as, e.g., the Matlab version of robustfit method (DuMouchel&O'Brien, 1989). For methods analyzed below, we have used the approach based on (6).…”

mentioning

confidence: 99%

Methods for Blind Estimation of Speckle Variance in SAR Images: Simulation Results and Verification for Real-Life Data

Abramov

Abramova

Ponomarenko

et al. 2014

Computational and Numerical Simulations

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mentioning

confidence: 99%

Methods for Blind Estimation of Speckle Variance in SAR Images: Simulation Results and Verification for Real-Life Data

Abramov

Abramova

Ponomarenko

et al. 2014

Computational and Numerical Simulations

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“…Wavelet different reduction (WDR) and Adaptive Scanned Wavelet Different Reduction (ASWDR), on the other hand, are the advanced versions acknowledged in the committee. These are among the most outstanding compression algorithms which provide the smallest error per compression rate but transmitted the best perceptual quality image (Hashemi-Berenjabad, Mahloojifar & Akhavan, 2011;Bekhtin. 2011: Lashari, Ibrahim & Senan.…”

Section: Thresholding Algorithm For Image Compressionmentioning

confidence: 99%

Thresholding And Quantization Algorithms for Image Compression Techniques: A Review

Lashari¹,

Ibrahim²,

Taujuddin³

et al. 2018

APJITM

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With increasing demand on digital images, there is a need to compress the image to entertain the limited bandwidth and storage capacity. Recently, there is a growing interest among researchers focusing on compression of various types of images and data. Amongst various compression algorithms, transform-based compression is one of the promising algorithms. Despite the technological advances in transmission and storage, the demands placed on the bandwidth of communication and storage capacities by far outstrips its availability. This paper presents a review of image compression principle, compression techniques and various thresholding algorithms (pre-processing algorithms) and quantization algorithm (post-processing algorithms). This paper intends to give an overview to the relevant parties to choose the suitable image compression algorithms to suit with the need.

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“…Однако независимо от типа системы ДЗ, общей особенностью изображений, формируемых этими системами, является присутствие на них помех и искажений, которые ухудшают как визуальное качество полученных снимков, так и резуль- А. С. Григорьева, В. В. Абрамова, В. В. Лукин, Н. В. Кожемякина, К. Д. Абрамов таты их обработки. Характеристики искажающих помех следует учитывать на разных этапах обработки: при сжатии данных ДЗ [4,5], при извлечении полезной информации (классификация, поиск границ, объектов и т.п.) [6,7].…”

Section: Introductionunclassified

Специфика Оценивания Характеристик Сложных Помех С Учетом Межканальной Корреляции На Гиперспектральных Изображениях

Григорьева¹,

Абрамова²,

Абрамов³

et al. 2018

aktt

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The article deals with the scatter-plot method of automatic evaluation of mixed noise characteristics in multi-channel images. The aim is to solve the problematic issues associated with the adaptation of this method to hyperspectral images processing. The tasks to be solved are: to investigate the influence of the formation method of the jointly processed multichannel groups of images on the accuracy and stability of the aforementioned method; to formulate the recommendations on the choice of jointly processed images and the method of combination. The applied methods are the following: robust estimation of signal parameters, spectral, correlation and regression analysis. The following results were obtained. Three possible ways of groups forming of three channel images were considered: 1) joint processing of images belonging to adjacent channels; 2) joint processing of images with the highest cross-correlation coefficients; 3) joint processing of images with the lowest cross-correlation coefficients. It was defined that if the cross-correlation coefficients of images in the group are low, and the images have of complex structure, it is possible a significant reduction of the method accuracy, up to a complete loss of its working capacity. The method demonstrates sufficiently high accuracy and stability when the groups are formed of the neighbor channel images or of the images with the highest cross-correlation coefficients, and the values of the estimated noise parameters for these issues have no significant differences. Conclusions. The group formation method significantly affects not only the accuracy, but also the operability of the considered estimation method, and in order to increase the reliability of the method, it is appropriate to form groups of images with rather high levels of inter-channel correlation. However, since the accuracy of the method when groups are formed of the neighbor images and of images with the highest levels of cross-correlation have no significant differences, in order to maintain the high performance of the method, it is recommended to form groups of jointly processed images applying the images obtained in the neighbor spectral zones

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Adaptive wavelet codec for noisy image compression

Cited by 12 publications

References 9 publications

Methods for Blind Estimation of Speckle Variance in SAR Images: Simulation Results and Verification for Real-Life Data

Methods for Blind Estimation of Speckle Variance in SAR Images: Simulation Results and Verification for Real-Life Data

Thresholding And Quantization Algorithms for Image Compression Techniques: A Review

Специфика Оценивания Характеристик Сложных Помех С Учетом Межканальной Корреляции На Гиперспектральных Изображениях

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