Showing posts with label image lossy compression. Show all posts
Showing posts with label image lossy compression. Show all posts

Friday, 25 August 2023

A Fast and Accurate Prediction of BPG Compression Parameters in Optimal Operation Point Neighbourhood for Three-channel Noisy Images | Chapter 7 | Fundamental Research and Application of Physical Science Vol. 8

This stage considers the lossy compression of three-channel images debased by additive silvery Gaussian noise. The better portable drawings (BPG) encoder that has three different movement modes is studied. As for additional encoders, a noise draining effect is observed and it influences the encoder performance. For certain environments (image complicatedness and noise intensity), the supposed optimal movement point (OOP) may exist. The main feature of OOP is that the quality of a compacted image (calculated concerning the true countenance) is better than the quality of the corresponding strident image in accordance with a given metric (either common such as mean square mistake or some visual value metric). Knowledge having to do with the OOP existence and compression limits in it for a given strident image can be valuable. In the case of OOP existence, it wash to compress a given representation in OOP or its community. If OOP does not exist, a more “careful” lossy compression is expedient. The question is that in practice the valid image is not available, and, so, it is impossible to reckon full-reference versification for compressed and roar-free images. Meanwhile, we show in this paper that it is likely to predict condensation parameters for a given cacophonous image earlier. Moreover, this prediction is fast and accurate enough for a conclusion undertaking on which coder parameter to set to reach OOP. In addition, in this place paper, we demonstrate that it is likely to predict the compression limits not only in OOP but also in allure neighborhood. This allows for endeavor more reliable conclusions. Prediction opportunities are shown for two optic quality versification and three typical modes of the BPG coder movement: 4:4:4, 4:2:2, and 4:2:0. One novel way of prognosis accuracy improvement established the joint use of two input limits is shown.

Author(s) Details:

Vladimir Lukin,
National Aerospace University, Kharkov, Ukraine.

Bogdan Kovalenko,
National Aerospace University, Kharkov, Ukraine.

Benoit Vozel,
University of Rennes, Lannion, France.

Please see the link here: https://stm.bookpi.org/FRAPS-V8/article/view/11676

Monday, 28 November 2022

Prediction of Optimal Operation Point Existence and Its Parameters in BPG-Based Automatic Lossy Compression of Noisy Images| Chapter 1 | Current Overview on Science and Technology Research Vol. 9

 This branch focuses on lossy compression of noisy concepts. In opposite to lossy compression of clamor-free images, there are few peculiarities relating to cacophony filtering effect and analysis of condensation technique act. As a result of specific noise cleaning, the so-called optimal movement point (OOP) may survive. OOP is related to such limits of a coder that quality of a compressed figure is closer to the matching noise-free (true) concept compared to quality of uncompressed (original, boisterous) image where feature is characterized by the metric, conventional or optical one. If OOP for a given cacophonous image lives, it is expedient to automatically compress an countenance under interest in OOP or, at least, its surroundings. However, since the valid image is not at disposal in essence, it occurs impossible to decide does OOP exist or not. In this affiliate, we demonstrate that it is, usually, possible to predict OOP life (according to different versification) before image condensation. It is also possible to fairly set the coder parameters for the better compact graphics (BPG) coder, which command a price of the main attention. The first part concerns a basic case of additive silver Gaussian noise in one-component (grayscale) countenances. We demonstrate that increase (decline) of the conventional metric PSNR and able to be seen with eyes quality metric PSNR-HVS-M maybe predicted. If increase is anticipated, the decision on OOP existence is tackled and vice versa. For the case of OOP absence, a habit for setting the parameter Q that controls condensation in BPG is proposed. Thus, it enhances possible to carry out lossy condensation automatically. The extensions of the projected approach to joint compression of three-component concepts are proposed. OOP existence in this place case is even more probable. Image sub-examining in color components is studied. The chance of OOP existence for ocular quality metrics PSNR-HA and MDSI is illustrated.

Author(s) Details:

Vladimir Lukin,
National Aerospace University, Kharkov, Ukraine.

Bogdan Kovalenko,
National Aerospace University, Kharkov, Ukraine.

Sergii Kryvenko,
National Aerospace University, Kharkov, Ukraine.

Victoriya Naumenko,
National Aerospace University, Kharkov, Ukraine.

Benoit Vozel,
University of Rennes 1, Lannion, France.

Please see the link here:
https://stm.bookpi.org/COSTR-V9/article/view/8755

Friday, 1 July 2022

Compression of Noisy Images Taking into Account Visual Quality: A Comprehensive Study | Chapter 6 | Research Developments in Science and Technology Vol. 8

This chapter discusses the lossy compression of pictures that include additive noise damage. The examination is done from the standpoint of compressed picture visual quality, which is the chapter's major contribution. The compression ratio for a number of coders is investigated and is controlled in various ways. Lossless coding typically doesn't yield compression ratios high enough for many real-world uses. The visual quality metrics WSNR, MS-SSIM, PSNR-HVS-M, and PSNR-HVS are employed since they are the best suitable for the application under consideration. The goal is to determine the optimal operating point (OOP) based on measurements for visual quality. It is shown that, under some circumstances, picture filtering caused by lossy compression, or the possibility of OOP, may cause compressed images to have slightly higher visual quality than the original noisy images. The "optimal" coder settings that allow for the observation of this beneficial impact depend on the noise standard deviation. In OOP, we suggest a technique for determining coder parameters. This makes it possible to create automatic methods for compressing noisy pictures close to the ideal operating point, or if visual quality increases or decreases inadvertently. Another benefit is that this case's compression ratio is fairly high. The outcomes of a collection of test photos in grayscale with different noise variations are displayed.


Author(s) Details:

Vladimir Lukin,
National Aerospace University, Kharkov, Ukraine.

Bogdan Kovalenko,
National Aerospace University, Kharkov, Ukraine.

Sergii Kryvenko,
National Aerospace University, Kharkov, Ukraine.

Nikolay Ponomarenko,
National Aerospace University, Kharkov, Ukraine and Tampere University, Tampere, Finland.

Karen Egiazarian,
Tampere University, Tampere, Finland.

Jaakko Astola,
Tampere University, Tampere, Finland.