# BPG-Based Automatic Lossy Compression of Noisy Remote Sensing Images
_by Vozel Benoit (IETR - MULTIP) - 2022.11.10_

###### tags: `VAADER` `Seminar`

## Video
{%youtube HRfsNOVGWX4%}

## Abstract
_Work by Vladimir Lukin, Bogdan Kovalenko, Sergii Kryvenko, Victoriya Naumenko and Benoit Vozel_

We investigate lossy compression of noisy images. In this case, there are some peculiarities relating to noise filtering effect and analysis of compression technique performance. As a result of noise filtering due to lossy compression, the so-called optimal operation point (OOP) may exist. OOP is related to such parameters of a coder that quality of a compressed image is closer to the corresponding noise-free (true) image compared to quality of uncompressed (original, noisy) image where quality is characterized by a certain metric, conventional (PSNR) or visual one (PSNR-HVS-M, PSNR-HA, MDSI). If OOP for a given noisy image exists, it occurs expedient to automatically compress an image under interest in OOP or, at least, its neighbourhood. We show that it is, in general, possible to predict OOP existence (according to different metrics) before image compression. It is also possible to reasonably set the coder parameters where better portable graphics (BPG) coder is paid here the main attention. The extensions of the proposed approach to joint compression of three-component images are discussed. Image subsampling in color components is studied. The possibility of OOP existence for visual quality metrics PSNR-HA and MDSI is illustrated.