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Loss functions for denoising compressed images: a comparative study

Oberlin, Thomas and Malgouyres, François and Wu, Jin-Yi Loss functions for denoising compressed images: a comparative study. (2019) In: 27th European Signal Processing Conference (EUSIPCO 2019), 2 September 2019 - 6 September 2019 (A Coruña, Spain).

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Official URL: https://doi.org/10.23919/EUSIPCO.2019.8902653

Abstract

This paper faces the problem of denoising compressed images, obtained through a quantization in a known basis. The denoising is formulated as a variational inverse problem regularized by total variation, the emphasis being placed on the data-fidelity term which measures the distance between the noisy observation and the reconstruction. The paper introduces two new loss functions to jointly denoise and dequantize the corrupted image, which fully exploit the knowledge about the compression process, i.e., the transform and the quantization steps. Several numerical experiments demonstrate the effectiveness of the proposed loss functions and compare their performance with two more classical ones.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-02952604
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited On:18 Sep 2020 09:48

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