Cool-Chic: Perceptually Tuned Low Complexity Overfitted Image Coder

Abstract

This paper summarises the design of the Cool-Chic candidate for the Challenge on Learned Image Compression. This candidate attempts to demonstrate that neural coding methods can lead to low complexity and lightweight image decoders while still offering competitive performance. The approach is based on the already published overfitted lightweight neural networks Cool-Chic, further adapted to the human subjective viewing targeted in this challenge.

Challenge on Learned Image Compression (CLIC), DCC2024