INR-MDSQC: Implicit Neural Representation Multiple Description Scalar Quantization for robust image Coding

Autor:	Le, Trung Hieu, Pic, Xavier, Antonini, Marc
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing
Druh dokumentu:	Working Paper
Popis:	Multiple Description Coding (MDC) is an error-resilient source coding method designed for transmission over noisy channels. We present a novel MDC scheme employing a neural network based on implicit neural representation. This involves overfitting the neural representation for images. Each description is transmitted along with model parameters and its respective latent spaces. Our method has advantages over traditional MDC that utilizes auto-encoders, such as eliminating the need for model training and offering high flexibility in redundancy adjustment. Experiments demonstrate that our solution is competitive with autoencoder-based MDC and classic MDC based on HEVC, delivering superior visual quality. Comment: Accepted at IEEE MMSP 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.13919 Zobrazit plný text záznamu View this record from Arxiv