학술논문
Enhancement of CNN-based Probability Modeling by Locally Trained Adaptive Prediction for Efficient Lossless Image Coding
Document Type
Conference
Source
2022 Picture Coding Symposium (PCS) Picture Coding Symposium (PCS), 2022. :79-83 Dec, 2022
Subject
Language
ISSN
2472-7822
Abstract
An autoregressive image generative model that estimates the conditional probability distributions of image signals pel-by-pel is a promising tool for lossless image coding. In this paper, a generative model based on a convolutional neural network (CNN) was combined with a locally trained adaptive predictor to improve its accuracy. Furthermore, sets of parameters that adjust the estimated probability distribution were numerically optimized for each image to minimize the resulting coding rate. Simulation results indicate that the proposed method improves the coding efficiency obtained by the CNN-based model for most of the tested images.