Lifting-based lossless image coding using cellular neural network predictors and context estimators optimized by adaptive differential evolution

Abstract

This paper proposes a novel lifting-based lossless image coding using CNN predictors and context estimators optimized by JADE. Our method adopts five types of CNN predictors for enabling not only CNN prediction based on the nature of the input image but also an optimal prediction for efficient compression can be realized. Introducing new optimizable parameters for context estimation enables further improvement of context estimation. Also, the efficiency of arithmetic coding is enhanced by introducing a grouping algorithm considering predictor utilization. The encoding experiments on various images support that the proposed method outperforms well-known existing lossless coding methods.