An Efficient Entropy Coding of Sparse Coefficients Based on Sparsity Adaptation and Atom Reordering for Image Compression

Abstract

Sparse coding is a technique that represents an input signal as a linear combination of a small number of atoms in the dictionary. When sparse coding is applied to image compression, it is necessary to perform efficient code assignment taking into account the statistical properties of weighting factors for each atom. In this paper, we analyze in detail the position indices and magnitude of non-zero coefficients in a dictionary designed by K-SVD. Based on the analyzed results, we propose an efficient entropy coding method introducing sparsity adaptation and atom reordering. Simulation results show that the proposed method can reduce the amount of generated bits by up to 6.2% compared to the conventional methods.