Direction-adaptive context modeling for sign coding in embedded wavelet image coder

Abstract

The conventional embedded wavelet image coder exploiting the adjacent neighbors is limited to efficiently compress the sign coefficients, since the wavelet coefficients are highly correlated along the dominant image features, such as edges or contours. To solve the problem, in this paper, we propose the direction-adaptive sign context modeling by adaptively exploiting the neighbors suitable to the dominant image features. Experimental results show that the sign coding based on the proposed context modeling reduces the sign bits up to 5.5% compared to the conventional sign coding method.

Entropy-Based Evaluation of Context Models for Wavelet-Transformed Images

“…The sign is not considered by INTER since little correlation exists between signs of different subbands[24]-[29].…”