Improved Best Prediction Mode(s) Selection Methods Based on Structural Similarity In H.264 I-Frame Encoder

Abstract

In H.264 I-frame encoder, the best infra prediction modes are chosen by utilizing the rate-distortion (R-D) optimization whose distortion is the sum of the squared differences (SSD, means the same as MSE) between the reconstructed and the original blocks. Recently a new image measurement called structural similarity (SSIM) based on the degradation of structural information was brought forward. It is proved that the SSIM can provide a better approximation to the perceived image distortion than the currently used PSNR (or MSE). In this paper, we propose two improved prediction modes selection methods based on SSIM for H.264 I-frame encoder. The first one is the SSIM-based R-D optimization (SBRDO) method, the other is the fast mode selection method based on SSIM (FMSBS). Experiments show that both the proposed method can improve the coding efficiency while maintaining the same perceptual reconstructed image quality.