Intensity Gradient Technique for Efficient Intra-Prediction in H.264/AVC

This study presents an intensity gradient approach for intra-prediction in H.264 encoding system, which enhances the performance and efficiency of previous fast algorithms. We propose a preprocessing stage in which eight orientation features are extracted from a macro block by the intensity gradient filters. The orientation features are utilized to select a subset of prediction modes to be involved in the rate-distortion calculation so that the encoding time can be reduced. The simulation results indicate that the intensity gradient based algorithm for intra-prediction contributes better tradeoff between rate-distorion performance and encoding complexity than the previous algorithms. Compared to H.264 reference software, the proposed algorithm introduces slight PSNR degradation and bit rate increase but saves around 76% of the total encoding time with all intra-frame coding.