IMPROVE THE HEVC ALGORITHM COMPLEXITY BASED ON THE VISUAL PERCEPTION

Abstract

The visual perception, we want to mention here is the three visual methods in image processing. It is Just Noticeable Difference (JND), Luminance Histogram Bin Variation and Edge Detection. Based on these three methods, we reduce CU (coding unit) splitting coding time. In addition, we use the previous edge detection data to reduce the candidate of PU mode. HEVC (high-efficiency video coding), as the latest video coding standard, can achieve up to 50%-bit rate saving while maintaining the same subjective quality compared to H.264/AVC. However, HEVC takes very high computational complexity. In this research, we will combine two methods of CU splitting and PU mode deciding to improve this problem. Experimental results show that the proposed algorithm can achieve about 36.25% encoder time saving on average with 0.123dB PSNR loss while result in negligible BD-Bitrate loss compared with HM 16.0 (HEVC test model).