Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram br

The video frame type decision is one of the key factors affecting the efficiency of video coding. Thispaper proposes an adaptive video frame type decision algorithm based on local luminance histogram to improvethe x265 encoding performance. Firstly, the local luminance histograms of frames are calculated at the level of64x64 Coding Tree Unit (CTU), and the difference of local luminance histogram between frames is used torepresent the degree of scene variation between frames. Secondly, Intra-coded picture (I-frame) detectionwindow is introduced. I-frame is determined by comparing the degree of scene variation between frames.Finally, the Mini Group Of Picture (MiniGOP) size is determined according to the correlation between thedegree of scene variation and MiniGOP size, so as to determine adaptively Generalized P and B picture (GPB-frame) and Bidirectionally predicted picture (B-frame). Experimental results show that compared with therelevant algorithms in x265, the proposed algorithm can effectively reduce the coding complexity of x265, anddecide I/GPB/B-frame efficiently and adaptively with nearly 5% less coding time