2015/11/15 by Chao Wang, Wang, Chao, Xuanqin Mou +3
Computer Science · #Advanced Data Compression Techniques #E.4 #FOS: Computer and information sciences #I.4.2 #Image and Video Quality Assessment #Multimedia (cs.MM) #Video Coding and Compression Technologies
paper · pdf · doi:10.48550/arxiv.1511.04691
openalex publication_date 2015/11/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In video coding, it is expected that the encoder could adaptively select the encoding parameters (e.g., quantization parameter) to optimize the bit allocation to different sources under the given constraint. However, in hybrid video coding, the dependency between sources brings high complexity for the bit allocation optimization, especially in the block-level, and existing optimization methods mostly focus on frame-level bit allocation. In this paper, we propose a macroblock (MB) level bit allocation method based on the minimum maximum (MINMAX) criterion, which has acceptable encoding complexity for offline applications. An iterative-based algorithm, namely maximum distortion descend (MDD), is developed to reduce quality fluctuation among MBs within a frame, where the Structure SIMilarity (SSIM) index is used to measure the perceptual distortion of MBs. Our extensive experimental results on benchmark video sequences show that the proposed method can greatly enhance the encoding performance in terms of both bits saving and perceptual quality improvement.