Joint Source/Channel Coding Based on Two-Dimensional Optimization for Scalable H.264/AVC Video

Abstract

The scalable extension of the H.264/AVC video coding standard (SVC) demonstrates superb adaptability in video communications. Joint source and channel coding (JSCC) has been shown to be very effective for such scalable video consisting of parts of different significance. In this paper, a new JSCC scheme for SVC transmission over packet loss channels is proposed which performs two‐dimensional optimization on the quality layers of each frame in a rate‐distortion (R‐D) sense as well as on the temporal hierarchical structure of frames under dependency constraints. To compute the end‐to‐end R‐D points of a frame, a novel reduced trellis algorithm is developed with a significant reduction of complexity from the existing Viterbi‐based algorithm. The R‐D points of frames are sorted under the hierarchical dependency constraints and optimal JSCC solution is obtained in terms of the best R‐D performance. Experimental results show that our scheme outperforms the existing scheme of [13] with average quality gains of 0.26 dB and 0.22 dB for progressive and non‐progressive modes respectively.

A Novel Method for Bitrate Control within Macroblocks Using Kalman and FIR Filters

“…While there are many techniques used within video codes to improve the quality of low bitrate video, service providers tend to desire even smaller bitrates with better quality. One of the easiest ways to achieve such requirements from service providers is rate control, which is performed by controlling a quantization parameter in a video codec [3]- [5].…”