In embedded multimedia applications, improving video quality under constraints of bandwidth and storage is an important problem. In this paper, we discuss the relationship among picture resolution, quantization precision and subjective quality in video coding for embedded systems. Then we propose a principle of tradeoff between picture resolution and quantization precision. Video coding based on the tradeoff principle can achieve higher subjective quality at low bitrates, and significantly reduce the burden of decoders. Experimental results on both MPEG-2 codec and H.264 codec prove that the tradeoff principle is valuable and feasible for embedded systems.
Traditional video coding uses fixed keyframe setting, which cannot exert all the potentials of inter-frame prediction. Dynamic adaptive keyframe setting can improve the efficiency and quality of video coding. However, it generally requires time-consuming preprocessing of video analysis, which prevents it from being practical. In this paper, we propose a novel method of keyframe setting: Fast Dynamic Adaptive Keyframe Setting. The method adopts a quasi single-pass strategy of exploiting information generated by original motion-estimation, so the additional computing costs are acceptable. The method can improve both objective and subjective quality, and can be applied to any motion-estimation based video coding. Experimental results on both MPEG-2 codec and H.264 codec prove that the method is viable and valuable.