A Rate-distortion Based Quantization Level Adjustment Algorithm in Block-based Video Compression.
ABSTRACT In this paper, a rate-distortion based quantization level adjustment (RDQLA) algorithm is presented. Based on the rate-distortion
criterion, the quantization level adjustment algorithm effectively improves coding efficiency by adaptively optimizing quantization
levels of the signals near the boundaries of quantization cells and adjusting quantization levels per block. In addition,
it has no overhead and is fully compatible with the existing compression standards. The proposed algorithm can be applied
in any block based image and video coding method. In particular, the algorithm has been verified on the platform of H.264.
Experimental results show that the proposed algorithm improves objective and subjective performances substantially. It is
shown that the proposed algorithm has a gain of several dB comparing with the newest H.264 standard for high bit rates.
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ABSTRACT: It is desired to obtain the best possible image quality subject a predefined bit rate in video coding. Aiming on improving quantization performance for signals in non-flat region, the fast rate-distortion based quantization level adjustment algorithm (FRDQLA) was proposed in our former work. It can improve the objective coding performance efficiently. In this paper, a perceptual FRDQLA algorithm is proposed. By introducing the HVS model, the perceptual weighted rate-distortion cost is calculated. The signal is quantized, coupled with an advanced vision model based perceptual distortion measure for rate-distortion optimization to produce coded images with improved visual quality. The proposed algorithm has no overhead and is completely compatible with the standard decoder. Experimental results show that the proposed algorithm can efficiently improve the subjective viewing quality and reduce the bit rate 11%.01/2011;