Integrating a Smooth Psychovisual Threshold into an Adaptive JPEG Image Compression

The visual quality image output of JPEG compression is determined by quantization process. The popular quality factor in the extended JPEG image compression has been widely used to scale up the quantization tables. The scaling quantization table using quality factor is used to determine the quality image output. The scaling up on the quantization tables increases their values uniformly thus produces higher compression performance. However, the effects of the scaling up on the human visual system have not been taken into consideration. This paper examines the quantization table design based on adaptive psychovisual threshold and numerical analysis of the compression performance in terms of quality image reconstruction and average bit length of Huffman code. The comparison between extended JPEG image compression using the typical quality factor and quality scale of psychovisual threshold has been done. The experimental results of adaptive quantization tables based on psychovisual threshold show an improvement on the quality of image reconstruction at the lower average bit length of Huffman's code.

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