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Improvement of Image Compression Approach Using the Human Visual System

M. Rahali, H. Loukil, M. S. Bouhlel

Abstract



An images compression becomes a need to ensure their archiving and facilitate their transmission. The very paper comprises a proposal of an image compression approach using the human visual system (HVS). Actually, if the classical methods of image compression use quantization to reduce high frequencies, our brainchild consists in integrating the perception and modeling of the human vision to improve an image compression approach by using the discrete wavelet transform and quantization through the neural networks. In the new technique, a preprocessing phase can be added which is a compromise between the two laws: Weber-Fechner law considers which the sensitivity of the human eye to luminance is regarded as a logarithmic function and the A-law which is used in the field of telephony. The results of comparative experiments between our new approach, which use the human visual system, and the classical approach shows a significant improvement of the image quality notably for high compression ratios.

Keywords


Image Compression, HVS, Weber-Fechner law, A-law, Discrete Wavelet Transform, Kohonen’s Networks.

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