The understanding and characterization of various forms of image degradation due to compression is important. The most commonly use image distortion measure is the mean squared error (MSE). However, the MSE value does not provide a good subjective performance measure, since it does not take human perception into account. In this research, we present a wavelet approach to measure the visual quality of compressed images based on a psycho-visual human vision model. Wavelet filter banks are shown to have a good space-frequency localization property and can be directly linked to the Michelson contrast and compactly supported features. Experiment results are provided to demonstrate the effectiveness of the Haar wavelet.<\/p>\n","protected":false},"excerpt":{"rendered":"
The understanding and characterization of various forms of image degradation due to compression is important. The most commonly use image distortion measure is the mean squared error (MSE). However, the MSE value does not provide a good subjective performance measure, since it does not take human perception into account. 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