Wavelet Image Coding Measurement based on System Visual Human

A reliable quality measurement is a much needed tool for determining the type and amount of image distortion for the embedded zero tree wavelet image coding based on perceptual techniques. Attempts to improve quality measurement include incorporation of simple models of the human visual system (HVS) and multi-dimensional tool design, it is essential to adapt perceptually based metrics which objectively enable to asses the visual quality measurement. Our paper proposes an objective quality metric based on various psychovisual models, yielding the objective factor called Probability Score (PS) that correlates well with visual error perception, and demonstrating very good performance. Thus, we avoid the traditional subjective criteria called mean opinion score (MOS), which involves human observers, are inconvenient, timeconsuming, and influenced by environmental conditions. Widely used pixelwise measure, the peak signal to noise ratio (PSNR) cannot capture the artifacts like blurriness or blockiness. The model therefore called the Modified Wavelet Visible Difference Predictor MWVDP, is based both on traditional psychometric function and the Daly model visible difference predictor (VDP) and integrates various psychovisual models.