Abstract
We present an innovative approach to the objective quality evaluation that could be computed using the mean difference between the original and tested images in different wavelet subbands. Discrete wavelet transform (DWT) subband decomposition properties are similar to human visual system characteristics facilitating integration of DWT into image-quality evaluation. DWT decomposition is done with multiresolution analysis of a signal that allows us to decompose a signal into approximation and detail subbands. DWT coefficients were computed using reverse biorthogonal spline wavelet filter banks. Wavelet coefficients are used to compute new image-quality measure (IQM). IQM is defined as perceptual weighted difference between coefficients of original and degraded image.
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