Journal of Electronic ImagingRestoration of wavelet-compressed images
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We investigate the characteristics of compression noise in images compressed by scalar quantization of the data's wavelet transform coefficients. Such quantization noise is both experimentally and theoretically shown to be spatially varying in the pixel domain, with statistical correlations between the errors at the pixel locations. A quantization covariance matrix is presented that can find use in general restoration scenarios where the observed image or images have been compressed by scalar quantization of image wavelet coefficients. Deblurring is presented as an example use of the quantization model, which demonstrates the model's advantage over the common assumption of independent and identically distributed noise.