Image noise analysis with a fast lifting wavelet algorithm for objective image quality evaluation

An essential determinant of the value of surrogate digital images is their quality. Over the past years, there have been many attempts to develop models or metrics for image quality that incorporate elements of human visual sensitivity. However, there is no current standard and objective definition of spectral image quality. This paper proposes a reliable automatic method for objective image quality measurement by noise analysis throughout the spatial frequency range with a fast lifting wavelet algorithm. The wavelet frequency deconstruction is actually to extract the feature of edges in sub-band images. The technique provides a means to relate the quality of an image to the interpretation and quantification throughout the frequency range, in which the noise level is estimated for quality evaluation. The experimental results of using this method for image quality measurement exhibit good correlation to subjective visual quality assessments.