Reduced-Reference Quality Assessment Based on the Entropy of DWT Coefficients of Locally Weighted Gradient Magnitudes
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Reduced-Reference Quality Assessment Based on
the Entropy of DWT Coefficients of Locally
Weighted Gradient Magnitudes
Abstract— Perceptual image quality assessment (IQA) attempts to use computational models to estimate the image quality in accordance with subjective evaluations. Reducedreference IQA (RRIQA) methods make use of partial information or features extracted from the reference image for estimating the quality of distorted images. Finding a balance between the number of RR features and accuracy of the estimated image quality is essential and important in IQA. In this paper, we propose a training-free low-cost RRIQA method that requires a very small number of RR features (six RR features). The proposed RRIQA algorithm is based on the discrete wavelet transform (DWT) of locally weighted gradient magnitudes. < final year projects >
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