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Due to rapid growth in multimedia technology, it becomes necessary to analyse image processing system. Important factor for analysis is image quality assessment as it plays a primary role in the design and quality monitoring of imaging and image acquisition systems. Image Quality assessment can be further referred for image processing systems. Quality analysis is achieved in two ways, subjectively and objectively. In subjective measurement expert people give their views of image quality i.e., MOS whereas objective techniques are applied with the help of mathematical algorithms. Commonly used objective quality metrics like FSIM, VIF, MSSIM etc. fail on some image impairments as seen in results. Paper proposes a similarity measure for image quality checking which is taking in to account perceived image features like edge, color, intensity, which are highly affected by commonly occurring variety of noise. HVS model is explicitly employed in the proposed measure. Experiments done on standard image quality assessment (IQA) database demonstrate that proposed criterion behaves in same way as subjective measure than existing similarity measures. The proposed methodology will further extend its support in video quality assessment too.


Feature Structural Similarity (FSIM), Image Quality Criterion (IQC), Mean Opinion Score (MOS), Measure, Visual Information Fidelity (VIF)