Multiple-scale Structural Similarity Image Quality Assessment Based on Internal Generative Mechanism
SUN Yanjing①② YANG Yufen① LIU Donglin① SHI Wenjuan①
①(School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China) ②(Jiangsu Province Laboratory of Electrical and Automation Engineering for Coal Mining, China University of Mining and Technology, Xuzhou 221008, China)
In order to improve image information uncertainty measurement of the Multiple-scale Structural SIMilarity (MSSIM), a novel algorithm called iMSSIM based on internal generative mechanism is proposed, combining with Human Visual System (HVS). Firstly, internal generative mechanism based on the Piecewise AutoRegressive (PAR) model decomposes distorted image and the original image into two parts, the predicted part of image content using MSSIM algorithm assessment and image information uncertainty Part using PSNR assessment. Then, Mean Square Error is used as weight to combine the two scores to acquire the overall image quality assessmet results. Experiments performed on benchmark IQA databases demonstrate that the proposed algorithm not only has the best performance in different types of distortion, but also is better than the existing algorithms.
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