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No-reference image quality assessment based on natural scene statistics and wavelet

Jin Bo,Li Chaofeng,Wu Xiaojun School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China  
To estimate a range of image distortions,a novel no-reference image quality assessment method is proposed based on wavelet multi-scale transformation.For natural scene statistics(NSS) model,the sub-band energy of wavelet transformation has a linear distribution with scale index.According to this principle,the energy distribution of ideal image could be predicted from high-scale sub-band energy,which was not badly affected by distortion.Meanwhile,an effective method for identifying and compensating for an inappropriate distortion was presented.Finally,the quality metric was constructed by quantifying the difference between predicted energy and real energy in degradation image.Experimental results showed that the new method was consistent with subjective assessment and outperformed the other methods.
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