No-reference Image Quality Assessment of High Dynamic Range Image Based on Tensor Domain Perceptual Features

For the traditional no-reference image quality assessment method cannot be directly applied to the quality evaluation of high dynamic range(HDR)images,a no-reference HDR image quality assessment method based on tensor domain perceptual features is proposed.Firstly,tensor decomposition is used to obtain the tensor sub-bands with luminance distortion and chrominance distortion.Then,the Auto-Regressive(AR)model is adopted to simulate the process that human brain adopts to predict the tensor sub-bands and obtain the perceptual prediction image of the tensor sub-bands.Finally,the AR coefficients are employed to represent perceptual predictive characteristics of HDR image in tensor domain,and the quality score of the HDR image is obtained via support vector regression model,combining with the dynamic range and proportion of brighter areas of the tensor sub-bands and the perceptual prediction image.Experimental results tested on two public HDR image databases of Nantes and EFPL show that the proposed method can achieve high consistent alignment with subjective assessment.The performance indices of SROCC and PLCC are all above 0.93,RMSE are 0.340 7 and 0.377 1,respectively.