Abstract:

Given that the existing no-reference quality assessment methods for 2D images cannot be well used in stereoscopic images, we propose a no-reference (NR) image quality assessment method based on the disparity map and complex contourlet transform so as to effectively measure the quality of different types of distorted images. Firstly, we extract the disparity map that can reflect the 3D information, decompose the image by the complex contourlet transform and extract the following features: the energy of the sub-band coefficients within scales and the energy differences between scales. Then those features are fed to the support vector regression (SVR) model which can predict the image quality. Experimental results show that the proposed method outperforms current 3D IQA methods.

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