Objective quality assessment of synthesized images by local variation measurement

Highlights：

• In this work, we propose a full-reference (FR) quality assessment method to measure the distortion in the synthesized images by local variation measurement consisting of three-modules.

• Firstly, since the distortion in the synthesized image mainly occurs in the region with high-frequency structure information, the Neutrosophic domain is employed to evaluate the degradation of local image structure.

• Secondly, by considering that the texture of the synthesized image might be damaged due to the warping of 2D image or the loss of information in the occlusion region, we evaluate the visual quality of local texture by using the features obtained from frequency domain.

• Thirdly, to measure the stretching distortion which is unique in the synthesized image, the visual quality of extracted stretching area is measured by entropy.

• Finally, a pooling operation is used to combine the quality scores of the three modules to obtain the final predicted quality score.

摘要

•In this work, we propose a full-reference (FR) quality assessment method to measure the distortion in the synthesized images by local variation measurement consisting of three-modules.•Firstly, since the distortion in the synthesized image mainly occurs in the region with high-frequency structure information, the Neutrosophic domain is employed to evaluate the degradation of local image structure.•Secondly, by considering that the texture of the synthesized image might be damaged due to the warping of 2D image or the loss of information in the occlusion region, we evaluate the visual quality of local texture by using the features obtained from frequency domain.•Thirdly, to measure the stretching distortion which is unique in the synthesized image, the visual quality of extracted stretching area is measured by entropy.•Finally, a pooling operation is used to combine the quality scores of the three modules to obtain the final predicted quality score.