Pseudoreference Subaperture Images and Microlens Image-Based Blind Light Field Image Quality Measurement

Abstract

Light field image (LFI) records the radiation intensity and direction information of light in scene, offering powerful capabilities for computer vision. It is found that the distortion caused by LFI processing is obviously reflected in the two representations of LFI, that is, subaperture images (SAIs) and microlens images (MLI). Specifically, on the one hand, pseudoreference SAI (PSAI) of a distorted SAI, which is rendered with the adjacent distorted SAIs, can be used to measure the distortion of the involved SAIs. On the other hand, macropixel blocks (MPBs) of MLI can be adopted to measure LFI global angular distortion. Therefore, a PSAIs- and MLI-based blind LFI quality measurement (PM-BLFIQM) method is proposed in this article. First, the local light field (LLF) is defined to generate PSAI of the central distorted SAI in each LLF of LFI, and then a pseudo-full-reference quality measurement metric based on PSAIs is presented. Second, to measure the angular consistency of the distorted LFI, an MLI-based feature extraction scheme is proposed for MPBs and their mean removal version by using discrete cosine transform and singular value decomposition. Finally, the quality of the distorted LFI is predicted with the features extracted from LLFs and MLI. Experimental results demonstrate that both PSAI and MPB are effective for measuring the quality of distorted LFI. In addition, the results on three LFI databases show that the proposed method achieves higher Spearman rank-order correlation coefficient (SROCC) and Pearson linear correlation coefficient (PLCC) values, so it outperforms the state-of-the-art methods in terms of consistency with human visual perception.