No-Reference Image Quality Assessment Using Orthogonal Color Planes Patterns

Abstract

This paper proposes a new general-purpose no-reference image quality assessment (NR-IQA) method based on color texture analysis. Specifically, the proposed method uses the statistics of the orthogonal color planes pattern (OCPP) descriptor to characterize image quality. The OCPP descriptor, proposed in this paper, is an extension of the local binary pattern operator that incorporates color information. To make NR-IQA methods more generic, that is, more sensitivity to different types of degradation (e.g., color and contrast degradation), it is important to take into consideration the color information. In the proposed NR-IQA method, we use the statistics of the OCPP descriptor as an input vector to a regression algorithm, which models the nonlinear relationship between the OCPP statistics and the subjective opinion scores. Experimental results show that proposed IQA method is quite efficient when compared to popular state-of-the-art NR-IQA methods.