No-reference stereoscopic image quality measurement based on generalized local ternary patterns of binocular energy response

Abstract

Perceptual no-reference (NR) quality measurement of stereoscopic images has become a challenging issue in three-dimensional (3D) imaging fields. In this article, we propose an efficient binocular quality-aware features extraction scheme, namely generalized local ternary patterns (GLTP) of binocular energy response, for general-purpose NR stereoscopic image quality measurement (SIQM). More specifically, we first construct the binocular energy response of a distorted stereoscopic image with different stimuli of amplitude and phase shifts. Then, the binocular quality-aware features are generated from the GLTP of the binocular energy response. Finally, these features are mapped to the subjective quality score of the distorted stereoscopic image by using support vector regression. Experiments on two publicly available 3D databases confirm the effectiveness of the proposed metric compared with the state-of-the-art full reference and NR metrics.