Learning Blind Quality Evaluator for Stereoscopic Images Using Joint Sparse Representation

Abstract

Perceptual quality prediction for stereoscopic images is of fundamental importance in determining the level of quality perceived by humans in terms of the 3D viewing experience. However, the existing no-reference quality assessment (NR-IQA) framework has its limitation in addressing binocular combination for stereoscopic images. In this paper, we propose a… (More)
DOI: 10.1109/TMM.2016.2594142

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