Real-Time No-Reference Image Quality Assessment Based on Filter Learning

CVPR 2013 Peng YeJayant KumarLe KangDavid Doermann

This paper addresses the problem of general-purpose No-Reference Image Quality Assessment (NR-IQA) with the goal of developing a real-time, cross-domain model that can predict the quality of distorted images without prior knowledge of non-distorted reference images and types of distortions present in these images. The contributions of our work are two-fold: first, the proposed method is highly efficient... (read more)

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