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Two Low-Level Feature Distributions Based No Reference Image Quality Assessment
2022
Applied Sciences
No reference image quality assessment (NR IQA) aims to develop quantitative measures to automatically and accurately estimate perceptual image quality without any prior information about the reference image. In this paper, we introduce two low-level feature distributions (TLLFD) based method for NR IQA. Different from the deep learning method, the proposed method characterizes image quality with the distributions of low-level features, thus it has few parameters, simple model, high efficiency,
doi:10.3390/app12104975
fatcat:3wngmceb4rgpfcbfjj7x3xm5fm