期刊
IET IMAGE PROCESSING
卷 13, 期 5, 页码 833-842出版社
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-ipr.2018.5520
关键词
regression analysis; image enhancement; feature extraction; Pearson correlation; regression algorithm; mean opinion scores; maximising contrast minimum artefact; tested contrast measurement tools; contrast enhancement algorithms; subsequent test; independent test; MCMA algorithm; optimal linear combination; MOS values; training contrast-enhanced images; local pixel diversity; histogram shape preservation; low dynamic range; contrast-related quality aspect; histogram-wise features; image enhancement quality; objective image quality assessment tool; image contrast enhancement methods; performance measurement; MCMA method
An objective image quality assessment tool is proposed to measure image enhancement quality with emphasis on contrast. In the proposed tool, which is based on maximizing contrast with minimum artefact (MCMA), local and global properties of an image are measured through pixel-wise and histogram-wise features, respectively. To this aim, three sub-measures are introduced, each of which able to detect one contrast-related quality aspect: (i) low dynamic range of image; (ii) histogram shape preservation during image enhancement process; and (iii) local pixel diversity. These sub-measures are combined through a subjective test to adapt them to the mean opinion scores (MOSs) of a diverse set of training contrast-enhanced images. A regression algorithm performs the adaptation by fitting the three sub-measures to the MOS values and finding an optimal linear combination by maximizing the Pearson correlation. In order to evaluate the performance of the MCMA algorithm, another independent, subsequent, subjective test was performed on a set of images enhanced by various known contrast enhancement algorithms to obtain MOS values and to compare them with the output of the proposed MCMA method. The experimental results show that MCMA has the highest correlation to the MOS when compared to the existing tested contrast measurement tools.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据