Color-Enriched Gradient Similarity for Retouched Image Quality Evaluation

Leida LI  Yu ZHOU  Jinjian WU  Jiansheng QIAN  Beijing CHEN  

IEICE TRANSACTIONS on Information and Systems   Vol.E99-D   No.3   pp.773-776
Publication Date: 2016/03/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2015EDL8204
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
image quality assessment,  image retouching,  gradient similarity,  color colorfulness,  saturation,  

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Image retouching is fundamental in photography, which is widely used to improve the perceptual quality of a low-quality image. Traditional image quality metrics are designed for degraded images, so they are limited in evaluating the quality of retouched images. This letter presents a RETouched Image QUality Evaluation (RETIQUE) algorithm by measuring structure and color changes between the original and retouched images. Structure changes are measured by gradient similarity. Color colorfulness and saturation are utilized to measure color changes. The overall quality score of a retouched image is computed as the linear combination of gradient similarity and color similarity. The performance of RETIQUE is evaluated on a public Digitally Retouched Image Quality (DRIQ) database. Experimental results demonstrate that the proposed metric outperforms the state-of-the-arts.