No reference quality assessment for Thangka color image based on superpixel
| Autor: | Jiahao Meng, Wenjin Hu, Fuliang Zeng, Yuqi Ye |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Correlation coefficient
Computer science Color image Image quality business.industry No reference 020207 software engineering Pattern recognition 02 engineering and technology Color space Spearman's rank correlation coefficient Thangka Signal Processing 0202 electrical engineering electronic engineering information engineering Media Technology Entropy (information theory) 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | Journal of Visual Communication and Image Representation. 59:407-414 |
| ISSN: | 1047-3203 |
| DOI: | 10.1016/j.jvcir.2019.01.039 |
| Popis: | In view of the situation that a large number of Thangka images are missing part of color information because of time and environmental factors, the existing image evaluation methods are inconsistent with the result of subjective evaluation. This paper aims at evaluating the damaged Thangka color image, and proposes a new method of image quality evaluation based on superpixel and color entropy. In this algorithm, we use the uniformity of Thangka color image to extract color feature based on CIE 1976 L* a* b* (CIELAB) color space and superpixel. Therefore, the loss of color information in the complex area of Thangka images is well handled. The color entropy is used to quantify the color distribution and structure characteristics of each superpixel, and then we can get the preliminarily evaluation score. In the end, large amounts of data are obtained through some operations such as image deformation and rotating by the Generative Adversarial Nets (GANs), which makes the final evaluation score more reliable. Experimental results show that this method can obtain a good consistency with the subjective results, and Spearman rank order the correlation coefficient (SROCC) and Pearson linear correlation coefficient (PLCC) of the new method already exceed 0.9. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect