Vol.62, No.2, 2020, pp.817-831, doi:10.32604/cmc.2020.06076
OPEN ACCESS
RESEARCH ARTICLE
Difference of Visual Information Metric Based on Entropy of Primitive
  • Yanghong Zhang1, Feng Sun2, Liwei Tian1, Jinfeng Li3, Longqing Zhang3, Shengfu Lan3
1 Guangdong University of Science and Technology, Dong Guan, China.
2 Lenovo (Shanghai) Information Technology Co., Ltd., Shanghai, China.
* Corresponding Author: Longqing Zhang. Email: xfzlq@126.com.
Abstract
Image sparse representation is a method of efficient compression and coding of image signal in the process of digital image processing. Image after sparse representation, to enhance the transmission efficiency of the image signal. Entropy of Primitive (EoP) is a statistical representation of the sparse representation of the image, which indicates the probability of each base element. Based on the EoP, this paper presents an image quality evaluation method-Difference of Visual Information Metric (DVIM). The principle of this method is to evaluate the image quality with the difference between the original image and the distorted image. The comparative experiments between DVIM & PSNR & SSIM are carried out. It was found that there was a great improvement in the image quality evaluation of geometric changes. This method is an effective image quality evaluation method, which overcomes the weakness of other quality evaluation methods for geometrically changing images to a certain extent, and is more consistent with the subjective observation of the human eye.
Keywords
Entropy of primitive, visual information, visual information difference measurement.
Cite This Article
Zhang, Y., Sun, F., Tian, L., Li, J., Zhang, L., et al. (2020). Difference of Visual Information Metric Based on Entropy of Primitive. CMC-Computers, Materials & Continua, 62(2), 817–831.