@Article{cmc.2020.06076,
AUTHOR = {Yanghong Zhang, Feng Sun, Liwei Tian, Jinfeng Li, Longqing Zhang, Shengfu Lan},
TITLE = {Difference of Visual Information Metric Based on Entropy of Primitive},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {62},
YEAR = {2020},
NUMBER = {2},
PAGES = {817--831},
URL = {http://www.techscience.com/cmc/v62n2/38278},
ISSN = {1546-2226},
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.},
DOI = {10.32604/cmc.2020.06076}
}