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.
Cite This Article
APA Style
Zhang, Y., Sun, F., Tian, L., Li, J., Zhang, L. et al. (2020). Difference of visual information metric based on entropy of primitive. Computers, Materials & Continua, 62(2), 817-831. https://doi.org/10.32604/cmc.2020.06076
Vancouver Style
Zhang Y, Sun F, Tian L, Li J, Zhang L, Lan S. Difference of visual information metric based on entropy of primitive. Comput Mater Contin. 2020;62(2):817-831 https://doi.org/10.32604/cmc.2020.06076
IEEE Style
Y. Zhang, F. Sun, L. Tian, J. Li, L. Zhang, and S. Lan "Difference of Visual Information Metric Based on Entropy of Primitive," Comput. Mater. Contin., vol. 62, no. 2, pp. 817-831. 2020. https://doi.org/10.32604/cmc.2020.06076