Entropy 2014, 16(2), 990-1001; doi:10.3390/e16020990
Article

Prediction Method for Image Coding Quality Based on Differential Information Entropy

1,* , 2
, 2
 and 1
Received: 27 October 2013; in revised form: 19 December 2013 / Accepted: 26 January 2014 / Published: 17 February 2014
(This article belongs to the Special Issue Advances in Information Theory)
View Full-Text   |   Download PDF [2324 KB, updated 20 February 2014; original version uploaded 17 February 2014]
Abstract: For the requirement of quality-based image coding, an approach to predict the quality of image coding based on differential information entropy is proposed. First of all, some typical prediction approaches are introduced, and then the differential information entropy is reviewed. Taking JPEG2000 as an example, the relationship between differential information entropy and the objective assessment indicator PSNR at a fixed compression ratio is established via data fitting, and the constraint for fitting is to minimize the average error. Next, the relationship among differential information entropy, compression ratio and PSNR at various compression ratios is constructed and this relationship is used as an indicator to predict the image coding quality. Finally, the proposed approach is compared with some traditional approaches. From the experiments, it can be seen that the differential information entropy has a better linear relationship with image coding quality than that with the image activity. Therefore, the conclusion can be reached that the proposed approach is capable of predicting image coding quality at low compression ratios with small errors, and can be widely applied in a variety of real-time space image coding systems for its simplicity.
Keywords: image compression; quality prediction; differential information entropy
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Tian, X.; Li, T.; Tian, J.-W.; Li, S. Prediction Method for Image Coding Quality Based on Differential Information Entropy. Entropy 2014, 16, 990-1001.

AMA Style

Tian X, Li T, Tian J-W, Li S. Prediction Method for Image Coding Quality Based on Differential Information Entropy. Entropy. 2014; 16(2):990-1001.

Chicago/Turabian Style

Tian, Xin; Li, Tao; Tian, Jin-Wen; Li, Song. 2014. "Prediction Method for Image Coding Quality Based on Differential Information Entropy." Entropy 16, no. 2: 990-1001.


Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert