Prediction Method for Image Coding Quality Based on Differential Information Entropy

Entropy

Xin Tian¹  Tao Li²  Jin-Wen Tian² 

[1] School of Electronic Information, Wuhan University, Wuhan 430072, China; E-Mail:;The National Key Laboratory of Science & Technology on Multi-Spectral Information Processing, School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; E-Mails:

关键词: image compression;    quality prediction;    differential information entropy;   

DOI  :  10.3390/e16020990

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland