A NEW IMAGE QUALITY ESTIMATION APPROACH FOR JPEG2000 COMPRESSED IMAGES

被引：0

作者：

Chetouani, Aladine ^{[1
]}

Beghdadi, Azeddine ^{[1
]}

机构：

[1] Univ Paris 13, Inst Galilee, Lab Traitement & Transport Informat, F-93430 Villetaneuse, France

来源：

2011 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT) | 2011年

关键词：

Image Quality; Artificial Neural Networks; Subjective Scores; Artifacts;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

No Reference (NR) Image Quality Metrics (IQMs) for JPEG2000 compressed images consider generally the ringing effect as the dominant degradation. However, for a certain bite rate, blur degradation appears and becomes the most annoying. We propose here to estimate the quality of JPEG2000 compressed images by first identifying the dominant distortion and then selecting the appropriate metric (blur or ringing). The degradation identification is here realized using an Artificial Neural Networks (ANN). The performances of the proposed method are evaluated in terms of classification accuracy and correlation with subjective scores.

引用

页码：581 / 584

页数：4

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