A No-Reference Image Blur Metric Based on the Cumulative Probability of Blur Detection (CPBD)

被引：425

作者：

Narvekar, Niranjan D. ^{[1
,2
]}

Karam, Lina J. ^{[1
]}

机构：

[1] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ 85287 USA

[2] Dialog Res Inc, Eatontown, NJ 07724 USA

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 2011年 / 20卷 / 09期

关键词：

Blur detection; blur metric; no-reference; objective; perceptual; sharpness metric; visual quality;

D O I：

10.1109/TIP.2011.2131660

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a no-reference image blur metric that is based on the study of human blur perception for varying contrast values. The metric utilizes a probabilistic model to estimate the probability of detecting blur at each edge in the image, and then the information is pooled by computing the cumulative probability of blur detection (CPBD). The performance of the metric is demonstated by comparing it with existing no-reference sharpness/blurriness metrics for various publicly available image databases.

引用

页码：2678 / 2683

页数：6

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