A Fast Wavelet-Based Algorithm for Global and Local Image Sharpness Estimation

被引：220

作者：

Vu, Phong V. ^{[1
]}

Chandler, Damon M. ^{[1
]}

机构：

[1] Oklahoma State Univ, Sch Elect & Comp Engn, Stillwater, OK 74078 USA

来源：

IEEE SIGNAL PROCESSING LETTERS | 2012年 / 19卷 / 07期

基金：

美国国家科学基金会;

关键词：

Blur; image quality; local image sharpness; sharpness; wavelet;

D O I：

10.1109/LSP.2012.2199980

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this letter, we present a simple, yet effective wavelet-based algorithm for estimating both global and local image sharpness (FISH, Fast Image Sharpness). FISH operates by first decomposing the input image via a three-level separable discrete wavelet transform (DWT). Next, the log-energies of the DWT subbands are computed. Finally, a scalar index corresponding to the image's overall sharpness is computed via a weighted average of these log-energies. Testing on several image databases demonstrates that, despite its simplicity, FISH is competitive with the currently best-performing techniques both for sharpness estimation and for no-reference image quality assessment.

引用

页码：423 / 426

页数：4

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