S3: A Spectral and Spatial Measure of Local Perceived Sharpness in Natural Images

被引:310
作者
Vu, Cuong T. [1 ]
Phan, Thien D. [1 ]
Chandler, Damon M. [1 ]
机构
[1] Oklahoma State Univ, Sch Elect & Comp Engn, Stillwater, OK 74078 USA
基金
美国国家科学基金会;
关键词
Blur; human visual system (HVS); natural scenes; sharpness; spectral slope; total variation (TV); BLUR;
D O I
10.1109/TIP.2011.2169974
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 an algorithm designed to measure the local perceived sharpness in an image. Our method utilizes both spectral and spatial properties of the image: For each block, we measure the slope of the magnitude spectrum and the total spatial variation. These measures are then adjusted to account for visual perception, and then, the adjusted measures are combined via a weighted geometric mean. The resulting measure, i.e., S-3 (spectral and spatial sharpness), yields a perceived sharpness map in which greater values denote perceptually sharper regions. This map can be collapsed into a single index, which quantifies the overall perceived sharpness of the whole image. We demonstrate the utility of the S-3 measure for within-image and across-image sharpness prediction, no-reference image quality assessment of blurred images, and monotonic estimation of the standard deviation of the impulse response used in Gaussian blurring. We further evaluate the accuracy of in local sharpness estimation by comparing S-3 maps to sharpness maps generated by human subjects. We show that S-3 can generate sharpness maps, which are highly correlated with the human-subject maps.
引用
收藏
页码:934 / 945
页数:12
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