Multi-scale Superpixel Based Homomorphic Filtering for the Component Image Enhancement

被引：0

作者：

Song, Pingting ^{[1
]}

Wang, Jianlin ^{[1
]}

Guo, Yongqi ^{[1
]}

Zhao, Liqiang ^{[1
]}

Qiu, Kepeng ^{[1
]}

机构：

[1] Beijing Univ Chem Technol, Beijing 100029, Peoples R China

来源：

PROCEEDINGS OF 2020 CHINESE INTELLIGENT SYSTEMS CONFERENCE, VOL II | 2021年 / 706卷

关键词：

Superpixel segmentation; Homomorphic filtering; Image enhancement; Multi-scale fusion; ADAPTIVE HISTOGRAM EQUALIZATION;

D O I：

10.1007/978-981-15-8458-9_23

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Aiming at the low accuracy of visual measurement caused by the nonuniform illumination image of components during industrial processing and assembly, a multi-scale superpixel based homomorphic filtering method for the component image enhancement is proposed. Firstly, the image is segmented into multiple subblocks using superpixel segmentation in different scales. Secondly, different subblocks are homomorphically filtered at each scale. Finally, images of different scales which have been filtered are weighted according to the standard deviation and fused to get the enhanced image. The experimental results show that the proposed method can effectively improve the average value and average gradient value of the enhanced image.

引用

页码：212 / 221

页数：10

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