基于稀疏去噪的DTCWT火焰图像融合检测

doi:10.3969/j.issn.1000-3428.2012.23.054

计算机工程 ›› 2012, Vol. 38 ›› Issue (23): 219-223. doi: 10.3969/j.issn.1000-3428.2012.23.054

基于稀疏去噪的DTCWT火焰图像融合检测

王静静^a，张小刚^a，陈华^b

(湖南大学 a. 电气与信息工程学院；b. 信息科学与工程学院，长沙 410082)

收稿日期:2012-02-13 出版日期:2012-12-05 发布日期:2012-12-03
作者简介:王静静(1986－)，女，硕士研究生，主研方向：工业过程图像处理；张小刚，教授、博士生导师；陈华(通讯作者)，讲师
基金资助:
国家自然科学基金资助项目(60874096, 61174050, 61203016)

DTCWT Fusion Detection for Flame Image Based on Sparse De-noising

WANG Jing-jing ^a, ZHANG Xiao-gang^a, CHEN Hua ^b

(a. College of Electrical and Information Engineering; b. College of Information Science and Engineering, Hunan University, Changsha 410082, China)

Received:2012-02-13 Online:2012-12-05 Published:2012-12-03

摘要/Abstract

摘要： 燃煤火焰图像黑把子区域的边缘模糊或不完整，无法直接使用Canny检测算子准确检测出边缘信息。针对该问题，提出基于稀疏去噪的双树复小波变换(DTCWT)火焰图像融合检测方法。利用稀疏去噪对2幅单帧火焰图像进行DTCWT融合，采用Canny检测算子检测边缘。实验结果表明，该方法能够得到噪声较低的图像和比较完整的黑把子边缘信息。

关键词: 火焰图像, 图像稀疏表示, 稀疏字典, DTCWT融合, Canny检测算子

Abstract: The edge of the black handle region in the coal-fired flame images is fuzzy or incomplete, directly using the Canny detection operator cannot accurately detect the edge information. Aiming at this problem, this paper proposes the DTCWT fusion detection method based on sparse de-noising for flame image. It uses DTCWT fusion method based on sparse de-noising to fusion two single frame flame image, then using Canny detection operator for detection and processing. Experimental results show that this method can detect completely black handle edge information on basis of fusing low noise and full shape of the black handle region.

Key words: flame image, image spare representation, sparse dictionary, Dual-tree Complex Wavelet Transform(DTCWT) fusion, Canny detection operator

中图分类号:

TN911.73

王静静, 张小刚, 陈华. 基于稀疏去噪的DTCWT火焰图像融合检测[J]. 计算机工程, 2012, 38(23): 219-223.

WANG Jing-Jing, ZHANG Xiao-Gang, CHEN Hua. DTCWT Fusion Detection for Flame Image Based on Sparse De-noising[J]. Computer Engineering, 2012, 38(23): 219-223.

https://www.ecice06.com/CN/Y2012/V38/I23/219

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