DocumentCode
3174743
Title
Detail enhancement and noise reduction with true color image edge detection based on wavelet multi-scale
Author
Xiao, Feng ; Zhou, Mingquan ; Geng, Guohua
Author_Institution
Inst. of Visualization Technol., Northwest Univ., Xi´´an, China
fYear
2011
fDate
8-10 Aug. 2011
Firstpage
1061
Lastpage
1064
Abstract
To the problem of the existing multi-scale edge detection methods couldn´t tackle de-noising and edge detail preservation of images, the article proposed a multi-scale edge detection algorithm which took soft threshold method to implement detail enhancement and noise reduction of the true color image. Firstly, obtaining the true color images at different scales through wavelet multi-scale edge detection algorithm, then based on the improved soft threshold filter function, selecting appropriate threshold of the obtained image edges to perform noise reduction while enhance the edge details of the reservation; and finally, carrying out the weighted 2-norm fusion of edges of different-scale-image. Experiment results show that the algorithm can make full use of color and gradient information of true color images to effectively suppress noise, enhance the image edge details.
Keywords
edge detection; filtering theory; image colour analysis; image denoising; image enhancement; wavelet transforms; detail enhancement; edge detail preservation; gradient information; noise reduction; noise suppression; scale-image; soft threshold filter function; true color image edge detection; wavelet multiscale algorithm; weighted 2-norm fusion; Algorithm design and analysis; Color; Image color analysis; Image edge detection; Noise; Noise reduction; Smoothing methods; edge detection; edges fusion; enhance details; true color image; wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location
Deng Leng
Print_ISBN
978-1-4577-0535-9
Type
conf
DOI
10.1109/AIMSEC.2011.6010635
Filename
6010635
Link To Document