DocumentCode :
2085152
Title :
Image Denoise Using Auto-Adapted Empirical Mode Decomposition Algorithm
Author :
Liang, LingFei ; Ping, Ziliang
Author_Institution :
Sch. of Electron. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2009
fDate :
17-19 Oct. 2009
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, a new image denoise method is presented. The main contribution of our approach is to apply an auto-adapted empirical mode decomposition algorithm (AAEMD) to remove the noise. By means of AAEMD, the image can be decomposed into a number of intrinsic mode function (IMF), and the histogram of IMF observes the normal distribution, whether the original image has noise or not. Here, histogram matching is applied for denoise in the first few IMF images. In other words, the histogram of the new IMF images after Appling histogram matching observes the special normal distribution. At last, the modified and unmodified IMF images are added up to get the denoise image. Experiments prove that the novel algorithm is efficient in image denosise and better than current algorithms.
Keywords :
image denoising; image matching; auto-adapted empirical mode decomposition; histogram matching; image denoising; intrinsic mode function; Acoustic reflection; Data analysis; Frequency; Gaussian distribution; Histograms; Image analysis; Physics; Signal analysis; Signal processing; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
Type :
conf
DOI :
10.1109/CISP.2009.5301486
Filename :
5301486
Link To Document :
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