DocumentCode
596644
Title
A new wavelet hard threshold to process image with strong Gaussian Noise
Author
Cheng Chen ; Ningning Zhou
Author_Institution
Comput. Coll., Nanjing Univ. of posts & Telecommun., Nanjing, China
fYear
2012
fDate
18-20 Oct. 2012
Firstpage
558
Lastpage
561
Abstract
Wavelet transform method has been widely used in image filtering, the wavelet threshold de-noising method can treat Gaussian noise with randomness well. This paper proposes that after the wavelet transform the high frequency coefficients need a more accurate processing, And the classical hard threshold method has been improved by introducing the measure of medium truth scale. The new method can effectively handle strong Gaussian noise with larger variance through theoretical analysis and experimental simulation, and get a fine recovery image. It also provides a new approach for wavelet de-noising.
Keywords
Gaussian noise; filtering theory; image denoising; image restoration; image segmentation; wavelet transforms; fine image recovery; high frequency coefficients; image filtering; image processing; medium truth scale; strong Gaussian noise handling; wavelet hard threshold; wavelet threshold denoising method; wavelet transform method; Filtering; Gaussian noise; Noise reduction; Pollution measurement; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-1743-6
Type
conf
DOI
10.1109/ICACI.2012.6463226
Filename
6463226
Link To Document