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
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;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
DOI :
10.1109/ICACI.2012.6463226