DAUBECHIES COMPLEX WAVELET TRANSFORM BASED MULTILEVEL SHRINKAGE FOR DEBLURRING OF MEDICAL IMAGES IN PRESENCE OF NOISE
Deblurring in the presence of noise is a hard problem, especially in ultrasonic and CT images. In this paper, we propose a new method of image deblurring in presence of noise, using symmetric Daubechies complex wavelet transform. The proposed method is based on shrinkage of multilevel Daubechies complex wavelet coefficients, and is adaptive as it uses shrinkage function based on the variance of wavelet coefficients as well as the mean and the median of absolute wavelet coefficients at a particular level. The results obtained after the application of the proposed method demonstrate an improved performance over other related methods available in literature.
daubechies complex wavelet transform deconvolution colored noise removal multilevel thresholding medical image deblurring