Optimal determination of wavelet threshold and decomposition level via heuristic learning for noise reduction

Comparative Evaluation of Speckle Reduction Filters for Ultrasound Kidney Images

“…The luminance between two images is determined by mean intensity of pixels in the image, contrast is determined by standard deviation of image and the structural is determined by the correlation between two images [24]. Let and then (17) σ σ σ σ (18) σ σ σ ( 19) Where, and are the mean and standard deviation over a window in the image f(x,y).…”

“…Most of the existing Wavelet denoising algorithms were developed for the images corrupted by additive noise, whereas the ultrasound images are corrupted by multiplicative noise hence requires log-transform of the image during the application of Wavelet transform. An Exponential operation is performed to convert the image back into non logarithmic format [15], [17], [18], [19]. In [11] the wavelet based Adaptive Bayesian shrinkage based on context modeling for ultrasound images were discussed, which works better in terms of noise removal and edge preservation when compared with Wiener filter and AWMF.…”

An Approach to Determining the Decomposition Level for Wavelet De-Nosing Based on Gamma Test

“…Similar idea has been taken in [9], but using χ 2 hypothesis test to verify the white noise instead of WEE. In [10], a GA was used to search the optimal settings for threshold and decomposition level by evaluating the second-order correlation and high-order correlation between the estimated noise and the de-noised signal for the reason that the original signal and noise are mutually independent. However, the GA developed in [4], to obtain the optimal parameters for wavelet basis, decomposition level, threshold function, threshold selection rules, and threshold rescaling method, incorporated an different objective function which attempts to minimize the mean square error (MSE) between the original signal and the de-noised version of the corrupted signal, but the paper did not clearly document how to obtain the original signal.…”