Speckle Reduction Filter Using Wavelet-Based Methods for Medical Imaging Application.

摘要

One of the most significant features of diagnostic echocardiographic images is to reduce speckle noise and make better image quality In this paper ve proposed a simple and effective filter design for image denoising and contrast enhancement based on multiscale wavelet denoising method, Wavelet threshold algorithms replace wavelet coefficients with small magnitude by zero and keep or shrink the other coefficients, This is basically a local procedure since wavelet coefficients characterize the local regularity of a function, After ve estimate distribution of noise within echocardiographic image then apply to fitness Wavelet threshold algorithm. A common way of the estimating the speckle noise level in coherent imaging is to calculate the mean-to-standard-deviation ratio of the pixel intensity often termed the Equivalent Number of Looks(ENL) over a uniform image area, Unfortunately we found this measure not very robust mainly because of the difficulty to identify a uniform area in a real image. For this reason we will only use here the S/MSE ratio and which corresponds to the standard SNR in case of additive noise. We have simulated some echocardiographic images by specialized hardware for real-time application; processing of a 512*512 images takes about 1 minute. Our experiments show flat the optimal threshold level depends on the spectral content of the image. high spectral Content tends to over-estimate the noise standard deviation estimation performed at the finest level of the DWT. As a result a lower threshold parameter is required to get the optimal S/MSE. The standard WCS theory predicts a threshold flat depends on the number of signal samples only.