speckle noise removal matlab code download
#1

Hai i am student and i have done my project in digital image processing.
i want some reference code which will be useful for my project which make it legible to understand.
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#2
speckle noise removal matlab code download

Abstract

The quality of the ultrasound medical images is usually degraded by two important problems - the transducer influence and the speckle noise. To remove the multiplicative speckle noise, in this paper it is presented a method based on a blind, time-domain, deconvolution algorithm. The proposed approach uses the envelope of the acquired radio-frequency signals for the numerical implementation. It is a two steps blind deconvolution, where firstly, the point spread function is automatically estimated from the measured data, and secondly, the data are reconstructed in a non-blind way using proposed algorithm. It has a nonlinear implementation which at each step intends to eliminate the most important part of speckle noise and blur as possible. The results on real image tests are compared with Tikhonov regularization. Our method shows better results for scatters detection and speckle noise removal.

Introduction

A new effective method for speckle noise reduction in ultrasound imaging is introduced in this paper. The proposed method is based on Extra-Energy Reduction (EER) function in the vector field, which is addressed by vector triangular formula. It is reasonable to decide that the calculated the energy of a pixel by vector triangular formula is less than the usual absolute distance energy of the same pixel then the pixel must be noisy. The noisy pixel with higher energy is moved to equilibrium situation by subtracting the extra energy for any type of functional operation (e.g. image segmentation, pattern recognition, objects classification). The implemented method reduces extra-energy from an image and provides a proper gray level distribution into the entire image. The technique demonstrates very impressive noise suppression without loss of important information compared to some existing state-of-the-art speckle denoising methods.
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