NOISE SUPPRESSION OF RECEIVER FUNCTIONS USING CURVELET TRANSFORM

2016 ◽  
Vol 59 (2) ◽  
pp. 125-138
Author(s):  
QI Shao-Hua ◽  
LIU Qi-Yuan ◽  
CHEN Jiu-Hui ◽  
GUO Biao
2010 ◽  
Vol 7 (1) ◽  
pp. 105-112 ◽  
Author(s):  
Zhi-yu Zhang ◽  
Xiao-dan Zhang ◽  
Hai-yan Yu ◽  
Xue-hui Pan

Author(s):  
Tajinder Kaur ◽  
Dinesh Kumar ◽  
Ekta Walia ◽  
Manjit Sandhu

In medical image processing, image denoising has become a very essential exercise all through the diagnose. Negotiation between the preservation of useful diagnostic information and noise suppression must be treasured in medical images. In case of ultrasonic images a special type of acoustic noise, technically known as speckle noise, is the major factor of image quality degradation. Many denoising techniques have been proposed for effective suppression of speckle noise. Removing noise from the original image or signal is still a challenging problem for researchers. In this paper, a Curvelet transform based denoising with improved thresholds is proposed for ultrasound images.


2020 ◽  
Vol 64 (2) ◽  
pp. 241-254
Author(s):  
Lieqian Dong ◽  
Changhui Wang ◽  
Mugang Zhang ◽  
Deying Wang ◽  
Xiaofeng Liang

2017 ◽  
Author(s):  
Hailong Sun ◽  
Hongye Wang ◽  
Xin Chen ◽  
Wei Zheng

2000 ◽  
Author(s):  
Edward Awh ◽  
John Serences ◽  
Kelsey Libner ◽  
Michi Matsukura

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