scholarly journals Speckle Noise Removal by Energy Models with New Regularization Setting

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Bo Chen ◽  
Jinbin Zou ◽  
Weiqiang Zhang
Keyword(s):  
Total Variation ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Noise Removal ◽  
Energy Models ◽  
Energy Diffusion ◽  
Total Variation Model ◽  
Local Coordinates ◽  
Diffusion Speed ◽  
Adaptive Total Variation

In this paper, we introduce two novel total variation models to deal with speckle noise in ultrasound image in order to retain the fine details more effectively and to improve the speed of energy diffusion during the process. Firstly, two new convex functions are introduced as regularization term in the adaptive total variation model, and then, the diffusion performances of Hypersurface Total Variation (HYPTV) model and Logarithmic Total Variation (LOGTV) model are analyzed mathematically through the physical characteristics of local coordinates. We have shown that the larger positive parameter in the model is set, the greater energy diffusion speed appears to be, but it will cause the image to be too smooth that required adequate attention. Numerical experimental results show that our proposed LOGTV model for speckle noise removal is superior to traditional models, not only in visual effect but also in quantitative measures.

scholarly journals Image Denoising Using Total Variation Model Guided by Steerable Filter

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Wenxue Zhang ◽  
Yongzhen Cao ◽  
Rongxin Zhang ◽  
Yuanquan Wang
Keyword(s):  
Diffusion Process ◽  
Total Variation ◽  
Noise Removal ◽  
Edge Preserving ◽  
Linear Diffusion ◽  
Proposed Model ◽  
Total Variation Model ◽  
Adaptive Total Variation ◽  
Steerable Filter ◽  
Tv Model

We propose an adaptive total variation (TV) model by introducing the steerable filter into the TV-based diffusion process for image filtering. The local energy measured by the steerable filter can effectively characterize the object edges and ramp regions and guide the TV-based diffusion process so that the new model behaves like the TV model at edges and leads to linear diffusion in flat and ramp regions. This way, the proposed model can provide a better image processing tool which enables noise removal, edge-preserving, and staircase suppression.

scholarly journals A Convex Adaptive Total Variation Model Based on the Gray Level Indicator for Multiplicative Noise Removal

2013 ◽  
Vol 2013 ◽  
pp. 1-21 ◽  
Author(s):  
Gang Dong ◽  
Zhichang Guo ◽  
Boying Wu
Keyword(s):  
Total Variation ◽  
Multiplicative Noise ◽  
Noise Removal ◽  
Time Behavior ◽  
Gray Level ◽  
Level Indicator ◽  
Total Variation Model ◽  
Long Time ◽  
Multiplicative Noise Removal ◽  
Adaptive Total Variation

This paper focuses on the problem of multiplicative noise removal. Using a gray level indicator, we derive a new functional which consists of the adaptive total variation term and the global convex fidelity term. We prove the existence, uniqueness, and comparison principle of the minimizer for the variational problem. The existence, uniqueness, and long-time behavior of the associated evolution equation are established. Finally, experimental results illustrate the effectiveness of the model in multiplicative noise reduction. Different from the other methods, the parameters in the proposed algorithms are found dynamically.

Speckle noise removal applied to ultrasound image of carotid artery based on total least squares model

2016 ◽  
Vol 24 (5) ◽  
pp. 749-760
Author(s):  
Lei Yang ◽  
Jun Lu ◽  
Ming Dai ◽  
Li-Jie Ren ◽  
Wei-Zong Liu ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Least Squares ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Noise Removal ◽  
Total Least Squares

scholarly journals A Median Filter With Evaluating of Temporal Ultrasound Image for Impulse Noise Removal for Kidney Diagnosis

2020 ◽  
Vol 1 (2) ◽  
pp. 71-77
Author(s):  
Rasheed Ihsan ◽  
Saman Almufti ◽  
Ridwan Marqas
Keyword(s):  
Information Quality ◽  
Kidney Diseases ◽  
Median Filter ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Noise Removal ◽  
Ultrasound Images ◽  
Examination Methods ◽  
Detection And Diagnosis ◽  
Temporal Dimensions

Ultrasound imaging helps the doctor to view the tissues and organs in the body's abdominal area with no ionization risks compared to other internal organ examination methods dependent on radiation. It offers highly precise renal imaging of suspected acute kidney diseases. This paper proposes temporary filtering methods to improve ultrasound images from ultrasonic kidney video. The proposed filters focus on the detection and diagnosis of kidney disease by processing consecutive images of the acquired kidney video. Extending the spatial median image filters to temporal dimensions after the picture frames are manually clipped and aligned in MATLAB by image processing Toolbox to suppress speckle noise, and enhance a doctor's diagnostic information quality.

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