A review of some powerful noise elimination techniques for Land Processing

Author(s):  
J. A. Stein ◽  
T. Langston
Keyword(s):  
Author(s):  
Ryo Takagi ◽  
Toshikatsu Washio ◽  
Yoshihiko Koseki

Abstract Purpose In this study, the robustness and feasibility of a noise elimination method using continuous wave response of therapeutic ultrasound signals were investigated when tissue samples were moved to simulate the respiration-induced movements of the different organs during actual high-intensity focused ultrasound (HIFU) treatment. In addition to that, the failure conditions of the proposed algorithm were also investigated. Methods The proposed method was applied to cases where tissue samples were moved along both the lateral and axial directions of the HIFU transducer to simulate respiration-induced motions during HIFU treatment, and the noise reduction level was investigated. In this experiment, the speed of movement was increased from 10 to 40 mm/s to simulate the actual movement of the tissue during HIFU exposure, with the intensity and driving frequency of HIFU set to 1.0–5.0 kW/cm2 and 1.67 MHz, respectively. To investigate the failure conditions of the proposed algorithm, the proposed method was applied with the HIFU focus located at the boundary between the phantom and water to easily cause cavitation bubbles. The intensity of HIFU was set to 10 kW/cm2. Results Almost all HIFU noise was constantly able to be eliminated using the proposed method when the phantom was moved along the lateral and axial directions during HIFU exposure. The noise reduction level (PRL in this study) at an intensity of 1.0, 3.0, and 5.0 kW/cm2 was in the range of 28–32, 38–40, and 42–45 dB, respectively. On the other hand, HIFU noise was not basically eliminated during HIFU exposure after applying the proposed method in the case of cavitation generation at the HIFU focus. Conclusions The proposed method can be applicable even if homogeneous tissues or organs move axially or laterally to the direction of HIFU exposure because of breathing. A condition under which the proposed algorithm failed was when instantaneous tissue changes such as cavitation bubble generation occurred in the tissue, at which time the reflected continuous wave response became less steady.


Author(s):  
Jinyuan Wu ◽  
Alan Baumbaugh ◽  
Craig Drennan ◽  
Randy Thurman-Keup ◽  
Jonathan Lewis ◽  
...  

2017 ◽  
Vol 53 (2) ◽  
pp. 64-66 ◽  
Author(s):  
Tianyi Li ◽  
Xiaodong Xu ◽  
Tao Yin ◽  
Wei Li ◽  
Haigang Yang

Author(s):  
Ahmed Abdulqader Hussein ◽  
Sabahaldin A. Hussain ◽  
Ahmed Hameed Reja

<p>A modified mixed Gaussian plus impulse image denoising algorithm based on weighted encoding with image sparsity and nonlocal self-similarity priors regularization is proposed in this paper. The encoding weights and the priors imposed on the images are incorporated into a variational framework to treat more complex mixed noise distribution. Such noise is characterized by heavy tails caused by impulse noise which needs to be eliminated through proper weighting of encoding residual. The outliers caused by the impulse noise has a significant effect on the encoding weights. Hence a more accurate residual encoding error initialization plays the important role in overall denoising performance, especially at high impulse noise rates. In this paper, outliers free initialization image, and an easier to implement a parameter-free procedure for updating encoding weights have been proposed. Experimental results demonstrate the capability of the proposed strategy to recover images highly corrupted by mixed Gaussian plus impulse noise as compared with the state of art denoising algorithm. The achieved results motivate us to implement the proposed algorithm in practice.</p>


2018 ◽  
Vol 11 (2) ◽  
pp. 166-180 ◽  
Author(s):  
Long Xin ◽  
Delin Luo ◽  
Han Li

PurposeThe purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling (AAR) for unmanned aerial vehicle, which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.Design/methodology/approachMethods and techniques for marker detection, feature matching and pose estimation have been designed and implemented in the visual measurement system.FindingsThe simple blob detection (SBD) method is adopted, which outperforms the Laplacian of Gaussian method. And a novel noise-elimination algorithm is proposed for excluding the noise points. Besides, a novel feature matching algorithm based on perspective transformation is proposed. Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.Practical implicationsThe visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.Originality/valueThe SBD method is used to detect the features and a novel noise-elimination algorithm is proposed. Besides, a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.


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