Engineering Commons^™

Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patches, within a given search window.

The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video …

An Improved Algorithm Of Trubulence Signal Denoising Based On Lms Adaptive Filtering, Xue Chen, Da-Lei Song, Xin Luan, Hua Yang, Xiu-Yan Liu

Journal of Marine Science and Technology

Restricted by observation instruments and methods, the measured turbulence signals in the open ocean are inevitably affected by noise. To maximum eliminate the noise caused by the vibration of the instruments and improve the accuracy of the measured turbulence signals, an improved turbulence signal denoising algorithm based on least mean square (LMS) adaptive filter is proposed in this paper. The key point of the improved algorithm is to obtain the optimal weight value by the adaptive adjustment and remove the vibration noise from the measured shear signals in frequency domain. Through taking the Nasmyth theoretical spectrum as the desired signal …

Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie

Russell C. Hardie

In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patches, within a given search window. The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video …

Leveraging Stacked Denoising Autoencoder In Prediction Of Pathogen-Host Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Jiangning Song

Faculty of Engineering and Information Sciences - Papers: Part B

In big data research related to bioinformatics, one of the most critical areas is proteomics. In this paper, we focus on the protein-protein interactions, especially on pathogen-host protein-protein interactions (PHPPIs), which reveals the critical molecular process in biology. Conventionally, biologists apply in-lab methods, including small-scale biochemical, biophysical, genetic experiments and large-scale experiment methods (e.g. yeast-two-hybrid analysis), to identify the interactions. These in-lab methods are time consuming and labor intensive. Since the interactions between proteins from different species play very critical roles for both the infectious diseases and drug design, the motivation behind this study is to provide a basic framework …

Electrocardiogram Signal Analysis For R-Peak Detection And Denoising With Hybrid Linearization And Principal Component Analysis, Harjeet Kaur, Rajni Rajni

Turkish Journal of Electrical Engineering and Computer Sciences

In the areas of biomedical and healthcare, electrocardiogram (ECG) signal analysis is one of the major aspects of research. The accuracy in the detection of subtle characteristic features in ECG is of great significance. This paper deals with an algorithm based on hybrid linearization and principal component analysis for ECG signal denoising and R-peak detection. The ECG data have been taken from the MIT-BIH Arrhythmia Database for performance evaluation. The signal is denoised by applying the hybrid linearization method, which is an arrangement of the extended Kalman filter along with discrete wavelet transform, and then principal component analysis is employed …