An Edge-Preserving Motion-Compensated Approach for Video Deinterlacing

2010 ◽  
pp. 57-62 ◽  
Author(s):  
Daulet Zhanguzin ◽  
Maria Trocan ◽  
Beata Mikovicova
Keyword(s):  
Edge Preserving ◽  
Video Deinterlacing

An Edge Dependent Weighted Filter for Video Deinterlacing

2015 ◽  
Vol E98.A (2) ◽  
pp. 788-791
Author(s):  
Hao ZHANG ◽  
Mengtian RONG ◽  
Tao LIU
Keyword(s):  
Video Deinterlacing

Edge-Preserving Error Diffusion for Multi-Toning Based on Dual Quantization

2017 ◽  
Vol 2017 (18) ◽  
pp. 123-129
Author(s):  
Takuma Kiyotomo ◽  
Keisuke Hoshino ◽  
Yuki Tsukano ◽  
Hiroki Kibushi ◽  
Takahiko Horiuchi
Keyword(s):  
Error Diffusion ◽  
Edge Preserving

Edge-preserving total variation regularization for dual-energy CT images

2019 ◽  
Vol 2019 (13) ◽  
pp. 147-1-147-8
Author(s):  
Sandamali Devadithya ◽  
David Castañóon
Keyword(s):  
Total Variation ◽  
Ct Images ◽  
Dual Energy ◽  
Dual Energy Ct ◽  
Total Variation Regularization ◽  
Edge Preserving

Material Identification in Presence of Metal for Baggage Screening

2020 ◽  
Vol 2020 (14) ◽  
pp. 294-1-294-8
Author(s):  
Sandamali Devadithya ◽  
David Castañón
Keyword(s):  
Atomic Number ◽  
Effective Atomic Number ◽  
Simulated Data ◽  
Dual Energy ◽  
Basis Functions ◽  
Total Variation Regularization ◽  
Ct Scanner ◽  
Edge Preserving ◽  
Baggage Screening ◽  
Dual Energy Imaging

Dual-energy imaging has emerged as a superior way to recognize materials in X-ray computed tomography. To estimate material properties such as effective atomic number and density, one often generates images in terms of basis functions. This requires decomposition of the dual-energy sinograms into basis sinograms, and subsequently reconstructing the basis images. However, the presence of metal can distort the reconstructed images. In this paper we investigate how photoelectric and Compton basis functions, and synthesized monochromatic basis (SMB) functions behave in the presence of metal and its effect on estimation of effective atomic number and density. Our results indicate that SMB functions, along with edge-preserving total variation regularization, show promise for improved material estimation in the presence of metal. The results are demonstrated using both simulated data as well as data collected from a dualenergy medical CT scanner.

Pre-Processing of Hyperspectral Images Using Nonlinear Filters

2013 ◽  
Vol 11 (1) ◽  
pp. 8-13
Author(s):  
V. Behar ◽  
V. Bogdanova
Keyword(s):  
Signal To Noise Ratio ◽  
Correlation Coefficients ◽  
Hyperspectral Images ◽  
Spectral Correlation ◽  
Edge Preserving ◽  
Improvement Factor ◽  
Filter Output ◽  
Average Improvement ◽  
Processing Procedure

Abstract In this paper the use of a set of nonlinear edge-preserving filters is proposed as a pre-processing stage with the purpose to improve the quality of hyperspectral images before object detection. The capability of each nonlinear filter to improve images, corrupted by spatially and spectrally correlated Gaussian noise, is evaluated in terms of the average Improvement factor in the Peak Signal to Noise Ratio (IPSNR), estimated at the filter output. The simulation results demonstrate that this pre-processing procedure is efficient only in case the spatial and spectral correlation coefficients of noise do not exceed the value of 0.6

New edge preserving enlargement algorithm for images

2013 ◽  
Vol 32 (11) ◽  
pp. 3182-3184
Author(s):  
Ye YUAN ◽  
Zhong-xu TIAN
Keyword(s):  
Edge Preserving

Edge-preserving filter with similarity noise detection for impulse noise reduction

2013 ◽  
Vol 32 (3) ◽  
pp. 739-741
Author(s):  
Xin LIU ◽  
Hong-wei GE ◽  
Bing-chun XU
Keyword(s):  
Noise Reduction ◽  
Impulse Noise ◽  
Noise Detection ◽  
Edge Preserving

Image Fusion Method Based on Multi-scale Directional Fast Guided Filter and Convolutional Sparse Representation

2019 ◽  
Vol 12 (3) ◽  
pp. 263-269
Author(s):  
Liu Xian-Hong ◽  
Chen Zhi-Bin
Keyword(s):  
Image Fusion ◽  
Sparse Representation ◽  
Filter Bank ◽  
Guided Filter ◽  
Fusion Method ◽  
Edge Preserving ◽  
Directional Information ◽  
Multi Scale ◽  
Directional Filter ◽  
Image Fusion Method

Background: A multi-scale multidirectional image fusion method is proposed, which introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving decomposition based on the fast guided filter. Methods: The proposed method has the advantages of preserving edges and extracting directional information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian (NSML) to be the external input is also presented simultaneously. Results: Experimental results have demonstrated the superiority of the proposed method over conventional methods in terms of visual effects and objective evaluations. Conclusion: In this paper, combining fast guided filter and nonsubsampled directional filter bank, a multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method has the features of edge-preserving and extracting directional information.

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