Image denoising method used in earthquake ruin scene based on multi-scale mathematical morphology

2012 ◽  
Vol 10 (s2) ◽  
pp. S21002-321004 ◽  
Author(s):  
Yanxing Song Yanxing Song ◽  
Shucong Liu Shucong Liu ◽  
Jingsong Yang Jingsong Yang
Keyword(s):  
Image Denoising ◽  
Mathematical Morphology ◽  
Denoising Method ◽  
Multi Scale

scholarly journals A New Image Denoising Method with Gan Models

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Xueji Huang
Keyword(s):  
Image Denoising ◽  
Image Features ◽  
Denoising Method ◽  
Residual Structure ◽  
Multi Scale ◽  
Residual Noise ◽  
Theoretical System ◽  
Feature Filtering ◽  
Low Dimensional ◽  
Denoised Image

In order to obtain clear images and solve the problems of low image quality caused by noise disturbance, a lot of researches have been done on image denoising techniques. In the theoretical system of algorithms studied so far, many algorithms can effectively remove noise in low-dimensional images, but at the same time, the results are slightly inferior when processing high-dimensional images. This paper proposes a q-GAN, which uses multi-scale in generating networks. The convolution kernel extracts image features and transforms the denoising problem into the feature domain. In the feature domain, a residual structure is used to denoise, and the noise distribution is removed from the feature distribution. There are residual noise features in the obtained denoising features, which are removed by subsequent feature filtering of the network structure, and finally a denoised image is generated by fusing the noiseless features.

scholarly journals An Adaptive Weighted Image Denoising Method Based on Morphology

2021 ◽  
Vol 15 ◽  
pp. 271-279
Author(s):  
Jinjuan Wang ◽  
Shan Duan ◽  
Qun Zhou
Keyword(s):  
Image Processing ◽  
Image Denoising ◽  
Mathematical Morphology ◽  
Edge Preservation ◽  
Denoising Method ◽  
Edge Information ◽  
Processing Step ◽  
Blurred Image ◽  
Image Edge ◽  
Cascaded Filter

In its generation, transmission and record, image signal is often interfered by various noises, which have severally affected the visual effects of images; therefore, it is a very important pre-processing step to take proper approaches to reduce noises. Conventional denoising methods have also blurred image edge information while removing noises, which can be overcome by the method based on mathematical morphology. While eliminating different noises from images, it can not only keep clear object edges, but also preserve as many image details as possible and it also has excellent capacities in noise resistance and edge preservation. With image denoising and mathematical morphology as the research subject, this paper analyzes the generation and characteristics of common image noises, studies the basic theories of mathematical morphology and its applications in image processing, discusses the method to select structural elements in mathematical morphology and proposes a filtering algorithm which combines image denoising and mathematical morphology. This method conducts morphological filtering and denoising on noised image with filter cascade and its performance is verified with stimulation testing. The experiment results prove that the approach to build the morphological filter into cascaded filter through series and parallel connection can to a certain extent, affect the effect of common filter while being applied to different image processing.

An image Denoising Method Based On Multi Resulation Bilateral Filter

2018 ◽  
Vol 6 (12) ◽  
pp. 448-452
Author(s):  
Md Shaiful Islam Babu ◽  
Kh Shaikh Ahmed ◽  
Md Samrat Ali Abu Kawser ◽  
Ajkia Zaman Juthi
Keyword(s):  
Image Denoising ◽  
Bilateral Filter ◽  
Denoising Method

Sonar image denoising method based on NSCT circle sample

2009 ◽  
Vol 29 (1) ◽  
pp. 68-70
Author(s):  
Chun-rui TANG ◽  
Dan-dan LIU
Keyword(s):  
Image Denoising ◽  
Denoising Method ◽  
Sonar Image

Improved anisotropic diffusion ultrasound image denoising method based on logarithmic compression

2013 ◽  
Vol 32 (11) ◽  
pp. 3218-3220
Author(s):  
Jin YANG ◽  
Zhi-qin LIU ◽  
Yao-bin WANG ◽  
Xiao-ming GAO
Keyword(s):  
Image Denoising ◽  
Anisotropic Diffusion ◽  
Ultrasound Image ◽  
Denoising Method
Sign in / Sign up

Export Citation Format

Share Document