Sliding Window Based Blind Image Inpainting To Remove Impulse Noise from Image

2016 ◽  
Vol 4 (10) ◽  
pp. 17120-17127
Author(s):  
Madhuri Derle ◽  
Gorakshanath Gagare
Keyword(s):  
Impulse Noise ◽  
Image Inpainting ◽  
Sliding Window ◽  
Blind Image

scholarly journals Low Dimensional Manifold Regularization Based Blind Image Inpainting and Non-Uniform Impulse Noise Recovery

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 200551-200560
Author(s):  
Mei Gao ◽  
Baosheng Kang ◽  
Xiangchu Feng ◽  
Lixia Cao ◽  
Wenjuan Zhang
Keyword(s):  
Impulse Noise ◽  
Image Inpainting ◽  
Manifold Regularization ◽  
Dimensional Manifold ◽  
Low Dimensional ◽  
Low Dimensional Manifold ◽  
Blind Image

scholarly journals Execution of Median Filter Built on FPGA for Trimming Noise Meeting the Real Time Requirements

2019 ◽  
Vol 8 (4) ◽  
pp. 7855-7858
Keyword(s):  
Real Time ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Median Filter ◽  
Sliding Window ◽  
Spatial Filter ◽  
Effective Technique ◽  
The Real ◽  
Time Requirements ◽  
Suppression Process

As images plays a vital in all aspects, there is a need to met the real time requirements in processing the image. Major challenges raised in processing the image is noise. The utmost typical difficult is effective denoising creation as well as quick functioning in the processing of digital image noise suppression process for the need of real time consequences to afford image with high quality this project was introduced. Generally filters plays a major role to remove the impulse noise in acquired images. The filter named sliding window spatial filter which is familiar as median filter is effective technique to eradicate impulse noise from the devoleped image. But in real time, it is very difficult to execute. To overcome this, FPGA methodology is introduced to fulfills the support besides the optimization of major constraints like area, speed, power. In addition to this, it assures technical sustenance of eradicating noise in image as per requirements in real time. Regarding the design and structure appearances in FPGA, Xilinx software is used for simulation and code has been written in Verilog language.

scholarly journals A Hybrid Filter with Impulse Detection for Removal of Random Valued Impulse Noise from Colour Videos

2012 ◽  
pp. 62-67
Author(s):  
S. Anusha ◽  
Hemanth Kumar ◽  
S.K.P. Chaitanya
Keyword(s):  
Impulse Noise ◽  
Three Dimensional ◽  
Sliding Window ◽  
Temporal Information ◽  
Superior Performance ◽  
Video Sequences ◽  
Median Filtering ◽  
Hybrid Filter ◽  
Directional Filtering ◽  
Simulation Results

This paper presents a three dimensional hybrid filter to remove random valued impulse noise from colour video sequences. The switching median technique is utilized to protect noise free isolated pixels from filtering so as to avoid blurring of frames. The restoration of noisy pixels is done by brightness information obtained from median filtering and chromaticity information is obtained from vector directional filtering. This hybrid filter is applied in three dimensional sliding window where spatial as well as temporal information about neighbourhood is available for restoration of frame under consideration. Only noise free pixels of three dimensional sliding window are used for restoration of frame under consideration. Simulation results show that the proposed three dimensional hybrid filter yields superior performance in comparison to other filtering methods

scholarly journals An Intelligent Forensics Approach for Detecting Patch-Based Image Inpainting

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xinyi Wang ◽  
He Wang ◽  
Shaozhang Niu
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Time Complexity ◽  
Image Inpainting ◽  
Image Forensics ◽  
Detection Accuracy ◽  
Semantic Level ◽  
Wide Range ◽  
Blind Image ◽  
Deep Learning Model

Image inpainting algorithms have a wide range of applications, which can be used for object removal in digital images. With the development of semantic level image inpainting technology, this brings great challenges to blind image forensics. In this case, many conventional methods have been proposed which have disadvantages such as high time complexity and low robustness to postprocessing operations. Therefore, this paper proposes a mask regional convolutional neural network (Mask R-CNN) approach for patch-based inpainting detection. According to the current research, many deep learning methods have shown the capacity for segmentation tasks when labeled datasets are available, so we apply a deep neural network to the domain of inpainting forensics. This deep learning model can distinguish and obtain different features between the inpainted and noninpainted regions. To reduce the missed detection areas and improve detection accuracy, we also adjust the sizes of the anchor scales due to the inpainting images and replace the original nonmaximum suppression single threshold with an improved nonmaximum suppression (NMS). The experimental results demonstrate this intelligent method has better detection performance over recent approaches of image inpainting forensics.

scholarly journals Wavelet frame based blind image inpainting

2012 ◽  
Vol 32 (2) ◽  
pp. 268-279 ◽  
Author(s):  
Bin Dong ◽  
Hui Ji ◽  
Jia Li ◽  
Zuowei Shen ◽  
Yuhong Xu
Keyword(s):  
Image Inpainting ◽  
Wavelet Frame ◽  
Blind Image
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