An Efficient Median Filter (EMF) algorithm for removal or enhancement of gray scale images are highly corrupted impulse noise is proposed in this paper. Noise in image are represent the pixel value 0’s and 255’s are ensures that black and white dot in image. In proposed algorithm take an image and select 3x3 size window and target or center pixel value check if its value is 0’s or 255’s then image is corrupted otherwise noise free image. If image is noisy and target pixels neighboring pixel value is between 0’s and 255’s then we replace pixel value with the median value and if target pixels neighboring pixel value is 0’s or 255’s then we replace pixel value with the mean value. Else increased the window size and again repeat this process until image is denoised. The proposed filter algorithm shows better simulation result as compare the existing algorithms. The simulation result shows better and efficient performance of PSNR and MSE and computation time.

/pdf/removal-of-high-density-impulse-noise-using-efficient-median-2dpanpbzau.pdf

Removal of High Density Impulse Noise using Efficient Median Filter for Digital Image

The compositing of videos is considered one of the most important steps on the post-production process. The compositing process combines several videos that may be recorded at different times or locations into a final one. Computer generated footages and visual effects are combined with real footages using video compositing techniques. High reality shots of many movies were introduced to the audience who cannot discover that those shots are not real. Many techniques are used for achieving high realistic results of video compositing. In this paper, a survey of video compositing techniques, a comparison among compositing techniques, and many examples for video compositing using existing techniques are presented.

/pdf/what-is-the-truth-a-survey-of-video-compositing-techniques-4hdzdb9hx0.pdf

What is the Truth: A Survey of Video Compositing Techniques

Impulse noise is the prime factor which reduces the quality of the digital image and it erases the important details of the images. De-noising is an indispensable task to restore the image features from the corrupted lowquality images and improve the perceptual quality of images. Several techniques are used for image quality enhancement and image restoration. In this work, an image de-noising scheme is developed to detect and correct the impulse noise from the image by using fuzzy entropy. The proposed algorithm is designed in two phases, such as noise detection phase, and correction phase. In the noise detection phase, the fuzzy entropy of pixels in a window of interest (WoI) is computed to detect whether the pixel is noisy or not. The Fuzzy entropy of pixel greater than specified alpha cut value will be considered as noise pixel and submitted to correction phase. In the correction phase noise pixel value is replaced with a fuzzy weighted mean of the uncorrupted pixels in the WoI. The proposed Fuzzy entropy based impulse noise detection and correction method are implemented using MATLAB. The experimentation has been carried out on different standard images and the analysis is performed by comparing the performance of the proposed scheme with that of the existing methods such as DBA, MDBUTMF, AMF, NAFSM, BDND, and CM , using PSNR, SSIM, and NAE as metric parameters. The proposed method will give good results compared to state of the art methods in image restoration.

/pdf/fuzzy-entropy-based-impulse-noise-detection-and-correction-3dw77g1jf4.pdf

Fuzzy Entropy based Impulse Noise Detection and Correction Method for Digital Images

Corrupted digital images are recovered by using median filters. The most frequently occur noise is salt and pepper type impulse noise. As the noise increases it becomes hard to recover the noisy digital image. Different median filters have been suggested to recover it. Size of the window taken in the filter is also the important factor at different level of noises. The performance of standard median filter (SMF), centered weighted median (CWM) filter and directional weighted median (DWM) filter is tested on gray scale images corrupted with variable percentage of salt & pepper noise impulse noise. It is also tested for different window sizes of filters. Some filter performs better at low noise while some performs better at high noise. At higher level of noise, large window size in the filters works better than small window size. These comparisons are very helpful in deciding the best filter at different level of noise.

Analysis of Non Linear Filters with Various Density of Impulse Noise for Different Window Size

Images are used to show proof or demonstration valuable information and it plays an vital role in research and technology. The main disadvantages of digital images are presence of blare and deprivation during their attainment or transmission. This paper presents a novel method of image restoration using Intensity Value Sharing Algorithm (IVSA). 

		In this paper, the comparison of known image demising techniques is discussed and a new method, the sharing difference between pixels intensity based approach is proposed and used for the removal of impulse noise. Restoration methods can primarily preserve image details while suppressing impulsive noise. The principle of these methods is introduced and analyzed with different simulation results using MATLAB. Most of the prior known techniques are applicable for the demising of images degraded with less noise density. Here a new algorithm is presented which is better than the existing algorithms. Performances of the techniques are compared with the parameters MSE, PSNR and SSIM.

https://www.jetir.org/papers/JETIRC006400.pdf

A Fusion Approach to Eliminate Speckle Noise from Digital Images Using IVSA Algorithm

This paper presents an efficient and simple adaptive method for high density salt-and-pepper noise removal. A noise detector is utilized to check whether the selected pixel is noisy or noise free. Noise pixels will then be subjected to the second stage of the filtering action, while the noise free pixels are left unaltered. Since not every pixel is filtered, undue distortion can be avoided. The noise free pixels are only considered in the filter operation for finding the value of the processed pixel. The window size is selected as 3 X 3 in the first step. If all pixels within the window are considered to be noise, then change the selected window size to 5 X 5. If all the pixels within the selected 5 x 5 window are considered to be noise, then the processing pixel is replaced by the previous resultant pixel. This technique requires one nonnoise original image as training image. The key point of the filter operation is based on the solution of the equations system X=A -1 B in the nonnoise original image. An algorithm to extract the data from the nonnoisy image and form it in the linear equation system is presented. Comparison of the given filter with other existing filters is provided in this paper. The results demonstrate that the proposed technique can obtain better performances than other existing denoising techniques. The proposed method works well for high-density salt & pepper noise even up to a noise density of 97%.

/pdf/an-efficient-and-simple-switching-filter-for-removal-of-high-54if9r53n3.pdf

An Efficient and Simple Switching Filter for Removal of High Density Salt-and-Pepper Noise

In this paper, an efficient filter method for salt-and-pepper noise removal is proposed This method is developed by using cubic B-spline A noise detector is employed to check whether the selected pixel is noisy or noise free In this method, noise free pixels are left unaltered Since not every pixel is filtered, undue distortion can be avoided Noise pixels are subjected to the filtering operation to reconstruct the intensity values of the noisy pixels The noise free pixels are only considered in the filter operation The cubic B- spline is used as a fitting function to generate additional values within the noise free pixels The noisy pixel is replaced by the mean value of these pixel values The window size is selected as 3 X 3 in the first step If all pixels within the window are considered to be noise, then change the selected window size to 5 X 5 If all the pixels within this window are considered to be noise, then the noisy pixel is replaced by the previous resultant pixel Comparison of the given filter with other existing filters is provided in this paper The results demonstrate that the proposed technique can obtain better performances than other existing denoising techniques As a result of this, the proposed method removes the noise effectively even at noise level as high as 97%

/pdf/an-efficient-switching-filter-based-on-cubic-b-spline-for-pvsc290m78.pdf

Hani M. Ibrahem

Papers

An Efficient and Simple Switching Filter for Removal of High Density Salt-and-Pepper Noise

An Efficient Switching Filter Based on Cubic B-Spline for Removal of Salt-and-Pepper Noise