Enhancing the Performance of One Dimensional Median Filter

2019 ◽  
Vol 118 (7) ◽  
pp. 73-76
Author(s):  
Sharanabasappa ◽  
P Ravibabu
Keyword(s):  
Impulse Noise ◽  
Rank Order ◽  
Median Filter ◽  
Filter Method ◽  
Salt And Pepper Noise ◽  
Edge Preservation ◽  
Word Level ◽  
Look Ahead ◽  
Filter Architecture ◽  
Salt And Pepper

Nowadays, during the process of Image acquisition and transmission, image information data can be corrupted by impulse noise. That noise is classified as salt and pepper noise and random impulse noise depending on the noise values. A median filter is widely used digital nonlinear filter  in edge preservation, removing of impulse noise and smoothing of signals. Median filter is the widely used to remove salt and pepper noise than rank order filter, morphological filter, and unsharp masking filter. The median filter replaces a sample with the middle value among all the samples present inside the sample window. A median filter will be of two types depending on the number of samples processed at the same cycle i.e, bit level architecture and word level architecture.. In this paper, Carry Look-ahead Adder median filter method will be introduced to improve the hardware resources used in median filter architecture for 5 window and 9 window for 8 bit and 16 bit median filter architecture.

scholarly journals High Density Video Impulse Noise Reduction Scheme Based on Spatially Growing Modified Median Filter

2020 ◽  
Vol 9 (4) ◽  
pp. 1193-1200
Keyword(s):  
Impulse Noise ◽  
Median Filter ◽  
Sliding Window ◽  
High Density ◽  
Filter Method ◽  
Salt And Pepper Noise ◽  
Reduction Scheme ◽  
Digital Videos ◽  
Window Method ◽  
Salt And Pepper

In this paper a spatially growing modified median filter method has been proposed for the restoration of digital videos which are adulterated by the saturated impulse noise i.e., salt-and pepper noise. The proposed denoising process executes filtering action only to the corrupted pixels in the video keeping noise free pixels in the video unharmed. The current study has used a spatially growing window method for the exclusion of high density noise present in the digital videos. It has used sliding window of increasing dimension centered at any pixel and sequentially swapped the noise corrupted pixels by the median value of the trimmed window. However, if the whole pixels in the window are noise corrupted then the dimension of sliding window is enlarged in order to obtained the noise free pixels for median computing. At the same time, this process has been found to be capable to removing the high density salt and pepper noise and also well preserved the fine details of the videos. Experimentally, it has been found that the proposed method generate enhanced PSNR and SSIM results

scholarly journals Elimination of Impulse Noise using Mean Median filter for Image Enhancement

2019 ◽  
pp. 278-288
Author(s):  
Trupti Arun Jangale ◽  
Raj Kumar Paul
Keyword(s):  
Impulse Noise ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Human Perception ◽  
Experimental Result ◽  
Second Step ◽  
Salt And Pepper Noise ◽  
Noisy Pixel ◽  
A New Technique ◽  
Salt And Pepper

In this method, we've got introduced a new technique for the improvement of gray scale images, when images are corrupted by salt and pepper noise that's additionally referred to as an impulse noise. Our suggested phenomena show a better output for Medium density impulse noise as compare to the opposite renowned filters like standard Median Filter (SMF), a decision based mostly Median Filter (DBMF) and modified decision based Median Filter (MDBMF), Nonlinear filter (NLF) and so on. Our projected technique worked on two steps, within the beginning is that the detection of noisy pixels and within the second step is that the removal of noisy pixels. For detection of noisy constituent apply condition pixels values lies in between 0 to 255 it noisy it's noisy free pixels. In our second step that's the removal of noisy pixel recommended technique that's replaces the noisy pixel by alpha trimmed mean median value. Different grayscale pictures are tested via proposed technique. The experimental result shows higher Peak Signal to Noise ratio (PSNR) values and with higher visual and human perception.

scholarly journals A NEW DENOISING APPROACH FOR THE REMOVAL OF IMPULSE NOISE FROM COLOR IMAGES AND VIDEO SEQUENCES

2012 ◽  
Vol 31 (3) ◽  
pp. 185 ◽  
Author(s):  
Rajamani Arumugham ◽  
Krishnaveni Vellingiri ◽  
Wassim Ferose Habeebrakuman ◽  
Kalaikamal Mohan
Keyword(s):  
Impulse Noise ◽  
Visual Quality ◽  
Color Images ◽  
Video Sequences ◽  
Computational Time ◽  
Sorting Algorithm ◽  
Salt And Pepper Noise ◽  
Video Signals ◽  
Salt And Pepper

In this paper a novel Lone Diagonal Sorting (LDS) algorithm for denoising color images and videos co-rrupted with salt and pepper noise is proposed. The proposed lone diagonal sorting algorithm uses diagonal sorting alone for denoising of impulse noise. The algorithm has been implemented and tested for various color images and video signals and appreciable performance in terms of PSNR, MSE and SSIM is obtained. Our algorithm has been compared with other standard algorithms. A drastic improvement in the computational time has been achieved without compromising much on the visual quality after reconstruction.

scholarly journals An efficient Scheme to Remove Low Density Impulse Noise From A Digital Image

2016 ◽  
Vol 15 (12) ◽  
pp. 7284-7289
Author(s):  
Dr. Jihad N. Abdeljalil Al-Balqa
Keyword(s):  
Noise Reduction ◽  
Impulse Noise ◽  
Low Density ◽  
Salt And Pepper Noise ◽  
Reduction Scheme ◽  
Iir Filter ◽  
Noise Impulse ◽  
Efficient Scheme ◽  
Adaptive Noise ◽  
Salt And Pepper

An improved adaptive noise reduction scheme for images that are highly corrupted by Salt-and-Pepper noise(impulse noise), is proposed in this paper which efficiently removes the salt and pepper noise while preserving the details. The proposed scheme efficiently identifies and reduces salt and pepper noise. The algorithm utilizes an IIR filter with controlled parameters to get better image quality than the existing methods of noise removing. A comparative analysis between the proposed scheme and other techniques of noise reduction or removing is presented in order to show the advantages of the proposed scheme in removing the noisy pixels and producing a better PSNR.

Different applied median filter in salt and pepper noise

2018 ◽  
Vol 70 ◽  
pp. 789-798 ◽  
Author(s):  
Uğur Erkan ◽  
Levent Gökrem ◽  
Serdar Enginoğlu
Keyword(s):  
Median Filter ◽  
Salt And Pepper Noise ◽  
Salt And Pepper

Reduction of Noise in Restoration of Images Using Mean and Median Filtering Techniques

2021 ◽  
Vol 9 (9) ◽  
pp. 301-313
Author(s):  
Vimal Chauhan
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Median Filter ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Digital Cameras ◽  
Salt And Pepper Noise ◽  
Satellite Imaging ◽  
Mean Filter ◽  
Salt And Pepper

Abstract: The purpose of this paper is to present a study of digital technology approaches to image restoration. This process of image restoration is crucial in many areas such as satellite imaging, astronomical image & medical imaging where degraded images need to be repaired Personal images captured by various digital cameras can easily be manipulated by a variety of dedicated image processing algorithms [2]. Image restoration can be described as an important part of image processing technique. Image restoration has proved to be an active field of research in the present days. The basic objective is to enhance the quality of an image by removing defects and make it look pleasing [2]. In this paper, an image restoration algorithm based on the mean and median calculation of a pixel has been implemented. We focused on a certain iterative process to carry out restoration. The algorithm has been tested on different images with different percentage of salt and pepper noise. The improved PSNR and MSE values has been obtained. Keywords: De-Noising, Image Filtering, Mean Filter & Median Filter, Salt and Pepper Noise, Denoising Techniques, Image Restoration.

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