scholarly journals CONSTANT TIME SCANNING AND BETTER EDGE PRESERVATION FOR BETTER PERFORMING AND QUALITY OF MEDIAN FILTER

Author(s):  
RITWIK SHARMA ◽  
SHUBHAM HARNAL

The median filter is an important filter in many image processing algorithms and especially in removal of salt and pepper noise. Traditional median filters either focus on improving the performance or the quality of the median filtering. Generally, the methods which optimize performance do so at the cost of quality and vice-versa. In this paper a novel approach to median filtering is presented providing both better performance and quality without sacrificing either. The analysis is presented with respect to image processing and the results obtained are presented in tabular form.

Digital Image processing is basically a computer-algorithm which is used to enhance the quality of image to understand the feature of image and exact the meaningful features information from image. Image processing has wider range of algorithms to be applied to the input image and can escape the difficulty as the signal distortion and add noise in input image at the time of processing of images. Noises affect the image visualization and degraded the image quality, sometimes chaotic variation in value of pixel intensity, lighting effect or because of poor contrast, image can’t be used directly because many time interest feature information not received as output that’s one reason image processing is significant for removal of noise from images, so noise removal is becomes trending field in image processing. Median filter method is one of most popular method to eradicate the effect of noise from image and it enhances the image quality to take meaningful feature easily from image. In this paper removing of noise using median filter to enhance the image quality is discussed, also the importance and applications of enhancement technique are covered. Parameter PSNR and MSE is also used to analysis the image quality along with the visualization of image. Simulation results show that Median filter gives good outcome for salt & pepper noise as compare to other filtering method. MATLAB software is used as simulation tool.


Author(s):  
Vorapoj Patanavijit ◽  
Kornkamol Thakulsukanant

<p>In the past two decades, the SPN (salt and pepper noise) suppressing method is worldwide interested researches on computer vision and image processing hence many SPN suppressing methods have been proposed. In general, the primary goal of SPN removal method is the suppressing of SPN in digital images thereby one of the recent effective and powerful SPN suppressing methods is a new switching-based median filtering (NSMF), which is innovated for suppressing high density SPN. Consequently, this paper thoroughly examines its efficiency and constrain of a new switching-based median filtering when this filter is used for contaminated image, which is synthesized by SPN and RVIN (random-value impulsive noise). In these simulations, six well-known images (Lena, Mobile, Pepper, Pentagon, Girl, Resolution) with two impulsive noise classes (SPN and RVIN) are used for measuring the its efficiency and constrain. An evaluation of the efficiency is conducted with many previous methods in forms of subjective and objective indicators.</p>


2019 ◽  
Vol 118 (7) ◽  
pp. 73-76
Author(s):  
Sharanabasappa ◽  
P Ravibabu

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.


2020 ◽  
Vol 7 (3) ◽  
pp. 432
Author(s):  
Windi Astuti

Various types of image processing that can be done by computers, such as improving image quality is one of the fields that is quite popular until now. Improving the quality of an image is necessary so that someone can observe the image clearly and in detail without any disturbance. An image can experience major disturbances or errors in an image such as the image of the screenshot is used as a sample. The results of the image from the screenshot have the smallest sharpness and smoothness of the image, so to get a better image is usually done enlargement of the image. After the screenshot results are obtained then, the next process is cropping the image and the image looks like there are disturbances such as visible blur and cracked. To get an enlarged image (Zooming image) by adding new pixels or points. This is done by the super resolution method, super resolution has three stages of completion, first Registration, Interpolation, and Reconstruction. For magnification done by linear interpolation and reconstruction using a median filter for image refinement. This method is expected to be able to solve the problem of improving image quality in image enlargement applications. This study discusses that the process carried out to implement image enlargement based on the super resolution method is then built by using R2013a matlab as an editor to edit programs


Author(s):  
Vimal Chauhan

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.


2014 ◽  
Vol 912-914 ◽  
pp. 1509-1512
Author(s):  
Kai Jun Chen

Proposed on the basis of nondestructive testing technology, such as ultrasonic testing and X-ray detecting, image processing of hull welding based on MATLAB is a simple detecting method to detect the quality of welding. By image processing, physical dimensions, such as circumferences and shapes, as well as the intensity and texture features of welds can be concluded. Then, through numerical analysis, quality problems, including porosities, slags, undercuts, overlaps, welding defects and others, if exist, can be determined. This method decreases the cost and reduces the harm to people’s health. Experimental results showed that the detecting system can calculate and determine the major features of the welds effectively and accurately, and possesses good practical value.


1985 ◽  
Vol 24 (04) ◽  
pp. 164-168 ◽  
Author(s):  
P. Mitraszewski ◽  
P. Penczek ◽  
W. Grochulski

SummaryStatistical and deterministic properties of median filters are briefly discussed and their inherent advantages as a prospective tool in scintigraphic data processing are pointed out. The ability of median filters of suppressing impulse noise while the edge-like features of an image are preserved, is demonstrated on phantom data. The residual high-frequency noise remaining after median filtering can be subsequently reduced by standard smoothing procedures. A simple algorithm, made up of the superposition of a median and an averaging filter, is presented and shown to be a promising candidate in the quest for fast and easy-to-implement processing routine.


Author(s):  
Hatim Zaini ◽  
Ziad Alqadi

Colored digital images are affected by salt and pepper noise, affecting their clarity, contents and properties. The negative effect on the image increases with the increase in the noise level. Filters based on average and median filters are not able to remove SAPN with high noise ratios, and accordingly, blurred images are obtained that cannot be dealt with in various image processing operations. In this paper research a modification will be add to median and average filters making them capable of reducing the noise even it has a high noise ratio, the modified average and median filters will be implanted and some comparisons with other popular filters will be made to show the enhancement of the modified filters.


This paper discusses about various methods involved in detection of avian pox in the birds using images. Digital images are corrupted while sending and receiving the images because of noisy sensors which degrade the quality of image. Pre-processing becomes an initial and crucial step in image processing to remove the noise and maintain fine details and texture of the image. Pre-processed images can be used for further work. Mean, Median, Weiner, Mean Maximum, Mean Minimum filters are used and performance tests are made using Signal Noise Ratio. Based on the performance test, removal of impulse noise is well done by Median filter and produces the best result when compared to other filters. K-Means clustering and SVM are used for identification of the disease.


Sign in / Sign up

Export Citation Format

Share Document