{"title":"用 WAF 和 WMF 提高平均值和中值滤波器的性能","authors":"","doi":"10.59018/1223309","DOIUrl":null,"url":null,"abstract":"Salt and spice noise is considered one of the most common types of noise that affect grayscale and color digital images, as it affects them negatively, and this negative effect increases with an increase in the noise ratio. Many digital filters are used to mitigate the negative effects of salt and pepper noise, and the most widely used of these filters are the average filter and the median filter. The average and median filters work on processing all pixels in the image, whether these pixels are intact from the noise or infected with it, and accordingly, mitigating this noise, especially if it has a high noise ratio, is ineffective. In this research paper, new window average and window median filters will be proposed to enhance the performance of standard average and median filters. The proposed filter will treat the infected pixels, leaving the clean pixels as they were. For a noisy pixel, a special window will be created and the pixel value will equal the mean (or average) of the cleaned pixels in the window (excluding the noisy pixels). To simplify the window processing an index window will be used, this window will point to the noisy and cleaned pixels in the selected pixel window. Several images with various values of noise ratios will be tested; several windows with different sizes will be examined to get the most suitable window size. The selected window size will be used to filter various noisy images, the obtained results will be compared with average and median filter results to show the improvements provided by the proposed method.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"WAF and WMF to improve the performance of average and median filters\",\"authors\":\"\",\"doi\":\"10.59018/1223309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Salt and spice noise is considered one of the most common types of noise that affect grayscale and color digital images, as it affects them negatively, and this negative effect increases with an increase in the noise ratio. Many digital filters are used to mitigate the negative effects of salt and pepper noise, and the most widely used of these filters are the average filter and the median filter. The average and median filters work on processing all pixels in the image, whether these pixels are intact from the noise or infected with it, and accordingly, mitigating this noise, especially if it has a high noise ratio, is ineffective. In this research paper, new window average and window median filters will be proposed to enhance the performance of standard average and median filters. The proposed filter will treat the infected pixels, leaving the clean pixels as they were. For a noisy pixel, a special window will be created and the pixel value will equal the mean (or average) of the cleaned pixels in the window (excluding the noisy pixels). To simplify the window processing an index window will be used, this window will point to the noisy and cleaned pixels in the selected pixel window. Several images with various values of noise ratios will be tested; several windows with different sizes will be examined to get the most suitable window size. The selected window size will be used to filter various noisy images, the obtained results will be compared with average and median filter results to show the improvements provided by the proposed method.\",\"PeriodicalId\":38652,\"journal\":{\"name\":\"ARPN Journal of Engineering and Applied Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ARPN Journal of Engineering and Applied Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.59018/1223309\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ARPN Journal of Engineering and Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59018/1223309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
WAF and WMF to improve the performance of average and median filters
Salt and spice noise is considered one of the most common types of noise that affect grayscale and color digital images, as it affects them negatively, and this negative effect increases with an increase in the noise ratio. Many digital filters are used to mitigate the negative effects of salt and pepper noise, and the most widely used of these filters are the average filter and the median filter. The average and median filters work on processing all pixels in the image, whether these pixels are intact from the noise or infected with it, and accordingly, mitigating this noise, especially if it has a high noise ratio, is ineffective. In this research paper, new window average and window median filters will be proposed to enhance the performance of standard average and median filters. The proposed filter will treat the infected pixels, leaving the clean pixels as they were. For a noisy pixel, a special window will be created and the pixel value will equal the mean (or average) of the cleaned pixels in the window (excluding the noisy pixels). To simplify the window processing an index window will be used, this window will point to the noisy and cleaned pixels in the selected pixel window. Several images with various values of noise ratios will be tested; several windows with different sizes will be examined to get the most suitable window size. The selected window size will be used to filter various noisy images, the obtained results will be compared with average and median filter results to show the improvements provided by the proposed method.
期刊介绍:
ARPN Journal of Engineering and Applied Sciences (ISSN 1819-6608) is an online peer-reviewed International research journal aiming at promoting and publishing original high quality research in all disciplines of engineering sciences and technology. All research articles submitted to ARPN-JEAS should be original in nature, never previously published in any journal or presented in a conference or undergoing such process across the globe. All the submissions will be peer-reviewed by the panel of experts associated with particular field. Submitted papers should meet the internationally accepted criteria and manuscripts should follow the style of the journal for the purpose of both reviewing and editing. Our mission is -In cooperation with our business partners, lower the world-wide cost of research publishing operations. -Provide an infrastructure that enriches the capacity for research facilitation and communication, among researchers, college and university teachers, students and other related stakeholders. -Reshape the means for dissemination and management of information and knowledge in ways that enhance opportunities for research and learning and improve access to scholarly resources. -Expand access to research publishing to the public. -Ensure high-quality, effective and efficient production and support good research and development activities that meet or exceed the expectations of research community. Scope of Journal of Engineering and Applied Sciences: -Engineering Mechanics -Construction Materials -Surveying -Fluid Mechanics & Hydraulics -Modeling & Simulations -Thermodynamics -Manufacturing Technologies -Refrigeration & Air-conditioning -Metallurgy -Automatic Control Systems -Electronic Communication Systems -Agricultural Machinery & Equipment -Mining & Minerals -Mechatronics -Applied Sciences -Public Health Engineering -Chemical Engineering -Hydrology -Tube Wells & Pumps -Structures