{"title":"基于PSNR和MSE的中值滤波与Gabor滤波对皮肤癌MRI图像的性能分析","authors":"S. Likhitha, R. Baskar","doi":"10.1109/SMART55829.2022.10047499","DOIUrl":null,"url":null,"abstract":"Themain aim of this research is to filter Skin Cancer MRI images based on the image processing technologies using novel median filter algorithm and is compared with Gabor filter algorithm. This research contains two groups, each with a sample size of 20 with Gpower of 80 percent. The performance of the novel median filter is evaluated and the performance measurements such as PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) are compared with the Gabor filter. According to the data obtained by simulating with matlab, the novel median filter's PSNR is 31.64, and its MSE is 9.094, whereas the Gabor filter's PSNR (Peak Signal to Noise Ratio) is 27.02, and its MSE (Mean Square Error) is 11.52. From the statistical analysis, it is observed that the significant value of PSNR (Peak Signal to Noise Ratio) (0.409) and $\\mathbf{p} > 0.05$ and value of MSE (0.010) of the algorithm is $\\mathbf{p} < 0.05$. In this study, it is found that the novel Median filter performs better than the Gabor filter in terms of PSNR and MSE.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance Analysis of Median Filter in Comparison with Gabor Filter for Skin Cancer MRI Images Based on PSNR and MSE\",\"authors\":\"S. Likhitha, R. Baskar\",\"doi\":\"10.1109/SMART55829.2022.10047499\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Themain aim of this research is to filter Skin Cancer MRI images based on the image processing technologies using novel median filter algorithm and is compared with Gabor filter algorithm. This research contains two groups, each with a sample size of 20 with Gpower of 80 percent. The performance of the novel median filter is evaluated and the performance measurements such as PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) are compared with the Gabor filter. According to the data obtained by simulating with matlab, the novel median filter's PSNR is 31.64, and its MSE is 9.094, whereas the Gabor filter's PSNR (Peak Signal to Noise Ratio) is 27.02, and its MSE (Mean Square Error) is 11.52. From the statistical analysis, it is observed that the significant value of PSNR (Peak Signal to Noise Ratio) (0.409) and $\\\\mathbf{p} > 0.05$ and value of MSE (0.010) of the algorithm is $\\\\mathbf{p} < 0.05$. In this study, it is found that the novel Median filter performs better than the Gabor filter in terms of PSNR and MSE.\",\"PeriodicalId\":431639,\"journal\":{\"name\":\"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMART55829.2022.10047499\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMART55829.2022.10047499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本研究的主要目的是利用新的中值滤波算法对基于图像处理技术的皮肤癌MRI图像进行滤波,并与Gabor滤波算法进行比较。这项研究包含两组,每组的样本量为20,Gpower为80%。评估了新型中值滤波器的性能,并将PSNR(峰值信噪比)和MSE(均方误差)等性能指标与Gabor滤波器进行了比较。通过matlab仿真得到的数据表明,新型中值滤波器的PSNR为31.64,MSE为9.094,而Gabor滤波器的PSNR(峰值信噪比)为27.02,MSE(均方误差)为11.52。从统计分析中可以看出,该算法的峰值信噪比PSNR (Peak Signal to Noise Ratio)的显著值为0.409,且$\mathbf{p} > 0.05$, MSE(0.010)的显著值为$\mathbf{p} < 0.05$。本研究发现,在PSNR和MSE方面,新型中值滤波器优于Gabor滤波器。
Performance Analysis of Median Filter in Comparison with Gabor Filter for Skin Cancer MRI Images Based on PSNR and MSE
Themain aim of this research is to filter Skin Cancer MRI images based on the image processing technologies using novel median filter algorithm and is compared with Gabor filter algorithm. This research contains two groups, each with a sample size of 20 with Gpower of 80 percent. The performance of the novel median filter is evaluated and the performance measurements such as PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) are compared with the Gabor filter. According to the data obtained by simulating with matlab, the novel median filter's PSNR is 31.64, and its MSE is 9.094, whereas the Gabor filter's PSNR (Peak Signal to Noise Ratio) is 27.02, and its MSE (Mean Square Error) is 11.52. From the statistical analysis, it is observed that the significant value of PSNR (Peak Signal to Noise Ratio) (0.409) and $\mathbf{p} > 0.05$ and value of MSE (0.010) of the algorithm is $\mathbf{p} < 0.05$. In this study, it is found that the novel Median filter performs better than the Gabor filter in terms of PSNR and MSE.