{"title":"基于灰狼优化和青蛙跳跃算法的图像融合算法","authors":"Afrah U Mosa, Waleed A Mahmoud Al-Jawher","doi":"10.11113/ijic.v13n1-2.412","DOIUrl":null,"url":null,"abstract":"Data fusion is a “formal framework in which are expressed the means and tools for the alliance of data originating from different sources.” It aims at obtaining information of greater quality; the exact definition of 'greater quality will depend upon the application. It is a famous technique in digital image processing and is very important in medical image representation for clinical diagnosis. Previously many researchers used many meta-heuristic optimization techniques in image fusion, but the problem of local optimization restricted their searching flow to find optimum search results. In this paper, the Grey Wolf Optimization (GWO) algorithm with the help of the Shuffled Frog Leaping Algorithm (SFLA) has been proposed. That helps to find the object and allows doctors to take some action. The optimization algorithm is examined with a demonstrated example in order to simplify its steps. The result of the proposed algorithm is compared with other optimization algorithms. The proposed method's performance was always the best among them.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":"2677 1","pages":"0"},"PeriodicalIF":1.3000,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Fusion Algorithm using Grey Wolf optimization with Shuffled Frog Leaping Algorithm\",\"authors\":\"Afrah U Mosa, Waleed A Mahmoud Al-Jawher\",\"doi\":\"10.11113/ijic.v13n1-2.412\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data fusion is a “formal framework in which are expressed the means and tools for the alliance of data originating from different sources.” It aims at obtaining information of greater quality; the exact definition of 'greater quality will depend upon the application. It is a famous technique in digital image processing and is very important in medical image representation for clinical diagnosis. Previously many researchers used many meta-heuristic optimization techniques in image fusion, but the problem of local optimization restricted their searching flow to find optimum search results. In this paper, the Grey Wolf Optimization (GWO) algorithm with the help of the Shuffled Frog Leaping Algorithm (SFLA) has been proposed. That helps to find the object and allows doctors to take some action. The optimization algorithm is examined with a demonstrated example in order to simplify its steps. The result of the proposed algorithm is compared with other optimization algorithms. The proposed method's performance was always the best among them.\",\"PeriodicalId\":50314,\"journal\":{\"name\":\"International Journal of Innovative Computing Information and Control\",\"volume\":\"2677 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovative Computing Information and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11113/ijic.v13n1-2.412\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovative Computing Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11113/ijic.v13n1-2.412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Image Fusion Algorithm using Grey Wolf optimization with Shuffled Frog Leaping Algorithm
Data fusion is a “formal framework in which are expressed the means and tools for the alliance of data originating from different sources.” It aims at obtaining information of greater quality; the exact definition of 'greater quality will depend upon the application. It is a famous technique in digital image processing and is very important in medical image representation for clinical diagnosis. Previously many researchers used many meta-heuristic optimization techniques in image fusion, but the problem of local optimization restricted their searching flow to find optimum search results. In this paper, the Grey Wolf Optimization (GWO) algorithm with the help of the Shuffled Frog Leaping Algorithm (SFLA) has been proposed. That helps to find the object and allows doctors to take some action. The optimization algorithm is examined with a demonstrated example in order to simplify its steps. The result of the proposed algorithm is compared with other optimization algorithms. The proposed method's performance was always the best among them.
期刊介绍:
The primary aim of the International Journal of Innovative Computing, Information and Control (IJICIC) is to publish high-quality papers of new developments and trends, novel techniques and approaches, innovative methodologies and technologies on the theory and applications of intelligent systems, information and control. The IJICIC is a peer-reviewed English language journal and is published bimonthly