{"title":"使用APSO进行图像压缩","authors":"M. Saini, Rajiv Kapoor","doi":"10.1504/IJAISC.2012.048180","DOIUrl":null,"url":null,"abstract":"A novel framework has been proposed by integrating FIM with APSO to get their mutual benefits for achieving near optimum codebook for carrying an image compression. Proposed scheme uses adaptive strategies which have two main features that give APSO an upper hand over the PSO. This FAPSOVQ strategy is compared with FPSOVQ algorithm to show its efficiency in terms of preventing the global best particle from getting stuck in local optima as in the PSO. Peak-signal-to-noise ratio is taking as a parameter to show the efficiency of proposed scheme.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image compression using APSO\",\"authors\":\"M. Saini, Rajiv Kapoor\",\"doi\":\"10.1504/IJAISC.2012.048180\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel framework has been proposed by integrating FIM with APSO to get their mutual benefits for achieving near optimum codebook for carrying an image compression. Proposed scheme uses adaptive strategies which have two main features that give APSO an upper hand over the PSO. This FAPSOVQ strategy is compared with FPSOVQ algorithm to show its efficiency in terms of preventing the global best particle from getting stuck in local optima as in the PSO. Peak-signal-to-noise ratio is taking as a parameter to show the efficiency of proposed scheme.\",\"PeriodicalId\":364571,\"journal\":{\"name\":\"Int. J. Artif. Intell. Soft Comput.\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Artif. Intell. Soft Comput.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJAISC.2012.048180\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Artif. Intell. Soft Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJAISC.2012.048180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel framework has been proposed by integrating FIM with APSO to get their mutual benefits for achieving near optimum codebook for carrying an image compression. Proposed scheme uses adaptive strategies which have two main features that give APSO an upper hand over the PSO. This FAPSOVQ strategy is compared with FPSOVQ algorithm to show its efficiency in terms of preventing the global best particle from getting stuck in local optima as in the PSO. Peak-signal-to-noise ratio is taking as a parameter to show the efficiency of proposed scheme.
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