{"title":"最佳DCT量化","authors":"D. Monro, B. Sherlock","doi":"10.1109/DCC.1993.253131","DOIUrl":null,"url":null,"abstract":"The paper offers a solution to the problem of determining good quantization tables for use with the discrete cosine transform. Using the methods proposed, the designer of a system can choose a selection of test images and a coefficient weighting scenario, from which a quantization table can be produced, optimized for the choices made. The method is based on simulated annealing searches which the space of quantization tables to minimize some chosen measure.<<ETX>>","PeriodicalId":315077,"journal":{"name":"[Proceedings] DCC `93: Data Compression Conference","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Optimum DCT quantization\",\"authors\":\"D. Monro, B. Sherlock\",\"doi\":\"10.1109/DCC.1993.253131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper offers a solution to the problem of determining good quantization tables for use with the discrete cosine transform. Using the methods proposed, the designer of a system can choose a selection of test images and a coefficient weighting scenario, from which a quantization table can be produced, optimized for the choices made. The method is based on simulated annealing searches which the space of quantization tables to minimize some chosen measure.<<ETX>>\",\"PeriodicalId\":315077,\"journal\":{\"name\":\"[Proceedings] DCC `93: Data Compression Conference\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] DCC `93: Data Compression Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.1993.253131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] DCC `93: Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1993.253131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper offers a solution to the problem of determining good quantization tables for use with the discrete cosine transform. Using the methods proposed, the designer of a system can choose a selection of test images and a coefficient weighting scenario, from which a quantization table can be produced, optimized for the choices made. The method is based on simulated annealing searches which the space of quantization tables to minimize some chosen measure.<>