{"title":"基于gpu的调色板映射技术","authors":"Matthias Trapp, S. Pasewaldt, J. Döllner","doi":"10.24132/csrn.2019.2902.2.10","DOIUrl":null,"url":null,"abstract":"This paper presents a GPU-based approach to color quantization by mapping of arbitrary color palettes to input images using Look-Up Tables (LUTs). For it, different types of LUTs, their GPU-based generation, representation, and respective mapping implementations are described and their run-time performance is evaluated and compared.","PeriodicalId":322214,"journal":{"name":"Computer Science Research Notes","volume":"14 12","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Techniques for GPU-based Color Palette Mapping\",\"authors\":\"Matthias Trapp, S. Pasewaldt, J. Döllner\",\"doi\":\"10.24132/csrn.2019.2902.2.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a GPU-based approach to color quantization by mapping of arbitrary color palettes to input images using Look-Up Tables (LUTs). For it, different types of LUTs, their GPU-based generation, representation, and respective mapping implementations are described and their run-time performance is evaluated and compared.\",\"PeriodicalId\":322214,\"journal\":{\"name\":\"Computer Science Research Notes\",\"volume\":\"14 12\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Science Research Notes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24132/csrn.2019.2902.2.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science Research Notes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24132/csrn.2019.2902.2.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a GPU-based approach to color quantization by mapping of arbitrary color palettes to input images using Look-Up Tables (LUTs). For it, different types of LUTs, their GPU-based generation, representation, and respective mapping implementations are described and their run-time performance is evaluated and compared.
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