{"title":"用于帧缓冲显示的彩色图像量化","authors":"Paul S. Heckbert","doi":"10.1145/280811.281025","DOIUrl":null,"url":null,"abstract":"Algorithms for adaptive, tapered quantization of color images are described. The research is motivated by the desire to display high-quality reproductions of color images with small frame buffers. It is demonstrated that many color images which would normally require a frame buffer having 15 bits per pixel can be quantized to 8 or fewer bits per pixel with little subjective degradation. In most cases, the resulting images look significantly better than those made with uniform quantization. The color image quantization task is broken into four phases: 1) Sampling the original image for color statistics 2) Choosing a colormap based on the color statistics 3) Mapping original colors to their nearest neighbors in the colormap 4) Quantizing and redrawing the original image (with optional dither). Several algorithms for each of phases 2-4 are described, and images created by each given.","PeriodicalId":236803,"journal":{"name":"Seminal graphics: pioneering efforts that shaped the field","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"218","resultStr":"{\"title\":\"Color image quantization for frame buffer display\",\"authors\":\"Paul S. Heckbert\",\"doi\":\"10.1145/280811.281025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Algorithms for adaptive, tapered quantization of color images are described. The research is motivated by the desire to display high-quality reproductions of color images with small frame buffers. It is demonstrated that many color images which would normally require a frame buffer having 15 bits per pixel can be quantized to 8 or fewer bits per pixel with little subjective degradation. In most cases, the resulting images look significantly better than those made with uniform quantization. The color image quantization task is broken into four phases: 1) Sampling the original image for color statistics 2) Choosing a colormap based on the color statistics 3) Mapping original colors to their nearest neighbors in the colormap 4) Quantizing and redrawing the original image (with optional dither). Several algorithms for each of phases 2-4 are described, and images created by each given.\",\"PeriodicalId\":236803,\"journal\":{\"name\":\"Seminal graphics: pioneering efforts that shaped the field\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"218\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Seminal graphics: pioneering efforts that shaped the field\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/280811.281025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seminal graphics: pioneering efforts that shaped the field","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/280811.281025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Algorithms for adaptive, tapered quantization of color images are described. The research is motivated by the desire to display high-quality reproductions of color images with small frame buffers. It is demonstrated that many color images which would normally require a frame buffer having 15 bits per pixel can be quantized to 8 or fewer bits per pixel with little subjective degradation. In most cases, the resulting images look significantly better than those made with uniform quantization. The color image quantization task is broken into four phases: 1) Sampling the original image for color statistics 2) Choosing a colormap based on the color statistics 3) Mapping original colors to their nearest neighbors in the colormap 4) Quantizing and redrawing the original image (with optional dither). Several algorithms for each of phases 2-4 are described, and images created by each given.