Approches, Shengzhong Zhanga, Lei Yub, Yinqian Chengc
{"title":"图像无损压缩方法简介","authors":"Approches, Shengzhong Zhanga, Lei Yub, Yinqian Chengc","doi":"10.25236/ajms.2023.040301","DOIUrl":null,"url":null,"abstract":": The purpose of image compression is to reduce the number of bits required to represent data by removing data redundancy. Due to the large amount of image data, it is very difficult to store, transmit, and process, so the compression of image data becomes very important. This article introduced several lossless compression approaches such as Huffman, Fano, Run Length, Arithmetic, and LZW (Lempel–Ziv–Welch) Coding. The approach which can achieve compact code is regarded as closing to the best solution.","PeriodicalId":372277,"journal":{"name":"Academic Journal of Mathematical Sciences","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Introduction of Image Lossless Compression Approches\",\"authors\":\"Approches, Shengzhong Zhanga, Lei Yub, Yinqian Chengc\",\"doi\":\"10.25236/ajms.2023.040301\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": The purpose of image compression is to reduce the number of bits required to represent data by removing data redundancy. Due to the large amount of image data, it is very difficult to store, transmit, and process, so the compression of image data becomes very important. This article introduced several lossless compression approaches such as Huffman, Fano, Run Length, Arithmetic, and LZW (Lempel–Ziv–Welch) Coding. The approach which can achieve compact code is regarded as closing to the best solution.\",\"PeriodicalId\":372277,\"journal\":{\"name\":\"Academic Journal of Mathematical Sciences\",\"volume\":\"72 1\",\"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\":\"Academic Journal of Mathematical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25236/ajms.2023.040301\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Academic Journal of Mathematical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25236/ajms.2023.040301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Introduction of Image Lossless Compression Approches
: The purpose of image compression is to reduce the number of bits required to represent data by removing data redundancy. Due to the large amount of image data, it is very difficult to store, transmit, and process, so the compression of image data becomes very important. This article introduced several lossless compression approaches such as Huffman, Fano, Run Length, Arithmetic, and LZW (Lempel–Ziv–Welch) Coding. The approach which can achieve compact code is regarded as closing to the best solution.