{"title":"基于双向小差分的无损图像压缩","authors":"Chinchen Chang, Chi-Shiang Chan, J. Hsiao","doi":"10.1109/AINA.2003.1193008","DOIUrl":null,"url":null,"abstract":"We propose a lossless image compression method, in which we compress an image by saving the differences between the encoding pixels and their adjacent pixels. To deal with a pixel, we refer to not only its up pixel but also its left pixel and replace the value of the pixel itself with the value of difference. The experimental results show that the method gives quite an impressive performance. Since the values of most adjacent pixels in an image are closed, we can use this simple, effective way to compress the image.","PeriodicalId":382765,"journal":{"name":"17th International Conference on Advanced Information Networking and Applications, 2003. AINA 2003.","volume":"176 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Lossless image compression based on two-way smaller difference\",\"authors\":\"Chinchen Chang, Chi-Shiang Chan, J. Hsiao\",\"doi\":\"10.1109/AINA.2003.1193008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a lossless image compression method, in which we compress an image by saving the differences between the encoding pixels and their adjacent pixels. To deal with a pixel, we refer to not only its up pixel but also its left pixel and replace the value of the pixel itself with the value of difference. The experimental results show that the method gives quite an impressive performance. Since the values of most adjacent pixels in an image are closed, we can use this simple, effective way to compress the image.\",\"PeriodicalId\":382765,\"journal\":{\"name\":\"17th International Conference on Advanced Information Networking and Applications, 2003. AINA 2003.\",\"volume\":\"176 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"17th International Conference on Advanced Information Networking and Applications, 2003. AINA 2003.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AINA.2003.1193008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"17th International Conference on Advanced Information Networking and Applications, 2003. AINA 2003.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2003.1193008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lossless image compression based on two-way smaller difference
We propose a lossless image compression method, in which we compress an image by saving the differences between the encoding pixels and their adjacent pixels. To deal with a pixel, we refer to not only its up pixel but also its left pixel and replace the value of the pixel itself with the value of difference. The experimental results show that the method gives quite an impressive performance. Since the values of most adjacent pixels in an image are closed, we can use this simple, effective way to compress the image.