{"title":"基于AMBTC和位平面压缩的低复杂度图像压缩算法","authors":"Saad Al-Azawi, S. Boussakta, Alexandre Yakovlev","doi":"10.1109/WOSSPA.2011.5931432","DOIUrl":null,"url":null,"abstract":"This paper introduces a low complex image compression algorithm. The proposed algorithm is a combination of pattern squeezing, moments re-quantizing, absolute moments block truncation coding (AMBTC) and a postprocessing unit. One advantage of the proposed algorithm is that it reduces and controls the higher bit rate of the AMBTC while preserving a reasonable image quality. The complexity reduction has been accomplished by utilizing only four (2×2) bit patterns rather than a 32 or 64 (4×4) pattern fitting. This proposed size of pattern fitting reduces the computation costs by reducing the time and arithmetic operations required to search for the best match plane. The four (2×2) bit planes offer the advantage of bit rate control by performing multi level bit plane reduction. This operation has been named pattern squeezing. The algorithm performance has shown good image quality with lower bit rate.","PeriodicalId":343415,"journal":{"name":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Low complexity image compression algorithm using AMBTC and bit plane squeezing\",\"authors\":\"Saad Al-Azawi, S. Boussakta, Alexandre Yakovlev\",\"doi\":\"10.1109/WOSSPA.2011.5931432\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a low complex image compression algorithm. The proposed algorithm is a combination of pattern squeezing, moments re-quantizing, absolute moments block truncation coding (AMBTC) and a postprocessing unit. One advantage of the proposed algorithm is that it reduces and controls the higher bit rate of the AMBTC while preserving a reasonable image quality. The complexity reduction has been accomplished by utilizing only four (2×2) bit patterns rather than a 32 or 64 (4×4) pattern fitting. This proposed size of pattern fitting reduces the computation costs by reducing the time and arithmetic operations required to search for the best match plane. The four (2×2) bit planes offer the advantage of bit rate control by performing multi level bit plane reduction. This operation has been named pattern squeezing. The algorithm performance has shown good image quality with lower bit rate.\",\"PeriodicalId\":343415,\"journal\":{\"name\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOSSPA.2011.5931432\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2011.5931432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low complexity image compression algorithm using AMBTC and bit plane squeezing
This paper introduces a low complex image compression algorithm. The proposed algorithm is a combination of pattern squeezing, moments re-quantizing, absolute moments block truncation coding (AMBTC) and a postprocessing unit. One advantage of the proposed algorithm is that it reduces and controls the higher bit rate of the AMBTC while preserving a reasonable image quality. The complexity reduction has been accomplished by utilizing only four (2×2) bit patterns rather than a 32 or 64 (4×4) pattern fitting. This proposed size of pattern fitting reduces the computation costs by reducing the time and arithmetic operations required to search for the best match plane. The four (2×2) bit planes offer the advantage of bit rate control by performing multi level bit plane reduction. This operation has been named pattern squeezing. The algorithm performance has shown good image quality with lower bit rate.