{"title":"基于低复杂度Bandlet变换和改进EZBC的渐进式SAR图像压缩","authors":"Maryam Kuchakzadeh, H. Danyali, S. Samadi","doi":"10.1109/ICCKE.2014.6993416","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a progressive SAR image compression based on Bandlet transform (BT) and a modified Embedded Zero-Block Coding (EZBC) algorithm. Bandlet transform as a new developed adaptive multiresolution geometry analysis tool exhibits enormous potential in compression based on geometric regularity. Since in SAR images, important information is spread in the entire frequency spectrum, discrete wavelet transform (DWT) cannot provide optimal representation and instead Bandlet transform is employed to provide a sparse representation of the image. A modified version of EZBC algorithm is introduced to efficiently encode the Bandlet coefficient in a progressive manner in which fidelity of the reconstructed image in the decoder gradually improves as more bits are received and decoded. Numerical tests show that our method provide a significant improvement particularly for low bit rate SAR image compression.","PeriodicalId":152540,"journal":{"name":"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Progressive SAR image compression using low complexity Bandlet transform and modified EZBC\",\"authors\":\"Maryam Kuchakzadeh, H. Danyali, S. Samadi\",\"doi\":\"10.1109/ICCKE.2014.6993416\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a progressive SAR image compression based on Bandlet transform (BT) and a modified Embedded Zero-Block Coding (EZBC) algorithm. Bandlet transform as a new developed adaptive multiresolution geometry analysis tool exhibits enormous potential in compression based on geometric regularity. Since in SAR images, important information is spread in the entire frequency spectrum, discrete wavelet transform (DWT) cannot provide optimal representation and instead Bandlet transform is employed to provide a sparse representation of the image. A modified version of EZBC algorithm is introduced to efficiently encode the Bandlet coefficient in a progressive manner in which fidelity of the reconstructed image in the decoder gradually improves as more bits are received and decoded. Numerical tests show that our method provide a significant improvement particularly for low bit rate SAR image compression.\",\"PeriodicalId\":152540,\"journal\":{\"name\":\"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCKE.2014.6993416\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE.2014.6993416","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Progressive SAR image compression using low complexity Bandlet transform and modified EZBC
In this paper, we introduce a progressive SAR image compression based on Bandlet transform (BT) and a modified Embedded Zero-Block Coding (EZBC) algorithm. Bandlet transform as a new developed adaptive multiresolution geometry analysis tool exhibits enormous potential in compression based on geometric regularity. Since in SAR images, important information is spread in the entire frequency spectrum, discrete wavelet transform (DWT) cannot provide optimal representation and instead Bandlet transform is employed to provide a sparse representation of the image. A modified version of EZBC algorithm is introduced to efficiently encode the Bandlet coefficient in a progressive manner in which fidelity of the reconstructed image in the decoder gradually improves as more bits are received and decoded. Numerical tests show that our method provide a significant improvement particularly for low bit rate SAR image compression.