{"title":"基于小波变换的图像压缩技术在远程医疗中的应用","authors":"S. Vairaprakash, A. Shenbagavalli","doi":"10.1109/ICCTET.2013.6675981","DOIUrl":null,"url":null,"abstract":"In this paper we propose on efficient region of Interest coding technique based on [1]Multiwavelet transform, set portioning in hierarchical Algorithm of Medical Images. This new method reduces the importance of Background coefficient of [2]ROI Code block without compromising algorithm complexity. By using this coding method the compressed Bit stream are all embedded and suited for progressive Transmission. Extensive experimental results show that the proposed algorithm gives better quality of images using multi wavelets transform compared to that of other scalar wavelet transforms. In this paper we took 512×512 original image. By using multiwavelet transform we decomposed the original image in various levels, then the original image is compressed in to 4:1 compression ratio and also compared the performance of proposed method with existing method. The performance of the system has been evaluated based on bits per pixel (BPP), Peak Signal To Noise Ratio(PSNR), Mean Square Error, [3] (MSE), Compression Ratio (CR), and Cross Correlation(CC).","PeriodicalId":242568,"journal":{"name":"2013 International Conference on Current Trends in Engineering and Technology (ICCTET)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Certain investigation on image compression technique using wavelet transform for telemedicine application\",\"authors\":\"S. Vairaprakash, A. Shenbagavalli\",\"doi\":\"10.1109/ICCTET.2013.6675981\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose on efficient region of Interest coding technique based on [1]Multiwavelet transform, set portioning in hierarchical Algorithm of Medical Images. This new method reduces the importance of Background coefficient of [2]ROI Code block without compromising algorithm complexity. By using this coding method the compressed Bit stream are all embedded and suited for progressive Transmission. Extensive experimental results show that the proposed algorithm gives better quality of images using multi wavelets transform compared to that of other scalar wavelet transforms. In this paper we took 512×512 original image. By using multiwavelet transform we decomposed the original image in various levels, then the original image is compressed in to 4:1 compression ratio and also compared the performance of proposed method with existing method. The performance of the system has been evaluated based on bits per pixel (BPP), Peak Signal To Noise Ratio(PSNR), Mean Square Error, [3] (MSE), Compression Ratio (CR), and Cross Correlation(CC).\",\"PeriodicalId\":242568,\"journal\":{\"name\":\"2013 International Conference on Current Trends in Engineering and Technology (ICCTET)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Current Trends in Engineering and Technology (ICCTET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCTET.2013.6675981\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Current Trends in Engineering and Technology (ICCTET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCTET.2013.6675981","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Certain investigation on image compression technique using wavelet transform for telemedicine application
In this paper we propose on efficient region of Interest coding technique based on [1]Multiwavelet transform, set portioning in hierarchical Algorithm of Medical Images. This new method reduces the importance of Background coefficient of [2]ROI Code block without compromising algorithm complexity. By using this coding method the compressed Bit stream are all embedded and suited for progressive Transmission. Extensive experimental results show that the proposed algorithm gives better quality of images using multi wavelets transform compared to that of other scalar wavelet transforms. In this paper we took 512×512 original image. By using multiwavelet transform we decomposed the original image in various levels, then the original image is compressed in to 4:1 compression ratio and also compared the performance of proposed method with existing method. The performance of the system has been evaluated based on bits per pixel (BPP), Peak Signal To Noise Ratio(PSNR), Mean Square Error, [3] (MSE), Compression Ratio (CR), and Cross Correlation(CC).