{"title":"零树图像编码的自适应小波包基选择","authors":"R. Pandian, T. Vigneswaren","doi":"10.1504/IJSISE.2016.10000775","DOIUrl":null,"url":null,"abstract":"In this paper, we explore the possibility of wedding the adaptive wavelet packet transform with zerotree quantisation. We subject the input image to an adaptive wavelet packet decomposition, to get a full wavelet packet tree. We present a general zerotree structure for an arbitrary wavelet packet geometry in an image coding framework. Set Partitioning in Hierarchical Trees (SPIHT) and Zerotree Quantisation - Wavelet (ZQ-WV) coder are the other encoding methods. The limitations we have in these coders are that they have low performance in terms of Peak Signal-to-Noise Ratio (PSNR) and low visual quality at low bit rates.","PeriodicalId":56359,"journal":{"name":"International Journal of Signal and Imaging Systems Engineering","volume":"9 1","pages":"388"},"PeriodicalIF":0.6000,"publicationDate":"2016-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Adaptive wavelet packet basis selection for zerotree image coding\",\"authors\":\"R. Pandian, T. Vigneswaren\",\"doi\":\"10.1504/IJSISE.2016.10000775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we explore the possibility of wedding the adaptive wavelet packet transform with zerotree quantisation. We subject the input image to an adaptive wavelet packet decomposition, to get a full wavelet packet tree. We present a general zerotree structure for an arbitrary wavelet packet geometry in an image coding framework. Set Partitioning in Hierarchical Trees (SPIHT) and Zerotree Quantisation - Wavelet (ZQ-WV) coder are the other encoding methods. The limitations we have in these coders are that they have low performance in terms of Peak Signal-to-Noise Ratio (PSNR) and low visual quality at low bit rates.\",\"PeriodicalId\":56359,\"journal\":{\"name\":\"International Journal of Signal and Imaging Systems Engineering\",\"volume\":\"9 1\",\"pages\":\"388\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2016-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Signal and Imaging Systems Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJSISE.2016.10000775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Signal and Imaging Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSISE.2016.10000775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Adaptive wavelet packet basis selection for zerotree image coding
In this paper, we explore the possibility of wedding the adaptive wavelet packet transform with zerotree quantisation. We subject the input image to an adaptive wavelet packet decomposition, to get a full wavelet packet tree. We present a general zerotree structure for an arbitrary wavelet packet geometry in an image coding framework. Set Partitioning in Hierarchical Trees (SPIHT) and Zerotree Quantisation - Wavelet (ZQ-WV) coder are the other encoding methods. The limitations we have in these coders are that they have low performance in terms of Peak Signal-to-Noise Ratio (PSNR) and low visual quality at low bit rates.