{"title":"基于平稳小波的工业计算机断层图像压缩","authors":"Haina Jiang, Xiangyu Yang, Li Zeng","doi":"10.1109/ICWAPR.2013.6599303","DOIUrl":null,"url":null,"abstract":"To have higher resolution and precision, the amount of industrial computed tomography data has become larger and larger. Moreover, industrial computed tomography images are approximately piece-wise constant, which fits for encoding contour. Then, we develop an improved compression method based on wavelet contour coding Firstly, we merge Freeman encoding idea into our IMCE (an improved method for contours extraction based on stationary wavelet) to extract contours. Simultaneously, each contour point extracted by IMCE is directly stored by recording the relative coordinates not the actual ones through exploiting their continuity and logical linking. By that, the two steps of traditional contour-based compression method are simplified into only one. Lastly, Huffman coding is employed to further lossless compress them. Experimental results show that this method can gain good compression ratio as well as keeping ideal quality of decompressed image.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"153 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Compressing industrial computed tomography images based on stationary wavelet\",\"authors\":\"Haina Jiang, Xiangyu Yang, Li Zeng\",\"doi\":\"10.1109/ICWAPR.2013.6599303\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To have higher resolution and precision, the amount of industrial computed tomography data has become larger and larger. Moreover, industrial computed tomography images are approximately piece-wise constant, which fits for encoding contour. Then, we develop an improved compression method based on wavelet contour coding Firstly, we merge Freeman encoding idea into our IMCE (an improved method for contours extraction based on stationary wavelet) to extract contours. Simultaneously, each contour point extracted by IMCE is directly stored by recording the relative coordinates not the actual ones through exploiting their continuity and logical linking. By that, the two steps of traditional contour-based compression method are simplified into only one. Lastly, Huffman coding is employed to further lossless compress them. Experimental results show that this method can gain good compression ratio as well as keeping ideal quality of decompressed image.\",\"PeriodicalId\":236156,\"journal\":{\"name\":\"2013 International Conference on Wavelet Analysis and Pattern Recognition\",\"volume\":\"153 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Wavelet Analysis and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWAPR.2013.6599303\",\"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 Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2013.6599303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compressing industrial computed tomography images based on stationary wavelet
To have higher resolution and precision, the amount of industrial computed tomography data has become larger and larger. Moreover, industrial computed tomography images are approximately piece-wise constant, which fits for encoding contour. Then, we develop an improved compression method based on wavelet contour coding Firstly, we merge Freeman encoding idea into our IMCE (an improved method for contours extraction based on stationary wavelet) to extract contours. Simultaneously, each contour point extracted by IMCE is directly stored by recording the relative coordinates not the actual ones through exploiting their continuity and logical linking. By that, the two steps of traditional contour-based compression method are simplified into only one. Lastly, Huffman coding is employed to further lossless compress them. Experimental results show that this method can gain good compression ratio as well as keeping ideal quality of decompressed image.