{"title":"快速压缩域JPEG图像检索","authors":"G. Schaefer","doi":"10.1109/ICVISP.2017.29","DOIUrl":null,"url":null,"abstract":"While much progress has been achieved in the field of content-based image retrieval (CBIR), almost all CBIR techniques operate on pixel data although virtually all images are stored in compressed form. In this invited paper, we present efficient and effective CBIR techniques that operate directly in the compressed domain and thus do not require full decompression for feature extraction. In particular, we explore compressed domain techniques for JPEG images and show how CBIR features can be extracted from DCT coefficients, from differentially coded DC data, and from optimised Huffman and quantisation tables that are stored in the JPEG headers.","PeriodicalId":404467,"journal":{"name":"2017 International Conference on Vision, Image and Signal Processing (ICVISP)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Fast Compressed Domain JPEG Image Retrieval\",\"authors\":\"G. Schaefer\",\"doi\":\"10.1109/ICVISP.2017.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While much progress has been achieved in the field of content-based image retrieval (CBIR), almost all CBIR techniques operate on pixel data although virtually all images are stored in compressed form. In this invited paper, we present efficient and effective CBIR techniques that operate directly in the compressed domain and thus do not require full decompression for feature extraction. In particular, we explore compressed domain techniques for JPEG images and show how CBIR features can be extracted from DCT coefficients, from differentially coded DC data, and from optimised Huffman and quantisation tables that are stored in the JPEG headers.\",\"PeriodicalId\":404467,\"journal\":{\"name\":\"2017 International Conference on Vision, Image and Signal Processing (ICVISP)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Vision, Image and Signal Processing (ICVISP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVISP.2017.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Vision, Image and Signal Processing (ICVISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVISP.2017.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
While much progress has been achieved in the field of content-based image retrieval (CBIR), almost all CBIR techniques operate on pixel data although virtually all images are stored in compressed form. In this invited paper, we present efficient and effective CBIR techniques that operate directly in the compressed domain and thus do not require full decompression for feature extraction. In particular, we explore compressed domain techniques for JPEG images and show how CBIR features can be extracted from DCT coefficients, from differentially coded DC data, and from optimised Huffman and quantisation tables that are stored in the JPEG headers.