快速压缩域JPEG图像检索

G. Schaefer
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引用次数: 6

摘要

虽然基于内容的图像检索(CBIR)领域已经取得了很大进展,但几乎所有的CBIR技术都是在像素数据上操作的,尽管几乎所有的图像都是以压缩形式存储的。在这篇特邀论文中,我们提出了高效和有效的CBIR技术,该技术直接在压缩域中操作,因此不需要完全解压即可进行特征提取。特别是,我们探索了JPEG图像的压缩域技术,并展示了如何从DCT系数中提取CBIR特征,从差分编码的DC数据中提取CBIR特征,以及从存储在JPEG标头中的优化霍夫曼和量化表中提取CBIR特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Compressed Domain JPEG Image Retrieval
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.
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