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Shih-Fu Chang. Compressed-Domain Content-Based Image and Video Retrieval. In Symposium on Multimedia Communications and Video Coding, Polytechnic University, New York, NY, October 1995.

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In this paper, we focus on automated image retrieval using various types of visual features (including image templates). Specifically, we explore a unique approach which emphasizes the compressed-domain solutions. Given most images and videos stored in the compressed form, it is highly desirable to perform content-based visual retrieval directly in the compressed domain. In other words, extraction of visual features, matching of images and videos, or even manipulations of search results can be implemented using the compressed visual data without decompressing (or sometimes with minimal decoding). The advantage of performing these tasks in the compressed domain is obvious. The computational cost can be greatly reduced compared to the alternative which fully decodes the compressed material and executes the above tasks in the uncompressed domain. Not only that the decoding process is avoided, the amount of data in the compressed domain is also lower than in the uncompressed domain. We have applied the compressed-domain approach to image/video manipulation and compositing [2,11], texture/color-based image query [9], image matching [10], video indexing and editing [6, 25]


Shih-Fu Chang

BibTex Reference

   Author = {Chang, Shih-Fu},
   Title = {Compressed-Domain Content-Based Image and Video Retrieval},
   BookTitle = {Symposium on Multimedia Communications and Video Coding},
   Address = {Polytechnic University, New York, NY},
   Month = {October},
   Year = {1995}

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