Low-bitrate benefits of JPEG compression on sift recognition

Mohamed Elhoseiny, Bing Song, Jeremi Sudol, David McKinnon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Feature detection and image matching are two important tasks in photogrammetry. Their application continues to grow in a various fields, from simple photogrammetry tasks such as feature recognition, to the development of sophisticated models to deal with bandwidth problems in mobile devices. Due to low bit-rate requirement of the current mobile communication, Mobile Visual Search became a very challenging problem. In this direction, this paper presents important conclusions based on a comprehensive evaluation of SIFT matching performance against various parameters (e.g. JPEG quality/compression in model and test images, image resolution, etc). The main conclusion of the performed experiments is that reducing jpeg quality from 100% to 30% slightly impart the matching performance, while it significantly reduces the communication bandwidth requirement by ≈ 70%. © 2013 IEEE.
Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
DOIs
StatePublished - Dec 1 2013
Externally publishedYes

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