Automatic-target-recognition-assisted image coding

Lei Ma; Min Ahn Q Vong; Glen P. Abousleman; Jennie Si

doi:10.1117/12.477027

Automatic-target-recognition-assisted image coding

Lei Ma, Min Ahn Q Vong, Glen P. Abousleman, Jennie Si

IAFSE-ECEE: Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we present an intelligent image compression system whereby regions of interest (ROI) and background information are coded independently of each other. We apply less compression (more bits) to regions of interest (targets), and more compression (fewer bits) to background data. This methodology preserves relevant features of targets for further analysis, and preserves the background only to the extent of providing contextual information. The resulting system dramatically reduces the bandwidth/storage requirements of the digital imagery, while preserving the target-specific utility of the imagery.

Original language	English (US)
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Editors	F.A. Sadjadi
Pages	203-213
Number of pages	11
Volume	4726
DOIs	https://doi.org/10.1117/12.477027
State	Published - 2002
Event	Automatic Target Recognition XII - Orlando, FL, United States Duration: Apr 2 2002 → Apr 4 2002

Other

Other	Automatic Target Recognition XII
Country	United States
City	Orlando, FL
Period	4/2/02 → 4/4/02

Keywords

Image coding
Intelligent compression
Target recognition

ASJC Scopus subject areas

Electrical and Electronic Engineering
Condensed Matter Physics

Access to Document

10.1117/12.477027

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title = "Automatic-target-recognition-assisted image coding",

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AU - Si, Jennie

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N2 - In this paper, we present an intelligent image compression system whereby regions of interest (ROI) and background information are coded independently of each other. We apply less compression (more bits) to regions of interest (targets), and more compression (fewer bits) to background data. This methodology preserves relevant features of targets for further analysis, and preserves the background only to the extent of providing contextual information. The resulting system dramatically reduces the bandwidth/storage requirements of the digital imagery, while preserving the target-specific utility of the imagery.

AB - In this paper, we present an intelligent image compression system whereby regions of interest (ROI) and background information are coded independently of each other. We apply less compression (more bits) to regions of interest (targets), and more compression (fewer bits) to background data. This methodology preserves relevant features of targets for further analysis, and preserves the background only to the extent of providing contextual information. The resulting system dramatically reduces the bandwidth/storage requirements of the digital imagery, while preserving the target-specific utility of the imagery.

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