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Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement
Author(s) -
Myung-Ho Ju,
Dong-Min Kwak,
Hang-Bong Kang
Publication year - 2013
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/56788
Subject(s) - computer science , artificial intelligence , computer vision , image stitching , feature (linguistics) , image sensor , image (mathematics) , matching (statistics) , pattern recognition (psychology) , salient , enhanced data rates for gsm evolution , image fusion , feature detection (computer vision) , image processing , mathematics , philosophy , statistics , linguistics
In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods

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