Fusion of Noisy Multi-sensor Imagery
Keywords:
Image fusion, edge maps, information maps, noise filtering, multi-resolution, wavelets, Laplacian pyramids, multi-sensor images
Abstract
Interest in fusing multiple sensor data for both military and civil applications has beengrowing. Some of the important applications integrate image information from multiple sensorsto aid in navigation guidance, object detection and recognition, medical diagnosis, datacompression, etc. While, human beings may visually inspect various images and integrateinformation, it is of interest to develop algorithms that can fuse various input imagery to producea composite image. Fusion of images from various sensor modalities is expected to produce anoutput that captures all the relevant information in the input. The standard multi-resolution-based edge fusion scheme has been reviewed in this paper. A theoretical framework is given forthis edge fusion method by showing how edge fusion can be framed as information maximisation.However, the presence of noise complicates the situation. The framework developed is used toshow that for noisy images, all edges no longer correspond to information. In this paper, varioustechniques have been presented for fusion of noisy multi-sensor images. These techniques aredeveloped for a single resolution as well as using multi-resolution decomposition. Some of thetechniques are based on modifying edge maps by filtering images, while others depend onalternate definition of information maps. Both these approaches can also be combined.Experiments show that the proposed algorithms work well for various kinds of noisy multi-sensor images.
Published
2008-01-01
How to Cite
Mishra, A., & Rakshit, S. (2008). Fusion of Noisy Multi-sensor Imagery. Defence Science Journal, 58(1), 136-146. https://doi.org/10.14429/dsj.58.1631
Issue
Section
Research Papers
Copyright (c) 2016 Defence Science Journal
Where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India