Spatially adaptive multi-resolution multi-spectral image fusion based on bayesian approach

Jong Hyun Park, Moon Gi Kang

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

3 Citations (Scopus)

Abstract

In this paper, we propose two new spatially adaptive image fusion algorithms based on Bayesian approach for merging remotely sensed panchromatic and multi-spectral images. The two complementary images are modeled as correlated two dimensional stochastic signals and the high-resolution multi-spectral image is estimated by minimizing the mean squared error between the original high-resolution image and the estimated image. We assume that the estimator is locally linear and obtain the local linear minimum mean square error (MMSE) estimator for image fusion. Two MMSE image fusion algorithms are derived on different assumptions of the images. If we assume that pixels in the images are uncorrelated with their neighbors, the estimator becomes a point processor which is controlled by an adaptive gain expressed by the ratio of local cross-covariance between the two images and the local variance of the panchromatic image. On the other hand, if we assume that pixels in a small block are considered stationary and correlated with one another, the estimator uses the locally stationary cross-covariance matrix between the two images and auto-covariance matrix of the panchromatic image. For the second algorithm, we take Fast Fourier Transform (FFT) based approach in order to avoid complex matrix computations and achieve a fast algorithm. Experimental results show that the proposed algorithms are superior to conventional algorithms according to visual and quantitative comparisons.

Original languageEnglish
Title of host publicationImage Processing
Subtitle of host publicationAlgorithms and Systems, Neural Networks, and Machine Learning - Proceedings of SPIE-IS and T Electronic Imaging
DOIs
Publication statusPublished - 2006 Apr 17
EventImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning - San Jose, CA, United States
Duration: 2006 Jan 162006 Jan 18

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6064
ISSN (Print)0277-786X

Other

OtherImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning
CountryUnited States
CitySan Jose, CA
Period06/1/1606/1/18

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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    Park, J. H., & Kang, M. G. (2006). Spatially adaptive multi-resolution multi-spectral image fusion based on bayesian approach. In Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning - Proceedings of SPIE-IS and T Electronic Imaging [60640T] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6064). https://doi.org/10.1117/12.642765