Fusion of panchromatic image with multi-spectral image using robust adaptive normalized convolution
| Autor: | K. Joseph Abraham Sundar |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Image fusion
010504 meteorology & atmospheric sciences business.industry Computer science Machine vision ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Iterative reconstruction 010502 geochemistry & geophysics 01 natural sciences Window function Convolution Panchromatic film Geophysics Signal-to-noise ratio Artificial intelligence business Subspace topology 0105 earth and related environmental sciences |
| Zdroj: | Journal of Applied Geophysics. 169:118-124 |
| ISSN: | 0926-9851 |
| DOI: | 10.1016/j.jappgeo.2019.06.020 |
| Popis: | This paper proposes a novel technique for reconstruction of a high resolution (HR) image by fussing irregularly sampled data of panchromatic image and multi-spectral image. The idea behind the fusion process is normalized convolution which uses the technique of approximating the local signals by projecting on to subspace. The normalized convolution used in this paper contains the polynomial basis functions similar to that of a Taylor series expansion. The window function used in the adaptive normalized convolution helps in improving the analysis by grouping more samples of same sense. This in turn helps to escalate the signal to noise ratio and curtail the diffusion across discontinuities. The necessity of multi-sensor data in required in many fields such as defense, remote-sensing, machine vision, medical imaging and the proposed method supplied promising results to such applications. |
| Databáze: | OpenAIRE |
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