Enhanced Multispectral Band-to-Band Registration Using Co-Occurrence Scale Space and Spatial Confined RANSAC Guided Segmented Affine Transformation

Band-to-Band Registration (BBR) is a pre-requisite image processing operation essential for specific remote sensing multispectral sensors. BBR aims to align spectral wavelength channels at sub-pixel level accuracy over each other. The paper presents a novel BBR technique utilizing Co-occurrence Scal...

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Bibliographic Details
Published in:IEEE transactions on image processing 2024, Vol.33, p.6521-6534
Main Authors: Misra, Indranil, Kumar Rohil, Mukesh, Manthira Moorthi, S., Dhar, Debajyoti
Format: Article
Language:English
Subjects:
Affine transformations
Band-to-band registration
co-occurrence scale space
Data analysis
Image acquisition
Image enhancement
Image processing
Image registration
multispectral images
Normalized difference vegetative index
Pixels
Registration
Remote sensing
Satellite imagery
segmented affine transformation
spatial confined RANSAC
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Summary:Band-to-Band Registration (BBR) is a pre-requisite image processing operation essential for specific remote sensing multispectral sensors. BBR aims to align spectral wavelength channels at sub-pixel level accuracy over each other. The paper presents a novel BBR technique utilizing Co-occurrence Scale Space (CSS) for feature point detection and Spatial Confined RANSAC (SC-RANSAC) for removing outlier matched control points. Additionally, the Segmented Affine Transformation (SAT) model reduces distortion and ensures consistent BBR. The methodology developed is evaluated with Nano-MX multispectral images onboard the Indian Nano Satellite (INS-2B) covering diverse landscapes. BBR performance using the proposed method is also verified visually at a 4X zoom level on satellite scenes dominated by cloud pixels. The band misregistration effect on the Normalized Difference Vegetation Index (NDVI) from INS-2B is analyzed and cross-validated with the closest acquisition Landsat-9 OLI NDVI map before and after BBR correction. The experimental evaluation shows that the proposed BBR approach outperforms the state-of-the-art image registration techniques.
ISSN:1057-7149
1941-0042
1941-0042
DOI:10.1109/TIP.2024.3494555