Automated Thematic Registration of NOAA, CoastWatch, and AVHRR Images

Ferguson, Randolph L.; Krouse, Charles; Patterson, Marlene; Hare, Jonathan A.

doi:10.14358/pers.72.6.677

Cited by 2 publications

(1 citation statement)

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“…The advantage of the proposed image registration method is its viability of working in production mode. Similar tasks were reported by Ferguson et al, (2006), Lou et al, (2006), Eugenio and Marchell (2009), the fundamental difference between their approaches with the approach described in this article is the difference in the implementation of the software.FOSSdevelopment is emerging as an alternative approach for developing large software systems.FOSS offers new types and new kinds of processes to research, understand, improve and practice (Scacchiet al,2006). FOSS serves the collective interest of the global community to share and develop interoperable information infrastructure.…”

Section: Introductionsupporting

confidence: 74%

Automatic Image Registration Using Free and Open Source Software

Babu

Shekhar

Chandrasekar

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Image registration is the most critical operation in remote sensing applications to enable location based referencing and analysis of earth features. This is the first step for any process involving identification, time series analysis or change detection using a large set of imagery over a region. Most of the reliable procedures involve time consuming and laborious manual methods of finding the corresponding matching features of the input image with respect to reference. Also the process, as it involves human interaction, does not converge with multiple operations at different times. Automated procedures rely on accurately determining the matching locations or points from both the images under comparison and the procedures are robust and consistent over time. Different algorithms are available to achieve this, based on pattern recognition, feature based detection, similarity techniques etc. In the present study and implementation, Correlation based methods have been used with a improvement over newly developed technique of identifying and pruning the false points of match. Free and Open Source Software (FOSS) have been used to develop the methodology to reach a wider audience, without any dependency on COTS (Commercially off the shelf) software. Standard deviation from foci of the ellipse of correlated points, is a statistical means of ensuring the best match of the points of interest based on both intensity values and location correspondence. The methodology is developed and standardised by enhancements to meet the registration requirements of remote sensing imagery. Results have shown a performance improvement, nearly matching the visual techniques and have been implemented in remote sensing operational projects. The main advantage of the proposed methodology is its viability in production mode environment. This paper also shows that the visualization capabilities of MapWinGIS, GDAL's image handling abilities and OSSIM's correlation facility can be efficiently integrated to effectively use in remote sensing based production environment.

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Section: Introductionsupporting

confidence: 74%