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Project: Fully Automated Registration and Composite Generation of Multisensor and Multidate 
                 Satellite Image Data

 

People

Faculties : B.S. Manjunath, Sanjit K. Mitra and Michael Goodchild

Students : Yining Deng ,David Garza and Leila Fonseca

Collaborators : M. Lee (JPL) and Jack Estes  

Research

Ongoing research projects include multiscale registration using robust image segmentation and matching algorithms with the aim of developing faster registration algorithms. In addition, efficient data representation schemes are being investigated by integrating segmentation, registration, fusion and data decorrelation in a single framework. Such a compact representation would allow fast and convenient browsing and retrievals of image data. This is an interesting problem particularly in the context of large image databases such as the UCSB Alexandria Digital Library project.

 

Software

Contour Based Approach to Multisensor Image Registration:

Compiled registration code for NT, SGI, SUN, IBM/PC and UNIX.

Test Images

Several test images are also provided

Examples

Explorer user interface

Image Fusion

Multidate Image Registration

Multispectral (Landsat TM) Image Registration

Multisensor (Landsat TM - Spot) Image Registration

Description

Research on image registration addresses issues related to multiscale registration, integrating robust segmentation tools with the contour matching approach developed at UCSB, and in developing novel image representation schemes for maintaining large databases of satellite images.

The initial focus of the project has been on the implementation of the basic countour matching, the elastic matching apporach, and the evaluation of the prototyped methods using a graphical image processing user interface tool, namely the EXPLORER image processing environment on a Silicon Graphics workstation. The research work focused on extending the method of Li, Manjunath, and Mitra ("A Contour Based Approach to Multi-sensor Image Registration"). The method has been implemented using C programming language and ported to the EXPLORER interface. Preliminary tests of this method compared with some standard methods have been carried out at UCSB. This approach extracts contour information from each of two images, correlates salient features of the contours, and finds optimal transform parameters for aligning the images. After the two images are registered, they are combined to present the result.

Preliminary results of the fusion using the wavelet transform have been explored and showed to be very promising. This method works by assuming that the high frequency wavelet coefficients have greater energy in the image that contains useful features in that region than in the image that does not. The images are fused by constructing a wavelet pyramid using the the more dominant high frequency wavelet coefficients among the two images. The fused image is supplied from the inverse wavelet transform of this combined pyramid. This method has been ported to the EXPLORER interface on the SGI machine. Details are described in Li, Manjunath, and Mitra ("Multisensor Image Fusion Using the Wavelet Transform"). The developed registration and fusion methods have been evaluated by our collaborators in the Geography Department at UCSB. Extensive testing of the registration algorithm on a wide range of data has been carried out.

Publications

These materials are presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

  1. Hui Li, B. S. Manjunath and Sanjit K. Mitra "A contour-based approach to multisensor image registration", IEEE Transactions on Image Processing, vol.4, (no.3), pp.320-34, March 1995. [abstract]

  2. L. M. G. Fonseca and B. S. Manjunath, "Registration Techniques for Multisensor Remotely Sensed Imagery ", Journal of Photogrammetry Engineering and Remote Sensing, Sep 1996.[abstract]

  3. H. Li, B. S. Manjunath and S. K. Mitra, "Multisensor Image Fusion Using the Wavelet Transform," Proc. first international conference on image processing, ICIP 94, Austin, Texas,  Vol. I, pp. 51-55, Nov 1994. [abstract]

Registration Demo presentation (NASA workshop) 5.8Mb

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