@inproceedings {593, title = {Automatic registration of SAR and visible band remote sensing images}, booktitle = {Joint IEEE International Geoscience and Remote Sensing Symposium and 24th Canadian Remote Sensing Symposium}, year = {2002}, abstract = {

Image registration is one of the basic image processing operations in remote sensing. With an increasing number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques exists for different types of applications and data sources, however no algorithm is known that can accurately register multi-source images consistently. This research addresses this problem by investigating the development of a fully automatic registration system for synthetic aperture radar (SAR) and optical remote sensing images. The development of this new automatic image registration method is based on the extraction and matching of common features that are visible in both images. The algorithm involves the following five steps: noise removal, edge extraction, edge linking pattern extraction and pattern matching. The application of the developed automatic image registration model to SAR and optical image pairs showed that accurate ground control points (GCPs) could be identified automatically.

}, keywords = {algorithm, edge extraction, edge linking pattern extraction, fully automatic registration, geophysical measurement technique, geophysical signal processing, geophysical techniques, image registration, land surface, multi-source image, noise removal, optical imaging, pattern matching, radar imaging, radar remote sensing, Remote Sensing, remote sensing by radar, remote sensing image, SAR, sensor fusion, synthetic aperture radar, terrain mapping, visible band}, doi = {http://dx.doi.org/10.1109/IGARSS.2002.1026106}, author = {M Ali and D A. Clausi} } @inproceedings {601, title = {Shape Preserving Edge Enhancement in Remote Sensing Imagery}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium}, year = {2002}, abstract = {

A novel approach to geometric shape preservation of remote sensing SAR sea ice images is presented in this paper. This approach will complement the existing edge detection schemes. The final edge is evolved by iterations. During each iteration all existing edges are checked for missing link and missing links are found by checking the orientation of the existing edges and by searching for best gradient path. When open edges are reduced considerably, opening of the features that are critical for shape preservation are found by tracing the edges and closing the boundary.

}, keywords = {best gradient path, edge detection, geometric shape preservation, geophysical signal processing, image enhancement, iteration, iterative method, measurement technique, missing link, ocean, oceanographic techniques, orientation, radar imaging, radar remote sensing, remote sensing by radar, SAR, sea ice, shape preserving edge enhancement, spaceborne radar, synthetic aperture radar}, doi = {http://dx.doi.org/10.1109/IGARSS.2002.1026145}, author = {M S. Chowdhury and D A. Clausi} } @article {575, title = {The effect of speckle filtering on scale-dependent texture estimation of a forested scene}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, volume = {38}, year = {2000}, pages = {1160 - 1170}, abstract = {

Spatial fluctuations in microwave backscatter may be an important piece of information in discriminating tree stands. However, the presence of speckle in synthetic aperture radar (SAR) image data is a barrier to the exploitation of image texture. The authors explored a new methodology that combines a recent adaptive speckle reduction algorithm by Lopes et al. (1990) with a generic texture estimation scheme. They investigated the claim that this filter was capable of preserving backscatter texture. To understand if speckle reduction was destroying backscatter texture, they compared the strength of the relationship between forest inventory parameters and image texture as a function of spatial scale for both filtered and unfiltered images. They used Radarsat Fine mode image data: single look resolution is approximately 8.5 m, and pixel spacing is 3 m. Their study area was northern Vancouver Island, B.C., on the west coast of Canada. For the unfiltered data, they found that the ability of image texture to predict the forest parameters decreased as the texture scale increased from 3 to 13 m, suggesting greater information content in the small scale texture. For the filtered data, this relationship was much weaker at small scales and was not a function of distance. Their results suggest that the speckle filter was not retaining small scale texture, which is consistent with the theoretical hypotheses underlying its multiplicative noise model. They also show that there is significant information in small state SAR image texture that may be used as an adjunct to other spatial information for discriminating tree stands in the temperate rain forest

}, keywords = {adaptive signal processing, adaptive speckle reduction algorithm, backscatter texture, forest, forested scene, forestry, generic texture estimation scheme, geophysical measurement technique, geophysical signal processing, geophysical techniques, image texture, land surface, microwave backscatter, radar imaging, radar remote sensing, remote sensing by radar, SAR, scale-dependent texture estimation, spatial fluctuations, speckle, speckle filtering, synthetic aperture radar, tree stand, vegetation mapping}, issn = {0196-2892}, author = {M J. Collins and J Wiebe and D A. Clausi} } @inproceedings {503, title = {Multiresolution Network Flow Phase Unwrapping}, booktitle = {IEEE 2000 International Geoscience and Remote Sensing Symposium}, year = {2000}, abstract = {

Phase unwrapping is a key step in deriving topographic information from interferometric SAR. Several recent methods are based on a minimum cost network flow approach. The authors develop a new, computationally efficient, ldquo;divide-and-conquer rdquo; strategy for phase unwrapping

}, keywords = {divide and conquer methods, divide-and-conquer method, geophysical measurement technique, geophysical techniques, InSAR, interferometric SAR, land surface topography, multiresolution network flow phase unwrapping, phase unwrapping, radar remote sensing, radar theory, remote sensing by radar, synthetic aperture radar, terrain mapping, topography (Earth)}, doi = {http://dx.doi.org/10.1109/IGARSS.2000.861693}, author = {G F Carballo and P Fieguth} } @inproceedings {513, title = {Probabilistic cost functions for network flow phase unwrapping}, booktitle = {IEEE International Geoscience and Remote Sensing Symposium}, year = {1999}, abstract = {

Phase unwrapping is a key step in deriving topographic information from interferometric SAR. A recent method is based on minimizing the total weighted length of branch cuts by computing the minimum cost flow on a network. The authors provide a theoretical foundation to derive the network weights based on a probabilistic approach

}, keywords = {branch cuts, geophysical measurement technique, geophysical techniques, InSAR, interferometric SAR, land surface topography, minimizing, minimum cost flow, network flow phase unwrapping, network weights, probabilistic approach, probabilistic cost function, radar imaging, radar remote sensing, radar theory, remote sensing by radar, SAR, synthetic aperture radar, terrain mapping, theoretical foundation, topographic mapping, topography (Earth), total weighted length}, doi = {http://dx.doi.org/10.1109/IGARSS.1999.772009}, author = {G F Carballo and P Fieguth} }