Siamak Khorram

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Image misregistration has become one of the significant bottlenecks for improving the accuracy of multisource data analysis, such as data fusion and change detection. In this paper, the effects of misregistration on the accuracy of remotely sensed change detection were systematically investigated and quantitatively evaluated. This simulation research(More)
In this paper, a new feature-based approach to automated image-to-image registration is presented. The characteristic of this approach is that it combines an invariantmoment shape descriptor with improved chain-code matching to establish correspondences between the potentially matched regions detected from the two images. It is robust in that it overcomes(More)
This paper focuses on an automated ANN classification system consisting of two modules: an unsupervised Kohonen’s Self-Organizing Mapping (SOM) neural network module, and a supervised Multilayer Perceptron (MLP) neural network module using the Backpropagation (BP) training algorithm. Two training algorithms were provided for the SOM network module: the(More)
Among the supervised parametric classification methods, the maximum-likelihood (MLH) classifier has become popular and widespread in remote sensing. Reliable prior probabilities are not always freely available, and it is a common practice to perform the MLH classification with equal prior probabilities. When equal prior probabilities are used, the(More)
Commercial high spatial resolution satellite data now provide a synoptic and consistent source of digital imagery with detail comparable to that of aerial photography. In the work described here, per-pixel classification, image fusion, and GIS-based map refinement techniques were tailored to pan-sharpened 0.61 m QuickBird imagery to develop a six-category(More)
A pixel level data fusion approach based on correspondence analysis (CA) is introduced for high spatial and spectral resolution satellite data. Principal component analysis (PCA) is a well-known multivariate data analysis and fusion technique in the remote sensing community. Related to PCA but a more recent multivariate technique, correspondence analysis,(More)
Currently available land-cover data sets for large geographic regions are produced on an intermittent basis and are often dated. Ideally, annually updated data would be available to support environmental status and trends assessments and ecosystem process modeling. This research examined the potential for vegetation phenology based land-cover classification(More)
This paper introduces a new feature-based image registration technique which registers images by finding rotationand scale-invariant features and matching them using a novel feature matching algorithm based on an evidence accumulation process reminiscent of the generalized Hough transform. Once feature correspondence has been established, the transformation(More)
This paper introduces a new featurebased image registration algorithm which registers images by finding rotation and scale invariant features and matches them using an evidence accumulation process based on the Generalized Hough Transform. Once feature correspondence has been established, the transformation parameters are then estimated using Non-linear(More)