This paper presents a practical method of epipolar resampling of high-resolution satellite imagery. Satellite imagery imaged with a linear array CCD sensor has quite different geometric characteristics from aerial photographs, therefore the conventional method of epipolar resampling is not applicable to it. On the other hand, epipolar resampling method based on rigorous orientation model with h...

We introduce a method for validation of results obtained by clustering analysis of data. The method is based on resampling the available data. A figure of merit that measures the stability of clustering solutions against resampling is introduced. Clusters that are stable against resampling give rise to local maxima of this figure of merit. This is presented first for a one-dimensional data set,...

Resampling techniques are being widely used at different stages of satellite image processing. The existing methodologies cannot perfectly recover features from a completely under sampled image and hence an intelligent adaptive resampling methodology is required. We address these issues and adopt an error metric from the available literature to define interpolation quality. We also propose a ne...

Estimation of function expectation θ = Ef(X1, X2, ..., Xm) is considered. For independent variables X1, X2, ..., Xm, sample populations H1, H2, ...,Hm are available as the primary data. The resampling approach uses the usual simulation procedure. For that, the random variables {Xi} are not generated by random number generators in accordance with the estimated probabilistic distributions, but ar...

Parametric resampling schemes have been recently introduced in complex network analysis with the aim of assessing the statistical significance of graph clustering and the robustness of community partitions. We propose here a method to replicate structural features of complex networks based on the non-parametric resampling of the transition matrix associated with an unbiased random walk on the g...