Image reconstruction from multiscale critical points

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Abstract

A minimal variance reconstruction scheme is derived using derivatives of the Gaussian as filters. A closed form mixed correlation matrix for reconstructions from multiscale points and their local derivatives up to the second order is presented. With the inverse of this mixed correlation matrix, a reconstruction of the image can be easily calculated. Some interesting results of reconstructions from multiscale critical points are presented. The influence of limited calculation precision is considered, using the condition number of the mixed correlation matrix. © Springer-Verlag Berlin Heidelberg 2003.

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Kanters, F., Florack, L., Platel, B., & Ter Haar Romeny, B. M. (2003). Image reconstruction from multiscale critical points. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2695, 464–478. https://doi.org/10.1007/3-540-44935-3_32

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