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Laplacian Eigenimages in Discrete Scale Space
[chapter]
2012
Lecture Notes in Computer Science
Linear or Gaussian scale space is a well known multi-scale representation for continuous signals. However, implementational issues arise, caused by discretization and quantization errors. In order to develop more robust scale space based algorithms, the discrete nature of computer processed signals has to be taken into account. Aiming at a computationally practicable implementation of the discrete scale space framework we used suitable neighborhoods, boundary conditions and sampling methods. In
doi:10.1007/978-3-642-34166-3_18
fatcat:ub4k45c5ingbbg6ytfe3s6eqj4