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Grid Filters for Local Nonlinear Image Restoration

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tveldhui1998.pdf (11.32 MB)

Date

1998

Authors

Veldhuizen, Todd

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Volume Title

Publisher

University of Waterloo

Abstract

A new approach to local nonlinear image restoration is described, based on approximating functions using a regular grid of points in a many-dimensional space. Symmetry reductions and compression of the sparse grid make it feasible to work with twelve-dimensional grids as large as 22<sup>12</sup>. Unlike polynomials and neural networks whose filtering complexity per pixel is linear in the number of filter co-efficients, grid filters have O(1) complexity per pixel. Grid filters require only a single presentation of the training samples, are numerically stable, leave unusual image features unchanged, and are a superset of order statistic filters. Results are presented for additive noise, blurring, and superresolution.

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Keywords

Mechanical Engineering, Hysteresis, Fabric Mechanics, Fabric Bending, Textile Mechanics, Cloth Simulation, Friction Models

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Citation

URI

http://hdl.handle.net/10012/943

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Theses
Mechanical and Mechatronics Engineering