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Algorithms and software for the design of optimal stack and Boolean filters

Adaptive stack filtering and synthesis resulted in a simple approach to the design of stack filters under the mean absolute error criterion. The estimates of the Boolean function output decisions were derived from the probabilities of each possible binary window sequence. These probabilities were obtained by comparing corrupted and uncorrupted versions of the same image, or parts of an image. It was found that, in most cases, this simplified method produced identical results to those obtained from the method incorporating a check for the stacking property. The method was tested and the filter produced reasonable results.

Fast and efficient algorithms for stack filtering were developed. In addition, a detailed analysis of the behaviour of certain subclasses of stack filters has been conducted. The major results include a full training framework which has been set for optimal Boolean and stack filtering, making optimal design a manageable task. An application of a stack related filter as a code-division multiple-access (CDMA) detector was developed using the matched median filter. In this application, a matched median is used as a detector for direct-sequence multiple-access communication. Its performance is evaluated in a synchronous CDMA environment, where two types of interference are assumed: multiple-access interference and additive impulsive channel noise. Average bit-error probabilities computed using Monte-Carlo simulations have shown the effectiveness of the proposed scheme. The different techniques developed can be implemented in very large scale integration (VLSI). Chip/boards implementing the algorithms may figure in new television sets, video recorder/players, cameras and other imaging devices. The algorithms developed were shown to outperform existing algorithms in the literature through analytic derivation and computer simulations. Other areas that might benefit from the results include medicine, oil exploration and mining, computer vision (particularly fault inspection and on-line tasks).

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Tampere University of Technology
Hermiankatu 12 C
33720 Tampere
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