Symbolic substitution applications to image processing.
Optical hardware for symbolic substitution is under serious consideration for parallel optical computing applications. Symbolic substitution replaces chosen patterns of ones and zeros in a binary array with other chosen patterns of ones and zeros. Implemented with specialized substitution rules, symbolic substitution can be applied to the processing of imges that are represented in binary form. Important operations investigated in this paper are (1) nonlinear filtering operations applied to shapes (morphological transformations, including erosion, dilation, opening, closing) and (2) linear filtering operations applied to binary digital representations of continuous-tone images. Examples presented include a nonlinear noise-removal operation, thresholding, a gradient operator, and convolution. The results of an engineering study of system complexity for linear filtering operations are also presented.
Goodman
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Rhodes
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