A fast algorithm for cellular logic operations on sequential machines
This paper describes an algorithm to efficiently realize repeated Cellular Logic operations. These Cellular Logic operations include erosions and dilations as well as skeletonization (topology-preserving shrinking) and propagation procedures. In the proposed method only those image pixels which might change in an iteration are processed, based on the changed pixels in the previous iteration. Processing times for solid objects (maximum diameter 40 to 200 pixels, 256 x 256 image) on a 10 Mhz Motorola 68000 system range from 250 ms to 400 ms per iteration. A simpler suboptimal method is also described which is 2 to 3 times slower.
We study a new technique for optimal data compression subject to conditions of causality and different types of memory. The technique is based on the assumption that some information about compressed data can be obtained from a solution of the associated problem without constraints of causality and memory. This allows us to consider two separate problem related to compression and de- compression subject to those constraints. Their solutions are given and the analysis of the associated errors is provided. Keywords—stochastic signals, optimization problems in signal processing.