The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-IPI-670

“Nonlinear Optical Image Processing with Halftone Screens”

by Stephen Robert Dashiell

May 1976

Coherent optical systems are of interest in image or data processing because of their ability to rapidly handle large bandwidth data in parallel. They have been restricted to performing linear operations such as Fourier transformation and convolution, due to the inherent linear nature of an optical system at low power levels. In this dissertation, the combination of a nonlinear halftoning step followed by band pass spatial filtering to yield a specific nonlinear intensity function is explored.

A general analysis of the problem assuming infinite copy film gamma and saturation density is made. A constructive algorithm for designing a halftone cell shape and selecting the diffraction order to yield very general types of nonmonotonic nonlinearities is presented. Numerous examples of the synthesis procedure are given.

The design of non-monotonic halftone cells which allow a non-monotonic nonlinearity with an arbitrary number of changes of sign in slope to be obtained in the first diffraction order is considered. An iterative algorithm suitable for computer implementation, and numerous examples of halftone cells designed with this algorithm are given.

The effects of allowing the film gamma and saturation density to become finite are analyzed, and a technique for compensating a priori for some of the resulting degradations is given.

Experimental results with general halftone screens made on a plotting flatbed microdensitometer are presented. Logarithmic, exponential, and level slice characteristics have been achieved with monotonic cells. Intensity notch filter and quantization characteristics have been achieved with non-monotonic cells, Other generalizations of the technique are discussed, including the possibility of real-time nonlinear processing with optical input transducers.

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