Edge detection - Image-plane versus digital processingTo optimize edge detection with the familiar Laplacian-of-Gaussian operator, it has become common to implement this operator with a large digital convolution mask followed by some interpolation of the processed data to determine the zero crossings that locate edges. It is generally recognized that this large mask causes substantial blurring of fine detail. It is shown that the spatial detail can be improved by a factor of about four with either the Wiener-Laplacian-of-Gaussian filter or an image-plane processor. The Wiener-Laplacian-of-Gaussian filter minimizes the image-gathering degradations if the scene statistics are at least approximately known and also serves as an interpolator to determine the desired zero crossings directly. The image-plane processor forms the Laplacian-of-Gaussian response by properly combining the optical design of the image-gathering system with a minimal three-by-three lateral-inhibitory processing mask. This approach, which is suggested by Marr's model of early processing in human vision, also reduces data processing by about two orders of magnitude and data transmission by up to an order of magnitude.
Document ID
19880034395
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Huck, Friedrich O. (NASA Langley Research Center Hampton, VA, United States)
Fales, Carl L. (NASA Langley Research Center Hampton, VA, United States)
Park, Stephen K. (NASA Langley Research Center Hampton, VA, United States)
Triplett, Judith A. (Computer Sciences Corp. Hampton, VA, United States)