A microcomputer-based algorithm for digitized image simplification and information extraction

Spatial analysis of objects often requires significant image simplification prior to information extraction and application of a decision-making algorithm. Much decision making based on images (e.g., histologic diagnoses) requires identifying patterns in complex backgrounds (image simplification) and comparison of those patterns to other patterns (decision making). Automated extraction of information from images commonly requires the extraction system to recognize edges (contours) of structures and their internal discontinuities (such as gradations in density) and to selectively suppress irrelevant data in order to conserve memory and speed computation; data from homogeneous image areas occupy memory, but are noncontributory or redundant. This paper describes the development of a microcomputer-based algorithm that deletes all homogeneous information from overlaid digitized images, generating contours in the place of nonhomogeneities. Contours corresponding to different areas or objects depend on color differences between an object and its surroundings. Any set of contours can be deleted almost instantaneously, leaving only those of interest. Contours can be highlighted by an operator-driven interactive process if desired and can be deleted and retrieved until an appropriate image is obtained. This contour-generating and image-simplification algorithm facilitates three-dimensional reconstruction of an object from serial images by reducing the number of calculations required and yielding a cleaner final image.