Analysis of regularization edge detection in image processing
Allen Gee, David M. Doria · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Regularization is a paradigm for performing image segmentation and edge detection, that can be implemented in a neural network type architecture. Various topics and problems pertaining to the use of regularization for image processing applications are discussed. Topics include data fusion, sensor blur, and the operation on partitioned images. A mathematical analysis of the different topics is presented, including a modification of the original regularization energy functional to perform data fusion.