Theory and Applications of Digital Image Processing and Pattern Recognition

The processing of digital images by computers constitutes a new challenge to computer science because a huge amount of data has to be processed in extremely short time. This necessitates the development of new parallel process and operation structures to achieve acceptable response times. The tasks of preprocessing steps include the removal of noise, the calibration of the images and the enhancement of image quality. The resulting images are input to procedures that transform their contents into a compact form suitable within the scope of the given application. The ultimate goal is to make a rich set of methods for image analysis available and to apply them to different areas. However, in spite of all progress, the efficiency of any technical systems still falls behind the capabilities of human information processing where typical vision tasks (e.g. storing and retrieving of pictures) can be performed nearly without any conscious effort. not assigned KP: Department of Mathematics, not assigned KP: Institute for Software Technology and Parallel Systems, not assigned KP: Institute for Systems Science, not assigned KP: Institute of National Surveying and Engineering Geodesy not assigned KP: Institute of Photogrammetry and Remote Sensing, not assigned KP: Institute of Surveying, Remote Sensing and Landinformation, not assigned KP: University of Tennessee and at the Oak Ridge National Laboratory (ORNL)