Biological visual systems employ massively parallel processing to
perform real-world visual tasks in real time. A key to this remarkable
performance seems to be that biological systems construct
representations of their visual image data at multiple scales. A
Pyramid Framework for Early Vision describes a multiscale, or
`pyramid', approach to vision, including its theoretical foundations, a
set of pyramid-based modules for image processing, object detection,
texture discrimination, contour detection and processing, feature
detection and description, and motion detection and tracking. It also
shows how these modules can be implemented very efficiently on
hypercube-connected processor networks.
A Pyramid Framework for Early Vision is intended for both students of
vision and vision system designers; it provides a general approach to
vision systems design as well as a set of robust, efficient vision
modules.