Biological visual systems employ parallel processing to perform real-world visual tasks in real time. A key to this performance seems to be that biological systems construct representations of their visual image data at multiple scales. This text 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 efficiently implemented on hypercube-connected processor networks. The text 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.