A pyramid framework for early vision: multiresolutional computer vision
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.
The volume 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.
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A Pyramid Framework for Early Vision: Multiresolutional Computer Vision
Jean-Michel Jolion,Azriel Rosenfeld
No preview available - 2011
affine transformation algorithm applications approach background binary image blob blob detection bottom-up Burt cell classic clusters communication network compact object complete computer vision connected components Connection Machine constraint contrast curves defined described detection and delineation early vision edge detection edge pixels energy estimate example extracted feature space Figure filter fractal dimension frequency Gaussian global information gray level hierarchical multiresolution hierarchical processing histogram Hough space Hough transform human visual system IEEE image block Image Processing image segmentation input image iterations kernel labeled Laplacian level values Machine masks mathematical morphology modules motion multiresolution representation neighborhood neighbors node operator optical flow optimal original image parallel parameters parents processing mode processors proposed pyramid architecture pyramid based pyramid computer receptive field recursively regions resolution root Rosenfeld scale-space Section 2.2 shown signal SIMD smoothing spatial structure sub-images surface techniques texture trees vector vision system