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Hexagonal Image Processing provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates. Digital image processing is currently dominated by the use of square sampling lattices, however, hexagonal sampling lattices can also be used to define digital images. The strengths offered by hexagonal lattices over square lattices are considerable: • higher packing density, • uniform connectivity of points (pixels) in the lattice, • better angular resolution by virtue of having more nearest neighbours, and • superlative representation of curves. The utility of the HIP framework is demonstrated by implementing several basic image processing techniques (for the spatial and frequency domain) and some applications. The HIP framework serves as a tool for comparing processing of images defined on a square vs hexagonal grid, to determine their relative merits and demerits. The theory and algorithms covered are supplemented by attention to practical details such as accommodating hardware that support only images sampled on a square lattice. Including a Foreword written by Professor Narendra Ahuja, an eminent researcher in the field of Image Processing and Computer Vision, the book’s fresh approach to the subject offers insight and workable know-how to both researchers and postgraduates.

Image processing --- Hexagons. --- Digital techniques. --- Six-sided polygon --- Polygons --- Digital image processing --- Digital electronics --- Computer vision. --- Computer science. --- Optics, Lasers, Photonics, Optical Devices. --- Image Processing and Computer Vision. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Media Design. --- Informatics --- Science --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Lasers. --- Photonics. --- Optical data processing. --- Multimedia systems . --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- New optics --- Optics --- Light amplification by stimulated emission of radiation --- Masers, Optical --- Optical masers --- Light amplifiers --- Light sources --- Optoelectronic devices --- Nonlinear optics --- Optical parametric oscillators --- Optical equipment

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Hexagonal Image Processing provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates. Digital image processing is currently dominated by the use of square sampling lattices, however, hexagonal sampling lattices can also be used to define digital images. The strengths offered by hexagonal lattices over square lattices are considerable: ¢ higher packing density, ¢ uniform connectivity of points (pixels) in the lattice, ¢ better angular resolution by virtue of having more nearest neighbours, and ¢ superlative representation of curves. The utility of the HIP framework is demonstrated by implementing several basic image processing techniques (for the spatial and frequency domain) and some applications. The HIP framework serves as a tool for comparing processing of images defined on a square vs hexagonal grid, to determine their relative merits and demerits. The theory and algorithms covered are supplemented by attention to practical details such as accommodating hardware that support only images sampled on a square lattice. Including a Foreword written by Professor Narendra Ahuja, an eminent researcher in the field of Image Processing and Computer Vision, the book's fresh approach to the subject offers insight and workable know-how to both researchers and postgraduates.

Journalism --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- DIP (documentimage processing) --- beeldverwerking --- image processing --- grafische vormgeving --- media --- KI (kunstmatige intelligentie)