Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection (Advances in Computer Vision and Pattern Recognition)

This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

Computers & Technology

Ünsalan, Cem

Boyer, Kim L.

Computer Science

Springer

This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

This book describes the design of a complete, flexible system for perceptual organization in computer vision using graph theoretic techniques, voting methods, and an extension of the Bayesian networks called perceptual inference networks (PINs). The PIN, which forms the heart of the system and which is based on Bayesian probabilistic networks, exhibits potential for application in several areas of computer vision as well as a range of other spatial reasoning tasks. The text includes a highly comprehensive, classificatory review of prior work in perceptual organization and, within that framework, identifies key areas for future work by the computer vision research community.

Computer Perceptual Organization in Computer Vision (Machine Perception and Artificial Intelligence)

Sarkar, Sudeep

World Scientific Publishing Company

This book addresses the range image registration problem for automatic 3D model construction. The focus is on obtaining highly precise alignments between different view pairs of the same object to avoid 3D model distortions; in contrast to most prior work, the view pairs may exhibit relatively little overlap and need not be prealigned. To this end, a novel effective evaluation metric for registration, the Surface Interpenetration Measure (SIM) is defined. This measure quantifies the interleaving of two surfaces as their alignment is refined, putting the qualitative evaluation of "splotchiness," often used in reference to renderings of the aligned surfaces, onto a solid mathematical footing. The SIM is shown to be superior to mean squared error (i.e. more sensitive to fine scale changes) in controlling the final stages of the alignment process.The authors go on to combine the SIM with Genetic Algorithms (GAs) to develop a robust approach for range image registration. The results confirm that this technique achieves precise surface registration with no need for prealignment, as opposed to methods based on the Iterative Closest Point (ICP) algorithm, the most popular to date. Thorough experimental results including an extensive comparative study are presented and enhanced GA-based approaches to improve the registration still further are proposed. The authors also develop a global multiview registration technique using the GA-based approach. The results show considerable promise in terms of accuracy for 3D modeling.

ROBUST RANGE IMAGE REGISTRATION USING GENETIC ALGORITHMS AND THE SURFACE INTERPENETRATION MEASURE (Machine Perception and Artificial Intelligence)

Silva, Luciano

Bellon, Olga R P

See the best price to sell, buy, or rent books by Boyer, Kim L.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Boyer, Kim L.

See the best price to sell, buy, or rent books by Boyer, Kim L.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection (Advances in Computer Vision and Pattern Recognition)

Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection (Advances in Computer Vision and Pattern Recognition)

Computer Perceptual Organization in Computer Vision (Machine Perception and Artificial Intelligence)

ROBUST RANGE IMAGE REGISTRATION USING GENETIC ALGORITHMS AND THE SURFACE INTERPENETRATION MEASURE (Machine Perception and Artificial Intelligence)