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Night Vision Processing and Understanding [electronic resource] / by Lianfa Bai, Jing Han, Jiang Yue.

Author/Creator:
Bai, Lianfa author., Author,
Publication:
Singapore : Springer Singapore : Imprint: Springer, 2019.
Format/Description:
Book
1 online resource (XVI, 266 pages) : 177 illustrations, 123 illustrations in color.
Edition:
1st ed. 2019.
Series:
Computer Science (Springer-11645)
Contained In:
Springer eBooks
Status/Location:
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Details

Subjects:
Optical data processing.
Data mining.
Global analysis (Mathematics).
Manifolds (Mathematics).
Algorithms.
Artificial intelligence.
Local subjects:
Image Processing and Computer Vision. (search)
Data Mining and Knowledge Discovery. (search)
Global Analysis and Analysis on Manifolds. (search)
Algorithms. (search)
Artificial Intelligence. (search)
System Details:
text file PDF
Summary:
This book systematically analyses the latest insights into night vision imaging processing and perceptual understanding as well as related theories and methods. The algorithm model and hardware system provided can be used as the reference basis for the general design, algorithm design and hardware design of photoelectric systems. Focusing on the differences in the imaging environment, target characteristics, and imaging methods, this book discusses multi-spectral and video data, and investigates a variety of information mining and perceptual understanding algorithms. It also assesses different processing methods for multiple types of scenes and targets. Taking into account the needs of scientists and technicians engaged in night vision optoelectronic imaging detection research, the book incorporates the latest international technical methods. The content fully reflects the technical significance and dynamics of the new field of night vision. The eight chapters cover topics including multispectral imaging, Hadamard transform spectrometry; dimensionality reduction, data mining, data analysis, feature classification, feature learning; computer vision, image understanding, target recognition, object detection and colorization algorithms, which reflect the main areas of research in artificial intelligence in night vision. The book enables readers to grasp the novelty and practicality of the field and to develop their ability to connect theory with real-world applications. It also provides the necessary foundation to allow them to conduct research in the field and adapt to new technological developments in the future.
Contents:
Introduction
High Snr Hyperspectral Night Vision Image Acquisition with Multiplexing
Multi-Visual Task Based on Night Vision Data Structure and Feature Analysis
Feature Classification Based on Manifold Dimension Reduction for Night Vision Images
Night Vision Data Classification Based on Sparse Representation and Random Subspace
Learning Based Night Vision Image Recognition and Object Detection
Non-Learning Based Motion Cognitive Detection and Self-Adaptable Tracking for Night Vision Videos
The Colorization of Low Light Level Image Based on the Rule Mining.
Contributor:
Han, Jing, author., Author,
Yue, Jiang, author., Author,
SpringerLink (Online service)
Other format:
Printed edition:
Printed edition:
ISBN:
978-981-13-1669-2
9789811316692
9789811316685 (Printed edition)
9789811316708 (Printed edition)
Publisher Number:
10.1007/978-981-13-1669-2 doi
Access Restriction:
Restricted for use by site license.