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Image Fusion in Remote Sensing, Azarang, Arian Kehtarnavaz, Nasser


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Цена: 3912.00р.
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Автор: Azarang, Arian Kehtarnavaz, Nasser
Название:  Image Fusion in Remote Sensing
ISBN: 9783031011283
Издательство: Springer
Классификация:



ISBN-10: 3031011287
Обложка/Формат: Paperback
Страницы: 81
Вес: 0.20 кг.
Дата издания: 18.02.2021
Серия: Synthesis lectures on image, video, and multimedia processing
Язык: English
Иллюстрации: Xi, 81 p.
Размер: 235 x 191
Читательская аудитория: Professional & vocational
Подзаголовок: Conventional and deep learning approaches
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites.


Satellite Radar Interferometry

Автор: V. B. H. (Gini) Ketelaar
Название: Satellite Radar Interferometry
ISBN: 9048181259 ISBN-13(EAN): 9789048181254
Издательство: Springer
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Цена: 18284.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book investigates the applicability of satellite radar interferometry (InSAR) for deformation monitoring. The presented methodologies are demonstrated in an integrated way for the entire northern part of the Netherlands and a part of Germany.

Big Data Analytics for Satellite Image Processing and Remote Sensing

Автор: P. Swarnalatha, Prabu Sevugan
Название: Big Data Analytics for Satellite Image Processing and Remote Sensing
ISBN: 1522536434 ISBN-13(EAN): 9781522536437
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 31324.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization.Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.

Remote Sensing Image Fusion

Автор: Pohl, Christine , van Genderen, John
Название: Remote Sensing Image Fusion
ISBN: 0367873613 ISBN-13(EAN): 9780367873615
Издательство: Taylor&Francis
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Цена: 8114.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Remote Sensing Image Fusion: A Practical Guide gives an introduction to remote sensing image fusion providing an overview on the sensors and applications. It describes data selection, application requirements and the choice of a suitable image fusion technique. It comprises a diverse selection of successful image fusion cases th

Image Fusion in Remote Sensing: Conventional and Deep Learning Approaches

Автор: Azarang Arian, Kehtarnavaz Nasser
Название: Image Fusion in Remote Sensing: Conventional and Deep Learning Approaches
ISBN: 1636390765 ISBN-13(EAN): 9781636390765
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 8870.00 р.
Наличие на складе: Нет в наличии.

Описание: Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites. This book addresses image fusion approaches for remote sensing applications. Both conventional and deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches include component substitution, multi-resolution, and model-based algorithms. Then, the recently developed deep learning approaches involving single-objective and multi-objective loss functions are discussed. Experimental results are provided comparing conventional and deep learning approaches in terms of both low-resolution and full-resolution objective metrics that are commonly used in remote sensing. The book is concluded by stating anticipated future trends in pansharpening or image fusion in remote sensing.

Multispectral Image Analysis Using the Object-Oriented Paradigm

Автор: KUMAR NAVULUR
Название: Multispectral Image Analysis Using the Object-Oriented Paradigm
ISBN: 0367446243 ISBN-13(EAN): 9780367446246
Издательство: Taylor&Francis
Рейтинг:
Цена: 10104.00 р.
Наличие на складе: Поставка под заказ.

Описание: Featuring various hands-on examples to provide understanding of this new approach, Multispectral Image Analysis Using the Object-Oriented Paradigm shows how to extract information from remotely sensed data for applications in agriculture, visual simulation, civil government mapping, forestry, fire risk assessment, and more. This bo

Thermal Infrared Remote Sensing

Автор: Claudia Kuenzer; Stefan Dech
Название: Thermal Infrared Remote Sensing
ISBN: 9400766386 ISBN-13(EAN): 9789400766389
Издательство: Springer
Рейтинг:
Цена: 30745.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Here is a detailed review of thermal infrared remote sensing, covering basic principles and applications in land and sea surface temperature dynamics, urban heat islands, forest fires, volcanic activity, underground coal fires, geothermal systems and more.

Mathematical Models for Remote Sensing Image Processing

Автор: Gabriele Moser; Josiane Zerubia
Название: Mathematical Models for Remote Sensing Image Processing
ISBN: 3319663283 ISBN-13(EAN): 9783319663289
Издательство: Springer
Рейтинг:
Цена: 22359.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book maximizes reader insights into the field of mathematical models and methods for the processing of two-dimensional remote sensing images. It presents a broad analysis of the field, encompassing passive and active sensors, hyperspectral images, synthetic aperture radar (SAR), interferometric SAR, and polarimetric SAR data. At the same time, it addresses highly topical subjects involving remote sensing data types (e.g., very high-resolution images, multiangular or multiresolution data, and satellite image time series) and analysis methodologies (e.g., probabilistic graphical models, hierarchical image representations, kernel machines, data fusion, and compressive sensing) that currently have primary importance in the field of mathematical modelling for remote sensing and image processing. Each chapter focuses on a particular type of remote sensing data and/or on a specific methodological area, presenting both a thorough analysis of the previous literature and a methodological and experimental discussion of at least two advanced mathematical methods for information extraction from remote sensing data. This organization ensures that both tutorial information and advanced subjects are covered. With each chapter being written by research scientists from (at least) two different institutions, it offers multiple professional experiences and perspectives on each subject. The book also provides expert analysis and commentary from leading remote sensing and image processing researchers, many of whom serve on the editorial boards of prestigious international journals in these fields, and are actively involved in international scientific societies. Providing the reader with a comprehensive picture of the overall advances and the current cutting-edge developments in the field of mathematical models for remote sensing image analysis, this book is ideal as both a reference resource and a textbook for graduate and doctoral students as well as for remote sensing scientists and practitioners.

Remote Sensing Digital Image Analysis

Автор: John A. Richards
Название: Remote Sensing Digital Image Analysis
ISBN: 3642441017 ISBN-13(EAN): 9783642441011
Издательство: Springer
Рейтинг:
Цена: 11179.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Now in an updated edition that adds new and revised material, this book offers a comprehensive introduction to quantitative evaluation of satellite and aircraft derived remotely retrieved data. Each chapter includes practice problems.

Mathematical Models for Remote Sensing Image Processing

Автор: Gabriele Moser; Josiane Zerubia
Название: Mathematical Models for Remote Sensing Image Processing
ISBN: 3319882198 ISBN-13(EAN): 9783319882192
Издательство: Springer
Рейтинг:
Цена: 22359.00 р.
Наличие на складе: Поставка под заказ.

Описание: This book maximizes reader insights into the field of mathematical models and methods for the processing of two-dimensional remote sensing images. It presents a broad analysis of the field, encompassing passive and active sensors, hyperspectral images, synthetic aperture radar (SAR), interferometric SAR, and polarimetric SAR data. At the same time, it addresses highly topical subjects involving remote sensing data types (e.g., very high-resolution images, multiangular or multiresolution data, and satellite image time series) and analysis methodologies (e.g., probabilistic graphical models, hierarchical image representations, kernel machines, data fusion, and compressive sensing) that currently have primary importance in the field of mathematical modelling for remote sensing and image processing. Each chapter focuses on a particular type of remote sensing data and/or on a specific methodological area, presenting both a thorough analysis of the previous literature and a methodological and experimental discussion of at least two advanced mathematical methods for information extraction from remote sensing data. This organization ensures that both tutorial information and advanced subjects are covered. With each chapter being written by research scientists from (at least) two different institutions, it offers multiple professional experiences and perspectives on each subject. The book also provides expert analysis and commentary from leading remote sensing and image processing researchers, many of whom serve on the editorial boards of prestigious international journals in these fields, and are actively involved in international scientific societies. Providing the reader with a comprehensive picture of the overall advances and the current cutting-edge developments in the field of mathematical models for remote sensing image analysis, this book is ideal as both a reference resource and a textbook for graduate and doctoral students as well as for remote sensing scientists and practitioners.

Image Fusion in Remote Sensing: Conventional and Deep Learning Approaches

Автор: Azarang Arian, Kehtarnavaz Nasser
Название: Image Fusion in Remote Sensing: Conventional and Deep Learning Approaches
ISBN: 1636390749 ISBN-13(EAN): 9781636390741
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 5683.00 р.
Наличие на складе: Нет в наличии.

Описание: Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites. This book addresses image fusion approaches for remote sensing applications. Both conventional and deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches include component substitution, multi-resolution, and model-based algorithms. Then, the recently developed deep learning approaches involving single-objective and multi-objective loss functions are discussed. Experimental results are provided comparing conventional and deep learning approaches in terms of both low-resolution and full-resolution objective metrics that are commonly used in remote sensing. The book is concluded by stating anticipated future trends in pansharpening or image fusion in remote sensing.

Remote Sensing Image Processing

Автор: Camps Gustavo, Camps-Valls Gustavo
Название: Remote Sensing Image Processing
ISBN: 1608458199 ISBN-13(EAN): 9781608458196
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 5643.00 р.
Наличие на складе: Нет в наличии.

Описание: The remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms. This book comprehensively covers some of these fields.


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