Download or read book Multi Spectral Signal and Its Processing written by Melinda and published by Syiah Kuala University Press. This book was released on 2022-05-31 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: An event that rises and falls in the peak value of the amplitude of a certain data as measured through the data acquisition process is known as fluctuation. Fluctuations usually occur because the data obtained during the acquisition process is mixed with noise. Therefore, an analytical approach is needed that can process signal fluctuations to identify the characteristics of a material. This study uses an object made of H2O material used as a measurement platform or footing. The other ingredients are H2O mixed with HCl and H2O mixed with NaOH. The initial processing approach is related to the material identification system using a capacitive sensor based on the Impedance Spectroscopy (SI) method. This study aims to develop a method for processing multi-frequency signal fluctuations resulting from data acquisition of Multi-Spectral Capacitive Sensors (MSCS). An approach to representing the observed fluctuations in data acquisition results is based on the statistical mean and standard deviation of the observed noise spectral in a large number of data sets. The results of signal fluctuations are divided into several types, namely: Mean Fluctuation (MF), High Fluctuation (HF), and High High-Fluctuation (HHF). Several approaches are taken for processing fluctuations, such as the data consistency process to see the stability of the data from the initial processing stage. Next is the stage of grouping data with several new approach methods. Another method that we use is the segmentation method which uses several filters that can divide some signals in the form of fluctuation patterns into several segments. From several approach methods that have been carried out, the results show that some of these methods can identify multi-spectral fluctuation patterns so that it will be easier for the next identification process.
Download or read book Signal Theory Methods in Multispectral Remote Sensing written by David A Landgrebe and published by John Wiley & Sons. This book was released on 2005-02-04 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: An outgrowth of the author's extensive experience teaching senior and graduate level students, this is both a thorough introduction and a solid professional reference. * Material covered has been developed based on a 35-year research program associated with such systems as the Landsat satellite program and later satellite and aircraft programs. * Covers existing aircraft and satellite programs and several future programs *An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Download or read book Hyperspectral Data Processing written by Chein-I Chang and published by John Wiley & Sons. This book was released on 2013-04-08 with total page 1180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral Data Processing: Algorithm Design and Analysis is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in two different categories. Most materials covered in this book can be used in conjunction with the author’s first book, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, without much overlap. Many results in this book are either new or have not been explored, presented, or published in the public domain. These include various aspects of endmember extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization, as well as applications to conceal target detection, multispectral imaging, and magnetic resonance imaging. Hyperspectral Data Processing contains eight major sections: Part I: provides fundamentals of hyperspectral data processing Part II: offers various algorithm designs for endmember extraction Part III: derives theory for supervised linear spectral mixture analysis Part IV: designs unsupervised methods for hyperspectral image analysis Part V: explores new concepts on hyperspectral information compression Parts VI & VII: develops techniques for hyperspectral signal coding and characterization Part VIII: presents applications in multispectral imaging and magnetic resonance imaging Hyperspectral Data Processing compiles an algorithm compendium with MATLAB codes in an appendix to help readers implement many important algorithms developed in this book and write their own program codes without relying on software packages. Hyperspectral Data Processing is a valuable reference for those who have been involved with hyperspectral imaging and its techniques, as well those who are new to the subject.
Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Download or read book Signal Theory Methods in Multispectral Remote Sensing written by David A Landgrebe and published by John Wiley & Sons. This book was released on 2003-01-31 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: An outgrowth of the author's extensive experience teaching senior and graduate level students, this is both a thorough introduction and a solid professional reference. * Material covered has been developed based on a 35-year research program associated with such systems as the Landsat satellite program and later satellite and aircraft programs. * Covers existing aircraft and satellite programs and several future programs *An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Download or read book Optical Remote Sensing written by Saurabh Prasad and published by Springer Science & Business Media. This book was released on 2011-03-23 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data. Challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, pattern classification and target recognition, visualization of high dimensional imagery.
Download or read book Multispectral Image Processing And Pattern Recognition written by Jun Shen and published by World Scientific. This book was released on 2001-06-04 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:Introduction (J Shen et al.)3D Articulated Object Understanding, Learning, and Recognition from 2D Images (P S P Wang)On Geometric and Orthogonal Moments (J Shen et al.)Multispectral Image Processing: The Nature Factor (W R Watkins)Detection of Sea Surface Small Targets in Infrared Images Based on Multilevel Filter and Minimum Risk Bayes Test (Y-S Moon et al.)Minimum Description Length Method for Facet Matching (S Maybank & R Fraile)An Integrated Vision System for ALV Navigation (X Ye et al.)Fuzzy Bayesian Networks — A General Formalism for Representation, Inference and Learning with Hybrid Bayesian Networks (H Pan & L Liu)Extraction of Bibliography Information Based on Image of Book Cover (H Yang et al.)Radar Target Recognition Based on Parameterized High Resolution Range Profiles (X Liao & Z Bao) Readership: Computer scientists and electrical engineers. Keywords:
Download or read book Understanding Hyperspectral Image and Signal Processing written by Paul Gader and published by Wiley-Blackwell. This book was released on 2014 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the first texts to focus on investigating, designing and implementing algorithms and computer programs as an introduction to the rapidly evolving field of hyperspectral image and signal processing Covering a range of applications, the authors provide a tutorial on hyperspectral image analysis, focusing on the mathematical, physical, and algorithmic models necessary to devise programs that can extract the useful information that is present in measured hyperspectral data. The amount of data produced by a hyperspectral imaging device can be enormous so care and advanced processing steps must be taken to efficiently and effectively extract information. The reader will learn about these processing steps. The authors take the readers through the topic step-by-step; from the physics foundations of the acquisition process, to the particular algorithms and families of processing tools for classification, feature selection/extraction, visualization, unmixing and classification. Homework problems are provided whereby some problems are mathematical in nature whereas others involve writing brief computer programs. Describes the science and hardware technology underlying hyperspectral image analysis. Focuses on the mathematical and algorithmic concepts for processing hyperspectral data. Teaches readers the conceptual basis of how the hundreds of bands in spectral pixels can be used to gather information about the materials and objects that are present in the field of view (or scene) of a hyperspectral camera. Outlines how to write programs that can find things that are smaller than a single pixel, and in turn details how to write programs that can describe and classify components of a scene. Shows how programs can use spatial information together with spectral information to produce more accurate automated analyses of images. Illustrates methods with a number of examples from across several applications areas, such as estimating the extent of an oil spill, detecting toxic gases around industrial plants or for homeland security, imaging human tissue to aid medical diagnosis. Includes companion website hosted by the authors offering publicly available hyperspectral images and sample programs for processing, as well as Matlab code.
Download or read book Advances in Spectrum Analysis and Array Processing written by Simon S. Haykin and published by . This book was released on 1991 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this, the third and final volume in the series, ten experts investigate a broad range of topics covering fundamental issues and applications in popular and new algorithms for Spectral Analysis and Array Processing. It covers optimal model-based processing techniques for the detection of multiple narrowband sources; two-dimensional angle estimation; direction-finding algorithms for closely-spaced source scenarios; and the use of neural networks in solving source location problems.
Download or read book Signal Processing for Neuroscientists written by Wim van Drongelen and published by Elsevier. This book was released on 2006-12-18 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the 'golden trio' in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. - Multiple color illustrations are integrated in the text - Includes an introduction to biomedical signals, noise characteristics, and recording techniques - Basics and background for more advanced topics can be found in extensive notes and appendices - A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670
Download or read book Hyperspectral Imaging written by Chein-I Chang and published by Springer Science & Business Media. This book was released on 2003-07-31 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores the application of statistical signal processing to hyperspectral imaging and further develops non-literal (spectral) techniques for subpixel detection and mixed pixel classification. This text is the first of its kind on the topic anc can be considered a recipe book offering various techniques for hyperspectral data exploitation.
Download or read book Signal Processing for Remote Sensing written by C.H. Chen and published by CRC Press. This book was released on 2008 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuing in the footsteps of the pioneering first edition, Signal and Image Processing for Remote Sensing, Second Edition explores the most up-to-date signal and image processing methods for dealing with remote sensing problems. Although most data from satellites are in image form, signal processing can contribute significantly in extracting information from remotely sensed waveforms or time series data. This book combines both, providing a unique balance between the role of signal processing and image processing. Featuring contributions from worldwide experts, this book continues to emphasize mathematical approaches. Not limited to satellite data, it also considers signals and images from hydroacoustic, seismic, microwave, and other sensors. Chapters cover important topics in signal and image processing and discuss techniques for dealing with remote sensing problems. Each chapter offers an introduction to the topic before delving into research results, making the book accessible to a broad audience. This second edition reflects the considerable advances that have occurred in the field, with 23 of 27 chapters being new or entirely rewritten. Coverage includes new mathematical developments such as compressive sensing, empirical mode decomposition, and sparse representation, as well as new component analysis methods such as non-negative matrix and tensor factorization. The book also presents new experimental results on SAR and hyperspectral image processing. The emphasis is on mathematical techniques that will far outlast the rapidly changing sensor, software, and hardware technologies. Written for industrial and academic researchers and graduate students alike, this book helps readers connect the "dots" in image and signal processing. New in This Edition The second edition includes four chapters from the first edition, plus 23 new or entirely rewritten chapters, and 190 new figures. New topics covered include: Compressive sensing The mixed pixel problem with hyperspectral images Hyperspectral image (HSI) target detection and classification based on sparse representation An ISAR technique for refocusing moving targets in SAR images Empirical mode decomposition for signal processing Feature extraction for classification of remote sensing signals and images Active learning methods in classification of remote sensing images Signal subspace identification of hyperspectral data Wavelet-based multi/hyperspectral image restoration and fusion The second edition is not intended to replace the first edition entirely and readers are encouraged to read both editions of the book for a more complete picture of signal and image processing in remote sensing. See Signal and Image Processing for Remote Sensing (CRC Press 2006).
Download or read book Principles and Practices of Satellite Multispectral Image Mapping in the U S Geological Survey written by Richard D. Sanchez and published by . This book was released on 1986 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Workshop for Environmental Applications of Multispectral Imagery written by and published by . This book was released on 1975 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Control and Signal Processing Applications for Mobile and Aerial Robotic Systems written by Sergiyenko, Oleg and published by IGI Global. This book was released on 2019-10-25 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology continues to develop, certain innovations are beginning to cover a wide range of applications, specifically mobile robotic systems. The boundaries between the various automation methods and their implementations are not strictly defined, with overlaps occurring. Specificity is required regarding the research and development of android systems and how they pertain to modern science. Control and Signal Processing Applications for Mobile and Aerial Robotic Systems is a pivotal reference source that provides vital research on the current state of control and signal processing of portable robotic designs. While highlighting topics such as digital systems, control theory, and mathematical methods, this publication explores original inquiry contributions and the instrumentation of mechanical systems in the industrial and scientific fields. This book is ideally designed for technicians, engineers, industry specialists, researchers, academicians, and students seeking current research on today’s execution of mobile robotic schemes.
Download or read book Multivariate Image Processing written by Jocelyn Chanussot and published by Wiley-ISTE. This book was released on 2009-12-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate imagery is now a very common tool in numerous applications, ranging from satellite remote sensing and astrophysics to biomedical imagery, monitoring of the environment or industrial inspection. Multivariate must be understood in th emost general way: color and multispectral imaging, but also multimodal, multisource or multitemporal imagery. In all the cases, the multivariate image corresponds to a set of standard grey level images. The availability of the additional diversity, be it spectral temporal and s.o., provides an invaluable source of information, enabling to consider a wide range of new applications. However, in order to address these applications, theoretical developments are required in terms of signal and image processing, or, more generally speaking, information processing. As a matter of fact, most of the standard algorithms designed for grey level images do not generalize easily to multidimensional spaces and some specific derivations are required. This book aims at presenting the most recent advances in signal and image processing for the analysis of multivariate data. It should be helpful for electrical engineers, PhD students and researcher working in the field of signal processing, but also for any engineer dealing with some specific application where multidimensional data are processed.
Download or read book Real Time Recursive Hyperspectral Sample and Band Processing written by Chein-I Chang and published by Springer. This book was released on 2017-04-23 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016.
