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Signal Processing Magazine, IEEE

Issue 1 • Date Jan. 2014

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Displaying Results 1 - 24 of 24
  • [Front cover]

    Publication Year: 2014 , Page(s): C1
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  • [Table of contents]

    Publication Year: 2014 , Page(s): 1
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  • Staff Listing

    Publication Year: 2014 , Page(s): 2
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  • Risky Long-Term Research: Two Success Stories in Audio Signal Processing [From the Editor]

    Publication Year: 2014 , Page(s): 4
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  • A Lasting Journey [President's Message]

    Publication Year: 2014 , Page(s): 6
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  • Top Downloads in IEEE Xplore [Reader's Choice]

    Publication Year: 2014 , Page(s): 8 - 9
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  • New Members-at-Large, Directors-at-Large, and Class of Distinguished Lecturers for 2014 [Society News]

    Publication Year: 2014 , Page(s): 10 - 21
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  • Fresh approaches promise wireless quality and reliability improvements [Special Reports]

    Publication Year: 2014 , Page(s): 15 - 18
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  • Automotive Industry Is a Key Component to the Success of the DSP Sector [Special Reports]

    Publication Year: 2014 , Page(s): 18 - 21
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  • Signal and Image Processing in Hyperspectral Remote Sensing [From the Guest Editors]

    Publication Year: 2014 , Page(s): 22 - 23
    Cited by:  Papers (1)
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  • Detection Algorithms in Hyperspectral Imaging Systems: An Overview of Practical Algorithms

    Publication Year: 2014 , Page(s): 24 - 33
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (4074 KB) |  | HTML iconHTML  

    Hyperspectral imaging applications are many and span civil, environmental, and military needs. Typical examples include the detection of specific terrain features and vegetation, mineral, or soil types for resource management; detecting and characterizing materials, surfaces, or paints; the detection of man-made materials in natural backgrounds for the purpose of search and rescue; the detection o... View full abstract»

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  • Hyperspectral Target Detection : An Overview of Current and Future Challenges

    Publication Year: 2014 , Page(s): 34 - 44
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2964 KB) |  | HTML iconHTML  

    Over the last decade, hyperspectral imagery (HSI) obtained by remote sensing systems has provided significant information about the spectral characteristics of the materials in the scene. Typically, a hyperspectral spectrometer provides hundreds of narrow contiguous bands over a wide range of the electromagnetic spectrum. Hyperspectral sensors measure the reflective (or emissive) properties of obj... View full abstract»

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  • Advances in Hyperspectral Image Classification: Earth Monitoring with Statistical Learning Methods

    Publication Year: 2014 , Page(s): 45 - 54
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2700 KB) |  | HTML iconHTML  

    The technological evolution of optical sensors over the last few decades has provided remote sensing analysts with rich spatial, spectral, and temporal information. In particular, the increase in spectral resolution of hyperspectral images (HSIs) and infrared sounders opens the doors to new application domains and poses new methodological challenges in data analysis. HSIs allow the characterizatio... View full abstract»

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  • Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning

    Publication Year: 2014 , Page(s): 55 - 66
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2173 KB) |  | HTML iconHTML  

    Advances in hyperspectral sensing provide new capability for characterizing spectral signatures in a wide range of physical and biological systems, while inspiring new methods for extracting information from these data. HSI data often lie on sparse, nonlinear manifolds whose geometric and topological structures can be exploited via manifold-learning techniques. In this article, we focused on demon... View full abstract»

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  • A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing

    Publication Year: 2014 , Page(s): 67 - 81
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1529 KB) |  | HTML iconHTML  

    Blind hyperspectral unmixing (HU), also known as unsupervised HU, is one of the most prominent research topics in signal processing (SP) for hyperspectral remote sensing [1], [2]. Blind HU aims at identifying materials present in a captured scene, as well as their compositions, by using high spectral resolution of hyperspectral images. It is a blind source separation (BSS) problem from a SP viewpo... View full abstract»

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  • Nonlinear Unmixing of Hyperspectral Images: Models and Algorithms

    Publication Year: 2014 , Page(s): 82 - 94
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2075 KB) |  | HTML iconHTML  

    When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM). However, the LMM may be not valid, and other nonlinear models need to be considered, for instance, when there are multiscattering effects or intimate interactions. Consequently, over the last few years, several signi... View full abstract»

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  • Endmember Variability in Hyperspectral Analysis: Addressing Spectral Variability During Spectral Unmixing

    Publication Year: 2014 , Page(s): 95 - 104
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1958 KB) |  | HTML iconHTML  

    Variable illumination and environmental, atmospheric, and temporal conditions cause the measured spectral signature for a material to vary within hyperspectral imagery. By ignoring these variations, errors are introduced and propagated throughout hyperspectral image analysis. To develop accurate spectral unmixing and endmember estimation methods, a number of approaches that account for spectral va... View full abstract»

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  • Compressive Coded Aperture Spectral Imaging: An Introduction

    Publication Year: 2014 , Page(s): 105 - 115
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2932 KB) |  | HTML iconHTML  

    Imaging spectroscopy involves the sensing of a large amount of spatial information across a multitude of wavelengths. Conventional approaches to hyperspectral sensing scan adjacent zones of the underlying spectral scene and merge the results to construct a spectral data cube. Push broom spectral imaging sensors, for instance, capture a spectral cube with one focal plane array (FPA) measurement per... View full abstract»

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  • Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection

    Publication Year: 2014 , Page(s): 116 - 126
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (914 KB) |  | HTML iconHTML  

    Hyperspectral imaging is a powerful technology for remotely inferring the material properties of the objects in a scene of interest. Hyperspectral images consist of spatial maps of light intensity variation across a large number of spectral bands or wavelengths; alternatively, they can be thought of as a measurement of the spectrum of light transmitted or reflected from each spatial location in a ... View full abstract»

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  • Image Inpainting : Overview and Recent Advances

    Publication Year: 2014 , Page(s): 127 - 144
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (5869 KB) |  | HTML iconHTML  

    Image inpainting refers to the process of restoring missing or damaged areas in an image. This field of research has been very active over recent years, boosted by numerous applications: restoring images from scratches or text overlays, loss concealment in a context of impaired image transmission, object removal in a context of editing, or disocclusion in image-based rendering (IBR) of viewpoints ... View full abstract»

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  • Royalty-Free Video Coding Standards in MPEG [Standards in a Nutshell]

    Publication Year: 2014 , Page(s): 145 - 155
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (297 KB) |  | HTML iconHTML  

    On 7 March 2013, the Moving Picture Experts Group Licensing Association (MPEG LA) and Google announced that they have entered into an agreement granting Google a license to techniques, if the patents in MPEG LA might be essential to VP8. Under this agreement, hardware and software companies are free to use the VP8 technology when developing their own products. Considering that it is now common to ... View full abstract»

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  • Securing Digital Reputation in Online Social Media [Applications Corner]

    Publication Year: 2014 , Page(s): 149 - 155
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (989 KB) |  | HTML iconHTML  

    As computing and communication systems evolve rapidly and ubiquitously, it has become convenient and almost effortless for individual users to generate, share, and exchange information on online social media. Through online social media, a wide range of digital content, which covers blogging, forums, reviews, social networking, question-answer databases, digital video, mobile phone photography, an... View full abstract»

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  • [Dates Ahead]

    Publication Year: 2014 , Page(s): 156
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  • The Discipline of Signal Processing: Part 2 [Reflections]

    Publication Year: 2014 , Page(s): 157 - 159
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2004 KB) |  | HTML iconHTML  

    Discusses the field of signal processing engineering and reports on applications and technologies supported by its use. View full abstract»

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Aims & Scope

IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest. Its coverage ranges from fundamental principles to practical implementation, reflecting the multidimensional facets of interests and concerns of the community. Its mission is to bring up-to-date, emerging and active technical developments, issues, and events to the research, educational, and professional communities. It is also the main Society communication platform addressing important issues concerning all members.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Min Wu
University of Maryland, College Park
United States 

http://www/ece.umd.edu/~minwu/