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In digital imaging, a pixel, or pel, (picture element) is a single point in a raster image, or the smallest addressable screen element in a display device; it is the smallest unit of picture that can be represented or controlled. (Wikipedia.org)

Conferences related to Pixel

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2019 20th International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors XXXIII (TRANSDUCERS & EUROSENSORS XXXIII)

The world's premiere conference in MEMS sensors, actuators and integrated micro and nano systems welcomes you to attend this four-day event showcasing major technological, scientific and commercial breakthroughs in mechanical, optical, chemical and biological devices and systems using micro and nanotechnology.The major areas of activity in the development of Transducers solicited and expected at this conference include but are not limited to: Bio, Medical, Chemical, and Micro Total Analysis Systems Fabrication and Packaging Mechanical and Physical Sensors Materials and Characterization Design, Simulation and Theory Actuators Optical MEMS RF MEMS Nanotechnology Energy and Power

2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Early Vision and Sensors Color, Illumination and Texture Segmentation and Grouping Motion and TrackingStereo and Structure from Motion Image -Based Modeling Physics -Based Modeling Statistical Methods and Learning in VisionVideo Surveillance and Monitoring Object, Event and Scene Recognition Vision - Based Graphics Image and Video RetrievalPerformance Evaluation Applications

2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA)

Industrial Informatics, Computational Intelligence, Control and Systems, Cyber-physicalSystems, Energy and Environment, Mechatronics, Power Electronics, Signal and InformationProcessing, Network and Communication Technologies

2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC)

IEEE CCNC 2018 will present the latest developments and technical solutions in the areas of home networking, consumer networking, enabling technologies (such as middleware) and novel applications and services. The conference will include a peer-reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions

2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)

ASP-DAC 2018 is the 23rd annual international conference on VLSI design automation in Asia and South Pacific regions, one of the most active regions of design and fabrication of silicon chips in the world. The conference aims at providing the Asian and South Pacific CAD/DA and Design community with opportunities of presenting recent advances and with forums for future directions in technologies related to Electronic Design Automation (EDA). The format of the meeting intends to cultivate and promote an instructive and productive interchange of ideas among EDA researchers/developers and system/circuit/device designers. All scientists, engineers, and students who are interested in theoretical and practical aspects of VLSI design and design automation are welcomed to ASP-DAC.

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Periodicals related to Pixel

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.

Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...

Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...

Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.

Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.

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Most published Xplore authors for Pixel

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Xplore Articles related to Pixel

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Spectral information divergence for hyperspectral image analysis

[{u'author_order': 1, u'affiliation': u'Remote Sensing Signal & image Process. Lab., Maryland Univ., Baltimore, MD, USA', u'full_name': u'Chein-I Chang'}] Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International, None

The authors propose an information theoretic criterion, called spectral information divergence (SID) for spectral similarity and discriminability. It is derived from the concept of divergence arising in information theory and can be used to describe the statistics of a spectrum. Unlike spectral angle mapper (SAM) which extracts geometric features between two spectra, SID views each pixel spectrum as a random ...

Detection of Pedestrians Using Subtraction Stereo

[{u'author_order': 1, u'affiliation': u'Sch. of Sci. & Eng., Chuo Univ., Tokyo', u'full_name': u'Yuuki Hashimoto'}, {u'author_order': 2, u'affiliation': u'Sch. of Sci. & Eng., Chuo Univ., Tokyo', u'full_name': u'Yusuke Matsuki'}, {u'author_order': 3, u'affiliation': u'Sch. of Sci. & Eng., Chuo Univ., Tokyo', u'full_name': u'Tatsuya Nakanishi'}, {u'author_order': 4, u'affiliation': u'Sch. of Sci. & Eng., Chuo Univ., Tokyo', u'full_name': u'Kazunori Umeda'}, {u'author_order': 5, u'full_name': u'Kei Suzuki'}, {u'author_order': 6, u'full_name': u'Kazunori Takashio'}] 2008 International Symposium on Applications and the Internet, None

In this paper, detection of pedestrians using ldquosubtraction stereordquo is discussed. Subtraction stereo is a stereo vision method that focuses on the movement of objects to make a stereo camera robust and produces range images for moving regions. Features of pedestrians such as 3D position, height and width are obtained from range images obtained by subtraction stereo. Then a simple ...

A no-reference sharpness metric sensitive to blur and noise

[{u'author_order': 1, u'affiliation': u'Electrical Engineering Department, University of California at Santa Cruz, 95064, USA', u'full_name': u'Xiang Zhu'}, {u'author_order': 2, u'affiliation': u'Electrical Engineering Department, University of California at Santa Cruz, 95064, USA', u'full_name': u'Peyman Milanfar'}] 2009 International Workshop on Quality of Multimedia Experience, None

A no-reference objective sharpness metric detecting both blur and noise is proposed in this paper. This metric is based on the local gradients of the image and does not require any edge detection. Its value drops either when the test image becomes blurred or corrupted by random noise. It can be thought of as an indicator of the signal to ...

Jumping Scanning Path Error Diffusion: A Novel Halftoning Algorithm Improving Mid-tone Quality

[{u'author_order': 1, u'affiliation': u'Zhejiang Key Lab. of Service Robot, Zhejiang Univ., Hangzhou, China', u'full_name': u'Yan Zhou'}, {u'author_order': 2, u'affiliation': u'Zhejiang Key Lab. of Service Robot, Zhejiang Univ., Hangzhou, China', u'full_name': u'Chun Chen'}, {u'author_order': 3, u'affiliation': u'Zhejiang Key Lab. of Service Robot, Zhejiang Univ., Hangzhou, China', u'full_name': u'Qiang Wang'}, {u'author_order': 4, u'affiliation': u'Zhejiang Key Lab. of Service Robot, Zhejiang Univ., Hangzhou, China', u'full_name': u'Jiajun Bu'}] 2011 Workshop on Digital Media and Digital Content Management, None

In this paper, we describe a novel error diffusion scheme for higher halftone quality with less visual artifacts. The proposed algorithm improves mid-tone quality of error diffusion significantly by diffusing the error along a jumping scanning path. The algorithm calculates the accumulative error to determine the point where breaks up the scanning path. A cost function is developed to search ...

Learning IMED via shift-invariant transformation

[{u'author_order': 1, u'affiliation': u'Key Laboratory of Machine Perception (Peking University), MOE, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China', u'full_name': u'Bing Sun'}, {u'author_order': 2, u'affiliation': u'Key Laboratory of Machine Perception (Peking University), MOE, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China', u'full_name': u'Jufu Feng'}, {u'author_order': 3, u'affiliation': u'Key Laboratory of Machine Perception (Peking University), MOE, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China', u'full_name': u'Liwei Wang'}] 2009 IEEE Conference on Computer Vision and Pattern Recognition, None

The IMage Euclidean Distance (IMED) is a class of image metrics, in which the spatial relationship between pixels is taken into consideration. It was shown that calculating the IMED of two images is equivalent to performing a linear transformation called Standardizing Transform (ST) and then followed by the traditional Euclidean distance. However, while the IMED is invariant to image shift, ...

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Educational Resources on Pixel

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No eLearning Articles are currently tagged "Pixel"


  • Radiation Imaging Detectors Using SOI Technology

    <p>Silicon-on-Insulator (SOI) technology is widely used in high-performance and low-power semiconductor devices. The SOI wafers have two layers of active silicon (Si), and normally the bottom Si layer is a mere physical structure. The idea of making intelligent pixel detectors by using the bottom Si layer as sensors for X-ray, infrared light, high-energy particles, neutrons, etc. emerged from very early days of the SOI technology. However, there have been several difficult issues with fabricating such detectors and they have not become very popular until recently.</p><p>This book offers a comprehensive overview of the basic concepts and research issues of SOI radiation image detectors. It introduces basic issues to implement the SOI detector and presents how to solve these issues. It also reveals fundamental techniques, improvement of radiation tolerance, applications, and examples of the detectors.</p><p>Since the SOI detector has both a thick ensing region and CMOS transistors in a monolithic die, many ideas have emerged to utilize this technology. This book is a good introduction for people who want to develop or use SOI detectors.</p>

  • Optical Camera Communication: Fundamentals

    This chapter discusses the fundamentals of optical camera communication (OCC), with the OCC system employing the pervasive image sensor assembled in consumer electrons as the receiver. It occupies a wide spectrum, and can be easily built upon pervasive optical light sources and the pervasive consumer cameras. OCC emerges as a new form of visible light communication. It employs an image sensor assembled in consumer electronic devices, such as smartphone, iPad as a receiver to serve as an alternative to the photodiode (PD) or avalanche photodiode (APD) based receiver. The major driving force of OCC applications stems from the availability of commercial visible light LEDs for data transmission and the possibility of utilizing the camera in the smart devices to decode signal received from LEDs. The imaging lens projects light on to the image sensor, which is comprised of multiple PD‐based pixels to detect the incident optical (photon) radiation. Each activated pixel generates a voltage proportional to the number of impinging photons.

  • Optical Camera Communication: Modulation and System Design

    This chapter reviews modulation schemes and discusses system design issues in optical camera communication (OCC). It can be accomplished by employing multilevel coding (MLC) and multi‐stage decoding (MSD) with a deterministic mapper applied to multiple binary linear codes. Furthermore, a non‐uniform map per coupled with a binary low density parity check (LDPC) code can be used to generate the desired in put distribution. The pixel, being basically a power detection unit and a fundamental element in an image sensor, responds to the instantaneous field count rate process. Its output appears as hot noise process, whose count rate is proportional to the instantaneous received power. Pulse amplitude modulation (PAM) is one of the most popular intensity modulation schemes developed for an optical communication system, and on‐off keying (OOK), as a binary‐level version of PAM, is also widely used.

  • Image and Video Matting:A Survey

    If you've ever wanted to add that missing member of your family to a group photograph, you can now, given newly developed technology. Simply find a picture of the missing person, determine a "matte" that will lift them out and leave the background behind, and use the matte to insert them in the original image. Matting refers to the problem of accurate foreground estimation in images and video. The matte defines which pixels are foreground, which are background, and for pixels along the boundary or in semi-transparent regions such as hair, the matte defines the mixture of foreground and background at each pixel. Matting is one of the key techniques in many image editing and film production applications, thus has been extensively studied in the research literature. With the recent advances of digital cameras, using matting techniques to create novel composites or facilitate other editing tasks has gained increasing interest from both professionals as well as consumers. Consequently, va ious matting techniques and systems have been proposed to try to efficiently extract high quality mattes from both still images and video sequences. Image and Video Matting: A Survey provides a comprehensive review of existing image and video matting algorithms and systems, with an emphasis on the advanced techniques that have been recently proposed. Various methods are described and contrasted and finally tested against a uniform set of examples. Image and Video Matting: A Survey is most appropriate for a graduate level course in computational photography, or for any student or serious practitioner interested in the inner workings of matting methods.

  • A Survey of Photometric Stereo Techniques

    Reconstructing the shape of an object from images is an important problem in computer vision that has led to a variety of solution strategies. This monograph focuses on photometric stereo, that is, techniques that exploit the observed intensity variations caused by illumination changes to recover the orientation of the surface. In the most basic setting, a diffuse surface is illuminated from at least three directions and captured with a static camera. Under some conditions, this allows to recover per-pixel surface normals. Modern approaches generalize photometric stereo in various ways; for example, relaxing constraints on lighting, surface reflectance and camera placement, or creating different types of local surface estimates. Starting with an introduction for readers unfamiliar with the subject, A Survey of Photometric Stereo Techniques discusses the foundations of this field of research. It then summarizes important trends and developments that have emerged in the last three decad s. The focus is on approaches with the potential to be applied in a broad range of scenarios. This implies, for example, simple capture setups, relaxed model assumptions, and increased robustness requirements. This is an ideal reference for anyone looking for an understanding of the diverse concepts and ideas around this topic and how we can move towards more general techniques than traditional photometric stereo

  • Image Alignment and Stitching:A Tutorial

    Image Alignment and Stitching: A Tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. Image Alignment and Stitching: A Tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It closes with a discussion of open research problems in the area. Image Alignment and Stitching: A T torial is an invaluable resource for anyone planning or conducting research in this particular area, or computer vision generally. The essentials of the topic are presented in a tutorial style and an extensive bibliography guides towards further reading.

  • Detector Testing

    The testing of infrared (IR) detectors is an important and interesting part of the IR business. There is considerable preparation before carrying out any tests; indeed, the preparation takes much more time than the test itself. Although not always included in the test plan, it is useful to know in advance the approximate expected values of the raw data, as well as the computed values that will be reported. This chapter records raw data for each pixel of interest under one or more conditions (bias, irradiance, integration time, etc.) and analyzes the results. It talks about the conditions under which one need to collect the data, how one can analyze that data to determine characteristics of interest, and the associated uncertainties. The nature of focal plane arrays (FPAs) and their specifications require some additional parameters. FPAs are now built that respond to X‐rays, ultraviolet, visible, and very short IR wavelengths.

  • Electronics for FPA Operation

    The combination of detectors and readout integrated circuit (ROIC) is commonly referred to in the industry as a focal plane array (FPA). This chapter focuses on the drive signals and outputs of FPA. The drive signals is divided into two main groups: biases and clocks. ROIC outputs are either analog or digital. The choice must consider several characteristics, but the primary advantages of analog outputs are lower power consumption, better noise performance, and less area on the ROIC. Data from FPAs is normally organized as frames of data, where each frame includes one value for each pixel in the array. Testing FPAs requires all the power supply and reference voltages along with clocking and control signals to operate the ROIC. FPAs are commonly mounted on a leadless ceramic chip carrier (LCCC) for wire‐bonding before test, and for the test itself. The wire‐bonding process is standard to the general semiconductor business.

  • Studies in Perception

    This chapter contains sections titled: From Lab to Museum, Making a Computer- Processed Picture, Studies in Perception, Art at the End of the Mechanical Age, Between Vector and Pixel

  • Segmentation of Brain Magnetic Resonance Images

    This chapter presents the application of different rough-fuzzy clustering algorithms for segmentation of brain magnetic resonance (MR) images. One of the important issues of the partitive-clustering-algorithm-based brain MR image segmentation method is the selection of initial prototypes of different classes or categories. The concept of discriminant analysis, based on the maximization of class separability, is used to circumvent the initialization and local minima problems of the partitive clustering algorithms. The chapter first deals with the pixel classification problem, and then gives an overview of the feature extraction techniques employed in segmentation of brain MR images, along with the initialization method of c-means algorithm based on the maximization of class separability. It presents implementation details, experimental results, and a comparison among different c-means algorithms. The algorithms compared are hard c-means (HCM), fuzzy c-means (FCM), possibilistic c-means (PCM), FPCM, rough c-means (RCM), and rough-fuzzy c-means (RFCM). fuzzy set theory; image classification; image segmentation; magnetic resonance imaging; pattern clustering; rough set theory