Search results for "Image sensor"

showing 10 items of 63 documents

Smart camera design for realtime High Dynamic Range imaging

2011

International audience; Many camera sensors suffer from limited dynamic range. The result is that there is a lack of clear details in displayed images and videos. This paper describes our approach to generate high dynamic range (HDR) from an image sequence while modifying exposure times for each new frame. For this purpose, we propose an FPGA-based architecture that can produce a real-time high dynamic range video from successive image acquisition. Our hardware platform is build around a standard low dynamic range CMOS sensor and a Virtex 5 FPGA board. The CMOS sensor is a EV76C560 provided by e2v. This 1.3 Megapixel device offers novel pixel integration/readout modes and embedded image pre…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingACM IEEEImagingVideosHardware[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingHigh-dynamic-range imaging0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraImage sensorImage resolutionHigh dynamic range[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPipelinesCMOS sensorDynamic rangePixelbusiness.industrySensors020208 electrical & electronic engineeringReal time systems020207 software engineeringFrame rate[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Scene-based noise reduction on a smart camera

2012

International audience; Raw output data from CMOS image sensors tends to exhibit significant noise called Fixed-Pattern Noise (FPN) due to on-die variations between pixel photodetectors. FPN is often corrected by subtracting its value, estimated through calibration, from the sensor's raw signal. This paper introduces an on-line scene-based technique for an improved FPN compensation which does not rely on calibration, and hence is more robust to the dynamic changes in the FPN which may occur slowly over time. Development has been done with a special emphasis on real-time hardware implementation on a FPGA-based smart camera. Experimental results on different scenes are depicted showing that t…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesSignalCompensation (engineering)010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionSmart cameraImage sensor[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPixelNoise (signal processing)business.industry020208 electrical & electronic engineeringEmphasis (telecommunications)Artificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Smart NeuroCam with High Level Configuration Tool

2017

Thème de la conférence : New Circuits and Systems; International audience

[SPI.AUTO] Engineering Sciences [physics]/AutomaticSmart image sensor[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[ SPI.AUTO ] Engineering Sciences [physics]/AutomaticHardware_INTEGRATEDCIRCUITSComputingMilieux_MISCELLANEOUS[SPI.AUTO]Engineering Sciences [physics]/AutomaticHardware_LOGICDESIGN
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Detecting motion independent of the camera movement through a log-polar differential approach

1997

This paper is concerned with a differential motion detection technique in log-polar coordinates which allows object motion tracking independently of the camera ego-motion when camera focus is along the movement direction. The method does not use any explicit estimation of the motion field, which can be calculated afterwards at the moving points. The method, previously formulated in Cartesian coordinates, uses the log-polar coordinates, which allows the isolation of the object movement from the image displacement due to certain camera motions. Experimental results on a sequence of real images are included, in which a moving object is detected and optical flow is calculated in log-polar coord…

business.industryCamera matrixComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowImage processingReal imageGeneralized coordinatesMatch movingMotion fieldCamera auto-calibrationMotion estimationPinhole camera modelComputer visionArtificial intelligenceImage sensorbusinessFocus (optics)Camera resectioning
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Measuring the Spatial and Spectral Performance of WorldView-3

2015

The new WorldView-3 satellite provides a unique combination of very high spatial resolution and super-spectral capabilities. This presentation explores the practical and theoretical usefulness of this platform as compared against other hyperspectral and multispectral sensors.

business.industryComputer scienceMultispectral imageHigh spatial resolutionHyperspectral imagingSatelliteComputer visionArtificial intelligenceEarth remote sensingImage sensorbusinessImage resolutionRemote sensingFourier Transform Spectroscopy and Hyperspectral Imaging and Sounding of the Environment
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Two-step cross correlation-based algorithm for motion estimation applied to fertilizer granules' motion during centrifugal spreading

2011

Imaging systems are progressing in both accuracy and ro- bustness, and their use in precision agriculture is increasing accordingly. One application of imaging systems is to understand and control the cen- trifugal fertilizing spreading process. Predicting the spreading pattern on the ground relies on an estimation of the trajectories and velocities of ejected granules. The algorithms proposed to date have shown low ac- curacy, with an error rate of a few pixels. But a more accurate estimation of the motion of the granules can be achieved. Our new two-step cross- correlation-based algorithm is based on the technique used in particle image velocimetry (PIV), which has yielded highly accurate…

fluid mechanicsImage processing01 natural sciences010305 fluids & plasmas010309 opticsmotion estimationMotion estimationcameras0103 physical sciencesComputer visionImage sensorMathematicsCross-correlationPixelbusiness.industrycentrifugesGeneral EngineeringfertilisersFluid mechanicsSubpixel renderingAtomic and Molecular Physics and Opticsimage processingParticle image velocimetryvelocimetersArtificial intelligencebusinessAlgorithm
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Miniature MOEMS hyperspectral imager with versatile analysis tools

2019

The Fabry-Perot interferometers (FPI) are essential components of many hyperspectral imagers (HSI). While the Piezo-FPI (PFPI) are still very relevant in low volume, high performance applications, the tunable MOEMS FPI (MFPI) technology enables volume-scalable manufacturing, thus having potential to be a major game changer with the advantages of low costs and miniaturization. However, before a FPI can be utilized, it must be integrated with matching optical assembly, driving electronics and imaging sensor. Most importantly, the whole HSI system must be calibrated to account for wide variety of unwanted physical and environmental effects, that significantly influence quality of hyperspectral…

hyperspectral imagerComputer sciencebusiness.industryHyperspectral imagerdata analysisspektrikuvausData analysisHyperspectral imagingOtaNanoVNIRMOEMSVNIRkuvantaminenFabry-Perot interferometerImage sensorbusinessComputer hardwarehyperspektrikuvantaminen
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HYPERSPECTRAL REFLECTANCE SIGNATURES AND POINT CLOUDS FOR PRECISION AGRICULTURE BY LIGHT WEIGHT UAV IMAGING SYSTEM

2018

Abstract. The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, w…

lcsh:Applied optics. Photonics010504 meteorology & atmospheric sciencesRemote sensing applicationComputer scienceUAV0211 other engineering and technologiesPoint cloudmedical imagingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONStereoscopyImage processing02 engineering and technologylcsh:Technology01 natural scienceslaw.inventionimaging spectrometerremote sensinglawFabry-Perot interferometerComputer vision021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingprecision agriculturelcsh:Tbusiness.industrytarget detectionlcsh:TA1501-1820Hyperspectral imagingairbornehyperspectral sensorsPhotogrammetrypiezo actuatorslcsh:TA1-2040RadiometryPrecision agricultureArtificial intelligencemultispectral image sensorslcsh:Engineering (General). Civil engineering (General)business
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Tree species recognition in species rich area using UAV-borne hyperspectral imagery and stereo-photogrammetric point cloud

2017

Abstract. Recognition of tree species and geospatial information of tree species composition is essential for forest management. In this study we test tree species recognition using hyperspectral imagery from VNIR and SWIR camera sensors in combination with 3D photogrammetric canopy surface model based on RGB camera stereo-imagery. An arboretum forest with a high number of tree species was used as a test area. The imagery was acquired from the test area using UAV-borne cameras. Hyperspectral imagery was calibrated for providing a radiometrically corrected reflectance mosaic, which was tested along with the original uncalibrated imagery. Alternative estimators were tested for predicting tree…

lcsh:Applied optics. Photonicshyperspectral imaging0211 other engineering and technologiesPoint cloud02 engineering and technologyUAVslcsh:TechnologyImage sensor021101 geological & geomatics engineeringRemote sensing040101 forestryPixellcsh:Ttree species recognitionlcsh:TA1501-1820Hyperspectral imaging04 agricultural and veterinary sciencesOtaNanoVNIRTree (data structure)GeographyPhotogrammetryphotogrammetric point cloudlcsh:TA1-2040stereo-photogrammetry0401 agriculture forestry and fisheriesRGB color modellcsh:Engineering (General). Civil engineering (General)
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SNAPSHOT SPECTRAL AND COLOR IMAGING USING A REGULAR DIGITAL CAMERA WITH A MONOCHROMATIC IMAGE SENSOR

2017

Spectral imaging (SI) refers to the acquisition of the three-dimensional (3D) spectral cube of spatial and spectral data of a source object at a limited number of wavelengths in a given wavelength range. Snapshot spectral imaging (SSI) refers to the instantaneous acquisition (in a single shot) of the spectral cube, a process suitable for fast changing objects. Known SSI devices exhibit large total track length (TTL), weight and production costs and relatively low optical throughput. We present a simple SSI camera based on a regular digital camera with (i) an added diffusing and dispersing phase-only static optical element at the entrance pupil (diffuser) and (ii) tailored compressed sensing…

lcsh:Applied optics. Photonicsmedicine.medical_specialtybusiness.product_categoryhyperspectral imagingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyimaging systemscomputational imaging01 natural scienceslcsh:Technology010309 opticsEntrance pupilComputational photographyOpticsColor gel0103 physical sciencesmultispectral imaging0202 electrical engineering electronic engineering information engineeringmedicineComputer visionImage sensorDigital camerabusiness.industryColor imagelcsh:Tlcsh:TA1501-1820Spectral imagingCompressed sensinglcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligenceMonochromatic colorbusinesslcsh:Engineering (General). Civil engineering (General)
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