Search results for "Bilateral filter"

showing 3 items of 3 documents

Three-Dimensional Integral-Imaging Display From Calibrated and Depth-Hole Filtered Kinect Information

2016

We exploit the Kinect capacity of picking up a dense depth map, to display static three-dimensional (3D) images with full parallax. This is done by using the IR and RGB camera of the Kinect. From the depth map and RGB information, we are able to obtain an integral image after projecting the information through a virtual pinhole array. The integral image is displayed on our integral-imaging monitor, which provides the observer with horizontal and vertical perspectives of big 3D scenes. But, due to the Kinect depth-acquisition procedure, many depthless regions appear in the captured depth map. These holes spread to the generated integral image, reducing its quality. To solve this drawback we …

0209 industrial biotechnologyIntegral imagingbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyCondensed Matter PhysicsStereo display01 natural sciencesElectronic Optical and Magnetic Materials010309 optics020901 industrial engineering & automationDepth mapCamera auto-calibrationComputer graphics (images)0103 physical sciencesRGB color modelComputer visionBilateral filterArtificial intelligenceElectrical and Electronic EngineeringbusinessParallaxComputingMethodologies_COMPUTERGRAPHICSCamera resectioningJournal of Display Technology
researchProduct

Multispectral image denoising with optimized vector non-local mean filter

2016

Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …

FOS: Computer and information sciencesMulti-spectral imaging systemsComputer Vision and Pattern Recognition (cs.CV)Optimization frameworkMultispectral imageComputer Science - Computer Vision and Pattern Recognition02 engineering and technologyWhite noisePixels[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringComputer visionUnbiased risk estimatorMultispectral imageMathematicsMultispectral imagesApplied MathematicsBilateral FilterNumerical Analysis (math.NA)Non-local meansAdditive White Gaussian noiseStein's unbiased risk estimatorIlluminationComputational Theory and MathematicsRestorationImage denoisingsymbols020201 artificial intelligence & image processingNon-local mean filtersComputer Vision and Pattern RecognitionStatistics Probability and UncertaintyGaussian noise (electronic)Non- local means filtersAlgorithmsNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFace Recognitionsymbols.namesakeNoise RemovalArtificial IntelligenceFOS: MathematicsParameter estimationMedian filterMathematics - Numerical AnalysisElectrical and Electronic EngineeringFusionPixelbusiness.industryVector non-local mean filter020206 networking & telecommunicationsPattern recognitionFilter (signal processing)Bandpass filters[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsStein's unbiased risk estimators (SURE)NoiseAdditive white Gaussian noiseComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingArtificial intelligenceReconstructionbusinessModel
researchProduct

Full-parallax 3D display from the hole-filtered depth information

2015

In this paper we introduce an efficient hole-filling algorithm for synthetic generation of microimages that are displayed on an integral imaging monitor. We apply the joint bilateral filter and the median filter to the captured depth map. We introduce in any step of the iterative algorithm with the data from a new Kinect capture. As a result, this algorithm can improve the quality of the depth maps and remove unmeasured depth holes effectively. This refined depth information enables to create a tidy integral image, which can be projected into an integral imaging monitor. In this way the monitor can display 3D images with continuous views, full parallax and abundant 3D reconstructed scene fo…

Integral imagingbusiness.industryComputer scienceIterative methodComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONObserver (special relativity)Stereo displayDepth mapComputer graphics (images)Median filterComputer visionBilateral filterArtificial intelligencebusinessParallax2015 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON)
researchProduct