... One goal of MPEG-7 is to provide a stan-dardized method of describing features of multimedia data. For images and video, colors or â2001 CRC Press LLC 5.5.2 Postprocessing5.5.3 Shape and Color ... conversationalservices, Internetvideo applications, sign language andlip-reading communication, video stor-age and retrieval services (e.g., VOD), video store and forward services (e.g., video mail), and multipoint ... Adali University of Maryland, Baltimore, Maryland Horst Bunke Institute für Informatik und Angewandte Mathematik, Universität Bern,Switzerland Frank M. Candocia University of Florida, Gainesville,...
... sim-plifications for real-time imageandvideo processing, Hardware platforms for real-time image andvideo processing, Software methods for real-time imageandvideo processing P1: IML/FFX P2: ... developments in the field of multidimensional signal processing have all led to the creation of the field of real-time imageandvideo processing. Here, an overview of the history ofimageprocessing is stated ... a brief overview of the other chapters.1.2 PARALLELISM IN IMAGE/ VIDEO PROCESSING OPERATIONSReal-time imageandvideoprocessing systems involve processing vast amounts ofimage data ina timely...
... theCompressedFormFigure 1.3 : Processing in the domain of alternative representation.1.3 Overview of Different ImageandVideo CompressionTechniques and StandardsVarious imageandvideo compression techniques ... ofvideo resizing, in particular video downsampling, is discussed in thenext chapter on transcoding.In chapter six, transcoding of images and videos is discussed. As most of the imageandvideo ... than their original domains of representation, whichare spatial and spatiotemporal for images and videos, respectively. Two suchpopular representations of images and videos are formed by their...
... YAVGis made as a product of brightnessL of the input image, Exposure (integration) Time tET of the sensor, gain G of the imageprocessing pipeline, and aconstant K,see[9], and computed with YAVG= ... on ImageandVideo Processing own peculiarities, different behavior, and effect on the image. The task of the video- level control algorithm is to maintainthe correct average luminance value of ... describe twobasic methods: mixing of images and hard switching betweenimages. Figure 12(a) depicts a soft switch between long- and short-exposure images, where two images are mixed in atransition...
... EURASIP Journal on ImageandVideoProcessing 3(a) (b) (c)Figure 1: Examples of images from minimally invasive medical procedures showing specular highlights. (a) Laparoscope imageof theappendix, ... 4 EURASIP Journal on ImageandVideo Processing (a) (b)Figure 3: Example of a colonoscopic image before and after median filtering.(a) (b)(c) (d)Figure 4: Illustration of the area that is used ... transition between c(x) and csm(x). Figure 5 illustrates the approach by showing therelevant images and masks. 10 EURASIP Journal on ImageandVideo Processing Table 3: Performance of the colour channel...
... respect to the center ofimage (a); (d) rectangular axis-oriented patch on polar image; (e) transformation of the image (d) and its patch o nto the origin al image; (f) examples of rectangular patches ... detector; final detections of (g, h) bare heads andof hard hats(i, j). EURASIP Journal on ImageandVideoProcessing 7True detections (66%)(a) (b) (c)False detections out of scale (24%)False ... unreliable.Most of the other head detectors approaches that do notrely on shapes, exploit color features (ty p ically of hair and EURASIP Journal on ImageandVideoProcessing 3Domain-specificvideo...
... space-varying mean and stationary covariance as a model for the pdf of the image. Geman and Geman [11] proposed a Gibbsdistribution to model thepdf ofthe image. Alternatively, if the image is assumed ... non-stationary image mean, Rf and Rnare the correlation matrices of the idealimageandnoise,respectively,andSbisadiagonalmatrixconsistingofthederivativesofs(.) evaluatedc1999 by CRC Press LLC ImageandVideoRestorationA.MuratTekalpUniversityofRochester53.1Introduction53.2ModelingIntra-FrameObservationModelãMultispectralObserva-tionModelãMultiframeObservationModelãRegularizationModels53.3ModelParameterEstimationBlurIdenticationãEstimationofRegularizationParametersãEstimationoftheNoiseVariance53.4Intra-FrameRestorationBasicRegularizedRestorationMethodsãRestorationofIm-agesRecordedbyNonlinearSensorsãRestorationofImagesDegradedbyRandomBlursãAdaptiveRestorationforRing-ingReductionãBlindRestoration(Deconvolution)ãRestora-tionofMultispectralImagesãRestorationofSpace-VaryingBlurredImages53.5MultiframeRestorationandSuperresolutionMultiframeRestorationãSuperresolutionãSuperresolutionwithSpace-VaryingRestoration53.6ConclusionReferences53.1 ... the dataand a constantsum of pixel intensities. This approach requires thesolution of a system of nonlinear equations. The number of equations and unknowns are on theorder of the number of pixels...