Search results for "image resolution"

showing 10 items of 377 documents

<title>Methodology for quantitative analysis of scaling effects in multiresolution datasets acquired with airborne sensors flying at different …

2001

Scaling issues are always playing a critical role in most studies based on remote sensing data. The process of getting quantitative scaling information from raw multi-resolution images is not trivial, and many aspects must be taken very carefully into consideration. To get a better picture about the role of spatial resolution, we conducted a series of flights in summer 1997, in several test sites over Spain and Portugal. In order to minimize the time of acquisition (to get minimal changes in atmospheric status and solar illumination) we used three flight altitude levels, that produced images with 1.25 m, 3 m and 12 m resolutions. The main steps in our methodology are: a) Geometrical registr…

Data setData processingGeographyAltitudeRobustness (computer science)Multiresolution analysisBidirectional reflectance distribution functionSensor fusionImage resolutionRemote sensingSPIE Proceedings
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Integration of high and low resolution NDVI data for monitoring vegetation in Mediterranean environments

1998

Abstract The integration of the useful features of high and low spatial and temporal resolution satellite data is a major issue in remote sensing studies. The current work presents the development and testing of a procedure based on classification and regression analysis techniques for generating an NDVI data set with the spatial resolution of Landsat TM images and the temporal resolution of NOAA AVHRR maximum-value composites. The procedure begins with a classification of the high resolution TM data which yields land use references. These are degraded to low spatial resolution in order to produce abundance images comparable with the AVHRR data. Linear regressions are then applied between t…

Data setMultivariate statisticsFuzzy classificationTemporal resolutionSoil ScienceEnvironmental scienceGeologyRegression analysisComputers in Earth SciencesImage resolutionMultispectral ScannerNormalized Difference Vegetation IndexRemote sensing
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Algorithms for Image Reconstruction

2010

Three-dimensional (3D) imaging is becoming one of the most important applications of radioactive materials in medicine. It offers good spatial resolution, a 3D insight into the human body, and a high sensitivity in the picomolar range because markers for biological processes can be detected well when labeled with radioactive materials. In addition, the technical equipment has undergone many technological achievements. This is true for single-photon emission computed tomography (SPECT), positron emission tomography (PET), and X-ray computed tomography (CT), which is often used in connection with the nuclear medical imaging systems, as also described in chapter 5 about sources in nuclear medi…

Data setmedicine.diagnostic_testPositron emission tomographyComputer sciencemedicineMedical imagingIterative reconstructionSensitivity (control systems)AlgorithmImage resolutionEmission computed tomographyFeature detection (computer vision)
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MRI resolution enhancement using total variation regularization

2009

We propose a novel method for resolution enhancement for volumetric images based on a variational-based reconstruction approach. The reconstruction problem is posed using a deconvolution model that seeks to minimize the total variation norm of the image. Additionally, we propose a new edge-preserving operator that emphasizes and even enhances edges during the up-sampling and decimation of the image. The edge enhanced reconstruction is shown to yield significant improvement in resolution, especially preserving important edges containing anatomical information. This method is demonstrated as an enhancement tool for low-resolution, anisotropic, 3D brain MRI images, as well as a pre-processing …

Decimationmedicine.diagnostic_testbusiness.industryComputer scienceMagnetic resonance imagingIterative reconstructionImage segmentationTotal variation denoisingArticleComputer Science::Computer Vision and Pattern RecognitionNorm (mathematics)medicineComputer visionSegmentationArtificial intelligenceDeconvolutionAnisotropybusinessImage resolution2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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A wavelet-based demosaicking algorithm for embedded applications

2010

This paper presents an alternative to the spatial reconstruction of the sampled color filter array acquired through a digital image sensor. A demosaicking operation has to be applied to the raw image to recover the full-resolution color image. We present a low-complexity demosaicking algorithm processing in the wavelet domain. Produced images are available at the output of the algorithm either in the spatial representation or directly in the wavelet domain for high-level post processing in the latter domain. Results show that the computational complexity has been lowered by a factor of five compared to state of the art demosaicking algorithms.

DemosaicingComputer scienceColor imagebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformIterative reconstructionDigital imageWaveletColor filter arrayComputer visionArtificial intelligencebusinessImage resolutionAlgorithm2010 Conference on Design and Architectures for Signal and Image Processing (DASIP)
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Time multiplexing super-resolved imaging without a priori knowledge of the spatial distribution of the encoding structured illumination

2021

Time multiplexing is a super-resolution technique that sacrifices time to overcome the resolution reduction obtained because of diffraction. There are many super resolution methods based on time multiplexing, but all of them require a priori knowledge of the time changing encoding mask, which is projected on the object and used to encode and decode the high-resolution information. In this paper, we present a time multiplexing technique that does not require the a priori knowledge on the projected encoding mask. First, the theoretical concept of the technique is demonstrated; then, numerical simulations and experimental results are presented.

DiffractionComputer sciencebusiness.industryResolution (electron density)02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesMultiplexingAtomic and Molecular Physics and Optics010309 opticsReduction (complexity)OpticsEncoding (memory)0103 physical sciencesA priori and a posteriori0210 nano-technologybusinessImage resolutionAlgorithmComputer Science::Information TheoryOptics Express
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Super-resolved Imaging based upon spatial depolarization of light

2010

In this paper we present a new approach allowing the surpassing of the diffraction based limitation for the achievable resolution provided by imaging systems. It is based on an encoding-decoding process of various spatial pixels or regions in the field of view of the imaged object by orthogonal and differently time varying polarization states. The reconstruction of the original spatial information is obtained by applying a decoding process in a way similar to the encoding one. Although all the spatial information is summed and mixed together by the system, the decoding provides super resolved imaging since in every spatial position the undesired spatial information having time varying polar…

DiffractionHistoryPixelbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONField of viewDepolarizationPolarization (waves)Computer Science ApplicationsEducationOpticsGeographybusinessImage resolutionSpatial analysisDecoding methodsJournal of Physics: Conference Series
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Super-resolved imaging with randomly distributed, time- and size-varied particles

2009

In this paper we present a super-resolved approach aimed at overcoming the diffraction limit in imaging systems. It is based on place randomly and time-varied particles having different sizes on the top of the sample. By considering particle sizes smaller than the object's minimum detail that an imaging system can resolve, it is possible to recover a high resolution image from a set of low resolution images while before capturing each image we produce a randomly modified distribution of the particles by vibrating the sample. The simulation process as well as experimental results validates the proposed approach that includes effectively decreasing the F number of the imaging system while bei…

DiffractionMaterials sciencebusiness.industryResolution (electron density)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Image processingSample (graphics)Atomic and Molecular Physics and OpticsOpticsComputer Science::Computer Vision and Pattern RecognitionParticleParticle sizebusinessImage resolutionJournal of Optics A: Pure and Applied Optics
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Investigating the performance of reconstruction methods used in structured illumination microscopy as a function of the illumination pattern's modula…

2016

Surpassing the resolution of optical microscopy defined by the Abbe diffraction limit, while simultaneously achieving optical sectioning, is a challenging problem particularly for live cell imaging of thick samples. Among a few developing techniques, structured illumination microscopy (SIM) addresses this challenge by imposing higher frequency information into the observable frequency band confined by the optical transfer function (OTF) of a conventional microscope either doubling the spatial resolution or filling the missing cone based on the spatial frequency of the pattern when the patterned illumination is two-dimensional. Standard reconstruction methods for SIM decompose the low and hi…

DiffractionMicroscopeOptical sectioningFrequency bandComputer scienceStructured illumination microscopy01 natural scienceslaw.invention010309 opticsOpticsOptical microscopelawLive cell imagingOptical transfer function0103 physical sciencesMicroscopyFluorescence microscopeComputer vision010306 general physicsImage resolutionbusiness.industrySuperresolutionSpatial frequencyArtificial intelligencebusinessLuminescenceFrequency modulationSPIE Proceedings
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Non-Homogeneity of Lateral Resolution in Integral Imaging

2013

We evaluate the lateral resolution in reconstructed integral images. Our analysis takes into account both the diffraction effects in the image capture stage and the lack of homogeneity and isotropy in the reconstruction stage. We have used Monte Carlo simulation in order to assign a value for the resolution limit to any reconstruction plane. We have modelled the resolution behavior. Although in general the resolution limit increases proportionally to the distance to the lens array, there are some periodically distributed singularity planes. The phenomenon is supported by experiments.

DiffractionPhysicsIntegral imagingbusiness.industryIsotropyMonte Carlo methodIterative reconstructionCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsSingularityOpticsHomogeneity (physics)Electrical and Electronic EngineeringbusinessImage resolutionJournal of Display Technology
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