The Experts below are selected from a list of 300528 Experts worldwide ranked by ideXlab platform
Gholamreza Anbarjafari - One of the best experts on this subject based on the ideXlab platform.
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discrete wavelet transform based satellite Image Resolution enhancement
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:Satellite Images are being used in many fields of research. One of the major issues of these types of Images is their Resolution. In this paper, we propose a new satellite Image Resolution enhancement technique based on the interpolation of the high-frequency subbands obtained by discrete wavelet transform (DWT) and the input Image. The proposed Resolution enhancement technique uses DWT to decompose the input Image into different subbands. Then, the high-frequency subband Images and the input low-Resolution Image have been interpolated, followed by combining all these Images to generate a new Resolution-enhanced Image by using inverse DWT. In order to achieve a sharper Image, an intermediate stage for estimating the high-frequency subbands has been proposed. The proposed technique has been tested on satellite benchmark Images. The quantitative (peak signal-to-noise ratio and root mean square error) and visual results show the superiority of the proposed technique over the conventional and state-of-art Image Resolution enhancement techniques.
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Image Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition
IEEE Transactions on Image Processing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:In this correspondence, the authors propose an Image Resolution enhancement technique based on interpolation of the high frequency subband Images obtained by discrete wavelet transform (DWT) and the input Image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input Image into different subbands. Then the high frequency subbands as well as the input Image are interpolated. The estimated high frequency subbands are being modified by using high frequency subband obtained through SWT. Then all these subbands are combined to generate a new high Resolution Image by using inverse DWT (IDWT). The quantitative and visual results are showing the superiority of the proposed technique over the conventional and state-of-art Image Resolution enhancement techniques.
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Satellite Image Resolution Enhancement Using Complex Wavelet Transform
IEEE Geoscience and Remote Sensing Letters, 2010Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:In this letter, a satellite Image Resolution enhancement technique based on interpolation of the high-frequency subband Images obtained by dual-tree complex wavelet transform (DT-CWT) is proposed. DT-CWT is used to decompose an input low-Resolution satellite Image into different subbands. Then, the high-frequency subband Images and the input Image are interpolated, followed by combining all these Images to generate a new high-Resolution Image by using inverse DT-CWT. The Resolution enhancement is achieved by using directional selectivity provided by the CWT, where the high-frequency subbands in six different directions contribute to the sharpness of the high-frequency details such as edges. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional bicubic interpolation, wavelet zero padding, and Irani and Peleg based Image Resolution enhancement techniques.
Hasan Demirel - One of the best experts on this subject based on the ideXlab platform.
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discrete wavelet transform based satellite Image Resolution enhancement
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:Satellite Images are being used in many fields of research. One of the major issues of these types of Images is their Resolution. In this paper, we propose a new satellite Image Resolution enhancement technique based on the interpolation of the high-frequency subbands obtained by discrete wavelet transform (DWT) and the input Image. The proposed Resolution enhancement technique uses DWT to decompose the input Image into different subbands. Then, the high-frequency subband Images and the input low-Resolution Image have been interpolated, followed by combining all these Images to generate a new Resolution-enhanced Image by using inverse DWT. In order to achieve a sharper Image, an intermediate stage for estimating the high-frequency subbands has been proposed. The proposed technique has been tested on satellite benchmark Images. The quantitative (peak signal-to-noise ratio and root mean square error) and visual results show the superiority of the proposed technique over the conventional and state-of-art Image Resolution enhancement techniques.
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Image Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition
IEEE Transactions on Image Processing, 2011Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:In this correspondence, the authors propose an Image Resolution enhancement technique based on interpolation of the high frequency subband Images obtained by discrete wavelet transform (DWT) and the input Image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input Image into different subbands. Then the high frequency subbands as well as the input Image are interpolated. The estimated high frequency subbands are being modified by using high frequency subband obtained through SWT. Then all these subbands are combined to generate a new high Resolution Image by using inverse DWT (IDWT). The quantitative and visual results are showing the superiority of the proposed technique over the conventional and state-of-art Image Resolution enhancement techniques.
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Satellite Image Resolution Enhancement Using Complex Wavelet Transform
IEEE Geoscience and Remote Sensing Letters, 2010Co-Authors: Hasan Demirel, Gholamreza AnbarjafariAbstract:In this letter, a satellite Image Resolution enhancement technique based on interpolation of the high-frequency subband Images obtained by dual-tree complex wavelet transform (DT-CWT) is proposed. DT-CWT is used to decompose an input low-Resolution satellite Image into different subbands. Then, the high-frequency subband Images and the input Image are interpolated, followed by combining all these Images to generate a new high-Resolution Image by using inverse DT-CWT. The Resolution enhancement is achieved by using directional selectivity provided by the CWT, where the high-frequency subbands in six different directions contribute to the sharpness of the high-frequency details such as edges. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional bicubic interpolation, wavelet zero padding, and Irani and Peleg based Image Resolution enhancement techniques.
Joseph A Osullivan - One of the best experts on this subject based on the ideXlab platform.
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micro insert a prototype full ring pet device for improving the Image Resolution of a small animal pet scanner
The Journal of Nuclear Medicine, 2008Co-Authors: Heyu Wu, Tae Yong Song, Joseph A OsullivanAbstract:High-Resolution PET scanners dedicated to small-animal imaging have been developed by several research groups since the 1990s (1–11). Combining high-Resolution and quantitative imaging capability, small-animal PET has been a driving force behind the development of molecular imaging that brings together scientists from different disciplines to study biologic effects at the molecular level (12,13). Small-animal PET has also been adopted by the pharmaceutical industry to study pharmacokinetics and pharmacodynamics to accelerate development of new drugs (14). The increasing demand for small-animal PET has led to commercialization of several small-animal PET technologies (15). Current technologic research and development is focused on further improvement of the Resolution or sensitivity of small-animal PET systems (16). Most commercial small-animal PET scanners use inorganic scintillators for γ-ray detection, a proven technology that provides good Image Resolution and system sensitivity at a reasonable cost. To achieve high spatial Resolution, the scintillation crystals are usually cut into small cross-sections of 1–2 mm. To maintain good detection efficiency, the crystal length is typically around 10 mm or longer. To offer high system sensitivity, the radius of the detector ring is usually small to maximize the solid angle coverage of the detectors. A common dilemma is that as a design improves one aspect of the scanner performance (such as sensitivity), it often degrades other aspects of system performance (such as Image Resolution). It is, therefore, difficult to improve multiple aspects of system performance without a dramatic change in detector technology or system design (17), which would inevitably increase the complexity and cost of a PET system. As a result, most commercial small-animal PET scanners have an Image Resolution between 1.3- and 2-mm full width at half maximum (FWHM) and a system sensitivity of 2%–10% near the center of the field of view (FOV). Although these systems are adequate for many imaging applications, submillimeter-Resolution PET systems are highly desirable to better Image transgenic mice that are widely used to study human diseases. The fundamental limit of PET Image Resolution with short-range positron sources such as 18F was estimated to be around 0.6-mm FWHM (assuming a 10-cm system diameter) (18), suggesting room for improvement in the small-animal PET system design. We have proposed a novel geometry for PET, the “virtual-pinhole PET geometry” (19), that uses high- and low-Resolution γ-ray detectors in a coincidence detection system to provide high-Resolution PET Images. We recently demonstrated the feasibility of using a high-Resolution PET detector, rotated inside an existing small-animal PET scanner, to implement the virtual-pinhole PET geometry and obtain higher Image Resolution from a microPET F-220 system (Siemens Molecular Imaging, Inc.) (20). The current study describes the design and initial results of a full-ring micro insert device that can be integrated into a microPET F-220 scanner to improve its Image Resolution within a reduced FOV.
Theo Vlachos - One of the best experts on this subject based on the ideXlab platform.
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Wavelet domain Image Resolution enhancement
IEE Proceedings - Vision Image and Signal Processing, 2006Co-Authors: Alptekin Temizel, Theo VlachosAbstract:A wavelet-domain Image Resolution enhancement algorithm which is based on the estimation of detail wavelet coefficients at high Resolution scales is proposed. The method exploits wavelet coefficient correlation in a local neighbourhood sense and employs linear least-squares regression to estimate the unknown detail coefficients. Results show that the proposed method is considerably superior to conventional Image interpolation techniques, both in objective and subjective terms, while it also compares favourably with competing methods operating in the wavelet domain.
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wavelet domain Image Resolution enhancement using cycle spinning
Electronics Letters, 2005Co-Authors: Alptekin Temizel, Theo VlachosAbstract:A wavelet domain Image Resolution enhancement method is proposed. The method adopts the cycle-spinning methodology adapted for use in the wavelet domain. The perceptual and objective quality of Resolution enhanced Images compare favourably with recently emerged algorithms in the field.
Anton Kummert - One of the best experts on this subject based on the ideXlab platform.
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a signal theoretic approach to measure the influence of Image Resolution for appearance based vehicle detection
IEEE Intelligent Vehicles Symposium, 2008Co-Authors: Anselm Haselhoff, Sam Schauland, Anton KummertAbstract:In this work a framework to measure the influence of training Image Resolution on classification performance for appearance-based object detection algorithms is presented. It is shown that based on sampling theory a reasonable Image Resolution for feature extraction can be chosen in advance, that is prior to the time consuming feature extraction and testing of the classifier. This is possible due to measuring the signal energy that is preserved in a low Resolution Image with respect to the optimal case of a high Resolution Image. The approach is justified using an AdaBoost algorithm with Haar-like features for vehicle detection. Tests of classifiers, trained with different Resolutions, are performed and the results are presented. These results reveal that there is a good tradeoff between classification performance and computational load. The presented framework helps choosing a Resolution for a good description of the training data.
