Although imaging sensors are the dominant technologies for both user and industry applications, they still have several physical limitations, such as noise and limited spatial resolution. These limitations can be overcome, based on device electronics and physics technology. However, a promising solution is a signal processing approach that has been one of the most active research areas, and it is called Super Resolution (SR). This work proposes SR algorithm that uses an affine block-based with the Maximum Likelihood. A number of experiments were performed with the proposed system to obtain reconstructed High Resolution (HR) images of different resolutions from the same set of Low Resolution (LR) images. Also, a number of experiments were performed to evaluate its behavior as a function of the number of available LR images. The algorithm improves the accuracy of translational registration and accurately recovers HR image even in the case where just very a few input images are provided. This work should be especially useful to professionals in Image Processing, Signal Processing, and Electronics fields, or anyone else who may be considering utilizing Resolution Enhancement.
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Sahar A. Ismail, is Assistant Professor at Faculty of Engineering, Shoubra, Benha University, Cairo, Egypt. Her research interests include Artificial intelligent, Computer Vision, Image Processing, and Signal Processing.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Although imaging sensors are the dominant technologies for both user and industry applications, they still have several physical limitations, such as noise and limited spatial resolution. These limitations can be overcome, based on device electronics and physics technology. However, a promising solution is a signal processing approach that has been one of the most active research areas, and it is called Super Resolution (SR). This work proposes SR algorithm that uses an affine block-based with the Maximum Likelihood. A number of experiments were performed with the proposed system to obtain reconstructed High Resolution (HR) images of different resolutions from the same set of Low Resolution (LR) images. Also, a number of experiments were performed to evaluate its behavior as a function of the number of available LR images. The algorithm improves the accuracy of translational registration and accurately recovers HR image even in the case where just very a few input images are provided. This work should be especially useful to professionals in Image Processing, Signal Processing, and Electronics fields, or anyone else who may be considering utilizing Resolution Enhancement. 120 pp. Englisch. Seller Inventory # 9783659519130
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ismail SaharSahar A. Ismail, is Assistant Professor at Faculty of Engineering, Shoubra, Benha University, Cairo, Egypt. Her research interests include Artificial intelligent, Computer Vision, Image Processing, and Signal Processing. Seller Inventory # 5161923
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Although imaging sensors are the dominant technologies for both user and industry applications, they still have several physical limitations, such as noise and limited spatial resolution. These limitations can be overcome, based on device electronics and physics technology. However, a promising solution is a signal processing approach that has been one of the most active research areas, and it is called Super Resolution (SR). This work proposes SR algorithm that uses an affine block-based with the Maximum Likelihood. A number of experiments were performed with the proposed system to obtain reconstructed High Resolution (HR) images of different resolutions from the same set of Low Resolution (LR) images. Also, a number of experiments were performed to evaluate its behavior as a function of the number of available LR images. The algorithm improves the accuracy of translational registration and accurately recovers HR image even in the case where just very a few input images are provided. This work should be especially useful to professionals in Image Processing, Signal Processing, and Electronics fields, or anyone else who may be considering utilizing Resolution Enhancement.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch. Seller Inventory # 9783659519130
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Although imaging sensors are the dominant technologies for both user and industry applications, they still have several physical limitations, such as noise and limited spatial resolution. These limitations can be overcome, based on device electronics and physics technology. However, a promising solution is a signal processing approach that has been one of the most active research areas, and it is called Super Resolution (SR). This work proposes SR algorithm that uses an affine block-based with the Maximum Likelihood. A number of experiments were performed with the proposed system to obtain reconstructed High Resolution (HR) images of different resolutions from the same set of Low Resolution (LR) images. Also, a number of experiments were performed to evaluate its behavior as a function of the number of available LR images. The algorithm improves the accuracy of translational registration and accurately recovers HR image even in the case where just very a few input images are provided. This work should be especially useful to professionals in Image Processing, Signal Processing, and Electronics fields, or anyone else who may be considering utilizing Resolution Enhancement. Seller Inventory # 9783659519130
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Taschenbuch. Condition: Neu. Super Resolution | Reconstruction Of High-resolution Image From A Set Of Low-resolution Images | Sahar Ismail (u. a.) | Taschenbuch | 120 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659519130 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 105444494