Δημοσιεύσεις σε συνέδρια

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Browsing Δημοσιεύσεις σε συνέδρια by Author "Anastassopoulos, Vassilis"

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    Open Access
    Interpolation in multispectral data using neural networks
    (2011-12-08) Tsagaris, Vassilis; Panagiotopoulou, Antigoni; Anastassopoulos, Vassilis; Τσαγκάρης, Βασίλειος; Παναγιωτοπούλου, Αντιγόνη; Αναστασόπουλος, Βασίλειος
    Τμήμα Φυσικής (Δημοσ. Π.Π. σε συνέδρια)
    A novel procedure which aims in increasing the spatial resolution of multispectral data and simultaneously creates a high quality RGB fused representation is proposed in this paper. For this purpose, neural networks are employed and a successive training procedure is applied in order to incorporate in the network structure knowledge about recovering lost frequencies and thus giving fine resolution output color images. MERIS multispectral data are employed to demonstrate the performance of the proposed method.
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    Open Access
    Super-resolution image reconstruction employing Kriging interpolation technique
    (2011-12-08) Panagiotopoulou, Antigoni; Anastassopoulos, Vassilis; Παναγιωτοπούλου, Αντιγόνη; Αναστασόπουλος, Βασίλειος
    Τμήμα Φυσικής (Δημοσ. Π.Π. σε συνέδρια)
    In this paper a high-resolution (HR) image is reconstructed from a sequence of subpixel shifted, aliased low-resolution (LR) frames by means of a novel nonuniform interpolation super-resolution (SR) method. A gradient-based algorithm estimates the horizontal and vertical shifts for each frame. Then, the uniformly spaced sampling points of the HR image are produced by means of Kriging interpolation. Wiener filtering is employed to deal with the restoration problem. The novelty of the proposed nonuniform interpolation approach to SR image reconstruction lies in the employment of Kriging interpolation technique. Comparisons with the original image demonstrate the superiority of our method to a conventional nonuniform interpolation one of SR image reconstruction.
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    Open Access
    Super-resolution reconstruction of thermal infrared images
    (2011-12-08) Panagiotopoulou, Antigoni; Anastassopoulos, Vassilis; Παναγιωτοπούλου, Αντιγόνη; Αναστασόπουλος, Βασίλειος
    Τμήμα Φυσικής (Δημοσ. Π.Π. σε συνέδρια)
    In this paper a high-resolution (HR) thermal infrared image is reconstructed from a sequence of subpixel shifted, aliased low-resolution (LR) frames, by means of a stochastic regularized super-resolution (SR) method. The Huber (H) cost function is employed to measure the difference between the projected estimate of the HR image and each LR frame. The bilateral Total Variation (TV) regularization is incorporated as a priori knowledge about the solution. The proposed HTV super-resolution approach that employs the Huber norm in combination with the bilateral TV regularization exhibits superior performance to former SR method. Thus the effect of outliers is significantly reduced and the high-frequency edge structures of the reconstructed HR thermal infrared image are preserved. The proposed technique is also tested on frames that are corrupted by Gaussian noise and proves superior when compared to existing regularized SR method.