Download Image Analysis and Recognition: 12th International by Mohamed Kamel, Aurélio Campilho PDF

By Mohamed Kamel, Aurélio Campilho

ISBN-10: 3319208004

ISBN-13: 9783319208008

ISBN-10: 3319208012

ISBN-13: 9783319208015

This publication constitutes the completely refereed lawsuits of the twelfth foreign convention on picture research and popularity, ICIAR 2015, held in Niagara Falls, ON, Canada, in July 2015. The fifty five revised complete papers and five brief papers awarded have been conscientiously reviewed and chosen from eighty submissions. The papers are geared up within the following topical sections: picture caliber overview; photograph enhancement; photo segmentation, registration and research; picture coding, compression and encryption; dimensionality relief and category; biometrics; face description, detection and popularity; human task acceptance; robotics and 3D imaginative and prescient; scientific photograph research; and applications.

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Extra info for Image Analysis and Recognition: 12th International Conference, ICIAR 2015, Niagara Falls, ON, Canada, July 22-24, 2015, Proceedings

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Here, the fidelity term is given by T (Ax, y) = 1 − S(Ax, y), where S(·, ·) is the simplified version of the SSIM as a normalized metric [6,17,18]. The unconstrained counterpart of (4) was studied in [17]. In this case, an algorithm that uses a generalization of the soft-thresholding operator [11,23] is employed for solving the following optimization problem: min T (Ax, y) + γ x x∈D 1 . (5) The advantage of these formulations is that the concepts of similarity and sparsity are combined into a single optimization problem; therefore, solutions of this problem are similar to the observation y in the SSIM sense and also sparse.

In other words, the strength of the regularization tends to be the same for these two methods. Along with the images of the bottom row, the SSIM maps that depict the similarity between the original sub-image and its reconstructions are shown in the top row. The higher the brightness of these maps at a given location, the higher the SSIM at that particular point [28]. 9117). 9629). This should not be surprising since several recovered DCT coefficients are not set to zero by the proposed algorithm, which is not always the case for the other two methods.

SIAM J. Imaging Sci. Arch. 2(1), 183–202 (2009) 2. : Analyse Fonctionelle Theorie et Applications. Masson editeur, Paris (1963) 3. : From sparse solutions of systems of equations to sparse modeling of signals and images. SIAM Rev. 51(1), 34–81 (2009) 4. D. thesis, University of Waterloo (2010) 5. : On the mathematical properties of the structural similarity index. IEEE Trans. Image Proc. 21(4), 1488–1499 (2012) 6. : Structural similarity-based approximation of signals and images using orthogonal bases.

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