Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Adaptive Regularization For Image Restoration Using A Variational Inequality Approach, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Adaptive Regularization For Image Restoration Using A Variational Inequality Approach, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Faculty of Informatics - Papers (Archive)
In this paper, a generalized image restoration method is formulated as a variational inequality problem, whose solution is obtained using a dynamic system approach. In this method, the restored image and the regularization parameter are obtained simultaneously. In particular, the optimum regularization parameter is determined adaptively, depending on noise and image content. The restoration problem is presented in a generalized form so that it maybe be implemented using different norms; only L1 and L2 norms have been implemented in this paper. A comparison based on experimental results shows that the proposed method achieves comparable if not better performance as some …
Automatic Parameter Selection For Feature-Enhanced Radar Image Restoration, Moeness G Amin, Cher Hau Seng, Son Lam Phung, Abdesselam Bouzerdoum
Automatic Parameter Selection For Feature-Enhanced Radar Image Restoration, Moeness G Amin, Cher Hau Seng, Son Lam Phung, Abdesselam Bouzerdoum
Faculty of Informatics - Papers (Archive)
In this paper, we propose a new technique for optimum parameter selection in non-quadratic radar image restoration. Although both the regularization hyper-parameter and the norm value are influential factors in the characteristics of the formed restoration, most existing optimization methods either require memory intensive computation or prior knowledge of the noise. Here, we present a contrast measure-based method for automated hyper-parameter selection. The proposed method is then extended to optimize the norm value used in non-quadratic image formation and restoration. The proposed method is evaluated on the MSTAR public target database and compared to the GCV method. Experimental results show …
A Compressive Sensing Approach To Image Restoration, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
A Compressive Sensing Approach To Image Restoration, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Faculty of Informatics - Papers (Archive)
In this paper the image restoration problem is solved using a Compressive Sensing approach, and the translation invariant, a Trous, undecimated wavelet transform. The problem is cast as an unconstrained optimization problem which is solved using the Fletcher-Reeves nonlinear conjugate gradient method. A comparison based on experimental results shows that the proposed method achieves comparable if not better performance as other state-of-the-art techniques.
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Faculty of Informatics - Papers (Archive)
In this paper, we propose a new technique for image fusion in multi-view through-the-wall radar imaging system. As most existing image fusion methods for through-the-wall radar imaging only consider a global fusion operator, it is desirable to consider the differences between each pixel using a local operator. Here, we present a fuzzy logic-based method for pixel-wise image fusion. The performance of the proposed method is evaluated on both simulated and real data from through-the-wall radar imaging system. Experimental results show that the proposed method yields improved performance, compared to existing methods.