Fast and accurate algorithms for quadratic phase integrals in optics and signal processing
Proceedings of SPIE
Item Usage Stats
The class of two-dimensional non-separable linear canonical transforms is the most general family of linear canonical transforms, which are important in both signal/image processing and optics. Application areas include noise filtering, image encryption, design and analysis of ABCD systems, etc. To facilitate these applications, one need to obtain a digital computation method and a fast algorithm to calculate the input-output relationships of these transforms. We derive an algorithm of NlogN time, N being the space-bandwidth product. The algorithm controls the space-bandwidth products, to achieve information theoretically sufficient, but not redundant, sampling required for the reconstruction of the underlying continuous functions. © 2011 SPIE.
Linear Canonical Transforms
Design and analysis
Fast and accurate algorithms
Linear canonical transform
Published Version (Please cite this version)http://dx.doi.org/10.1117/12.884676
Showing items related by title, author, creator and subject.
Sarıyüce, A. E.; Gedik, B.; Jacques-Silva, G.; Wu, Kun-Lung; Catalyurek, U.V. (Association for Computing Machinery, 2016)A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, ...
Tse, Savio S.H. (Springer, 2008-10)We study the online bicriteria load balancing problem in this paper. We choose a system of distributed homogeneous file servers located in a cluster as the scenario and propose two online approximate algorithms for balancing ...
Akçay, H. G.; Aksoy, S. (Institute of Electrical and Electronics Engineers, 2008-07)The object-based analysis of remotely sensed imagery provides valuable spatial and structural information that is complementary to pixel-based spectral information in classification. In this paper, we present novel methods ...