Constraints to solve parallelogram grid problems in 2D non separable linear canonical transform

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Title: Constraints to solve parallelogram grid problems in 2D non separable linear canonical transform
Authors: Zhao, LiangHealy, John J.Muniraj, InbarasanCui, Xiao-GuangMalallah, Ra'edRyle, James P.Sheridan, John T.
Permanent link: http://hdl.handle.net/10197/8716
Date: 27-Apr-2017
Online since: 2017-08-14T15:49:02Z
Abstract: The 2D non-separable linear canonical transform (2D-NS-LCT) can model a range of various paraxial optical systems. Digital algorithms to evaluate the 2D-NS-LCTs are important in modeling the light field propagations and also of interest in many digital signal processing applications. In [Zhao 14] we have reported that a given 2D input image with rectangular shape/boundary, in general, results in a parallelogram output sampling grid (generally in an affine coordinates rather than in a Cartesian coordinates) thus limiting the further calculations, e.g. inverse transform. One possible solution is to use the interpolation techniques; however, it reduces the speed and accuracy of the numerical approximations. To alleviate this problem, in this paper, some constraints are derived under which the output samples are located in the Cartesian coordinates. Therefore, no interpolation operation is required and thus the calculation error can be significantly eliminated.
Funding Details: Science Foundation Ireland
Funding Details: Insight Research Centre
Type of material: Conference Publication
Keywords: Personal sensingDigital holographyABCD transformsNumerical approximation and analysisDiscrete optical signal processing
Other versions: https://spie.org/conferences-and-exhibitions/optics-and-optoelectronics
Language: en
Status of Item: Peer reviewed
Conference Details: Optics and Optoelectronics, Prague, Czech Republic, 24-27 April 2017
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Solar Energy Conversion (SEC) Cluster Research Collection
Electrical and Electronic Engineering Research Collection
Insight Research Collection

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