Sampling Theorems Associated with Offset Linear Canonical Transform by Polar Coordinates

The sampling theorem for the offset linear canonical transform (OLCT) of bandlimited functions in polar coordinates is an important signal analysis tool in many fields of signal processing and optics. This paper investigates two sampling theorems for interpolating bandlimited and highest frequency bandlimited functions in the OLCT and offset linear canonical Hankel transform (OLCHT) domains by polar coordinates. Based on the classical Stark’s interpolation formulas, we derive the sampling theorems for bandlimited functions in the OLCT and OLCHT domains, respectively. The first interpolation formula is concise and applicable. Due to the consistency of the OLCHT order, the second interpolation formula is superior to the first interpolation formula in computational complexity.

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Publication Details

Journal
Fractal and Fractional
Published
2024-09-26
DOI
https://doi.org/10.3390/fractalfract8100559
Citations
2
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
0.50

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article

Sampling Theorems Associated with Offset Linear Canonical Transform by Polar Coordinates

Hui Zhao, Bing‐Zhao Li
2 citations
Fractal and Fractional
Image and Signal Denoising Methods
0.50
article

Sampling Theorems Associated with Offset Linear Canonical Transform by Polar Coordinates

Hui Zhao, Bing‐Zhao Li
article en
2 citations

Abstract

The sampling theorem for the offset linear canonical transform (OLCT) of bandlimited functions in polar coordinates is an important signal analysis tool in many fields of signal processing and optics. This paper investigates two sampling theorems for interpolating bandlimited and highest frequency bandlimited functions in the OLCT and offset linear canonical Hankel transform (OLCHT) domains by polar coordinates. Based on the classical Stark’s interpolation formulas, we derive the sampling theorems for bandlimited functions in the OLCT and OLCHT domains, respectively. The first interpolation formula is concise and applicable. Due to the consistency of the OLCHT order, the second interpolation formula is superior to the first interpolation formula in computational complexity.

Fractal and FractionalVol. 8(10)
Beijing Institute of Technology (CN), Shijiazhuang Tiedao University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 35%
Image and Signal Denoising Methods
0.50
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