Fast parallel approach for 2-D DHT-based real-valued discrete Gabor transform

Authors:
Liang Tao;Hon Keung Kwan
Affiliations:
MOE Key Laboratory of Intelligent Computing and Signal Processing, School of Computer Science and Technology, Anhui University, Hefei, Anhui, China;Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada
Venue:
IEEE Transactions on Image Processing
Year:
2009

Citing 8
Cited 1

Matrix analysis

Matrix analysis
Discrete Gabor expansions

Signal Processing
Parallel lattice structure of block time-recursive generalized Gabor transforms

Signal Processing
Block Time-Recursive Real-Valued Discrete Gabor Transform Implemented by Unified Parallel Lattice Structures

IEICE - Transactions on Information and Systems
Noise Reduction for NMR FID Signals via Oversampled Real-Valued Discrete Gabor Transform

IEICE - Transactions on Information and Systems
Fast communication: Parallel lattice structures of block time-recursive discrete Gabor transform and its inverse transform

Signal Processing
Novel DCT-based real-valued discrete Gabor transform and its fast algorithms

IEEE Transactions on Signal Processing
A fast learning algorithm for Gabor transformation

IEEE Transactions on Image Processing

Multirate-based fast parallel algorithms for DCT-kernel-based real-valued discrete Gabor transform

Signal Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

Two-dimensional fast Gabor transform algorithms are useful for real-time applications due to the high computational complexity of the traditional 2-D complex-valued discrete Gabor transform (CDGT). This paper presents two block time-recursive algorithms for 2-D DHT-based real-valued discrete Gabor transform (RDGT) and its inverse transform and develops a fast parallel approach for the implementation of the two algorithms. The computational complexity of the proposed parallel approach is analyzed and compared with that of the existing 2-D CDGT algorithms. The results indicate that the proposed parallel approach is attractive for real time image processing.