Information Technology Journal

Volume 19 (1), 1-11, 2020


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Implementation of Wavelet-based Architecture for Optimization Image Filtering

Ogunlere Samson Ojo, Ajaegbu Chigozirim and Oladejo Daniel Oluwaninyo

Background and Objective: Existing implementations of wavelet-based image filtering architecture shad design complexities which translated to implementation complexities and low clock frequency. As a result, they failed to meet the requirement for real-time applications. Implementation of image filtering cannot be separated from optimization, hence, optimizations must be continually devised to meet real-time requirements of wavelet-based image filtering. This research aimed at the optimization of existing wavelet-based hardware architecture for embedded image filtering. Materials and Methods: This work presents a two-dimensional (2-D) discrete wavelet transform (DWT) architectural design using Verilog Hardware Description Language (Verilog HDL). To reduce implementation complexities, a basic linear algebra approach is used for the Haar transform. A register transfer level (RTL) optimization is proposed to shorten the worst-case filter path delay, thus increasing the maximum operating frequency. Validation of the proposed optimization involved, the design of a circuit for the DWT computation, simulation and implementation in field programmable gate array (FPGA). Results: Result achieved shows substantial decreased hardware cost, high signal-to-noise ratio (SNR) and high operating frequency when compared to the existing works used as benchmark. Conclusion: This work validates that compensating for the filtering delay in a multi-level wavelet-based image filtering architecture can optimize speed and resource utilization while obtaining a high SNR.

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How to cite this article:

Ogunlere Samson Ojo, Ajaegbu Chigozirim and Oladejo Daniel Oluwaninyo, 2020. Implementation of Wavelet-based Architecture for Optimization Image Filtering. Information Technology Journal, 19: 1-11.


DOI: 10.3923/itj.2020.1.11
URL: https://ansinet.com/abstract.php?doi=itj.2020.1.11

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