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DCT/IDCT filter design for ultrasound image filtering

Shakibaei, B. H., Flusser, J., Zhao, Y., Erkoyuncu, J. A. and Roy, R. ORCID: 0000-0001-5491-7437 (2021). DCT/IDCT filter design for ultrasound image filtering. Paper presented at the 25th International Conference on Pattern Recognition (ICPR), 10-15 Jan 2021, Milan, Italy.

Abstract

In this paper, a new recursive structure based on the convolution model of discrete cosine transform (DCT) for designing of a finite impulse response (FIR) digital filter is proposed. In our derivation, we start with the convolution model of DCT-II to use its Z-transform for the proposed filter structure perspective. Moreover, using the same algorithm, a filter base implementation of the inverse DCT (IDCT) for image reconstruction is developed. The computational time experiments of the proposed DCT/IDCT filter(s) demonstrate that the proposed filters achieve faster elapsed CPU time compared to the others. The image filtering and reconstruction performance of the proposed approach on ultrasound images are presented to validate the theoretical framework.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version of this paper has been published in 2020 25th International Conference on Pattern Recognition (ICPR) and can be found at 10.1109/ICPR48806.2021.9412838
Publisher Keywords: Wiener filters, Ultrasonic imaging, Finite impulse response filters, Convolution, Filtering, Filtering algorithms, Fetus
Subjects: T Technology > T Technology (General)
Departments: School of Mathematics, Computer Science & Engineering
Date available in CRO: 10 Nov 2021 14:03
Date deposited: 10 November 2021
Date of first online publication: 5 May 2021
URI: https://openaccess.city.ac.uk/id/eprint/26998
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