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High-speed low-complexity guided image filtering-based disparity estimation

High-speed low-complexity guided image filtering-based disparity estimation
High-speed low-complexity guided image filtering-based disparity estimation
Stereo vision is a methodology to obtain depth in a scene based on the stereo image pair. In this paper, we introduce a discrete wavelet transform (DWT)-based methodology for a state-of-the-art disparity estimation algorithm that resulted in significant performance improvement in terms of speed and computational complexity. In the initial stage of the proposed algorithm, we apply DWT to the input images, reducing the number of samples to be processed in subsequent stages by 50%, thereby decreasing computational complexity and improving processing speed. Subsequently, the architecture has been designed based on this proposed methodology and prototyped on a Xilinx Virtex-7 FPGA. The performance of the proposed methodology has been evaluated against four standard Middlebury Benchmark image pairs viz. Tsukuba, Venus, Teddy, and Cones. The proposed methodology results in the improvement of about 44.4% cycles per frame, 52% frames/s, and 61.5% and 59.6% LUT and register utilization, respectively, compared with state-of-the-art designs.
Vala, Charan Kumar
41279fa4-5cb5-469b-88ae-cc43a35c4325
Immadisetty, Koushik
f0936b4f-2881-4e77-8c9a-19097f24a465
Acharyya, Amit
f7c95a87-04ac-4d13-a74c-0c4d89b1c79c
Leech, Charles
6ba70c54-3792-41cd-a8d6-9e8884ae004f
Balagopal, Vibishna
dad9d32f-5fc2-4ec5-813c-b3b88b7f35d7
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Vala, Charan Kumar
41279fa4-5cb5-469b-88ae-cc43a35c4325
Immadisetty, Koushik
f0936b4f-2881-4e77-8c9a-19097f24a465
Acharyya, Amit
f7c95a87-04ac-4d13-a74c-0c4d89b1c79c
Leech, Charles
6ba70c54-3792-41cd-a8d6-9e8884ae004f
Balagopal, Vibishna
dad9d32f-5fc2-4ec5-813c-b3b88b7f35d7
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d

Vala, Charan Kumar, Immadisetty, Koushik, Acharyya, Amit, Leech, Charles, Balagopal, Vibishna, Merrett, Geoff V. and Al-Hashimi, Bashir (2017) High-speed low-complexity guided image filtering-based disparity estimation. IEEE Transactions on Circuits and Systems - I. (doi:10.1109/TCSI.2017.2729084).

Record type: Article

Abstract

Stereo vision is a methodology to obtain depth in a scene based on the stereo image pair. In this paper, we introduce a discrete wavelet transform (DWT)-based methodology for a state-of-the-art disparity estimation algorithm that resulted in significant performance improvement in terms of speed and computational complexity. In the initial stage of the proposed algorithm, we apply DWT to the input images, reducing the number of samples to be processed in subsequent stages by 50%, thereby decreasing computational complexity and improving processing speed. Subsequently, the architecture has been designed based on this proposed methodology and prototyped on a Xilinx Virtex-7 FPGA. The performance of the proposed methodology has been evaluated against four standard Middlebury Benchmark image pairs viz. Tsukuba, Venus, Teddy, and Cones. The proposed methodology results in the improvement of about 44.4% cycles per frame, 52% frames/s, and 61.5% and 59.6% LUT and register utilization, respectively, compared with state-of-the-art designs.

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Accepted/In Press date: 10 July 2017
e-pub ahead of print date: 10 August 2017

Identifiers

Local EPrints ID: 413464
URI: https://eprints.soton.ac.uk/id/eprint/413464
PURE UUID: 05f1d9e6-da87-4566-b31a-5de6d7978203
ORCID for Charles Leech: ORCID iD orcid.org/0000-0002-2403-3873
ORCID for Geoff V. Merrett: ORCID iD orcid.org/0000-0003-4980-3894

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Date deposited: 24 Aug 2017 16:30
Last modified: 06 Jun 2018 12:42

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Contributors

Author: Charan Kumar Vala
Author: Koushik Immadisetty
Author: Amit Acharyya
Author: Charles Leech ORCID iD
Author: Vibishna Balagopal
Author: Geoff V. Merrett ORCID iD

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