Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors
This paper proposes and evaluates the LFrWF, a novel lifting-based architecture to compute the discrete wavelet transform (DWT) of images using the fractional wavelet filter (FrWF). In order to reduce the memory requirement of the proposed architecture, only one image line is read into a buffer at a...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Multimedia |
| Online Access: | http://dx.doi.org/10.1155/2020/8823689 |
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| author | Mohd Tausif Ekram Khan Mohd Hasan Martin Reisslein |
| author_facet | Mohd Tausif Ekram Khan Mohd Hasan Martin Reisslein |
| author_sort | Mohd Tausif |
| collection | DOAJ |
| description | This paper proposes and evaluates the LFrWF, a novel lifting-based architecture to compute the discrete wavelet transform (DWT) of images using the fractional wavelet filter (FrWF). In order to reduce the memory requirement of the proposed architecture, only one image line is read into a buffer at a time. Aside from an LFrWF version with multipliers, i.e., the LFrWFm, we develop a multiplier-less LFrWF version, i.e., the LFrWFml, which reduces the critical path delay (CPD) to the delay Ta of an adder. The proposed LFrWFm and LFrWFml architectures are compared in terms of the required adders, multipliers, memory, and critical path delay with state-of-the-art DWT architectures. Moreover, the proposed LFrWFm and LFrWFml architectures, along with the state-of-the-art FrWF architectures (with multipliers (FrWFm) and without multipliers (FrWFml)) are compared through implementation on the same FPGA board. The LFrWFm requires 22% less look-up tables (LUT), 34% less flip-flops (FF), and 50% less compute cycles (CC) and consumes 65% less energy than the FrWFm. Also, the proposed LFrWFml architecture requires 50% less CC and consumes 43% less energy than the FrWFml. Thus, the proposed LFrWFm and LFrWFml architectures appear suitable for computing the DWT of images on wearable sensors. |
| format | Article |
| id | doaj-art-b1b2c7e0225c453bab8a39b147d7a14d |
| institution | Kabale University |
| issn | 1687-5680 1687-5699 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
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| series | Advances in Multimedia |
| spelling | doaj-art-b1b2c7e0225c453bab8a39b147d7a14d2025-02-03T01:04:29ZengWileyAdvances in Multimedia1687-56801687-56992020-01-01202010.1155/2020/88236898823689Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable SensorsMohd Tausif0Ekram Khan1Mohd Hasan2Martin Reisslein3Faculdade de Engenharia, Departamento de Informática, Universidade da Beira Interior, Covilhã, PortugalDepartment of Electronic Engineering, Zakir Husain College of Engineering & Technology, Aligarh Muslim University, Aligarh 202002, IndiaDepartment of Electronic Engineering, Zakir Husain College of Engineering & Technology, Aligarh Muslim University, Aligarh 202002, IndiaSchool of Electrical Computer and Energy Engineering, Arizona State University, Goldwater Center, East Tyler Mall 650, MC 5706, Tempe, AZ 85287-5706, USAThis paper proposes and evaluates the LFrWF, a novel lifting-based architecture to compute the discrete wavelet transform (DWT) of images using the fractional wavelet filter (FrWF). In order to reduce the memory requirement of the proposed architecture, only one image line is read into a buffer at a time. Aside from an LFrWF version with multipliers, i.e., the LFrWFm, we develop a multiplier-less LFrWF version, i.e., the LFrWFml, which reduces the critical path delay (CPD) to the delay Ta of an adder. The proposed LFrWFm and LFrWFml architectures are compared in terms of the required adders, multipliers, memory, and critical path delay with state-of-the-art DWT architectures. Moreover, the proposed LFrWFm and LFrWFml architectures, along with the state-of-the-art FrWF architectures (with multipliers (FrWFm) and without multipliers (FrWFml)) are compared through implementation on the same FPGA board. The LFrWFm requires 22% less look-up tables (LUT), 34% less flip-flops (FF), and 50% less compute cycles (CC) and consumes 65% less energy than the FrWFm. Also, the proposed LFrWFml architecture requires 50% less CC and consumes 43% less energy than the FrWFml. Thus, the proposed LFrWFm and LFrWFml architectures appear suitable for computing the DWT of images on wearable sensors.http://dx.doi.org/10.1155/2020/8823689 |
| spellingShingle | Mohd Tausif Ekram Khan Mohd Hasan Martin Reisslein Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors Advances in Multimedia |
| title | Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors |
| title_full | Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors |
| title_fullStr | Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors |
| title_full_unstemmed | Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors |
| title_short | Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors |
| title_sort | lifting based fractional wavelet filter energy efficient dwt architecture for low cost wearable sensors |
| url | http://dx.doi.org/10.1155/2020/8823689 |
| work_keys_str_mv | AT mohdtausif liftingbasedfractionalwaveletfilterenergyefficientdwtarchitectureforlowcostwearablesensors AT ekramkhan liftingbasedfractionalwaveletfilterenergyefficientdwtarchitectureforlowcostwearablesensors AT mohdhasan liftingbasedfractionalwaveletfilterenergyefficientdwtarchitectureforlowcostwearablesensors AT martinreisslein liftingbasedfractionalwaveletfilterenergyefficientdwtarchitectureforlowcostwearablesensors |