Digital image compression using approximate addition
This paper analyzes the usefulness of approximate addition for digital image compression. Discrete Cosine Transform (DCT) is an important operation in digital image compression. We used accurate addition and approximate addition individually while calculating the DCT to perform image compression. Ac...
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sg-ntu-dr.10356-1607182022-08-01T07:46:33Z Digital image compression using approximate addition Balasubramanian, Padmanabhan Nayar, Raunaq Maskell, Douglas Leslie School of Computer Science and Engineering Transport Research Centre Engineering::Computer science and engineering Image Processing Approximate Computing This paper analyzes the usefulness of approximate addition for digital image compression. Discrete Cosine Transform (DCT) is an important operation in digital image compression. We used accurate addition and approximate addition individually while calculating the DCT to perform image compression. Accurate addition was performed using the accurate adder and approximate addition was performed using different approximate adders individually. The accurate adder and approximate adders were implemented in an application specific integrated circuit (ASIC)-type design environment using a 32–28 nm complementary metal oxide semiconductor (CMOS) standard cell library and in a field programmable gate array (FPGA)-based design environment using a Xilinx Artix-7 device. Error analysis was performed to calculate the error parameters of various approximate adders by applying one million random input vectors. It is observed that the approximate adders help to better reduce the file size of compressed images than the accurate adder. Simultaneously, the approximate adders enable reductions in design parameters compared to the accurate adder. For an ASIC-type implementation using standard cells, an optimum approximate adder achieved 27.1% reduction in delay, 46.4% reduction in area, and 50.3% reduction in power compared to a high-speed accurate carry look-ahead adder. With respect to an FPGA-based implementation, an optimum approximate adder achieved 8% reduction in delay and 19.7% reduction in power while requiring 47.6% fewer look-up tables (LUTs) and 42.2% fewer flip-flops compared to the native accurate FPGA adder. Ministry of Education (MOE) Published version This research was funded by the Ministry of Education (MOE), Singapore under Academic Research Fund Tier-2 grant number MOE2018-T2-2-024. 2022-08-01T07:46:32Z 2022-08-01T07:46:32Z 2022 Journal Article Balasubramanian, P., Nayar, R. & Maskell, D. L. (2022). Digital image compression using approximate addition. Electronics, 11(9), 1361-. https://dx.doi.org/10.3390/electronics11091361 2079-9292 https://hdl.handle.net/10356/160718 10.3390/electronics11091361 2-s2.0-85128729018 9 11 1361 en MOE2018-T2-2-024 Electronics © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
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Engineering::Computer science and engineering Image Processing Approximate Computing Balasubramanian, Padmanabhan Nayar, Raunaq Maskell, Douglas Leslie Digital image compression using approximate addition |
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This paper analyzes the usefulness of approximate addition for digital image compression. Discrete Cosine Transform (DCT) is an important operation in digital image compression. We used accurate addition and approximate addition individually while calculating the DCT to perform image compression. Accurate addition was performed using the accurate adder and approximate addition was performed using different approximate adders individually. The accurate adder and approximate adders were implemented in an application specific integrated circuit (ASIC)-type design environment using a 32–28 nm complementary metal oxide semiconductor (CMOS) standard cell library and in a field programmable gate array (FPGA)-based design environment using a Xilinx Artix-7 device. Error analysis was performed to calculate the error parameters of various approximate adders by applying one million random input vectors. It is observed that the approximate adders help to better reduce the file size of compressed images than the accurate adder. Simultaneously, the approximate adders enable reductions in design parameters compared to the accurate adder. For an ASIC-type implementation using standard cells, an optimum approximate adder achieved 27.1% reduction in delay, 46.4% reduction in area, and 50.3% reduction in power compared to a high-speed accurate carry look-ahead adder. With respect to an FPGA-based implementation, an optimum approximate adder achieved 8% reduction in delay and 19.7% reduction in power while requiring 47.6% fewer look-up tables (LUTs) and 42.2% fewer flip-flops compared to the native accurate FPGA adder. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Balasubramanian, Padmanabhan Nayar, Raunaq Maskell, Douglas Leslie |
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Article |
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Balasubramanian, Padmanabhan Nayar, Raunaq Maskell, Douglas Leslie |
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Balasubramanian, Padmanabhan |
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Digital image compression using approximate addition |
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Digital image compression using approximate addition |
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Digital image compression using approximate addition |
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Digital image compression using approximate addition |
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Digital image compression using approximate addition |
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digital image compression using approximate addition |
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2022 |
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https://hdl.handle.net/10356/160718 |
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