Enhancing Image Processing Capabilities through Advanced Approximate Multipliers

This paper explores the utilization of advanced approximate multipliers and 4-2 compressors to enhance efficiency in digital image processing applications. As the demand for real-time image analysis grows, the need for computational efficiency becomes increasingly critical, especially in resource-constrained environments. The proposed approach employs approximate computing to achieve a significant reduction in processing speeds and energy consumption while maintaining acceptable levels of output quality. Through a systematic implementation using a Field-Programmable Gate Array (FPGA) and MATLAB, we demonstrate the effectiveness of approximation techniques in image blending and enhancement tasks. Experimental results highlight a favorable trade-off between accuracy and performance, indicating that minor inaccuracies do not significantly impair visual quality. Our findings suggest that integrating approximate computing methodologies can revolutionize various technology-driven industries by enabling faster and more efficient image processing solutions

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Publication Details

Journal
International Journal of Computational and Experimental Science and Engineering
Published
2025-04-03
DOI
https://doi.org/10.22399/ijcesen.1399
Primary Topic
Low-power high-performance VLSI design
Type
article
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article

Enhancing Image Processing Capabilities through Advanced Approximate Multipliers

R Madhu, Sri Kalyan Yarlagadda, Satya Gautam Vadlamudi
International Journal of Computational and Experimental Science and Engineering
Low-power high-performance VLSI design
article

Enhancing Image Processing Capabilities through Advanced Approximate Multipliers

R Madhu, Sri Kalyan Yarlagadda, Satya Gautam Vadlamudi
article en

Abstract

This paper explores the utilization of advanced approximate multipliers and 4-2 compressors to enhance efficiency in digital image processing applications. As the demand for real-time image analysis grows, the need for computational efficiency becomes increasingly critical, especially in resource-constrained environments. The proposed approach employs approximate computing to achieve a significant reduction in processing speeds and energy consumption while maintaining acceptable levels of output quality. Through a systematic implementation using a Field-Programmable Gate Array (FPGA) and MATLAB, we demonstrate the effectiveness of approximation techniques in image blending and enhancement tasks. Experimental results highlight a favorable trade-off between accuracy and performance, indicating that minor inaccuracies do not significantly impair visual quality. Our findings suggest that integrating approximate computing methodologies can revolutionize various technology-driven industries by enabling faster and more efficient image processing solutions

International Journal of Computational and Experimental Science and EngineeringVol. 11(2)
Jawaharlal Nehru Technological University, Kakinada (IN), Randall University (US)
Openalex Percentile: Top 95%
Low-power high-performance VLSI design
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Enhancing Image Processing Capabilities through Advanced Approximate Multipliers — R Madhu, Sri Kalyan Yarlagadda, et al. · International Journal of Computational and Experimental Science and Engineering (2025) | TGRS Research Map | TGRS