Performance enhancement of RGB image convolution using convolution kernel clustering algorithm for ARM64 processor architecture

Authors

DOI:

https://doi.org/10.18372/2073-4751.81.20144

Keywords:

convolution operation, NEON64, ARM64, SIMD optimization, vectorization, RGB images, convolution kernel clustering, digital image processing, sparse matrices, OpenCV

Abstract

The paper presents a method for improving the performance of RGB image convolution operation on the ARM64 platform using a convolution kernel element clustering algorithm. The proposed approach is based on vectorization of computations using NEON64 SIMD instructions and grouping of non-zero kernel elements with the same sign for efficient skipping of operations with zero elements. A mathematical model of vectorized convolution operation has been developed, which takes into account the specifics of sparse convolution kernel matrices. Experimental study on the Orange Pi 5 Pro platform demonstrated significant acceleration compared to the cv::filter2D() function of the OpenCV library: for medium-sized kernels (7×7 – 11×11), an acceleration of 5.0–9.7 times was achieved, for large kernels (12×12 – 15×15) – 1.7–5.5 times. The proposed method is particularly effective for processing high-resolution images and can be applied in real-time systems on single-board computers with limited computational resources.

References

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Published

2025-06-01

How to Cite

Shevchenko, A. (2025). Performance enhancement of RGB image convolution using convolution kernel clustering algorithm for ARM64 processor architecture. Problems of Informatization and Control, 1(81), 140–149. https://doi.org/10.18372/2073-4751.81.20144

Issue

Vol. 1 No. 81 (2025)

Section

Статті

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