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Abstract
The utilization of Zernike moments has been extensive in various fields, including image processing and pattern recognition, owing to their desirable characteristics. However, the application of Zernike moments is hindered by two significant obstacles: computational efficiency and accuracy. These issues become particularly noticeable when computing high-order moments. This study presents a novel GPU-based method for efficiently computing high-order Zernike moments by leveraging the computational power of the Single Instruction Multiple Data (SIMD) architecture. The experimental results demonstrate that the proposed method can compute Zernike moments up to order 500 within 0.5 seconds for an image of size 512×512. To achieve greater accuracy in Zernike moments computation, a k×k sub-region scheme was incorporated into our approach. The results show that the PSNR value of the Lena image reconstructed from 500-order Zernike moments computed using the 9×9 scheme can reach 39.20 dB.
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