Abstract
Synthetic Aperture Radar (SAR) imaging technology is gradually applied in the field of security inspection. However, the existence of speckle noise in SAR image will seriously affect its image interpretation and post-processing. To solve this problem, a SAR image preprocessing algorithm based on improved homomorphic wavelet transform (HWT) and Retinex is proposed. Firstly, the HWT is improved. The SAR images obtained after denoising by homomorphic wavelet threshold denoising method and total variation (TV) model denoising method were decomposed by \({\text{coi}}f4\) wavelet basis, and the low-frequency parts obtained by homomorphic wavelet threshold denoising method and the high-frequency parts obtained by TV model denoising method are recombined; Then, the recombined sub-image is reconstructed by inverse wavelet transform to achieve better denoising effect while retaining the effective boundary information; Finally, the single-scale Retinex (SSR) algorithm is used to enhance the reconstructed SAR image to further improve the image quality. Experimental results show that the proposed algorithm can effectively remove noise while enhancing the edge and detail information of the image, and improve image readability and the accuracy of security check target detection and recognition.
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Acknowledgments
We acknowledge funding from the sub project of national key R & D plan covid-19 patient rehabilitation training posture monitoring bracelet based on 4G network (Grant No.2021YFC0863200-6), the Hebei College and Middle School Students Science and Technology Innovation Ability Cultivation Special Project (Grant No.22E50075D), (Grant No.2021H010206), and (Grant No.2021H010203).
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Wang, J., Cheng, H., Wang, X., Zhao, Y., Liu, S., Yu, P. (2023). A SAR Image Preprocessing Algorithm Based on Improved Homomorphic Wavelet Transform and Retinex. In: Xu, Y., Yan, H., Teng, H., Cai, J., Li, J. (eds) Machine Learning for Cyber Security. ML4CS 2022. Lecture Notes in Computer Science, vol 13657. Springer, Cham. https://doi.org/10.1007/978-3-031-20102-8_29
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