基于联合域滤波的无人机载SAR图像块效应抑制方法

doi:10.12305/j.issn.1001-506X.2023.09.15

摘要/Abstract

摘要：

针对无人机载合成孔径雷达(synthetic aperture radar, SAR)成像系统因采用基于块的离散余弦变换压缩方法所产生的块效应问题, 提出一种基于联合域滤波的块效应抑制方法。首先, 从无人机载SAR成像系统工作原理出发, 介绍无人机载SAR图像的压缩处理流程, 分析产生块效应的机理。然后, 在地面端对SAR图像解压过程的变换域和像素域中分别加入块效应滤波处理手段, 其中变换域采用的是“十字型”转移块滤波方法, 像素域采用的是双边滤波方法。最后, 通过联合域滤波方法达到抑制无人机载SAR图像块效应的目的。实验结果表明, 在同等压缩系数条件下, 本文方法相比于其他滤波方法可以获得更好的峰值信噪比结果, 降低无人机载SAR图像因图像压缩造成的失真影响, 具有很强的块效应抑制能力。

关键词: 无人机, 合成孔径雷达图像, 块效应, 离散余弦变换

Abstract:

To address the block effect problem caused by the block-based discrete cosine transform (DCT) compression method of the unmanned aerial vehicle (UAV) borne synthetic aperture radar (SAR) imaging system, a block effect suppression method based on joint domain filtering is proposed. This method first starts from the working principle of the UAV-borne SAR imaging system, introduces the compression processing process of SAR image on the UAV platform, analyzes the mechanism of generating the block effect, and then adds the block effect filtering processing method to the transformation domain and pixel domain of the SAR image decompression process at the ground end. The transformation domain adopts the "cross-type" transfer block filtering method, the pixel domain adopts the bilateral filtering method. Finally the purpose of suppressing the SAR image block effect is achieved by the joint domain filtering method. Experimental results show that under the same compression coefficient conditions, the proposed method can obtain better peak to signal noise ratio (PSNR) results than other filtering methods, reduce the distortion effect of the UAV-borne SAR image due to image compression, and have strong block effect inhibition ability.

Key words: unmanned aerial vehicle (UAV), synthetic aperture radar (SAR) image, block effect, discrete cosine transform (DCT)

中图分类号:

TN958.98

王中宝, 尹奎英. 基于联合域滤波的无人机载SAR图像块效应抑制方法[J]. 系统工程与电子技术, 2023, 45(9): 2768-2776.

Zhongbao WANG, Kuiying YIN. Block effect suppression method of UAV-borne SAR image based on joint domain filtering[J]. Systems Engineering and Electronics, 2023, 45(9): 2768-2776.

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