目的 为了能够快速得到适于视觉解译的UWB SAR图像,提出了一种基于数据筛选的低频UWB SAR图像快速可视化算法。方法 该方法从统计学的角度出发,讨论了低频UWB SAR图像数据的统计特性和灰度分布模型;在此基础上,首次提出采用3σ准则对低频UWB SAR图像数据进行筛选;并使用修正映射函数映射。结果 对处理后所得图像进行质量评估,可以发现,所得灰度图在等效视数、中央凹特征和对比敏感度特征等方面要优于传统方法处理的处理结果,因而更符合人类视觉系统特征,更易于人眼视觉系统全面了解低频UWB SAR图像表征的场景信息。结论 与传统方法相比,该算法能自适应压缩图像动态范围,处理耗时短,所得图像细节突出,适于对低频UWB SAR图像数据实时处理。

Objective Visualization of ultra wide bandwidth synthetic aperture radar (UWB SAR) data involves mapping from a high dynamic range amplitude values to the gray values of a lower dynamic range display device. This step is vital in the processing of UWB SAR images. However, traditional visual methods are unsuitable for the processing of UWB SAR images because these methods do not consider the characters of UWB SAR and because these methods require long processing time. To compress the UWB SAR data dynamic range in a shorter time, a new fast visualization method based on screening data for UWB SAR images is proposed. Method In the new method, the distribution of low frequency UWB SAR data and gray-value images is first discussed to obtain easily the reasonable distribution model for UWB SAR images. A 3σ measurement and amend mapping function are used to screen the image data. Therefore, the high dynamic range of amplitude values is compressed in a small dynamic range. The quality of UWB SAR images should be evaluated to determine which image is convenient for the human visual system to obtain more geographic information. Result The proposed method costs less time compared with the original method, and the performance indicators of the former are better than that of the latter. The dark pixels are also stretched appropriately, and the bright details are preserved. Moreover, the images handled by the new method are suitable for the human visual system. Conclusion Therefore, this method will have a major role in the real-time processing of UWB SAR image data.