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噪声去除一直是基于卫星高度计资料的海洋中尺度涡提取研究的难点和热点,然而无论是卷积滤波器还是信息滤波器都存在对海面高度异常(SLA)数据的局部过处理现象。鉴于此,本文提出一种基于包络面去噪的海洋中尺度涡提取方法。该算法可利用分离层内的信息稳定性和层间的信息完备性,很好地改进了卷积运算没有考虑局部噪声的不足,进而有效地提高去噪能力。其具体流程为:首先,对初始化的原始数据场进行上下包络面构造,形成原始数据子场;然后,根据子场内部和子场间的稳健性,把原始数据场转换为子场集合;其次,利用子场极差和标准差,对子场集合进行信息重组,形成噪声去除后的信息场;最后,利用去噪后的信息场数据,采用Winding-Angle(WA)和泛克立金中尺度涡提取算法在西北太平洋进行对比验证实验。实验结果表明,本文提出的方法较前人的方法有较大的提升,准确率为91.23%,取得了较好的应用效果。
Noise removal has always been a difficult and hot topic in mesoscale vortex extraction based on satellite altimetry data. However, both the convolution filter and the information filter have local over-processing of SLA data. In view of this, this paper presents an ocean mesoscale vortex extraction method based on envelope denoising. The algorithm can make use of the information stability in the separation layer and the information completeness between layers, and improves the lack of consideration of local noise in the convolution operation, thus effectively improving the denoising capability. The specific process is as follows: Firstly, the original data field of the initialized data is constructed up and down envelope to form the original data sub-field; then, the original data field is converted into sub-field set according to the robustness between the sub-field and the sub-field; , The information field of noise sub-field is formed by reorganizing the information of the sub-field set by using the sub-field range and standard deviation. Finally, using the denoised information field data, using Winding-Angle (WA) Scale vortex extraction algorithm in the Northwest Pacific contrast verification experiment. Experimental results show that the method proposed in this paper has a greater improvement than the previous methods, with an accuracy of 91.23%, and achieved good results.