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Hybrid method to extract striation features from ship noise spectrogram

机译:杂交方法从船舶噪声谱图中提取抗议功能

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The features of interference striations excited by a passing ship are strongly determined by the acoustic waveguide properties. These striation position and orientation have been used for environmental inverse problems. The ship noise spectrogram can be very noisy due to measurement conditions, i.e., high ambient noise level or transmission loss noise. It is necessary to enhance the underlying interference structure before extracting the striation features of interest. A hybrid image processing method is introduced in this paper for interference structure enhancement. It first uses a Gabor filter bank to provide the local image intensity maximum value in different directions, and then locally equalizes the resulting image. Different ship noise data sets from different experiments are processed by the proposed method. Preliminary results demonstrate that the hybrid method can effectively identify striations in both low and high frequency regions, especially for the data set collected under particularly difficult measurement conditions due to strong current, surface wave, high ambient noise level, complex time-varying source spectrum, etc. Consequently, better estimates of the position and orientation of local striations can be obtained, which will likely improve the accuracy of striation-based inversion techniques.
机译:通过声波的特性强烈地确定由通过船激发的干涉条纹的特征。这些条件位置和方向已被用于环境逆问题。由于测量条件,即高环境噪声水平或传输损耗噪声,船噪声谱图可以非常嘈杂。在提取感兴趣的突变特征之前,有必要增强底层干扰结构。本文介绍了混合图像处理方法,用于干涉结构增强。首先使用Gabor滤波器组在不同方向上提供本地图像强度最大值,然后本地均衡所得到的图像。来自不同实验的不同船舶噪声数据集由所提出的方法处理。初步结果表明,混合方法可以有效地识别低频区域和高频区域中的条纹,特别是对于由于电流,表面波,高环境噪声水平,复杂的时变源谱,复杂的时变源谱而在特别困难的测量条件下收集的数据集,因此,可以获得可以获得局部条纹位置和取向的更好估计,这可能提高基于条纹的反转技术的准确性。

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