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The generation of a time correlated 2D random process for ocean wave motion

机译:生成海浪运动的时间相关的2D随机过程

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Increasingly, image analysis is concerned with image sequences as opposed to individual image frames. The need to generate model data for such image analysis problems is therefore apparent. One class of data which is well suited to the techniques discussed is that of the motion of ocean waves and time sequences of these images. This problem occurs in sensor modelling and analysis, for example, in sonar studies, the problem of studying the backscatter characteristics from waves is essential for understanding the sonar process and its uses in the analysis of sonar images. Similarly, the analysis of infrared sensor data for glint from ocean scenes presents unique problems. Both types of data involve wave motion and its effect on the analysis of such sequences presents particularly unique problems. This paper looks at the modelling of time sequences of ocean waves with application to the analysis of images, synthesised from the sensors mentioned previously.
机译:越来越多地,图像分析涉及图像序列,而不是单个图像帧。因此,需要为这种图像分析问题生成模型数据是显而易见的。非常适合讨论的技术的一类数据是这些图像的海浪和时间序列的运动的运动。传感器建模和分析中出现此问题,例如,在声纳研究中,研究从波的反向散射特性的问题对于了解声纳过程以及在分析声纳图像的分析中是必不可少的。同样,从海洋场景中闪烁的红外传感器数据的分析具有独特的问题。两种类型的数据涉及波动和其对对这些序列的分析的影响呈现出特别独特的问题。本文研究了从先前提到的传感器合成的图像分析的海浪时间序列的建模。

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