利用多普勒效应分析提高无线电台记录的涡旋结构和气流剖面可分辨性的算法

E. Semenishchev, A. Zelensky, M. Zhdanova, N. Gapon, A. Gavlicky, V. Voronin
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引用次数: 0

摘要

针对机器人复合体在粉尘和雾中处理产品的问题,提出了一种红外和可见光谱图像的融合技术和算法。原始数据处理基于多准则处理准则的使用,具有复杂的数据分析和不同类型数据过滤系数的交叉变化。基点的搜索是基于应用减少聚类范围(图像简化)的技术,并使用确定局部函数斜率的方法搜索过渡边界。作为评估有效性的测试数据,使用分辨率为1024x768(8位,彩色图像,可见范围)和1024x768(8位,彩色,红外图像)的传感器获得的成对测试图像。简单形状的图像被用作分析对象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm for increasing the discriminability of sections of vortex structures and wind flows recorded by radio frequency stations using Doppler effect analysis
The article proposes a fusion technique and an algorithm for combining images recorded in the IR and visible spectrum in relation to the problem of processing products by robotic complexes in dust and fog. Primary data processing is based on the use of a multi-criteria processing criterion with complex data analysis and cross-change of the filtration coefficient for different types of data. The search for base points is based on the application of the technique of reducing the range of clusters (image simplification) and searching for transition boundaries using the approach of determining the slope of the function in local areas. As test data used to evaluate the effectiveness, pairs of test images obtained by sensors with a resolution of 1024x768 (8-bit, color image, visible range) and 1024x768 (8 bit, color, IR image) are used. Images of simple shapes are used as analyzed objects.
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审稿时长
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