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The research of image segmentation methods for interested area extraction in image matching guidance

机译:图像匹配制导中感兴趣区域提取的图像分割方法研究

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The extraction of Region of Interest (ROI) is an important information guarantee in the application of imaging matchingguidance, which directly affects the acquisition probability and matching accuracy of the target. Image segmentation is animportant method to extract the Region of Interest of the target. Based on image segmentation algorithm, histogramequalization and morphological filtering, this paper proposes an effective image processing method to extract the Regionof Interest of the target. A variety of image threshold segmentation methods are applied to the actual processing flow,and their segmentation performance is compared and analyzed. Some image segmentation methods are obtained, whichare suitable for target region extraction in template image preparation and target potential region location in matchingrecognition. Preliminary localization of visible remote sensing images is carried, using color information, to obtainlocal regions, then enhance the image using histogram equalization method, finally morphological filtering is used toremove the edge noise. The Otsu method and Kittler minimum error method are processed in parallel, then thesegmentation results are fused, and the evaluation indexes such as area constraint, similarity and contrast are filtered toobtain the target region .Tests have been done with visible image and infrared image in this paper. The result indicates thatthe effectiveness of the morphological filter is more obvious after histogram equalization for the original image. Besides,the Otsu method and Kittler minimum error method are processed in parallel, then the segmentation results are fused toget preciser Region of Interest, thus ensuring the accuracy and timeliness of imaging matching guidance.
机译:感兴趣区域(ROI)的提取是成像匹配应用中的重要信息保证 指导,直接影响目标的获取概率和匹配精度。图像分割是 提取目标感兴趣区域的重要方法。基于图像分割算法的直方图 均衡和形态滤波,提出了一种有效的图像处理方法来提取区域 目标的利益。各种图像阈值分割方法被应用于实际处理流程, 并对其分割效果进行了比较和分析。获得了一些图像分割方法,这些方法 适用于模板图像准备中的目标区域提取和匹配中的目标潜在区域位置 认出。使用颜色信息进行可见遥感图像的初步定位,以获取 局部区域,然后使用直方图均衡化方法对图像进行增强,最后使用形态学滤波 消除边缘噪声。 Otsu方法和Kittler最小误差方法并行处理,然后 融合分割结果,并将诸如面积约束,相似性和对比度之类的评估指标过滤为 获得目标区域。本文对可见光图像和红外图像进行了测试。结果表明 对原始图像进行直方图均衡后,形态滤波器的效果更加明显。除了, 并行处理Otsu方法和Kittler最小误差方法,然后将分割结果融合到 获得更精确的关注区域,从而确保成像匹配指导的准确性和及时性。

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