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Hierarchical approaches to analysis of natural textures

机译:层次分析自然纹理的方法

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The surface textures of natural objects often have the visible fractal-like properties. A similar pattern of texture could be found looking at the forests in the aerial photographs or at the trees in the outdoor scenes when the image spatial resolution was changed. Or the texture patterns are different at different spatial resolution levels in the aerial photographs of villages. It creates the difficulties in image segmentation and object recognition because the levels of spatial resolution necessary to get the homogeneously and correctly labeled texture regions differ for different types of landscape. E.g. if the spatial resolution was sufficient for distinguishing between the textures of agricultural fields, water, and asphalt, the texture labeled areas of forest or suburbs are hardly fragmented, because the texture peculiarities corresponding to two stable levels of texture spatial resolution will be visible in this case. A hierarchical texture analysis could solve this problem, and we did it in two different ways: we performed the texture segmentation simultaneously for several levels of image spatial resolution, or we subjected the texture labeled image of highest spatial resolution to a recurring texture segmentation using the texture cells of larger sizes. The both approaches turned out to be rather fruitful for the aerial photographs as well as for the outdoor images. They generalize and support the hierarchical image analysis technique presented in another our paper. Some of the methods applied were borrowed from the living vision systems.
机译:天然物体的表面纹理通常具有可见的分形特征。当改变图像空间分辨率时,从航空摄影中的森林或室外场景中的树木中可以发现类似的纹理图案。或者在村庄的航拍照片中,在不同的空间分辨率级别上,纹理图案是不同的。由于在不同类型的景观中获得均匀且正确标记的纹理区域所需的空间分辨率级别不同,因此在图像分割和对象识别方面造成了困难。例如。如果空间分辨率足以区分农田,水和沥青的质地,则几乎不会将森林或郊区的带纹理标记的区域破碎,因为与这两个稳定水平的纹理空间分辨率相对应的纹理特性将在此可见案件。分层纹理分析可以解决此问题,我们可以通过两种不同的方式进行处理:我们针对多个级别的图像空间分辨率同时执行了纹理分割,或者对具有最高空间分辨率的纹理标记图像进行了周期性的纹理分割。较大尺寸的纹理单元。事实证明,这两种方法对于航空摄影以及室外图像都非常有用。他们归纳并支持另一篇论文中介绍的分层图像分析技术。某些应用的方法是从实时视觉系统中借用的。

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