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K-Coherence Terrain Texture Upscaling Using Gabor Wavelets

机译:使用Gabor小波升高的K-相干地形纹理

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Terrain texture is ubiquitous visual information that is widely used in geo-experience. It can describe a variety of surface characteristics such as terrain, plants, minerals, fur and skin and it covers the spectrum of textures from completely regular to near-regular to irregular. A near-regular texture deviates geometrically and photo-metrically from a regular congruent tiling. They can be readily observed in man-made and nature environments: buildings, wallpapers, floors, tiles, windows, fabric and honeycomb, animal fur, feathers and so on. This paper focuses on a class of near-regular textures (NRT) that are regular textures under locally smooth geometric and appearance deformations. In this paper, Gabor wavelet filter is introduced into K-Coherence calculation. In this method, the statistics of filtered wavelet are regarded as feature vectors, and the difference in two points is measured by the Euclidean Distance between feature vectors. In this way, the matching process of K-Coherence will be more accurate, which will further result in the improvement on terrain texture synthesis to some degree.
机译:地形纹理是广泛应用于地理体验的无处不在的视觉信息。它可以描述各种表面特征,如地形,植物,矿物质,毛皮和皮肤,它涵盖了完全定期的纹理谱,近乎定期达到不规则。近常规纹理从正常的同时平铺偏离几何上和照片。他们可以在人造和自然环境中容易地观察它们:建筑物,壁纸,地板,瓷砖,窗户,织物和蜂窝,动物毛皮,羽毛等。本文重点介绍一类近常规纹理(NRT),这些近似纹理在局部光滑的几何和外观变形下。本文将Gabor小波滤波器引入K-相干计算。在该方法中,滤波小波的统计数据被认为是特征向量,并且通过特征向量之间的欧几里德距离来测量两个点的差异。以这种方式,K-相干的匹配过程将更加准确,这将进一步导致地形纹理合成的改善到某种程度上。

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