Forest vegetation remote sensing image segmentation is an important kind of target, and effective determination of the scale of forest vegetation texture segmentation is an important research topic. This paper presents a method in which the blue noise theory is used to describe the characteristics of remote sensing images for forest vegetation texture. This is a new method for vegetation texture characterization and texture scale calculation. The correspondence between the research scale morphology and vegetation textures can be used in the selected detection area to iteratively search for blue noise characteristics. Iteration consists of the reduction of the region size through the geometric transformation and the obtaining of a spectral response region by fast Fourier transform so as to extract the blue noise characteristics from the spectral response. For regions with blue noise characteristics, the intensity distribution of forest vegetation texture is computed, and the texture size is calculated based on the current size of the area. Experimental results show that the gray scale and the distribution of forest vegetation texture units can be accurately measured, which lays reliable foundation for further texture segmentation.
刘小丹, 杨燊. 基于蓝噪声理论的遥感图像森林植被纹理测量[J]. 国土资源遥感, 2015, 27(2): 63-68.
LIU Xiaodan, YANG Shen. Forest vegetation texture measurement of remote sensing images based on the blue noise theory. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(2): 63-68.
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