【摘要】 提出了一种基于纹理分割的遥感图像目标探测算法(TBAD).将一幅图像分割成一系列的纹理,进而分析像素值在纹理上的分布特性.假设背景像素值在各个不同的纹理上可以用高斯分布描述,则各个纹理上远离高斯分布的像素点便是可能的目标点.TBAD估计背景的统计特性是在分割以后的纹理上进行的,因此可以探测任意大小和形状的目标.试验结果进一步验证了算法不论对于扩展目标还是弱小目标都具有很好的探测性能.更多还原

【Abstract】 A new texture-based anomaly detection(TBAD) approach was presented,which segmented one image into different textures and analyzes the distribution of pixel values of the textures.TBAD assumes that the background pixel values within textures can be modeled as Gaussian distributions with mean values that vary texture-to-texture.And the anomalies(man-made objects) have values that deviate significantly from the distribution of the texture.TBAD estimates background statistics over segmented textures,so it can detect objects of any size or shape.Extensive experiments applied to the real images of small target and extend target validate the good performance of the approach.更多还原