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中文摘要：
提出的图像分割新算法利用当图像分辨率改变时，不同目标斑点模式变化方式的不同以及相邻图像尺度间的Markov性，推导得出了多尺度似然比的表达式；该方法同时考虑了多尺度自回归（MAR）模型产生的残差信息和较粗尺度图像的灰度信息，增强了区分度，分割结果更精确；考虑了被分类像素的邻域特性，使其对噪声不敏感，具有稳健性。实验结果表明分割效果是显著的。
英文摘要：
This algorithm exploits characteristic variations in speckle pattern as image resolution is varied from coarse to fine, and so does Markov property among scales. A new expression of multiscale likelihood ratio is obtained. Algorithm fuses residuals produced by MAR model and gray value information of coarse scale image. It increases the distinction of different targets, in the meanwhile, segmentation is precise. The use of window in the pixel-by-pixel classification makes the method insensitive to noise and robust. Experimental results demonstrate that the method performs fairly well.
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