基于最大累积剩余熵的红外图像分割



经典阈值化分割方法是常用的图像分割方法之一,但对于低对比度,低信噪比的红外图像分割效果 不理想,将累积剩余熵运用于红外图像分割,即寻求使得累积剩余熵最大的灰度值作为分割阈值,实验结果表明：基于最大累积剩余熵的图像分割方法是一种有效的 红外图像分割方法,比起经典的阈值分割方法,分割红外图像的效果要好

-Segmentation based on maximum cumulative residual entropy classic infrared image thresholding method is one of the commonly used image segmentation method, but for low-contrast, low SNR infrared image segmentation is not satisfactory, the cumulative residual entropy applied to infrared image segmentation, that makes the search for the maximum cumulative residual entropy of gray values as a threshold value segmentation experimental results show that: image segmentation based on maximum cumulative residual entropy method is an effective infrared image segmentation method, compared to the classical threshold segmentation method, infrared image segmentation better than