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A method of image segmentation based on mutual information and threshold iteration of multi-spectral image fusion

机译:基于互信息和阈值迭代的多光谱图像融合图像分割方法

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The surface color of some mature fruit has little difference with the background color or the entire fruit surface color has inconsistent under the nature growth condition. This fruit image segmentation is very difficulty with the color threshold or the segmentation result is the serious error of the goal outline. A new mutual information threshold iteration segmentation method based on the multi-spectrum image fusion is proposed. First, gather visible light color image and the near-infrared image of the same target, fusion processing the multi-spectrum image using image fusion algorithm (PCA-LWT) based on PCA and lifting wavelet transformation; Then, carries on mutual information optimal threshold value iteration division to the fusion image. Through target extraction experiment of many tomato images, the result indicate carrying on mutual information optimal threshold value iteration segmentation to the visible light and the near-infrared PCA-LWT fusion image, may obtain good segmentation effect, and can solve this kind of image segmentation problem well.
机译:一些成熟果实的表面颜色与背景颜色或整个果实表面颜色的差异很小,在自然生长条件下具有不一致。这种果实图像分割非常困难,颜色阈值或分割结果是目标轮廓的严重错误。提出了一种基于多频率图像融合的新的互信息阈值迭代分段方法。首先,收集可见光彩色图像和相同目标的近红外图像,融合使用基于PCA和提升小波变换的图像融合算法(PCA-LWT)的多频谱图像;然后,执行互联图像的互信息最佳阈值迭代划分。通过对许多番茄图像的目标提取实验,结果表明携带相互信息的最佳阈值迭代分段对可见光和近红外PCA-LWT融合图像,可以获得良好的分割效果,并且可以解决这种图像分割问题嘛。

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