基于对比度增强的雾霾图像移动窗阈值分割算法

Yi-tao Liang, Meng Zhang, Kui-bin Zhao, Yongzhi Li
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引用次数: 1

摘要

在恶劣天气条件下,大气粒子的散射导致图像质量下降。进而影响后期图像的阈值分割。提出了一种基于对比度增强的移动窗口阈值分割算法。根据灰度的特点,通过不同的直方图增强,可以有效地提高图像的对比度。移动窗口阈值分割可以重建图像的灰度空间。按照一定的规则,人工选择一小块Am XAn,对子块进行阈值分割。然后从上到下逐行扫描得到整幅图像的阈值分割。然后,将分割结果合并在一起,对图像块相邻节点进行平滑处理,得到最终的图像分割。实验结果表明,图像灰度直方图完全增强了雾霾图像,有效抑制了噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Haze image moving window threshold segmentation algorithm based on contrast enhancement
Under the bad weather, scattering of atmospheric particles lead to the degradation of image quality. And then the later image threshold segmentation is affected. We propose a moving-window threshold segmentation algorithm based on contrast enhancement. According to the characteristics of gray levels and by way of different histogram enhancement, the image contrast can be effectively improved. Moving-window threshold segmentation can reconstruct image gray space. In accordance with the certain rules and artificial selection of a small piece of Am XAn, threshold segmentation of sub-block can be done. Then the threshold segmentation of the whole image can be obtained through progressive scan from top to bottom. Then, by combining the split result together and smoothing the image block adjacent joint, the final image segmentation is obtained. The experimental results show that image gray histogram completely enhances the haze image and efficiently restrains the noise.
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