一种基于局部方差的雾天图像增强方法

Algorithm based on local variance to enhance contrast of fog-degraded image

提出了一种基于图像局部方差的保持灰度级和亮度的雾天图像增强算法。即在对图像作局部处理的基础上,利用局部方差可以较好的体现图像细节信息的特性,通过计算并比较图像局部标准方差的大小来判断局部图像的增强程度,然后以灰度均值为基准进行局部灰度拉伸。该算法可以有效增强和保留图像细节,克服了传统直方图均衡化处理所造成的灰度级损失的缺点,保持了原图的灰度级和平均亮度,较好的抑制了噪声,图像视觉效果明显改善,因此特别适合于深度信息多变且对比度较低的雾天图像。实验结果表明该算法可以有效的增强雾天图像。

This paper presented an image contrast enhancement method based on local variance that can preserve brightness and gray levels. Because of the characteristic that local variance can show the detail of image, a method of contrast enhancement through local variance comparison to judge enhancement degree was proposed. It can not only enhance the image contrast and hold the details simultaneously, prevent gray levels losing, but also keep the contrast, brightness of the original image and suppress noise. Thus it is especially adapted to the fog-degraded images with scene depth variations. Experimental results show that the proposed algorithm is effective.