局部相关的非线性采矿图像增强算法

A Nonlinear Mine Work Enhancement Method Based on Local Correlation

在矿井作业中,由于亮度不够,产生粉尘和噪声等不良因素,使得采集到的图像对比度下降和细节缺失。为改善上述问题,采用一种基于局部相关的非线性图像增强算法。该算法是由亮度增强和对比度增强2个独立部分组合而成。首先,将彩色图像转换为灰度图像;其次,对灰度图像使用非线性传递函数进行亮度增强;最后,处理后图像中像素点通过与其周围像素的关系来进行对比度增强。实验结果表明,该方法可以有效增强图像细节,提高图像整体亮度,对比度和抑制噪声。

In mining,due to the insufficient brightness,dust and noise and other adverse factors,the contrast of the collected image is reduced and the details are missing.In order to solve the above problems,a nonlinear mine work enhancement method based on local correlation is adopted.The algorithm is composed of brightness enhancement and contrast enhancement.The algorithm is composed of brightness enhancement and contrast enhancement.Firstly,the color image is transformed into gray image;secondly,the gray image is enhanced by nonlinear transfer function;finally,the contrast of the pixels in the processed image is enhanced by the relationship between the pixels and their surroundings.Experimental results show that this method can effectively enhance the image details,improve the global brightness and contrast of the image,and suppress the noise.