摘要
矿山遥感图像的质量受成像区域环境的影响较大,加之成像器件固有的缺陷,易导致获取的图像存在一定程度的失真,影响对遥感图像的判读和分析。为此,在中值滤波(Median filtering,MF)算法的基础上进行了加权改进,提出了一种适合于遥感图像处理的自适应加权改进中值滤波算法(Adaptive weighted improved median filtering,AWIMF)。首先将遥感图像划分为多个尺寸为7×7的图像块,对每个图像块分别统计像素点灰度极大(小)值,将该类像素点标记为第1类疑似噪声点;其次计算每个图像块的像素点灰度中值,将各图像块中的每个像素点灰度值与对应的像素点灰度中值作差,将较大差值对应的像素点标记为第2类疑似噪声点,将2次检测均被标记为疑似噪声点的像素点确定为噪声点;然后,以每个噪声点为中心选取尺寸为5×5的滤波窗口,根据滤波窗口内各像素点灰度值与所在滤波窗口的像素点灰度中值的差值计算权重,分别将各像素点灰度值与对应的权重进行加权计算,实现对噪声点的高效滤波;最后,采用直方图规定化算法(Histogram specification,HS)对滤波后的图像对比度进行调节。采用内蒙古白云鄂博矿区遥感图像进行试验,结果表明,所提算法的性能相对于中值滤波及其已有的几类改进型算法而言,优势较明显。
The quality of mine remote sensing image is affected by the imaging regional environment greatly,and the imaging device inherent defects make access to the obtained remote sensing image with certain degree of distortion,which appeared all kinds of random noise. The median filtering（ MF） algorithm is weighted improved,a new adaptive weighted improved median filtering（ AWIMF） algorithm that is suitable for remote sensing image processing is proposed. Firstly,the image is divided into many image blocks with the size of 7 ×7,the maximum and minimum pixel gray values of each image block are counted out,and the pixels are marked as the class one suspected noise points; secondly,the pixel gray median values of each image block are calculated,each pixel gray value of the each image blocks and its corresponding pixel gray median values are made differential operation,the pixels corresponding with larger differential values are marked as the class two suspected noise points,the pixels that are marked as the suspected noise points in the process of noise detection are identified as noise points;thirdly,centered with each noise points,the filter windows with the size of 5×5 are selected,based on the each pixel gray values in the filtering windows and the gray median values of the corresponding filtering windows,the weighted values are calculated,each pixel gray value and its corresponding weighted value are conducted weighted calculation to filtering out the noise points effectively; finally,the filtered remote sensing image contrast is adjusted by adopting the histogram specification（ HS） algorithm,the remote sensing image of Baiyun Obo mining area,Inner Mongolia is used as the experimental data,the experimental results show that the performance of the algorithm proposed in this paper is superior to median filtering（ MF） algorithm and its several existing improved algorithms.
出处
《金属矿山》
CAS
北大核心
2016年第4期101-105,共5页
Metal Mine
关键词
矿山遥感图像
中值滤波
疑似噪声点
加权改进中值滤波
直方图规定化
Mine remote sensing image
Median filtering
Suspected noise point
Weighted improved median filtering
Histogram specification
