论文部分内容阅读
MASK匀光算法广泛应用于光学遥感图像增强领域,以消除影像的光照不均匀现象,但传统MASK匀光算法处理过的图像,存在反差不均匀现象,且易丢失原始影像的细节信息。针对传统MASK算法的不足,文章提出了一种基于局部统计特征的非线性MASK匀光算法,通过实际遥感图像实验,证明本文方法能在减小原始影像细节信息损失的前提下,消除光照不均匀的现象,且处理之后的图像反差得到增强,整体趋于一致,匀光效果较为理想。
The MASK uniform illumination algorithm is widely used in the field of optical remote sensing image enhancement to eliminate the uneven illumination of the image. However, the images processed by the traditional MASK uniform illumination method have the phenomenon of uneven contrast and easily lose the detail information of the original image. Aiming at the deficiency of traditional MASK algorithm, this paper presents a non-linear MASK uniform illumination algorithm based on local statistics. Experiments on actual remote sensing images show that this method can reduce the illumination unevenness under the premise of reducing the loss of original image detail information The image contrast after processing is enhanced, the whole tends to be consistent, the light uniformity effect is more ideal.