摘要
由于在遥感成像的区域中存在云的影响,从遥感图像中无法获取有云区域中的详细信息,因此对遥感图像的去云技术研究成为图像增强领域的研究热点。文章基于小波变换理论的遥感图像增强,提出一种基于中值滤波和小波分析结合运用于遥感图像增强的新算法。在计算机自动实现和用户交互实现时,将小波工具引入到云层提取、处理的过程中来,实现从单幅图像中去除薄云,改善效果而不增加其他副作用。对比遥感图像原图的直方图和增强后的直方图,经过新算法处理后图像均值变低,平均灰度降低。结果表明:该算法在去噪的同时能保留大量的图像边缘细节等重要信息,具有非常好的去噪效果。
Because of the influence of cloud in the remote sensing image region, it is impossible to obtain the detailed information of the cloud region from the remote sensing image, so the research on cloud removal technology of remote sensing image has become a research hotspot in the field of image enhancement. Based on wavelet transform theory, a new algorithm for remote sensing image enhancement based on median filtering and wavelet analysis is proposed in this paper. When the interaction between computer and user is implemented, wavelet tools are introduced into the process of cloud extraction and processing to remove thin clouds from a single image and improve the effect without increasing other side effects. Compared with the original histogram of remote sensing image and the enhanced histogram, the average value of image is lower and the average gray level is lower after the new algorithm processing. The results show that the algorithm can retain a lot of important information such as image edge details while denoising,and has a very good denoising effect.
引文
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