Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Changchun 130033, China.
Sensors (Basel). 2021 Aug 24;21(17):5684. doi: 10.3390/s21175684.
Since remote sensing images are one of the main sources for people to obtain required information, the quality of the image becomes particularly important. Nevertheless, noise often inevitably exists in the image, and the targets are usually blurred by the acquisition of the imaging system, resulting in the degradation of quality of the images. In this paper, a novel preprocessing algorithm is proposed to simultaneously smooth noise and to enhance the edges, which can improve the visual quality of remote sensing images. It consists of an improved adaptive spatial filter, which is a weighted filter integrating functions of both noise removal and edge sharpness. Its processing parameters are flexible and adjustable relative to different images. The experimental results confirm that the proposed method outperforms the existing spatial algorithms both visually and quantitatively. It can play an important role in the remote sensing field in order to achieve more information of interested targets.
由于遥感图像是人们获取所需信息的主要来源之一，因此图像的质量显得尤为重要。然而，图像中往往不可避免地存在噪声，并且目标通常会因成像系统的采集而变得模糊，从而导致图像质量下降。在本文中，提出了一种新颖的预处理算法，可同时平滑噪声并增强边缘，从而提高遥感图像的视觉质量。该算法由改进的自适应空间滤波器组成，它是一种加权滤波器，集成了去噪和边缘锐化的功能。其处理参数相对于不同的图像具有灵活性和可调节性。实验结果证实，该方法在视觉和定量方面均优于现有的空间算法。它可以在遥感领域发挥重要作用，以实现更多感兴趣目标的信息。
