论文标题
使用新的图像更平滑的方法及其在环境遥感中的应用，对多光谱卫星图像中现象的识别和分类
Identification and Classification of Phenomena in Multispectral Satellite Imagery Using a New Image Smoother Method and its Applications in Environmental Remote Sensing
论文作者
论文摘要
在本文中，提出了一种新的图像平滑方法，用于卫星图像及其在环境遥感中的应用。该方法基于整个图像上的全局梯度最小化。关于图像离散身份，连续最小化问题被离散化。使用有限的差分分化方法，得出了一个简单而有效的5*5像素模板。在不同频段中使用图像的衍生模板的卷积导致各种图像元素的歧视。此方法非常快，除了高度精确。为伊朗北部提出了一个案例研究，覆盖了里海的一部分。该方法与通常的拉普拉斯模板的比较表明，它更有能力区分图像中的现象。
In this paper a new method of image smoothing for satellite imagery and its applications in environmental remote sensing are presented. This method is based on the global gradient minimization over the whole image. With respect to the image discrete identity, the continuous minimization problem is discretized. Using the finite difference numerical method of differentiation, a simple yet efficient 5*5-pixel template is derived. Convolution of the derived template with the image in different bands results in the discrimination of various image elements. This method is extremely fast, besides being highly precise. A case study is presented for the northern Iran, covering parts of the Caspian Sea. Comparison of the method with the usual Laplacian template reveals that it is more capable of distinguishing phenomena in the image.
