Image Resolution Algorithm for Mixed Pixel in Remote Sensing Data
Image Resolution Algorithm for Mixed Pixel in Remote Sensing Data
复制标题
遥感数据混合像素图像分辨率算法
DOI：
10.1541/ieejeiss1987.121.5_961
复制
发表时间：
2001
影响因子：
--
通讯作者：
M. Nishida
中科院分区：
文献类型：
--
作者：
Y. Kageyama;M. Nishida
遥感数据中混合像元的图像分辨率算法影山洋一，成员，西田诚，成员（秋田大学）遥感数据中由几类组成的像元称为混合像元（mixel），由于数据的分辨率，混合像元存在很多。当混合像元位于边界区域时，可按类混合比例将其划分为土地覆盖类集合的纯像元。因此，本文提出了一种新的遥感数据混合像素的图像分辨率算法。该方法包括三个步骤。开始，用模糊推理估计组分的类别数和类别混合比。接下来，假设邻近像素的类混合比示出扩展像素与邻近八个像素之间的关系的强度。基于每个扩展像素和邻近像素的位置信息和假设，计算每个扩展像素和邻近像素之间的关联度。最后，利用计算绘制出扩展图像。作为经验的结果，很明显，所提出的方法是能够准确地放大mixel与以前的方法和传统的方法相比。
Image Resolution Algorithm for Mixed Pixel in Remote Sensing Data Yoichi Kageyama, Member, Makoto Nishida, Member (Akita University) A pixel composed of several classes in remote sensing data is called mixed pixel (mixel), and the mixel exists a lot due to resolution of data. When a mixel is in the boundary area, it can be divided into pure pixel of landcover class set in proportion to the class mixture ratio. Therefore, this paper proposes a new image resolution algorithm for mixel in remote sensing data. The approach consists of three steps. To begin with, component class number and class mixture ratio are estimated with the fuzzy reasoning. Next, it is assumed that class mixture ratio of vicinity pixels shows the intensity of the relation between the extension pixels and vicinity eight pixels. Degree of association between each extension pixel and vicinity pixels is computed based on their position information and the assumption. Finally, using the computation draws an extension image. As a result of experience, it became clear that the proposed approach was able to accurately magnify the mixel in comparison with the previous method and conventional method.