摘要
提出基于Hop fie ld神经网络的遥感图像超分辨率目标识别算法,它是利用模糊分类技术进行模糊分类,然后用分类结果约束Hop fie ld神经网络的方法.通过实验,可知Hop fie ld神经网络在学习样本少时,也能够输出分辨率相对较高的地物目标信息.因此,基于Hop fie ld神经网络的遥感图像处理方法,能够提高遥感图像的目标分辨率,使其目标特征信息更清晰.
A remote sensing image super resolution object recognition algorithm based on Hopfield Neural Networks is proposed. Fuzzy classification technology is used for classification. Then the result is used to restrict Hopfield Neural Networks. When there are only few learning samples, Hopfield Nerve Net can also output object information with higher resolution. Therefore, this remote sensing image processing approach can enhance the object resolution of remote sensing image and make the object character characteristic more in focus.
出处
《武汉理工大学学报（交通科学与工程版）》
2005年第6期970-973,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
湖北省自然科学基金项目资助(批准号:2003AB042)
