Intelligent Image Semantic Segmentation: A Review Through Deep Learning Techniques for Remote Sensing Image Analysis

Image semantic segmentation is an important part of fundamental in image interpretation and computer vision. With the development of convolutional neural network technology, deep learning-based image semantic segmentation methods have received more and more attention and research. At present, many excellent semantic segmentation methods have been proposed and applied in the field of remote sensing. In this paper, we summarized the semantic segmentation methods used for remote sensing image, including the traditional remote sensing image semantic segmentation methods and the methods based on deep learning, we emphasize on summarizing the remote sensing image semantic segmentation algorithms based on deep learning and classify them into different categories, and then we introduce the datasets that commonly used and data preparation methods including pre-processing and augmentation techniques. Finally, the challenges and future directions of research in this domain are analyzed and prospected. It is hoped that this study can widen the frontiers of knowledge and provide useful literature for researchers interested in advancing this field of research.