A Scale-Adaptive Super-Resolution Algorithm for Single Remote Sensing Image
Wenjuan Zhang, Zhen Li, Shanjing Chen, Yuxi Wang, Hongli Li · IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium · 2022
Single image super-resolution (SISR) algorithm is to recover a high-resolution image from a single low-resolution one and has been widely applied in remote sensing (RS) reconstruction. Numerous SISR models have been proposed for RS ap-plications. However, most existing methods suffer from an inability to reconstruct multi-scale RS images using one fixed pre-trained model. Here, we design a scale-adaptive SISR algorithm for RS images. The main contributions are three-fold: (1) to be applied for the multi-scale reconstruction, we first employ the bicubic interpolation to stretch the images before import so that our convolutional neural network can focus on refining the details of reconstruction images; (2) to extract the deep information of ground surface from RS images, we design multi-scale residual network to recover the image details; (3) we adopt the least-absolute-error loss to constraint our network for reconstructing the RS images. It is demonstrated that our model achieves excellent performance for super-resolution of RS images.