Visible and Infrared Image Fusion for Space Debris Recognition with Convolutional Sparse Representaiton

Space debris is becoming a serious problem for spacecraft in norm operation. Visible sensor is mainly used to avoid potential collision from space debris in space-based optical surveillance projects. Nevertheless, it strongly relies on illumination of sunrise. Inspired by image fusion technology with deep learning, we propose an all-weather space debris recognition method with convolutional sparse representation to deal with different illumination. First, infrared and visible image which contained space debris are fused with convolutional sparse representation, then the space debris is recognized with deep convolutional neural network for fused image. The experimental results prove the applicability of the method.