Satellite Image Small Target Super-Resolution Detection Based on ACGAN and Enhanced DETR

Abstract

In recent years, with the rapid development of deep learning, neural network and other related technologies and their wide application in image processing research, the degree of intelligence in the field of image processing research is getting higher and higher. Especially in the research of image small target detection, because of its relatively small shape, image small target has relatively few and unclear feature information and detail information, which makes it easy to make errors and omissions in recognition and detection. To improve the precision of satellite image small target detection, this paper processes a small image target super-resolution detection based on ACGAN and enhanced DETR. In this paper, ACGAN is used to classify and generate the feature information of small targets in images to enhance the feature information of small targets to be measured. Second, the DETR algorithm model is improved, and a small target detection algorithm model with image super-resolution enhancement is designed to generate high-resolution images by super-resolution reconstruction of images with enhanced target feature information to improve the detection accuracy of image small targets. The experiments in this paper show that after the processing of target feature enhancement and image super-resolution quality enhancement, the detection accuracy of image small targets has been improved significantly.