桂林电子科技大学学报2024，Vol.44Issue(6)：592-598,7.DOI:10.16725/j.1673-808X.2022202
基于协同对抗优化网络的图像压缩感知重建
Image compressive sensing reconstruction based on cooperative adversarial optimization network
摘要
Abstract
In view of the information loss in existing deep network-based image compressive sensing reconstruction algorithm,which leads to blurred reconstruction,a generative adversarial mechanism is introduced,and an image compressive sensing recon-struction algorithm based on cooperative adversarial optimization network is proposed.The algorithm inputs the image observations into the generator,and uses the multi-scale structure feature extraction module to refine the multi-level structure of the image;intro-duces an adversarial mechanism,and uses the non-local similar features of the image to confront the generated images of the genera-tor.,to achieve accurate reconstruction of the original image.The experimental results show that compared with the existing algo-rithm,the objective evaluation index of the reconstructed image increases the PSNR value by 1.68-2.33 dB,and the SSIM by 0.037 6-0.059 2.The visual effect of the image is outstanding,and it can effectively construct finer image features.关键词
压缩感知/图像重建/生成对抗/协同重构/深度学习Key words
compressed sensing/image reconstruction/generative adversarial/collaborative reconstruction/deep learning分类
信息技术与安全科学引用本文复制引用
林乐平,朱静,欧阳宁..基于协同对抗优化网络的图像压缩感知重建[J].桂林电子科技大学学报,2024,44(6):592-598,7.基金项目
国家自然科学基金(62001133,61661017,61362021) （62001133,61661017,61362021）
广西科技基地和人才专项(桂科AD19110060) （桂科AD19110060）
广西自然科学基金(2017GXNSFBA-198212) （2017GXNSFBA-198212）
广西无线宽带通信与信号处理重点实验室基金(GXKL06200114) （GXKL06200114）
