基于正则性约束的耦合自编码图像超分辨率重建
Image Super Resolution based on Auto-Encoder Networks with Joint Regularization
Abstract
超分辨率重建(Super-Resolution,SR)算法是利用一张或多张的低分辨率图像(LowResolution,LR)重建出一张高分辨率图像(HighResolution,HR)。超分辨率重建是计算机视觉领域中的一个热点问题,近年来基于深度学习的超分辨率重建方法取得了突破性进展,将超分辨性能提升到一个新的水平。然而,超分辨率重建是一个不适定问题,对于这样的问题,如何利用先验知识设定正则性约束建立优化模型是超分重建的关键问题,对于这样的问题,如何利用先验知识设定正则性约束建立优化模型是超分重建的关键问题。现有的深度学习方法还存在着以下不足:1.很少考虑利用图像先验信息对模型进行约束,导致模... Super-reslution is used to estimate a latent high-resolution image based on several low-resolution images from the same scene. The development of SR has been a hot issue in computer vision field which promotes the study of SR performance. Commonly, SR uses a priori knowledge to set the constraint rule, and then obtain the optimal solution under these constraints. These prior knowledge includes smo...