引导信号重建及其在图像放大中的应用
Guided Signal Reconstruction with Application to Image Magnification
AI总结：
本文提出利用引导子空间进行信号重建，通过共轭梯度法开发迭代算法，实现低内存和计算成本的最优重建，应用于图像放大时效果优于其他方法。
摘要：
我们研究了从信号在子空间上的投影重建信号的问题。所提出的信号重建算法利用引导子空间来表示重建信号的期望属性。我们证明最优重建信号属于一个称为“重建”集的凸有界集。我们还开发了基于共轭梯度法的迭代算法，以低内存和计算成本近似最优重建。所提出方法的有效性在图像放大中得到验证，重建图像质量优于一致性和泛化重建方案。
英文摘要：
We study the problem of reconstructing a signal from its projection on a subspace. The proposed signal reconstruction algorithms utilize a guiding subspace that represents desired properties of reconstructed signals. We show that optimal reconstructed signals belong to a convex bounded set, called the "reconstruction" set. We also develop iterative algorithms, based on conjugate gradient methods, to approximate optimal reconstructions with low memory and computational costs. The effectiveness of the proposed approach is demonstrated for image magnification, where the reconstructed image quality is shown to exceed that of consistent and generalized reconstruction schemes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
