AI 中文总结
针对维纳反卷积的振铃伪影问题，提出两种利用物理非负性和稀疏性先验的计算高效启发式方法，以抑制伪影并提升高速成像反卷积的适用性。
AI 中文摘要
随着高速成像技术的发展，对鲁棒的高速反卷积算法的需求日益增长。维纳反卷积仍是现有算法中最快、最简单的方法之一，但其存在振铃伪影，可能限制其适用性。在本工作中，我们开发了两种互补且计算高效的启发式方法，通过利用物理非负性和稀疏性先验来抑制这些振铃伪影。
英文摘要
With advances in high-speed imaging there is a growing need for robust high-speed deconvolution algorithms. Wiener deconvolution remains one of the fastest and simplest algorithms available, however it suffers from ringing artifacts that can limit its applicability. In this work, we develop two complementary, computationally efficient heuristic methods to suppress these ringing artifacts by using physical non-negativity and sparsity priors.
Comments5 pages, 2 figures
