针对不同应用设计可定制的图像去噪方法
Targeted Iterative Filtering
- 基于应用场景转换值空间，实现线性扩散去噪
- 在医疗和压缩图像上优于现有非线性方法
- 适合需要高精度去噪的领域如医学影像
图像去噪效果的评估依赖于具体应用场景，如图像压缩、静态图像采集和医学图像等，对去噪方法的行为要求各不相同。本文提出一种新型非线性扩散方案，其源自在特定应用决定的值空间中的线性扩散过程。实验表明，在变换空间中基于应用驱动的线性扩散，相比现有非线性扩散技术表现更优。
原文摘要 · Abstract (English)
The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different behavior of the applied denoising method. In this paper we propose a novel, nonlinear diffusion scheme that is derived from a linear diffusion process in a value space determined by the application. We show that application-driven linear diffusion in the transformed space compares favorably with existing nonlinear diffusion techniques.
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