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Super-resolution of grey-level images by inverse diffusion processes

机译:通过逆扩散过程超级分辨率的灰度图像

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Algorithms for resolution enhancement are needed in various applications of image processing and communication such as compression, and HDTV, in which the enhancement of low resolution images acquired by CCD-based electronic cameras is required. We develop a geometric algorithm, based on diffusion processes, which are used both for smoothing of the enlarged image, when "time" is flowing forward, and for enhancement. The latter is accomplished by allowing the "time" to flow backwards, i.e. by "solving" an inverse diffusion problem which is ill posed. In order to stabilize the flow as well as to enhance important features (e.g. edges) on the expense of less important image domains, we use modified and regularized Beltrami type diffusion equation.
机译:在图像处理和通信的各种应用中需要用于分辨率增强的算法,例如压缩和HDTV,其中需要由CCD的电子摄像机获取的低分辨率图像的增强。我们开发一种基于扩散过程的几何算法,这些算法用于平滑放大图像,当“时间”向前流动时,并且用于增强。通过允许“时间”向后流动,即通过“解决”逆扩散问题来实现的。为了稳定流动以及提高重要特征​​(例如边缘),以牺牲不太重要的图像域,我们使用修改和正则化的Beltrami型扩散方程。

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