论文标题
来自位于非整数位置的像素的基于denoising的图像重建
Denoising-based image reconstruction from pixels located at non-integer positions
论文作者
论文摘要
数字图像通常表示为常规2D阵列，因此像素以整数介绍的矩阵形式组织。但是，有许多图像处理操作，例如旋转或运动补偿，它们在非全能位置产生像素。通常，图像重建技术无法处理非整体位置的样品。在本文中，我们建议将基于三角测量的重建作为初始估计，后来由新型的自适应denoising框架进行了完善。模拟表明，相对于初始估计，可以实现高达1.8 dB（在PSNR方面）的改善。
Digital images are commonly represented as regular 2D arrays, so pixels are organized in form of a matrix addressed by integers. However, there are many image processing operations, such as rotation or motion compensation, that produce pixels at non-integer positions. Typically, image reconstruction techniques cannot handle samples at non-integer positions. In this paper, we propose to use triangulation-based reconstruction as initial estimate that is later refined by a novel adaptive denoising framework. Simulations reveal that improvements of up to more than 1.8 dB (in terms of PSNR) are achieved with respect to the initial estimate.
