论文标题
图像使用大地测量的歧管基础斑块空间的Gramian denosing
Image Denoising Using the Geodesics' Gramian of the Manifold Underlying Patch-Space
论文作者
论文摘要
随着现代社会中复杂相机的扩散，对准确和视觉令人愉悦的图像的需求正在增加。但是，相机捕获的图像的质量可能会因噪音而降解。因此，需要对图像进行一些处理来过滤噪声而不会丢失重要的图像特征。即使目前的文献提供了多种脱氧方法，但其降解的忠诚和效力有时不确定。因此，在这里，我们提出了一种能够产生准确图像的新颖和计算有效的图像denoising方法。为了保留图像平滑度，此方法输入从图像而不是像素分配的贴片。然后，它在斑块空间的基础上执行deNOTO，而不是在图像域中进行剥落，以更好地保留整个图像中的特征。我们根据基准图像处理方法验证了该方法的性能。
With the proliferation of sophisticated cameras in modern society, the demand for accurate and visually pleasing images is increasing. However, the quality of an image captured by a camera may be degraded by noise. Thus, some processing of images is required to filter out the noise without losing vital image features. Even though the current literature offers a variety of denoising methods, the fidelity and efficacy of their denoising are sometimes uncertain. Thus, here we propose a novel and computationally efficient image denoising method that is capable of producing accurate images. To preserve image smoothness, this method inputs patches partitioned from the image rather than pixels. Then, it performs denoising on the manifold underlying the patch-space rather than that in the image domain to better preserve the features across the whole image. We validate the performance of this method against benchmark image processing methods.
