Non-Linear Structure-Aware Image Sharpening with Difference of Smoothing Operators

Non-Linear Structure-Aware Image Sharpening with Difference of Smoothing Operators

In this paper, we propose an effective data-adaptive filtering mechanism for sharpening of noisy and moderately blurred images. We establish the connection of our proposed data-adaptive filtering procedure with the classic Difference of Gaussians (DoG) operator widely used in image processing and computer graphics. Our proposed filter renders a data adaptive and noise robust version of the clas...

Linear Smoothing Morphological Sharpening + Kuwahara-Nagao Operator

This report sheds some new light on an old and trusted tool in the image processing toolbox. The Kuwahara-Nagao operator is known as an edge preserving smoothing operator. This report shows that we don’t need to trust on our intuition to verify this claim but that it follows from basic principles. To that end we will first cast the classical Kuwahara-Nagao operator into a more modern framework ...

Semantic-Aware Image Smoothing

Structure-preserving image smoothing aims to extract semantically meaningful image structure from texture, which is one of the fundamental problems in computer vision and graphics. However, it is still not clear how to define this concept. On the other hand, semantic image labeling has achieved significant progress recently and has been widely used in many computer vision tasks. In this paper, ...

Non-linear operators in image restoration

We firstly present a variational approach such that during image restoration, edges detected in the original image are being preserved, and then we compare in a second part, the mathematical foundation of this method with respect to some of the well known methods recently proposed in the literature within the class of PDE based algorithms (anisotropic diffusion, mean curvature motion, min/max f...

Structure Preserving Image Smoothing