Quarter Laplacian Filter for Edge Aware Image Processing
This work addresses edge preservation in image processing for applications requiring real-time performance, but it appears incremental as it builds on existing Laplacian filter concepts with a smaller support region.
The paper tackles the problem of preserving corners and edges in image smoothing by introducing a quarter Laplacian filter with a 2x2 support region, which is more local than the traditional 3x3 Laplacian filter and can be implemented via a box filter for real-time performance, as demonstrated in tasks like image smoothing, texture enhancement, and low-light image enhancement.
This paper presents a quarter Laplacian filter that can preserve corners and edges during image smoothing. Its support region is $2\times2$, which is smaller than the $3\times3$ support region of Laplacian filter. Thus, it is more local. Moreover, this filter can be implemented via the classical box filter, leading to high performance for real time applications. Finally, we show its edge preserving property in several image processing tasks, including image smoothing, texture enhancement, and low-light image enhancement. The proposed filter can be adopted in a wide range of image processing applications.