Iterative Graph-Based Filtering for Image Abstraction and Stylization
Hamidreza Sadreazami, Amir A. Asif, Arash Mohammadi · IEEE Transactions on Circuits & Systems II Express Briefs · 2017
In this brief, motivated by the recent advances in graph signal processing, we address the problem of image abstraction and stylization. A novel unified graph-based multi-layer framework is proposed to perform iterative filtering without requiring any weight updates. The proposed graph-based filtering approach is shown to be superior to other existing methods due to iteratively using the filtered Laplacian in order to enhance the smoothened image signal at each layer. In order to render real images into painterly style ones and create a simple stylized format from color images, the low-contrast regions of an image are first smoothened using the proposed iterative graph filters in either vertex or spectral domains. The abstracted image is then quantized and sharpened using the proposed iterative highpass graph filter. The effectiveness of the graph-based image stylization method is verified through several experiments. It is shown that the proposed method can yield significantly improved visual quality for stylized images as compared to other existing methods.