An Edge-Directed Diffusion Equation-Based Image Restoration Approach for Font Generation

Abstract

The intelligent algorithms-based font generation has been a prevalent online application. In existing researches, visual communication effect of font generation results is usually neglected. To deal with this issue, this paper combines sparse representation and convex set projection restoration algorithm, and proposes a font generation image restoration method based on edge Diffusion equation. Firstly, the image is modeled using sparse representation methods, and sparsity constraints are introduced to make the solution sparse and convenient for computation. Then, the Inverse problem is transformed into a Convex optimization problem, and the global optimal solution is obtained by using the properties of Convex optimization. Finally, image restoration and reconstruction are realized by edge Diffusion equation. In this paper, we propose an image restoration method for font generation based on edge Diffusion equation. By combining sparse representation and convex set projection restoration algorithms, fast image restoration and high-quality reconstruction have been achieved. And performance evaluation was conducted using the peak signal-to-noise ratio (PSNR) metric. The experimental results have well verified the correctness of this method. The experimental results show that this method can effectively solve the ill posed problem in the Inverse problem, and achieve fast image restoration and high-quality reconstruction. Compared with traditional image restoration methods, this method has higher restoration quality and faster computational speed.

Keywords

• Image reconstruction
• edge-directed diffusion equation
• low-resolution images
• font generation