Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Emulated digital CNN-UM solution of partial differential equations: Research Articles
International Journal of Circuit Theory and Applications - Special Issue on CNN Technology (Part 2)
IEEE Transactions on Image Processing
Filling-in by joint interpolation of vector fields and gray levels
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Image inpainting is an interpolation problem where an image with missing or damaged parts is restored. The most often used image inpainting applications are for pictures or films known or damaged partially. Discarding some unwanted parts, text or objects from the whole image space, special effects can be carried out using image restoration. Complex mathematical models based on partial differential equations (PDE) or variational computing was proposed as techniques for restoring damaged or partially known images. Those methods are computational expensive and difficult to implement, even when a large serial processing computing power is available. The Cellular Neural Networks (CNN) based parallel processing ensures computing-time reduction if the processing algorithm can be implemented on a continuous-time analogue CNN-UM (Cellular Neural/Nonlinear Networks Universal Machine) or using FPGA (Field Programmable Gate Array) implemented emulated digital CNN-UM. Even if variational computing methods are used, the design of CNN templates ensuring the desired processing of the gray-scale image remains an important step. In the present paper, some variational based CNN methods are presented and analyzed that can be used for the reconstruction of damaged or partially known images. Efficiency of these impanting methods can be enhanced by combining them with nonlinear template that ensures the growth of the local properties spreading area along with regional ones.