Cross-Field Joint Image Restoration via Scale Map

Qiong Yan, Xiaoyong Shen, Li Xu, Shaojie Zhuo, Xiaopeng Zhang, Liang Shen, Jiaya Jia; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2013, pp. 1537-1544


Color, infrared, and flash images captured in different fields can be employed to effectively eliminate noise and other visual artifacts. We propose a two-image restoration framework considering input images in different fields, for example, one noisy color image and one dark-flashed nearinfrared image. The major issue in such a framework is to handle structure divergence and find commonly usable edges and smooth transition for visually compelling image reconstruction. We introduce a scale map as a competent representation to explicitly model derivative-level confidence and propose new functions and a numerical solver to effectively infer it following new structural observations. Our method is general and shows a principled way for cross-field restoration.

Related Material

author = {Yan, Qiong and Shen, Xiaoyong and Xu, Li and Zhuo, Shaojie and Zhang, Xiaopeng and Shen, Liang and Jia, Jiaya},
title = {Cross-Field Joint Image Restoration via Scale Map},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}