Notice of Violation of IEEE Publication PrinciplesImage Guided Depth Map Upsampling using Anisotropic TV- ${L^2}$

Notice of Violation of IEEE Publication Principles

???Image Guided Depth Map Upsampling using Anisotropic TV-L2???
by Xiaozhou Zhu, Xin Song, and Xiaoqian Chen
in the IEEE Signal Processing Letters, Vol 22, Issue 3, March 2015, pp. 318-321

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.

This paper contains significant portions of text from the paper cited below that were reused without attribution.

???Image Guided Depth Upsampling using Anisotropic Total Generalized Variation???
by David Ferstl, Christian Reinbacher, Rene Ranftl, Matthias Ruether, and Horst Bischof
in the Proceedings of the IEEE International Conference on Computer Vision, December 2013, pp. 993-1000

In this letter, we present a novel upsampling method to enhance the spatial resolution of depth maps. Given a low resolution depth map from a depth sensor and a registered high resolution intensity image from a camera, we formulate it as a convex optimization problem and solve it using the first-order primal-dual algorithm. The formulation combines an ${L^2}$ data term and an anisotropic total variation (TV) regularization term, thus it is more robust to noise and better preserves the fine details. Experimental results on Middlebury and real world datasets demonstrate that our method achieves favorable performance compared with state-of-the-art upsampling methods.