Removing depth map coding distortion by using post filter set


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Poster file of ICME2013.

N. Fukushima, T. Inoue, and Y. Ishibashi, "Removing depth map coding distortion by using post filter set," in Proc. IEEE International Conference on Multimedia and Expo (ICME), July 2013.

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Removing depth map coding distortion by using post filter set

  1. 1. Min filtered Max filtered Input signal Kernel Nearest value output Comparing difference max min 3. output 1. Input 2. max/min #Limitation: Only one edge in a Kernel window Removing Depth Map Coding Distortion by Using Post Filter Set Norishige Fukushima*, Tomohiko Inoue, Yutaka Ishibashi Graduate School of Engineering, Nagoya Institute of Technology Introduction and Overview Experimental Results Proposed Method Various codec, JPEG, JPEG2000, JPEG- LS, H.264/AVC, can encode depth map and these codecs have coding distortion. Objective of this paper is removing distortions by using post filter set. Problem and OverviewBackground Median Filter R-D curve of various image codecs 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 1 1 0 0 0 Box Filter Binary Weighted Range Filter (BWRF) Box Filter BWRFInput Profile curve position Min-max Blur Remove Filter Binary Weighted Range Filter 3D scene 2cm 8cm Source view Virtual views RAW Image RAW depth map RAW Image Coded/filtered depth map comparecompare Experimental Setup Depth map and image captured from Kinect. Depth maps are coded by various codecs. #Image is not compressed. [1]K. Lai, L .Bo, X. Ren, and D. Fox, “A large-scale hierarchical multi-view rgb-d object dataset.,” in Proc. ICRA, pp. 1817–1824, May 2011. [2] K.-J. Oh, A. Vetro, and Y.-S. Ho, “Depth coding using a boundary reconstruction filter for 3-d video systems,” IEEE Trans. CSVT, vol. 21, no. 3, pp. 350 – 359, Mar. 2011. Trans mission Encode Decode Post filtering View synthesis Depth Map Image Median Filter Min-Max Blur Remove Filter Weighted Range Filter Over quantization is recovered Boundary blur is removed Spike noise is removed Gaussian Filter Gaussian noise is removed Project site/Source code: Reference Computational Time 15 ms Intel Core i7 2.93GHz (4core HT) Parallelization: SSE4, Intel TBB Language:C++ IEEE International Conference on Multimedia & Expo (ICME), July 2013
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