Adaptive block truncation filter for MVC depth image enhancement

• Published in: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 544 - 548
• Main Authors: Xuyuan Xu, Lai-Man Po, Chun-Ho Cheung, Litong Feng, Kwok-Wai Cheung, Chi-Wang Ting, Ka-Ho Ng
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2014
• Subjects: 3DV-ATM; Adaptive filters; Depth Image based Rendering (DIBR); depth image compression; depth image filter; Image coding; Image edge detection; Information filters; Multiview Video Coding (MVC); Multiview Video plus Depth (MVD); PSNR; Video coding
• ISSN: 1520-6149; 2379-190X
• DOI: 10.1109/ICASSP.2014.6853655

In Multiview Video plus Depth (MVD) format, virtual views are generated from decoded texture videos with decoded depth images through Depth Image based Rendering (DIBR). 3DV-ATM is a reference model for H.264/AVC based Multiview Video Coding (MVC) and aims at achieving high coding efficiency for 3D video in MVD format. Depth images are first downsampled then coded by 3DV-ATM. However, sharp object boundary characteristic of depth images does not well match with the transform coding of 3DV-ATM. Depth boundaries are often blurred with ringing artifacts in the decoded depth images that result in noticeable artifacts in synthesized views. This paper presents a low complexity adaptive block truncation filter to recover the sharp object boundaries of depth images using adaptive block repositioning and expansion for increasing the depth values refinement accuracy. This new approach is very efficient and can avoid false depth boundary refinement when block boundaries lie around the depth edge regions and ensure sufficient information within the processing block for depth layers classification. Experimental results show that sharp depth edges can be recovered using the proposed filter and boundary artifacts in the synthesized views can be removed. The proposed method can provide improvement up to 3.25dB in the depth map enhancement and bitrate reduction of 3.06% in the synthesized views.