Wavelet-Based Technique for Mobile Device with Low Resolution Depth Image-Based Rendering

Depth Image-Based Rendering (DIBR) is an approach to generate a 3-D image by the original 2-D color image with the corresponding 2-D depth map. Although DIBR is a quite convenient to convert 2D images to 3D ones, there is a disadvantage in DIBR system that it cannot reach real-time processing due to the computing time. Against this, this paper proposes a method which is based on discrete wavelet transform and adaptive edge-oriented smoothing process, to speed up the computing of the system. The proposed method still preserves the original texture and thus the proposed method not only preserves the vertical texture but also reduces at least 60% of the computing time of the DIBR system.

[1]  Filippo Speranza,et al.  Stereoscopic imaging: filling disoccluded areas in depth image-based rendering , 2006, SPIE Optics East.

[2]  Fang-Hsuan Cheng,et al.  Real time multiple objects tracking and identification based on discrete wavelet transform , 2006, Pattern Recognit..

[3]  Liang-Gee Chen,et al.  Efficient Depth Image Based Rendering with Edge Dependent Depth Filter and Interpolation , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[4]  Chih-Hsien Hsia,et al.  Improved Low-Complexity Algorithm for 2-D Integer Lifting-Based Discrete Wavelet Transform Using Symmetric Mask-Based Scheme , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Chih-Hsien Hsia,et al.  Spatial domain complexity reduction method for depth image based rendering using wavelet transform , 2013, 2013 International Symposium on Intelligent Signal Processing and Communication Systems.

[6]  Marco Mattavelli,et al.  A scalable and programmable architecture for 2-D DWT decoding , 2002, IEEE Trans. Circuits Syst. Video Technol..

[7]  Luc Van Gool,et al.  Advanced three-dimensional television system technologies , 2002, Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission.

[8]  Liang Zhang,et al.  Stereoscopic image generation based on depth images for 3D TV , 2005, IEEE Transactions on Broadcasting.

[9]  Ying-li Tian,et al.  Robust Salient Motion Detection with Complex Background for Real-Time Video Surveillance , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.

[10]  Shang-Hong Lai,et al.  Improved novel view synthesis from depth image with large baseline , 2008, 2008 19th International Conference on Pattern Recognition.

[11]  Q. M. Jonathan Wu.  Wavelet-based Moving Object Segmentation , 2009 .

[12]  Taali Martin,et al.  Smoothing depth maps for improved steroscopic image quality , 2004, SPIE Optics East.

[13]  Pei-Jun Lee,et al.  Nongeometric Distortion Smoothing Approach for Depth Map Preprocessing , 2011, IEEE Transactions on Multimedia.

[14]  Peter H. N. de With,et al.  Background Estimation and Adaptation Model with Light-Change Removal for Heavily Down-Sampled Video Surveillance Signals , 2006, 2006 International Conference on Image Processing.

[15]  Andrew J. Woods,et al.  Image distortions in stereoscopic video systems , 1993, Electronic Imaging.

[16]  Minh N. Do,et al.  Depth image-based rendering from multiple cameras with 3D propagation algorithm , 2009, IMMERSCOM.

[17]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[18]  Chih-Hsien Hsia,et al.  Improved directional lifting-based discrete wavelet transform for low resolution moving object detection , 2012, 2012 19th IEEE International Conference on Image Processing.

[19]  Thirumalai,et al.  Image Coding of 3D Volume Using Wavelet Transform for Fast Retrieval of 2D Images , 2006 .

[20]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.