Data compression with spherical wavelets and wavelets for the image-based relighting

Authors:
Ze Wang;Chi-Sing Leung;Yi-Sheng Zhu;Tien-Tsin Wong
Affiliations:
Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of EE, City University of Hong Kong, Hong Kong, China;Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of CSE, The Chinese University of Hong Kong, Hong Kong, China
Venue:
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
Year:
2004

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Abstract

Image based relighting (IBL) solves the illumination control problem in the image-based modelling and rendering. However, it trades a drastic increase of storage requirement caused by the tremendous reference images pre-captured under various illumination conditions. In this paper, we propose a spherical wavelet transform and wavelet transform (SWT-WLT) based approach to compress the huge IBL dataset. Two major steps are involved. First, the spherical wavelet transform (SWT) is used to reduce the correlation between different reference images. Second, wavelet transform (WLT) is applied to compress those SW transformed images (SWT images). Due to the locality of SWT and WLT, the proposed method inherits an advantage of low memory requirement, hence, it is suitable for compressing arbitrarily large dataset. Using its integer format implementation this method can be further sped up with the help of bit shift operation. Simulations are given to evaluate its good features.