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

机译:使用球形小波和小波进行数据压缩以进行基于图像的重新照明

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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. (C) 2004 Published by Elsevier Inc.
机译:基于图像的重新照明(IBL)解决了基于图像的建模和渲染中的照明控制问题。但是,由于在各种光照条件下预先捕获的大量参考图像,导致存储需求急剧增加。在本文中,我们提出了一种基于球面小波变换和小波变换(SWT-WLT)的方法来压缩庞大的IBL数据集。涉及两个主要步骤。首先,使用球面小波变换(SWT)来减少不同参考图像之间的相关性。其次,应用小波变换(WLT)压缩那些SW变换图像(SWT图像)。由于SWT和WLT的局限性,所提出的方法继承了内存需求低的优点,因此适合于任意压缩大型数据集。使用其整数格式实现,可以借助移位操作进一步加快该方法的速度。通过仿真评估其良好功能。 (C)2004由Elsevier Inc.出版

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