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HEALPIX DCT technique for compressing PCA-based illumination adjustable images

机译:HEALPIX DCT技术用于压缩基于PCA的照明可调图像

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An illumination adjustable image (IAI), containing a set of pre-captured reference images under various light directions, represents the appearance of a scene with adjustable illumination. One of drawbacks of using the IAI representation is that an IAI consumes a lot of memory. Although some previous works proposed to use blockwise principal component analysis for compressing IAIs, they did not consider the spherical nature of the extracted eigen-coefficients. This paper utilizes the spherical nature of the extracted eigen-coefficients to improve the compression efficiency. Our compression scheme consists of two levels. In the first level, the reference images are converted into a few eigen-images (floating point images) and a number of eigen-coefficients. In the second level, the eigen-images are compressed by a wavelet-based method. The eigen-coefficients are organized into a number of spherical functions. Those spherical coefficients are then compressed by the proposed HEALPIX discrete cosine transform technique.
机译:照明可调整图像(IAI)包含一组在各种光方向下的预先捕获的参考图像,代表具有可调照明的场景的外观。使用IAI表示的缺点之一是IAI占用大量内存。尽管先前的一些工作建议使用块状主成分分析来压缩IAI,但他们并未考虑提取的特征系数的球形性质。本文利用提取的本征系数的球形特性来提高压缩效率。我们的压缩方案包括两个级别。在第一级中,参考图像被转换为​​一些本征图像(浮点图像)和许多本征系数。在第二级中,通过基于小波的方法来压缩特征图像。本征系数被组织为许多球形函数。然后通过提出的HEALPIX离散余弦变换技术压缩那些球面系数。

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