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HEALPIX DCT technique for compressing PCA-based illumination adjustable images

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Abstract

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.

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Acknowledgments

The work was supported by a research grant (CityU 116511) from General Research Fund, Hong Kong.

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Authors and Affiliations

  1. Institute of Technology Management, National Chung Hsing University, Taichung, Taiwan, ROC

    John Sum

  2. Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China

    Chi-Sing Leung, Ray C. C. Cheung & Tze-Yiu Ho

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  1. John Sum
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  2. Chi-Sing Leung
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  3. Ray C. C. Cheung
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  4. Tze-Yiu Ho
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Correspondence to John Sum.

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Sum, J., Leung, CS., Cheung, R.C.C. et al. HEALPIX DCT technique for compressing PCA-based illumination adjustable images. Neural Comput & Applic 22, 1291–1300 (2013). https://doi.org/10.1007/s00521-012-1003-5

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  • DOI: https://doi.org/10.1007/s00521-012-1003-5

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