Illumination estimation based on estimation of dominant chromaticity in nonnegative matrix factorization with sparseness constraint

Ji-Heon Lee; Ji-hoon Yoo; Jung-Min Sung; Yeong-Ho Ha

doi:10.1117/12.2078968

8 February 2015 Illumination estimation based on estimation of dominant chromaticity in nonnegative matrix factorization with sparseness constraint

Ji-Heon Lee, Ji-hoon Yoo, Jung-Min Sung, Yeong-Ho Ha

Author Affiliations +

Proceedings Volume 9395, Color Imaging XX: Displaying, Processing, Hardcopy, and Applications; 93950V (2015) https://doi.org/10.1117/12.2078968
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

Changing illumination cause the measurements of object colors to be biased toward chromaticity of illuminants. Various color constancy algorithms are already exist to remove the chromaticity of illuminants in an image for improving image quality. Recently, NMFsc(nonnegative matrix factorization with sparseness constraint) was introduced to extract the illuminant and reflectance component in an image. NMFsc extract illuminant component and reflectance component by using nonnegative matrix decomposition and sparseness constraints. However, if an image has a chromaticity distribution dominated by a particular chromaticity, the sparse constraint values include that dominant chromaticity, thereby inducing color distortion. Therefore, the proposed method modified the matrix decomposition in NMFsc by using standard deviation and K-means algorithm in chromaticity space. Next, non-negative matrix decomposition and sparseness constraints are performed on an image. Subsequently, illumination is estimated by combining the low sparse constraint values that excludes the dominant chromaticity. The performance of the proposed method is evaluated by using angular error for Ciurea 11,346 image data set. Experimental results illustrate that the proposed method reduces the angular error over previous methods.

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Ji-Heon Lee, Ji-hoon Yoo, Jung-Min Sung, and Yeong-Ho Ha "Illumination estimation based on estimation of dominant chromaticity in nonnegative matrix factorization with sparseness constraint", Proc. SPIE 9395, Color Imaging XX: Displaying, Processing, Hardcopy, and Applications, 93950V (8 February 2015); https://doi.org/10.1117/12.2078968

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