Nonuniform Lattice Regression for Modeling the Camera Imaging Pipeline

Hai Ting Lin¹, Zheng Lu², Seon Joo Kim³, and Michael S. Brown¹

¹National University of Singapore, Singapore

²University of Texas at Austin, USA

³SUNY Korea

Abstract. We describe a method to construct a sparse lookup table (LUT) that is effective in modeling the camera imaging pipeline that maps a RAW camera values to their sRGB output. This work builds on the recent in-camera color processing model proposed by Kim et al. [1] that included a 3D gamut-mapping function. The major drawback in [1] is the high computational cost of the 3D mapping function that uses radial basis functions (RBF) involving several thousand control points. We show how to construct a LUT using a novel nonuniform lattice regression method that adapts the LUT lattice to better fit the 3D gamut-mapping function. Our method offers not only a performance speedup of an order of magnitude faster than RBF, but also a compact mechanism to describe the imaging pipeline.

LNCS 7572, p. 556 ff.

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