Solving the out-of-gamut problem in image composition

Existing digital image composition algorithms neglect the out-of-gamut problem, i.e. some pixel values in a composited image exceed the displayable or printable range. The commonly used solutions, including hard clipping or linear scaling, result in either detail loss or global contrast reduction. Directly applying the existing high dynamic range (HDR) compression algorithms cannot achieve pleasant visual quality either. In our previous work, we proposed a gamut fitting algorithm by formulating gamut fitting as an energy-minimization problem and used the cubic polynomial in the Bernstein-B́zier form to compute the optimal mapping curve. Despite the good performance achieved, the problem of the previous algorithm lies in the necessity of fine tuning the weighting parameter in the proposed energy function. In this paper, we further improve our previous method by using piecewise mapping curves with multiple Bernstein polynomials to find the optimal mapping curve. The proposed approach can be regarded as a post-process to enhance the visual quality of the resulting images from image composition applications. The performance of the proposed method is compared with our previous method and the state-of-the-art HDR compression algorithms.