Computational geometry

Color as a Science

Tone mapping algorithms offer sophisticated methods for mapping a real-world luminance range to the luminance range of the output medium but they often cause changes in color appearance. In this work we conduct a series of subjective appearance matching experiments to measure the change in image colorfulness after contrast compression and enhancement. The results indicate that the relation between contrast compression and the color saturation correction that matches color appearance is non-linear and smaller color correction is required for small change of contrast. We demonstrate that the relation cannot be fully explained by color appearance models. We propose color correction formulas that can be used with existing tone mapping algorithms. We extend existing global and local tone mapping operators and show that the proposed color correction formulas can preserve original image colors after tone scale manipulation.

/pdf/color-correction-for-tone-mapping-4l6snu6gtx.pdf

Color correction for tone mapping

http://people.csail.mit.edu/pdidyk/papers/ComputationalDisplaysSurvey.pdf

Special Section on Advanced Displays: A survey on computational displays: Pushing the boundaries of optics, computation, and perception

One of the greatest simplifications of the transfer equation is where all incident and scattered light is assumed to be perfectly diffuse, only two opposite directions of light transport are considered, and the light intensity is assumed to vary along one axis only. Such two-flux approximations have been presented by many authors, starting with a paper by Schuster [1]. One of the most famous two-flux approximations is the approximation presented by Kubelka and Munk[2] in 1931 and further developed by Kubelka[3, 4]. Kubelka and Munk gave a comprehensive formulation and a treatment with a clear aim towards practical methods of measurement. It was quickly adapted for use by the papermaking industry[5-8] and has now been in widespread use for decades in the measurement and prediction of colour, brightness and opacity of paper sheets. Most of the information reported here is taken from the references cited at the end of the article which should be consulted for a more in-depth study.

/pdf/kubelka-munk-theory-in-describing-optical-properties-of-3lq6hppj0v.pdf

Kubelka-munk theory in describing optical properties of paper (ii)

We explore the potential of image-dependent gamut mapping as a constrained optimization problem. The performance of our new approach is compared to standard reference gamut mapping algorithms in psycho-visual tests.

Image-Dependent Gamut Mapping as Optimization Problem

The design of a gamut mapping algorithm (GMA) is always a compromise between preserving different competing aspects such as color, contrast, and lightness. A natural requirement of a GMA is that the algorithmic treatment of this competition has to avoid any additional artifacts such as discontinuities or loss of contrast. In this work, several common gamut mapping algorithms are studied from this aspect, resulting in the observation that problems with geometric discontinuities are widespread. For the assessment of the phenomena induced by local mapping properties, an algorithmic test is developed and applied. This new test supports both the quality check of existing as well as the development of new GMAs.

/pdf/continuity-of-gamut-mapping-algorithms-1z99oxqody.pdf

Continuity of gamut mapping algorithms

We propose a new geometric method to compute color gamut boundaries fast and geometrically accurate The method is designed for high-quality image-dependent gamut mapping in three dimensions For such a mapping the gamut boundary must be constructed for every image individually and we cannot rely on precomputed lookup tables This can only be practical if the gamut boundary can be computed very fast The proposed method is fast compared to other geometric methods without sacrificing geometric accuracy of the computed boundary

/pdf/toward-image-dependent-gamut-mapping-fast-and-accurate-gamut-21bxlf4brw.pdf

Toward image-dependent gamut mapping: fast and accurate gamut boundary determination

This paper deals with the potential of spatial gamut mapping methods as a complement to global gamut mapping algorithms. The main goal is to recover the original local contrast between neighboring pixels in addition to the usual optimization of preserving lightness, saturation and global contrast. As a typical representative for such a spatial mapping concept, we study unsharp masking applied to an image of the difference of the original and the result of a given gamut mapping algorithm. Thereby an edge preserving smoothing algorithm is used to avoid halo artefacts. In our psychophysical experiments every considered gamut mapping algorithm shows a significant gain in preference by our local contrast approach. The presented method can be seen as an additional feature towards an image-to-device gamut mapping design.

Adding Local Contrast to Global Gamut Mapping Algorithms

Due to its simplicity, the theory of K UBELKA-MUNK [1] has found a wide acceptance for modeling the optical properties of light scattering materials. However, the concept is not explicitly adapted to predict halftone prints on paper. In this respect, a recent improvement was given by BERG [2]. Our approach is an extension of BERG’s model in order to reduce the gap between the mathematical description of the paper’s point spread function and the experimental results of simple reflectance measurements.

/pdf/extending-kubelka-munk-s-theory-with-lateral-light-33px5wihm8.pdf

Klaus Simon

Papers

Image-Dependent Gamut Mapping as Optimization Problem

Continuity of gamut mapping algorithms

Toward image-dependent gamut mapping: fast and accurate gamut boundary determination

Adding Local Contrast to Global Gamut Mapping Algorithms

Extending Kubelka-Munk's Theory with Lateral Light Scattering