You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
An integrated gamut- and tone-management framework for color-accurate reproduction of high dynamic range images can prevent hue and luminance shifts while taking gamut boundaries into consideration. The proposed approach is conceptually and computationally simple, parameter-free, and compatible with existing tone-mapping operators.

Cited Abstract(s):
[1]: Imaging techniques seek to simulate the array of light that reaches our eyes to provide the illusion of sensing scenes directly. Both photography and computer graphics deal with the generation of images. Both disciplines have to cope with the high dynamic range in the energy of visible light that human eyes can sense. Traditionally photography and computer graphics took different approaches to the high dynamic range problem. Work over the last ten years though has unified these disciplines and created powerful new tools for the creation of complex, compelling and realistic images. This book provides a practical introduction to the emerging new discipline of high dynamic range imaging that combines photography and computer graphics. By providing detailed equations and code, the book gives the reader the tools needed to experiment with new techniques for creating compelling images. A supplemental website contains downloads and additional information.

[2]: Gamut mapping algorithms, implemented by color management systems, are an integral part of the color reproduction process. By adjusting the colors with appropriate algorithms, gamut mapping enables original colors to fit inside differently shaped color gamuts and authentically transfers images across a range of media. This book illustrates the range of possible gamut mapping strategies for cross-media color reproduction, evaluates the performance of various options and advises on designing new, improved solutions. Starting with overviews of color science, reproduction and management, the text includes: a detailed survey of 90+ gamut mapping algorithms covering color-by-color reduction and expansion, spatial reduction, spectral reduction and gamut mapping for niche applications; a step-by-step example of a colors journey from original to reproduction, via a digital workflow; a detailed analysis of color gamut computation, including a comparison of alternative techniques and an illustration of the gamuts of salient color sets and media; a presentation of both measurement-based and psychovisual evaluation of individual color reproductions; an overview of alternative approaches to gamut mapping proposed by the ISO and the CIE including an analysis of the building blocks of gamut mapping algorithms and the factors affecting their performance. Color Gamut Mapping is a comprehensive resource for practicing color and imaging engineers, scientists and researchers working in the development of imaging devices, software and solutions. It is also a valuable reference for students of color and imaging science, as well as photographers, graphic designers and artists.

[3]: High dynamic range (HDR) imaging is an area of increasing importance, but most display devices still have limited dynamic range (LDR). Various techniques have been proposed for compressing the dynamic range while retaining important visual information. Multi-scale image processing techniques, which are widely used for many image processing tasks, have a reputation of causing halo artifacts when used for range compression. However, we demonstrate that they can work when properly implemented. We use a symmetrical analysis-synthesis filter bank, and apply local gain control to the subbands. We also show that the technique can be adapted for the related problem of "companding", in which an HDR image is converted to an LDR image, and later expanded back to high dynamic range.
Reproduction of visual content on devices of different gamuts is typically divided into two categories, namely and . Traditionally the first class of techniques deals with mapping the color gamut between devices, attempting to produce the most accurate reproduction of colors possible given the restrictions of a given device or medium [2] . Tone mapping, on the other hand, is primarily concerned with compressing the luminance range of an HDR image or video such that the media can be visualized on a low dynamic range (LDR) display device [2]2 [1] .