Computational Colour Approach to Digital Imaging, Human Perception, Computer Vision and AR/VR/MR

数字成像、人类感知、计算机视觉和AR/VR/MR的计算颜色方法 ** 这个建议是关于不同观察者、不同的人、不同的相机和不同的灯光（日光、LED、荧光灯、钨丝灯）下如何感知物体的颜色。 颜色是一个非常跨学科的领域，涉及心理学，哲学，化学，物理学和计算机科学。我理解颜色的方法是将颜色感知视为一个计算过程。 因此，在我的实验室开发的颜色感知模型被制定为算法，可以测试它们是否只是提供预期的结果，其次是它们是否以与心理学家进行的心理物理实验中已知的人类颜色感知一致的方式运作。 理解和建模颜色感知的基本困难在于，由于人类只有3种类型的颜色敏感锥细胞，因此进入眼睛的光的波长与感知的颜色之间没有一一对应的关系。 还有许多其他的困难，例如相同的反射光谱在不同的环境中可能看起来不同，这些都有助于颜色成为一个迷人的研究领域。 然而，这些困难给数码相机工业、数码印刷工业、数码显示工业、纺织工业、照明工业、颜色的科学使用（例如，在医学应用中），艺术品的数字保存，以及最近在增强/混合现实应用中的颜色准确性。本提案中的研究项目涉及直接应用于所有这些技术领域的颜色科学的基本问题。拟议的研究的目标建立在我的实验室，包括工作的同色异谱，颜色恒常性及其限制，建立一套所有理论上可能的颜色，评估的显色性的光，并评估数码相机的颜色精度的最新进展。 拟议目标包括：（i）一种新的照明不变的方法，用于对象分类和识别，通常涉及机器学习;（ii）构建一个数据集，该数据集具有包含复杂的、空间变化的照明的场景的多光谱图像的精确地面真实值，以供颜色研究界使用;（iii）为增强现实应用提供色度和感知上精确的颜色;（iv）进一步发展辨色如何随色调而变化的新理论;及（v）从压缩感知的角度了解人类视觉。研究预算主要用于培训高素质的人员，即支持学生的工资和他们的会议旅行。我以前的学生现在都在彩色成像领域取得了成功。*****************

Computational Colour Approach to Digital Imaging, Human Perception, Computer Vision and AR/VR/MR ******This proposal is about how the colours of objects are perceived by different observers'different people, different camerasand under different lights (daylight, LED, fluorescent, tungsten). Colour is a very interdisciplinary field touching on psychology, philosophy, chemistry, physics, and computer science. My approach to understanding colour is to view colour perception as a computational process. As such, the models of colour perception developed in my laboratory are formulated as algorithms that can be tested both in terms of whether or not they simply provide the expected results, and secondly in terms of whether they operate in a way that is congruent with what is known about human colour perception from the psychophysical experiments conducted by psychologists. The fundamental difficulty in understanding and modeling colour perception is that because humans have only 3 types of colour-sensitive cones there is no one-to-one correspondence between the wavelengths of light entering the eye and perceived colour. There are many other difficulties too, such as how the same reflected-light spectrum may look different in different contexts, and these all contribute to colour being a fascinating field of research. These difficulties, however, present problems for the digital camera industry, the digital printing industry, the digital display industry, the textile industry, the lighting industry, the scientific use of colour (e.g., in medical applications), the digital preservation of artwork, and most recently to colour accuracy in augmented/mixed reality applications. The research projects in this proposal address fundamental issues of colour science that have direct application to all these technology areas. The objectives of the proposed research build on the recent progress in my laboratory that include work on metamerism, colour constancy and the limits thereof, establishing the set of all theoretically-possible colours, evaluating the colour rendering properties of lights, and evaluating the colour accuracy of digital cameras. The proposed objectives include: (i) a new illuminant-invariant approach to object classification and recognition with implications for machine learning generally; (ii) building a dataset with accurate ground truth of multispectral images of scenes containing complex, spatially-varying lighting for use by the colour research community; (iii) providing colorimetrically and perceptually accurate colour for augmented reality applications; (iv) further developing a new theory of how colour discrimination varies with hue; and (v) understanding human vision in terms of compressive sensing.***The research budget is chiefly for the training of highly qualified personnel; namely, support of student salaries and their conference travel. My previous students now all have successful careers in the colour-imaging field. *****************