"Physics-based colour models in computer vision, colour science, graphics and multimedia"

“计算机视觉、色彩科学、图形和多媒体中基于物理的色彩模型”

• 批准号: 217149-2012
• 负责人: Drew, Mark
• 金额: $ 2.48万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=523697
• 关键词: Physics; based; colour; models; computer

A.) Computational Photography: (i) I have recently generated re-integrated images starting with an image's desired gradient field pair, a longstanding problem, with greatly reduce artifacts. (ii) In a 2011 patent I show how to transfer the contrast from hi-D image data down to lower dimensional images, e.g. transfer the contrast from RGB+infrared down to colour images. This work uses the patent in (i); however, the solution found is global over the image. A local mapping should in principle be much more effective, and I propose a variational-equation solution. (iii) Then other problems could be attacked, such as image sharpening without halo artifacts, and anisotropic smoothing ("wrinkle remover"). B.) Graphics/Visualization: (i) In work on multiple-lighting image sets, lighting directions are required. But for "in the wild" objects directions are inaccurate, so instead I wish to discover them, along with finding lights' visibility subspaces. (ii) The above could be used to discover damage to artworks lent out by museums. (iii) In hi-D medical image visualization, I have generated perceptually meaningful colour outputs. However, clipping often occurs. If gamut-fitting is included into the optimization this problem could be solved whilst generating the visualization. C.) Computer Vision: (i) Shadow-free intrinsic (illumination invariant) images utilize the entropy in a feature space as a crucial step; I propose using video information, accumulating evidence over time. (ii) Another direction would apply the intrinsic image feature to dermoscopy images: the intrinsic image can be used to eliminate light-colour and intensity changes. I also propose removing skin colour, for a colour-image lesion atlas independent of skin colour. D.) Multimedia: If actors in large theatres were crowd-tracked in 2-D, audio depth plus a panning could be generated. E.) Colour: (i) A substantial proportion of papers use colour incorrectly. I propose a publication and reference codeset for a hierarchy of camera calibrations, from complete to simple, for guiding researchers in how to proceed. (ii) Colour Balance is critical for camera data. I recently presented a new algorithm to the iPhone Camera team at Apple and propose further investigating this.

a .)计算摄影：(i)我最近生成了重新整合的图像，从图像所需的梯度场对开始，这是一个长期存在的问题，大大减少了伪影。（ii）在2011年的专利中，我展示了如何将高清图像数据的对比度转移到低维图像，例如将RGB+红外图像的对比度转移到彩色图像。本作品使用(i)中的专利；然而，找到的解决方案是全局的图像。局部映射原则上应该更有效，我提出了一个变分方程解决方案。（iii）然后可以解决其他问题，例如无晕伪影的图像锐化和各向异性平滑（“除皱”）。b .)图形/可视化：(i)在多照明图像集的工作中，需要照明方向。但是对于“野外”对象的方向是不准确的，所以我希望发现它们，以及寻找灯光的可见性子空间。（ii）上述方法可用于发现博物馆外借艺术品的损坏情况。（iii）在高清医学图像可视化方面，我已经生成了具有感知意义的色彩输出。然而，剪辑经常发生。如果将色域拟合纳入优化中，则可以在生成可视化的同时解决这一问题。c .)计算机视觉：(i)无阴影固有（光照不变）图像利用特征空间中的熵作为关键步骤；我建议使用视频信息，随着时间积累证据。（ii）另一个方向是将内在图像特征应用于皮肤镜图像：内在图像可用于消除浅色和强度变化。我还建议去除肤色，以获得独立于肤色的彩色图像病变图谱。d .)多媒体：如果大型剧院中的演员在2-D中进行人群跟踪，则可以生成音频深度和平移。大肠)颜色：(i)相当比例的纸张使用颜色不正确。我提出了一个相机校准层次结构的出版物和参考代码集，从完整到简单，以指导研究人员如何进行。（ii）色彩平衡是相机数据的关键。最近，我向苹果公司的iPhone Camera团队展示了一种新的算法，并建议对此进行进一步研究。