"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: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=546529
• 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.）计算机摄影：（i）我最近生成了重新整合的图像，从图像的期望梯度场对开始，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，我展示了如何将对比度从高维图像数据向下转移到低维图像，例如将对比度从RGB+红外向下转移到彩色图像。这项工作使用了（i）中的专利;然而，所找到的解决方案在图像上是全局的。原则上，局部映射应该更有效，我提出了一个变分方程解。(iii)然后可以攻击其他问题，例如没有光晕伪影的图像锐化和各向异性平滑（“皱纹去除器”）。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“在野外”的物体，方向是不准确的，所以我希望找到它们，沿着寻找灯光的可见性子空间。(ii)以上这些可以用来发现博物馆借出的艺术品的损坏情况。(iii)在hi-D医学图像可视化中，我已经生成了感知上有意义的颜色输出。然而，削波经常发生。如果将色域拟合包括在优化中，则可以在生成可视化的同时解决该问题。C.）的计算机视觉：（i）无阴影内在（照明不变）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，随着时间的推移积累证据。(ii)另一个方向是将本征图像特征应用于皮肤镜图像：本征图像可以用于消除光颜色和强度变化。我还建议删除肤色，为一个彩色图像病变图谱独立的肤色。D.）的多媒体：如果大剧院的演员在2-D中被人群跟踪，则可以生成音频深度加上平移。E.）的颜色：（i）相当大比例的纸张不正确地使用颜色。我提出了一个出版物和参考代码集的层次结构的相机校准，从完整到简单，指导研究人员如何进行。(ii)色彩平衡对相机数据至关重要。我最近向苹果的iPhone相机团队提出了一种新算法，并建议进一步研究。