Transport-Aware Image Sensors

传输感知图像传感器

• 批准号: RGPIN-2017-06931
• 负责人: Genov, Roman
• 金额: $ 4.23万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=651688
• 关键词: Transport; Aware; Image; Sensors

The main objective of our research program for the next five-year term will be to design, prototype and demonstrate a new class of computational image sensor integrated circuits whose key property is that they are transport-aware. Unlike conventional image sensors, which record all incident light, transport-aware imagers can be programmed to selectively detect only some of that light, depending on the actual 3D paths it followed through a visual scene. Such an imager acquires selected components of light transport (e.g., direct-only contributions, indirect-only contributions, specular-indirect contributions, etc.) by physically blocking all “undesirable” light paths so they cannot contribute to the image formed on the sensor.****** Transport-aware cameras promise to dominate many high-end industrial, scientific and commercial 2D and 3D imaging applications in robotics and computer vision such as: augmented and virtual reality, self-driving cars, 3D printers and scanners, video games, biomedical imaging, and materials analysis. Conventional cameras which are currently widely used for these applications have very limited programmability needed to apply transport-aware imaging techniques. Current full-functionality transport-aware cameras require a large mechanically deforming digital micromirror device (DMD) to implement programmable sensor masking, which introduces the following handicaps: (i) excessive form factor – the size of a printer – a key barrier to the largest market of portable consumer electronics; (ii) prohibitive distortion due to DMD-imposed large-lens curvature, (iii) low electro-mechanical mask update speed significantly limiting the range of applications, (iv) high power dissipation hindering mobile implementations, and (v) high cost – in the range of thousands of dollars. We will develop a new class of computational image sensors that not only eliminate DMDs and their shortfalls, but, by electronic per-pixel masking, also offer previously unattainable versatility in coded-exposure imaging.****** The proposed image sensors combine spatial (intensity) and temporal (phase) exposure coding and will deliver previously unattainable performance levels to transport-aware cameras, a radically new class of cameras in their own right. Cameras based on such image sensors will offer an unrivaled view of the world around us in which refraction and scattering can be selectively attenuated or amplified and object surfaces can be reconstructed in 3D under challenging conditions well beyond of what is possible with the existing state of the art imaging technologies.

我们下一个五年期研究计划的主要目标将是设计，原型和演示一类新的计算图像传感器集成电路，其关键特性是它们是运输感知的。与记录所有入射光的传统图像传感器不同，运输感知成像器可以被编程为选择性地只检测其中一些光，这取决于它通过视觉场景所遵循的实际3D路径。这样的成像器获取光传输的选定分量（例如，仅直接贡献、仅间接贡献、投机-间接贡献等）通过物理阻挡所有“不需要的”光路，使它们不能对传感器上形成的图像做出贡献。 运输感知相机有望主导机器人和计算机视觉领域的许多高端工业、科学和商业2D和3D成像应用，例如：增强现实和虚拟现实、自动驾驶汽车、3D打印机和扫描仪、视频游戏、生物医学成像和材料分析。目前广泛用于这些应用的常规相机具有应用运输感知成像技术所需的非常有限的可编程性。当前的全功能运输感知摄像机需要大的机械变形数字图像处理设备（DMD）来实现可编程传感器掩蔽，这引入了以下障碍：（i）过大的形状因子-打印机的尺寸-便携式消费电子产品的最大市场的关键障碍;（ii）由于DMD施加的大透镜曲率而导致的禁止性失真，（iii）显著限制应用范围的低机电掩模更新速度，（iv）阻碍移动的实现的高功率耗散，以及（v）成本高-在数千美元的范围内。我们将开发一类新的计算图像传感器，不仅消除DMD及其不足，而且通过电子像素掩蔽，还提供编码曝光成像中以前无法实现的多功能性。 所提出的图像传感器结合了联合收割机空间（强度）和时间（相位）曝光编码，并将提供以前无法达到的性能水平，以运输感知相机，一个全新的一类相机在自己的权利。基于这种图像传感器的相机将为我们周围的世界提供无与伦比的视野，其中折射和散射可以选择性地衰减或放大，并且可以在远超出现有最先进成像技术的挑战性条件下以3D重建物体表面。