SBIR Phase II: Reflectance Sensitive Image Sensor for Illumination-Invariant Visual Perception

该小型企业创新研究（SBIR）第二阶段研究项目提出开发一种自适应CMOS图像传感器，该传感器可估计并在很大程度上消除感测到的光学图像中的照明变化，从而报告指示所观察场景的反射率的电子图像。通过消除照明引起的变化，从原始的光学图像，建议的传感器将根除视觉系统的脆弱性，照明变化和信号丢失，由于高动态范围。核心创新在于用于从感测图像估计照明场的信号处理技术。该技术有效地实现为分布在光电探测器之间的密集片上大规模并行模拟处理器，以产生反射敏感图像传感器。通过补偿照明，所提出的图像传感器固有地解决了宽动态范围问题，该宽动态范围问题通常导致常规相机过度曝光或曝光不足，从而产生不充分的图像。即使在光照条件没有使图像传感器饱和的情况下，视觉系统也必须考虑由光照引起的物体外观变化。包括汽车、生物识别、安全和移动的计算应用在内的大多数当前和未来的视觉应用都在不受约束的环境中运行，并且必须科普未知和广泛变化的照明条件。图像传感器正迅速进入人们的汽车、手机、个人数字助理、医疗和诊断设备、自动药物发现、尖端安全、监控和生物识别系统。

This Small Business Innovation Research (SBIR) Phase II research project proposes to develop an adaptive CMOS image sensor that estimates and largely eliminates illumination variations in sensed optical images thus reporting electronic images that are indicative of the reflectance of the viewed scene. By eliminating illumination-induced variations from the raw optical images the proposed sensor will eradicate the vision system's vulnerability to illumination variations and signal loss due to high dynamic range. The core innovation is in a signal processing technique for estimating the illumination field from sensed images. The technique efficiently implements as a dense on-chip massively parallel analog processor distributed among the photo-detectors to produce a reflectance sensitive image sensor. By compensating for illumination, the proposed image sensor inherently addresses the wide dynamic range problem, that routinely causes conventional cameras to over or under expose producing inadequate images. Even when illumination conditions do not saturate an image sensor, the vision system has to account for object appearance variations caused by illumination.The proposed research has the potential to broadly impact computer vision performance and reliability. Most present and future vision applications including automotive, biometric, security, and mobile computing applications operate in unconstrained environments and have to cope with unknown and widely varying illumination conditions. Image sensors are rapidly finding their way into people's cars, cell-phones, personal digital assistants, medical and diagnostic equipment, automated drug discovery, cutting edge security, surveillance and biometric systems.