Imaging performance in advanced small pixel and low light image sensors

Even though image sensor performance has improved tremendously over the years, there are two key areas where sensor performance leaves room for improvement. Firstly, small pixel performance is limited by low full well, low dynamic range and high crosstalk, which greatly impact the sensor performance. Also, low light color image sensors, which use color filter arrays, have low sensitivity due to the selective light rejection by the color filters. The quanta image sensor (QIS) concept was proposed to mitigate the full well and dynamic range issues in small pixel image sensors. In this concept, spatial and temporal oversampling is used to address the full well and dynamic range issues. The QIS concept however does not address the issue of crosstalk. In this dissertation, the high spatial and temporal oversampling of the QIS concept is leveraged to enhance small pixel performance in two ways. Firstly, the oversampling allows polarization sensitive QIS jots to be incorporated to obtain polarization information. Secondly, the oversampling in the QIS concept allows the design of alternative color filter array patterns for mitigating the impact of crosstalk on color reproduction in small pixels. Finally, the problem of performing color imaging in low light conditions is tackled with a proposed stacked pixel concept. This concept which enables color sampling without the use of absorption color filters, improves low light sensitivity. Simulations are performed to demonstrate the advantage of this proposed pixel structure over sensors employing color filter arrays such as the Bayer pattern. A color correction algorithm for improvement of color reproduction in low light is also developed and demonstrates improved performance.