Date of Final Oral Examination (Defense)


Type of Culminating Activity


Degree Title

PhD in Electrical and Computer Engineering


Electrical and Computer Engineering

Major Advisor

Dr. R. Jacob Baker


In recent years, vision systems based on CMOS image sensors have acquired significant ground over those based on charge-coupled devices (CCD). The main advantages of CMOS image sensors are their high level of integration, random accessibility, and low-voltage, low-power operation. Previously proposed high dynamic range enhancement schemes focused mainly on extending the sensor dynamic range at the high illumination end. Sensor dynamic range extension at the low illumination end has not been addressed. Since most applications require low-noise, high-sensitivity, characteristics for imaging of the dark region as well as dynamic range expansion to the bright region, the availability of a low-noise, high-sensitivity pixel device is particularly important.

In this dissertation, a dual-conversion-gain (DCG) pixel architecture was proposed; this architecture increases the signal to noise ratio (SNR) and the dynamic range of CMOS image sensors at both the low and high illumination ends. The dual conversion gain pixel improves the dynamic range by changing the conversion gain based on the illumination level without increasing artifacts or increasing the imaging readout noise floor. A MOSFET is used to modulate the capacitance of the charge sensing node. Under high light illumination conditions, a low conversion gain is used to achieve higher full well capacity and wider dynamic range. Under low light conditions, a high conversion gain is enabled to lower the readout noise and achieve excellent low light performance.

A sensor prototype using the new pixel architecture with 5.6μm pixel pitch was designed and fabricated using Micron Technology’s 130nm 3-metal and 2-poly silicon process. The periphery circuitries were designed to readout the pixel and support the pixel characterization needs. The pixel design, readout timing, and operation voltage were optimized. A detail sensor characterization was performed; a 127μV/e was achieved for the high conversion gain mode and 30.8μV/e for the low conversion gain mode. Characterization results confirm that a 42ke linear full well was achieved for the low conversion gain mode and 10.5ke for the high conversion gain mode. An average 2.1e readout noise was measured for the high conversion gain mode and 8.6e for the low conversion gain mode. The total sensor dynamic range was extended to 86dB by combining the two modes of operation with a 46.2dB maximum SNR. Several images were taken by the prototype sensor under different illumination levels. The simple processed color images show the clear advantage of the high conversion gain mode for the low light imaging.