Advancements in uncooled microbolometer technology over the last several years have opened up many commercial
applications which had been previously cost prohibitive. Thermal technology is no longer limited to the military and
government market segments. One type of thermal sensor with low NETD which is available in the commercial market
segment is the uncooled amorphous silicon (α-Si) microbolometer image sensor. Typical thermal security cameras focus
on providing the best image quality by auto tonemaping (contrast enhancing) the image, which provides the best contrast
depending on the temperature range of the scene. While this may provide enough information to detect objects and
activities, there are further benefits of being able to estimate the actual object temperatures in a scene. This
thermographic ability can provide functionality beyond typical security cameras by being able to monitor processes.
Example applications of thermography with thermal camera include: monitoring electrical circuits, industrial
machinery, building thermal leaks, oil/gas pipelines, power substations, etc... This paper discusses the methodology
of estimating object temperatures by characterizing/calibrating different components inside a thermal camera utilizing an
uncooled amorphous silicon microbolometer image sensor. Plots of system performance across camera operating
temperatures will be shown.
This paper provides results from testing and analysis of sun exposure effects on amorphous silicon (α-Si)
microbolometers and vanadium oxide (VOX) microbolometers. Gain and offset changes for each detector
type is provided. Results from different sun exposure levels corresponding to different geographic locations
and time of year are presented. Data associated with increasing exposure duration and number of exposures
is presented. The time constants associated with the sun exposure effects are also provided. Potential
mitigation processes and algorithms are explored reducing the impact on image quality. The effectiveness of
mitigation processes and algorithms is presented.
This paper is a follow-up to the paper presented at SPIE Electronic Imaging Science and Technology in San Jose, 2007,
"Characterization and system modeling of a 5-Mpixel CMOS array."
We expand and refined test methodologies used in the characterization and selection process of CMOS arrays targeting megapixel security camera applications. This paper presents work in the following areas: system gain, gain noise, binning noise, F-number response, system modeling, and temperature effects. Since security cameras must operate under harsh temperature extremes, performance under these conditions must be understood. Characterizations are made for the following areas: dark current, DSNU, hot pixels, clusters, temporal noise and spatial noise.
We present characterization results for a 5 million pixel CMOS image sensor designed for high speed applications. This sensor is capable of outputting 14 frames per second and incorporates on-chip 12-bit digitization. We present measurements of system gain, read noise, dark current, charge capacity, linearity, photo response non-uniformity, defects, and quantum efficiency. The image sensor incorporates exposure control functionality, windowing, on-chip binning, anti-blooming capability and rolling shutter architecture to implement image capture mode. The results show a favorable aspect of the ability to achieve high speed, high resolution, and very good sensitivity in a monolithic CMOS sensor. Architecture trades for high speed imaging systems utilizing CCDs and CMOS sensors are also presented.