Photo counting imaging is a promising imaging method for very low-level-light condition and super high-speed imaging.
An experimental setup with Geiger mode silicon avalanche photodiode single-photon counter was established in this
study. This experimental setup achieved photon counting imaging through serial two-dimensional scanning mode of
single APD. It extracts the extremely weak signal from the noise by scanning image, and then reconstructs the photon
distribution image. The feasibility of the experiment platform was verified with many experiments. The resolution bar
was scanned and imaged in different lighting condition. A Lena image was also scanned and imaged among several
illumination conditions. The resolution ability and imaging quality are evaluated in different illumination surroundings.
The imaging limited condition was concluded based on existing APD sensor. The experimental result indicates that the
imaging based Geiger mode APD is an excellent candidate for very low level light imaging.
The precision test of an infrared search and track system usually need field trial. It’s unsuitable for short-distance and
indoor test. This paper presents an indoor test technique for infrared search and track precision. The indoor test system
design and implementation are described in detail. The experimental results and analysis are provided. The movement of
the small target dial was driven by a high-precision stepper motor in this system. A blackbody was used to simulate the
radiation of targets. Controlling Computer connects to the stepper motor via RS-232 serial port. The software interface
written by Visual Basic sets the stepper motor’s running speed, direction and the operating angle value. The target’s track
coordinate is translated into azimuth and elevation angles through the algorithm of angle measurement. Then the value
recorded by the tested search and track system compare to the theoretical value given by the test system. The search and
track precision are analyzed and test.
Along with the extending application of uncooled infrared focal panel arrays, the requirements for high quality infrared imaging are increasing continuously. The nonuniformity correction technology based on existing unary linear theoretical model has become the bottleneck of infrared imaging quality improvement. Through theoretical analysis of un-cooled infrared focal panel array photoelectric response mechanism and its imaging process, the primary influencing factors for infrared sensor response and their nonuniformity are deduced in this paper. A theoretical model of binary nonlinear nonuniformity for uncooled infrared focal panel arrays is present. The impact of surrounding temperature on sensor response is taken into account in this model. Experimental test results are given in this paper. Statistic analysis results show that this model can give reasonable prediction of the responsive curve for uncooled infrared focal panel arrays sensor in wider scene radiation and surrounding temperature range. This model describes the exact photoelectric response relationship between infrared radiation and infrared detector output signal. Furthermore, this model reflects influencing factors of nonuniformity for infrared imaging more accurate than the existing unary linear theoretical model.
The number and distribution of non-effective pixels is an important quality figure that defines a given infrared focal
panel array (IRFPA). An accurate non-effective pixel detection algorithm is present in this paper. Through theoretical
analysis of IRFPA responsivity suitable definition of non-effective pixel is given. Based on this definition an adaptive
threshold is proposed to discriminate various non-effective pixels and normal pixels. Meanwhile, multi-temperature
matching approach helps us to pick out the hided non-effective pixel under a certain temperature range. Finally,
neighboring pixel interpolation is performed to substitute non-effective pixels according to spatial correlation. The
benefit of this method is reducing misjudgment of non-effective pixels, which will degrade infrared image quality. This
approach for detecting and replacing non-effective pixels is successfully applied to a set of frames obtained from an
IRFPA imaging. Results show that the detection and replacement accuracy of non-effective pixels is greatly improved by
this approach. Furthermore, the proposed algorithm is adaptable to a variety of non-effective pixel types.
Research of image processing algorithm is one of the key issues for infrared imager development. Nowadays, researchers
of image processing algorithm and designers of infrared imager have presented many image processing algorithms. It is
necessary to evaluate the practicability, real-time performance and adaptability of all these algorithms in advance of
application. Based on virtual instrumental technology, a general demo and evaluation system for infrared image
processing algorithms is developed. The system configuration is described in detail. The extendable property of this
system made it suitable for various algorithms demo and evaluation. The vision impression of image processing
algorithms demo is processed through labview programming. Designers can evaluate the performance of image
processing algorithms in time. This system benefits designers to optimize their algorithms directly. Examples are applied
in this system to prove its functions. Trial results show it is a useful tool for infrared imager developer and image
processing algorithm designer.
Firstly, the drawbacks of infrared image histogram equalization and its improved algorithm are analyzed. A novel technique which can not only enhance the contrast but also preserve detail information of infrared image is presented. It is called adaptive histogram subsection modification in this paper. The property of infrared image histogram is applied to determine the subsection position adaptively. The second-order differential coefficient of gray level probabilistic density curve is calculated from top down direction. The first inflexion is chosen as the subsection point between high probabilistic density gray levels and low probabilistic density gray levels in the histogram of infrared image. Then the histogram of low probabilistic density section and high probabilistic density section are mapped and modified respectively. Finally, subsection images are combined together and an output infrared image is reconstructed. The contrast is enhanced and the original gray levels are mostly preserved simultaneously during extending the dynamic range of gray levels in infrared image. Meanwhile, suitable distance is kept between gray levels to avoid large isolated grains defined as patchiness in the image. Several infrared images are adopted to demonstrate the performance of this method. Experimental results show that the infrared image quality is greatly improved by this approach. Furthermore, the proposed algorithm is simple and easy to perform.