Grzegorz Bieszczad

Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array

A microbolometer is an uncooled thermal sensor of infra-red radiation. In thermal imaging, microbolometers organized in arrays called focal plane arrays (FPA) are used. Because of technological process microbolometric FPAs features unwanted detector gain and offset nonuniformity. Because of that, the detector matrix, being exposed to uniform infrared radiation produces nonuniform image with superimposed fixed pattern noise (FPN). To eliminate FPN, nonuniformity correction (NUC) algorithms are used. The offset of detector in array depends from mean temperature of FPA. Every single detector in matrix has its temperature drift, so the characteristic of every detector changes over temperature. To overpass this problem, a temperature stabilization of FPA is commonly used, however temperature stabilization is a relatively power demanding process. In this article a method of offset calculation and correction for every detector in array in function of mean array temperature is described. The method of offset temperature characteristic estimation is shown. The elaborated method let to use unstabilized microbolometric focal plane array in thermographic camera. Method of offset correction was evaluated for amorphous silicon based UL 03 04 1 detector array form ULIS.

Sniper detection using infrared camera: technical possibilities and limitations

The paper discusses technical possibilities to build an effective system for sniper detection using infrared cameras. Descriptions of phenomena which make it possible to detect sniper activities in infrared spectra as well as analysis of physical limitations were performed. Cooled and uncooled detectors were considered. Three phases of sniper activities were taken into consideration: before, during and after the shot. On the basis of experimental data the parameters defining the target were determined which are essential in assessing the capability of infrared camera to detect sniper activity. A sniper body and muzzle flash were analyzed as targets. The simulation of detection ranges was done for the assumed scenario of sniper detection task. The infrared sniper detection system was discussed, capable of fulfilling the requirements. The discussion of the results of analysis and simulations was finally presented.

The calibration stand for thermal camera module with infrared focal plane array

In areas like military systems, surveillance systems, or industrial process control, more and more often there is a need to operate in limited visibility conditions or even in complete darkness. In such conditions vision systems can benefit by using thermal vision cameras. In thermal imaging an infrared radiation detector arrays are used. Contemporary infrared detector arrays suffers from technological imprecision which causes that the response to uniform radiation results in nonuniform image with superimposed fixed pattern noise (FPN). In order to compensate this noise there is a need to evaluate detectors characteristics like responsivity and offset of every detector in array. Some of the detectors in cooled detector arrays can be also defective. Signal from defective pixels has to be in such system replaced. In order to replace defective pixels, there is a need to detect them. Identification of so-called blinking pixels needs long time measurement, which in designed calibration stand is also possible. The paper presents the design of infrared detector array measurement stand allowing measurement of mentioned parameters. Measurement stand was also used to evaluate temporal noise of infrared detection modules. In article there is a description of optical system design and parameters of used reference blackbodies. To capture images from camera modules a specially designed digital image interface was used. Measurement control and calculations were made in specially written IRDiag software. Stand was used to measure parameters for cameras based on cooled focal plane arrays from Sofradir. Results of two-point nonuniformity correction are also presented.

Adaptable infrared image processing module implemented in FPGA

Rapid development of infrared detector arrays caused a need to develop robust signal processing chain able to perform operations on infrared image in real-time. Every infrared detector array suffers from so-called nonuniformity, which has to be digitally compensated by the internal circuits of the camera. Digital circuit also has to detect and replace signal from damaged detectors. At the end the image has to be prepared for display on external display unit. For the best comfort of viewing the delay between registering the infrared image and displaying it should be as short as possible. That is why the image processing has to be done with minimum latency. This demand enforces to use special processing techniques like pipelining and parallel processing. Designed infrared processing module is able to perform standard operations on infrared image with very low latency. Additionally modular design and defined data bus allows easy expansion of the signal processing chain. Presented image processing module was used in two camera designs based on uncooled microbolometric detector array form ULIS and cooled photon detector from Sofradir. The image processing module was implemented in FPGA structure and worked with external ARM processor for control and coprocessing. The paper describes the design of the processing unit, results of image processing, and parameters of module like power consumption and hardware utilization.

Digital image processing in high resolution infrared camera with use of programmable logic device

In article a digital system for high resolution infrared camera control and image processing is described. The camera is built with use of bolometric focal plane array of size 640 by 480 detectors. Single detector in array has size of 25 μm and can detect incident radiation from the spectral range of 8÷12 μm thanks to the special filter installed in specially designed entrance window. The most important tasks of infrared image processing system are array readout and correction of detectors offset and responsivity variations. The next tasks of the system are conversion of analog voltage signals from microbolometers in array to digital form and then composition of a thermal image. Microbolometer array needs to be controlled via several signals. The signal generator for readout circuit is capable of changing various timing parameters like frame rate or integration time of the detector array. The changes in these parameters can be done via special set of memory mapped registers. The infrared data received from detector array is transferred via data bus to modules performing image processing, for example techniques for image enhancement. Image processing algorithms necessary for infrared image generation are nonuniformity correction, bad pixel replacement and radiometric calibration. Optionally an additional image processing techniques can be performed like edge enhancement, dynamic range compression or object identification. The elaborated architecture of the system allowed easy change of parameters of the system and to adopt many new algorithms without significant hardware changes. Scientific work funded from science fund for years 2009-2011 as a development project.

Multispectral system for perimeter protection of stationary and moving objects

Introduction of a ground multispectral detection has changed organization and construction of perimeter security systems. The perimeter systems with linear zone sensors and cables have been replaced with a point arrangement of sensors with multispectral detection. Such multispectral sensors generally consist of an active ground radar, which scans the protected area with microwaves or millimeter waves, a thermal camera, which detects temperature contrast and a visible range camera. Connection of these three different technologies into one system requires methodology for selection of technical conditions of installation and parameters of sensors. This procedure enables us to construct a system with correlated range, resolution, field of view and object identification. The second technical problem connected with the multispectral system is its software, which helps couple the radar with the cameras. This software can be used for automatic focusing of cameras, automatic guiding cameras to an object detected by the radar, tracking of the object and localization of the object on the digital map as well as identification and alarming. In this paper two essential issues connected with multispectral system are described. We focus on methodology of selection of sensors parameters. We present usage of a spider-chart, which was adopted to the proposed methodology. Next, we describe methodology of automation of the system regarding an object detection, tracking, identification, localization and alarming.

Construction, parameters, and research results of thermal weapon sight

The paper presents the thermal sight for small arms weapons, which can be classified as 3rd gen thermal camera. The sight operates in LWIR (long wave infrared) spectra band and utilizes uncooled microbolometer focal plane array (FPA) with stabilized temperature (by means of Peltier module). The assumed technical and tactical characteristics of the presented sight were confirmed during laboratory test (including climate and vibration tests). The sight was also tested during field trials conducted at Military Institute of Armament Technology, where it was mounted on seven different weapon types with calibers from 5.56 to 12.7 mm.

Polarization state imaging in long-wave infrared for object detection

The article discusses the use of modern imaging polarimetry from the visible range of the spectrum to the far infrared. The paper presents the analyzes the potential for imaging polarimetry in the far infrared for remote sensing applications. In article a description of measurement stand is presented for examination of polarization state in LWIR. The stand consists of: infrared detector array with electronic circuitry, polarizer plate and software enabling detection method. The article also describes first results of measurements in presented test bed. Based on these measurements it was possible to calculate some of the Stokes parameters of radiation from the scene. The analysis of the measurement results show that the measurement of polarization state can be used to detect certain types of objects. Measuring the degree of polarization may allow for the detection of objects on an infrared image, which are not detectable by other techniques, and in other spectral ranges. In order to at least partially characterize the polarization state of the scene it is required to measure radiation intensity in different configurations of the polarizing filter. Due to additional filtering elements in optical path of the camera, the NETD parameter of the camera with polarizer in proposed measurement stand was equal to about 240mK. In order to visualize the polarization characteristics of objects in the infrared image, a method of imaging measurement results imposing them on the thermal image. Imaging of measurement results of radiation polarization is made by adding color and saturation to black and white thermal image where brightness corresponds to the intensity of infrared radiation.

Image processing module for high-speed thermal camera with cooled detector

Infrared cameras are used in various military applications for early detection and observation. In applications where very fast image acquisition is needed the so called cooled detectors are used. Cooled detectors are a kind of detectors that demands cryogenic cooling, but in return provide exceptional performance and temperature sensitivity with low integration times. These features predestinate cooled detectors for special purposes like airborne systems, where fast and precise infrared radiation measurement is needed. Modern infrared cooled detector arrays like HgCdTe Epsilon detector from Sofradir with spectral range of 3.5μm-5μm can provide high frame rate reaching 140Hz with full frame readout. Increasing frame rates of cooled infrared detectors demands fast and efficient image processing modules for necessary operations like nonuniformity correction, bad pixel replacement and visualization. For that kind of detector array a fast image processing module was developed. The module is made of two separate FPGA modules and configuration processor. One FPGA was responsible for infrared data processing, and was performing nonuniformity correction, bad pixel replacement, linear and nonlinear filtering in spatial domain and dynamic range compression. Second FPGA was responsible for interfacing infrared data stream to standard video interfaces. It was responsible for frame rate conversion, image scaling and interpolation, and controlling ASICs for video interface realization. Both FPGAs use several external resources like SRAM and DRAM memories. The input interface was developed to connect with Epsilink board which is a standard proximity board provided by Sofradir for this kind of detector. The image processing chain is capable of performing real-time processing on data stream of volume up to about 40 Megapixels per second.

Improved sum-of-squared-differences tracking algorithm for thermal vision systems

A modification of Sum-of-Squared-Differences algorithm is proposed to improve tracking efficiency of small objects in infra-red image sequences. The reason to use SSD algorithm is its better performance in tracking small objects, than in model based tracking algorithms. However traditional Sum-of-Squared-Differences (SSD) algorithm is sensitive to partial or full occlusions, background clutter and changes in object appearance. To increase immunity to this kind of noises the modification in model update procedure was developed. The experimental results illustrate that the proposed modification to SSD algorithm can improve overall algorithm performance in infrared operation. The paper describes the Sum-of-Squared Differences algorithm and its principal features in tracking objects on thermal image sequences. Next modification to SSD algorithm is described. Finally the experimental results are presented with comparison between traditional and modified SSD algorithm.