KEYWORDS: Cameras, Target detection, Signal to noise ratio, Minimum resolvable temperature difference, Image quality, 3D modeling, Target recognition, Interference (communication), Imaging systems, Temperature metrology
During the design of a system employing thermal cameras one always faces a problem of choosing the camera types best suited for the task. In many cases such a choice is far from optimal one, and there are several reasons for that. System designers often favor tried and tested solution they are used to. They do not follow the latest developments in the field of infrared technology and sometimes their choices are based on prejudice and not on facts. The paper presents the results of measurements of basic parameters of MWIR and LWIR thermal cameras, carried out in a specialized testing laboratory. The measured parameters are decisive in terms of image quality generated by thermal cameras. All measurements were conducted according to current procedures and standards. However the camera settings were not optimized for a specific test conditions or parameter measurements. Instead the real settings used in normal camera operations were applied to obtain realistic camera performance figures. For example there were significant differences between measured values of noise parameters and catalogue data provided by manufacturers, due to the application of edge detection filters to increase detection and recognition ranges. The purpose of this paper is to provide help in choosing the optimal thermal camera for particular application, answering the question whether to opt for cheaper microbolometer device or apply slightly better (in terms of specifications) yet more expensive cooled unit. Measurements and analysis were performed by qualified personnel with several dozen years of experience in both designing and testing of thermal camera systems with both cooled and uncooled focal plane arrays. Cameras of similar array sizes and optics were compared, and for each tested group the best performing devices were selected.
KEYWORDS: Sensors, Signal to noise ratio, Cameras, Microbolometers, Black bodies, Temperature metrology, Field programmable gate arrays, Signal detection
Microbolometer belongs to the group of thermal detectors and consist of temperature sensitive resistor which is exposed to measured radiation flux. Bolometer array employs a pixel structure prepared in silicon technology. The detecting area is defined by a size of thin membrane, usually made of amorphous silicon (a-Si) or vanadium oxide (VOx). FPAs are made of a multitude of detector elements (for example 384 × 288 ), where each individual detector has different sensitivity and offset due to detector-to-detector spread in the FPA fabrication process, and additionally can change with sensor operating temperature, biasing voltage variation or temperature of the observed scene. The difference in sensitivity and offset among detectors (which is called non-uniformity) additionally with its high sensitivity, produces fixed pattern noise (FPN) on produced image. Fixed pattern noise degrades parameters of infrared cameras like sensitivity or NETD. Additionally it degrades image quality, radiometric accuracy and temperature resolution. In order to objectively compare the two infrared cameras ones must measure and compare their parameters on a laboratory test stand. One of the basic parameters for the evaluation of a designed camera is NETD. In order to examine the NETD, parameters such as sensitivity and pixels noise must be measured. To do so, ones should register the output signal from the camera in response to the radiation of black bodies at two different temperatures. The article presets an application and measuring stand for determining the parameters of microbolometers camera. Prepared measurements were compared with the result of the measurements in the Institute of Optoelectronics, MUT on a METS test stand by CI SYSTEM. This test stand consists of IR collimator, IR standard source, rotating wheel with test patterns, a computer with a video grabber card and specialized software. The parameters of thermals cameras were measure according to norms and method described in literature.
KEYWORDS: Cameras, Thermography, Manufacturing, Sensors, Minimum resolvable temperature difference, Modulation transfer functions, 3D modeling, Target detection, Target recognition, Imaging systems
Measured range characteristics may vary considerably (up to several dozen percent) between different samples of the same camera type. The question is whether the manufacturing process somehow lacks repeatability or the commonly used measurement procedures themselves need improvement. The presented paper attempts to deal with the aforementioned question. The measurement method has been thoroughly analyzed as well as the measurement test bed. Camera components (such as detector and optics) have also been analyzed and their key parameters have been measured, including noise figures of the entire system. Laboratory measurements are the most precise method used to determine range parameters of a thermal camera. However, in order to obtain reliable results several important conditions have to be fulfilled. One must have the test equipment capable of measurement accuracy (uncertainty) significantly better than the magnitudes of measured quantities. The measurements must be performed in a controlled environment thus excluding the influence of varying environmental conditions. The personnel must be well-trained, experienced in testing the thermal imaging devices and familiar with the applied measurement procedures. The measurement data recorded for several dozen of cooled thermal cameras (from one of leading camera manufacturers) have been the basis of the presented analysis. The measurements were conducted in the accredited research laboratory of Institute of Optoelectronics (Military University of Technology).
In order to objectively compare the two infrared cameras ones must to measure and compare their parameters on a laboratory. One of the basic parameters for the evaluation of the designed camera is NEDT (noise equivalent delta temperature). In order to examine the NEDT ,parameters such as sensitivity and pixels noise must be measured. To do so, ones should register the output signal from the camera in response to the radiation of black bodies at two different temperatures. The article presents an application and measuring stand for determining the parameters of microbolometers camera. In addition to determination of parameters of a cameras the measuring stand allow to determine defective pixel map, the non uniformity correction (NUC) coefficients: 1-point and 2-point. Additionally, developed test stand serves as a test system to read the raw data from microbolometer detector. Captured image can be corrected with calculated non-uniformity correction coefficients. In a next step the image is processed and visualized on a monitor. Developed test stand allows for an initial assessment of the quality of designed readout circuit. It also allows for efficient testing and comparison of the number of sensors or readout circuits.
KEYWORDS: Sensors, Temperature metrology, Nonuniformity corrections, Signal detection, Detector arrays, Microbolometers, Cameras, Calibration, Black bodies, Camera shutters
Because of a significant impact of the microbolometer array temperature on the infrared image quality, it is necessary to compensate the influence of the temperature on the NUC process. In the most common applications two approaches are used: the first is a stabilization of the microbolometer array temperature by a thermoelectric cooler, the second is updating correction coefficients obtained from reference source, for example a shutter [14]. Both of the most common approaches have theirs disadvantages. The first case needs a considerable amount of energy for temperature stabilisation. The second one needs a reference target and a mechanical procedure to place the target at the front of the detector. Additionally, during calibration the reference target is blocking radiation from the scene, thus interrupting measurements with the thermal camera. In the article a non-uniformity correction method is presented which allows to compensate for the influence of detector’s temperature drift. For this purpose, dependency between output signal value and the temperature of the detector array was investigated. Additionally the influence of the temperature on the Offset and Gain coefficients was measured. Presented method utilizes estimated dependency between output signal of detectors and their temperature. In the presented method, the dependency between output signal value and the temperature of the detector is estimated during time of starting detector. The coefficients are estimated for every pixel. In the article proposed method allows to compensate the influence of detectors temperature fluctuation and increase a time between shutter actuation process.
Thermal imagers and used therein infrared array sensors are subject to calibration procedure and evaluation of their voltage sensitivity on incident radiation during manufacturing process. The calibration procedure is especially important in so-called radiometric cameras, where accurate radiometric quantities, given in physical units, are of concern. Even though non-radiometric cameras are not expected to stand up to such elevated standards, it is still important, that the image faithfully represents temperature variations across the scene. Detectors used in thermal camera are illuminated by infrared radiation transmitted through an infrared transmitting optical system. Often an optical system, when exposed to uniform Lambertian source forms a non-uniform irradiation distribution in its image plane. In order to be able to carry out an accurate non-uniformity correction it is essential to correctly predict irradiation distribution from a uniform source. In the article a non-uniformity correction method has been presented, that takes into account optical system’s radiometry. Predictions of the irradiation distribution have been confronted with measured irradiance values. Presented radiometric model allows fast and accurate non-uniformity correction to be carried out.
Uneven response of particular detectors (pixels) to the same incident power of infrared radiation is an inherent feature of microbolometer focal plane arrays. As a result an image degradation occurs, known as Fixed Pattern Noise (FPN), which distorts the thermal representation of an observed scene and impairs the parameters of a thermal camera. In order to compensate such non-uniformity, several NUC correction methods are applied in digital data processing modules implemented in thermal cameras. Coefficients required to perform the non-uniformity correction procedure (NUC coefficients) are determined by calibrating the camera against uniform radiation sources (blackbodies). Non-uniformity correction is performed in a digital processing unit in order to remove FPN pattern in the registered thermal images. Relevant correction coefficients are calculated on the basis of recorded detector responses to several values of radiant flux emitted from reference IR radiation sources (blackbodies). The measurement of correction coefficients requires specialized setup, in which uniform, extended radiation sources with high temperature stability are one of key elements. Measurement stand for NUC correction developed in Institute of Optoelectronics, MUT, comprises two integrated extended blackbodies with the following specifications: area 200×200 mm, stabilized absolute temperature range +15 °C÷100 °C, and uniformity of temperature distribution across entire surface ±0.014 °C. Test stand, method used for the measurement of NUC coefficients and the results obtained during the measurements conducted on a prototype thermal camera will be presented in the paper.
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.
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