Background is assumed to be uniform usually for evaluating the performance of thermal imaging systems, however the impact of background cannot be ignored for target acquisition in reality, background character is important research content for thermal imaging technology. A background noise parameter 𝜎 was proposed in MRTD model and used to describe background character. Background experiments were designed, and some typical backgrounds (namely lawn background, concrete pavement background, trees background and snow background) character were analyzed by 𝜎. MRTD including 𝜎 was introduced into MRTD-Channel Width (CW) model, the impact of above typical backgrounds for target information quantity were analyzed by MRTD-CW model with background character. Target information quantity for different backgrounds was calculated by MRTD-CW, and compared with that of TTP model. A target acquisition performance model based on MRTD-CW with background character will be research in the future.
The impact of nature environment on the synthesized performance of thermal imaging systems was researched comparing with the targeting task performance (TTP) model. A nature background noise factor was presented and introduced into the minimum resolvable temperature difference channel width (MRTD-CW) model. The method for determining the nature background noise factor was given. A information quantity model based on MRTD-CW model was proposed to evaluate the impact of nature environment on the synthesized performance of thermal imaging systems. A normalized parameter was introduced into the information quantity model. Different background experiments were performed, and the results were analyzed and compared with those of TTP model.
Based on the aliasing theory of focal plane array (FPA) thermal imaging systems, aliasing as noise (AAN) method and under-sampling system evaluation model based on information theory (EMIT) were analyzed. The aliasing was treated as one kind of noise and introduced into minimum resolvable temperature difference (MRTD) model, and the integral expressing of aliasing signal (IAS) method was proposed to evaluate the impact of aliasing on the performance of thermal imaging systems. IAS method was proved to be able to describe the impact of aliasing grade on the system performance effectively. The three MRTD models with different aliasing evaluation methods were researched contrastively by MRTD test experiment and target detection probability experiment. The MRTD model with IAS method was proved to evaluate the performance of under-sampling thermal imaging systems effectively, and could be used in the performance prediction of thermal imaging systems. In the future, the precision of IAS method will be researched further.
Background has a very important influence on point target operating range of infrared search and track system(IRST).
Based on the noise equation temperature difference(NETD) operating range model , a general noise parameter δ′ which
describes the influence of background and system noise on the operating range is presented, and a new operating range
model is founded including δ′. δ′ has clear meaning and gives explicit explanation for conventional detector-limited and
background-limited operating range model. The algorithm of δ′ based on the ratio of background region to target area is
proposed under natural sky background. The simulation shows that δ′ is valid for predicting point target operating range
Discrete sampling is one of the important characteristics of thermal imaging systems and has an important effect on the
target acquisition performance. Based on the study of discrete sampling theory, several discrete sampling evaluation
methods are analyzed, and the aliasing caused by under-sampling is considered as a noise of thermal imaging systems.
The aliasing noise is introduced into MRTD model with system noise. MRTD model with aliasing noise is deduced, and
its validity is verified by simulation experiments. MRTD model with aliasing noise is introduced into MRTD channel
width model. It is future work that the impact of discrete sampling on the general performance of thermal imaging
systems will be researched by MRTD channel width model.
Electronic devices are widely used in various industries, their temperature distribution cannot be obtained by traditional
test methods. In recent years, simulation softwares are used to simulate the thermal characteristics of electronic devices
and play a positive role on the reliability improvement, on the contrast, their validity cannot be verified. In this paper, the
chip temperature rise process is simulated by ICEPEAK software. Some factors that change thermal characteristics are
analyzed. The actual working temperature obtained by the thermal microscope is compared with the simulation
temperature. The validity of simulation temperature is tested and the relation is built between the actual temperature and
simulation temperature. Finally, it is pointed that thermal microscopes are the development direction on the electronic
devices design and reliability testing.
Traditional ACQUIRE models perform the discrimination tasks of detection (target orientation, recognition and
identification) for military target based upon minimum resolvable temperature difference (MRTD) and Johnson criteria
for thermal imaging systems (TIS). Johnson criteria is generally pessimistic for performance predict of sampled imager
with the development of focal plane array (FPA) detectors and digital image process technology. Triangle orientation
discrimination threshold (TOD) model, minimum temperature difference perceived (MTDP)/ thermal range model (TRM3)
Model and target task performance (TTP) metric have been developed to predict the performance of sampled imager,
especially TTP metric can provides better accuracy than the Johnson criteria. In this paper, the performance models
above are described; channel width metrics have been presented to describe the synthesis performance including
modulate translate function (MTF) channel width for high signal noise to ration (SNR) optoelectronic imaging systems
and MRTD channel width for low SNR TIS; the under resolvable questions for performance assessment of TIS are
indicated; last, the development direction of performance models for TIS are discussed.
Proc. SPIE. 6621, International Symposium on Photoelectronic Detection and Imaging 2007: Photoelectronic Imaging and Detection
KEYWORDS: Signal to noise ratio, Eye, Visual process modeling, Imaging systems, Sensors, Video, Optoelectronics, Human vision and color perception, Charge-coupled devices, Modulation transfer functions
The Square Integral Method based on the Minimum Resolvable Contrast (MRC) is to be introduced in this paper as
an evolution for the design and evaluation of optoelectronic imaging systems. It is well known that there exists an optimal
angle magnification which can make optoelectronic imaging systems and human eye matching optimally, so that
optoelectronic imaging systems can performance best. Based on MRC (Minimum Resolvable Contrast) and channel width,
a new method called Square Integral (SQI) method was presented for evaluating the general performance of a CCD imaging
system, and attaining the optimal angle magnification or optimal viewing distance. Results calculated with this method are
in good agreement with the experimental measurements. From the agreement between the practical use and the theoretical
predictions for the variation of CCD size, optical focus, luminance and human vision, it demonstrates that the SQI
method is an excellent universal measure for the optimal angle magnification and the performance of CCD imaging
Proc. SPIE. 6835, Infrared Materials, Devices, and Applications
KEYWORDS: Thermography, Signal to noise ratio, Eye, Imaging systems, Sensors, Optoelectronics, Human vision and color perception, Modulation transfer functions, Minimum resolvable temperature difference, Multichannel imaging systems
The Square Integral (SQI) Method based on MRTD (Minimum Resolvable Temperature Difference) is introduced for the
design and evaluation of thermal imaging systems. It is well known that there exists an optimal angle magnification which
can make optoelectronic imaging systems and human eye matching optimally, and make optoelectronic imaging systems
attaining the optimal performance. Based on MRTD and channel width, a new way called SQI method is presented for
evaluating the universal performance on thermal imaging systems, and attaining the optimal angle magnification or optimal
viewing distance. The method can give a rational description for the matching between thermal imaging systems and human
eye. Results calculated with this method are in agreement with experiment measurements quite perfectly. From the
coherence between measurement data and theoretical predictions with variable detector size, optics focus, luminance and
human vision, it appears that the SQI method is an excellent synthesized measure for the optimal angle magnification
and the performance of thermal imaging systems.