A new real-time infrared image enhancement algorithm which applies to FPGA is proposed in this paper. In real-time
infrared image processing, image's contrast is very low, the noise of the regular graph is effects of real-time infrared
image system precision primary factors, Seems particularly important how about to reduce infrared image noise and
improve the precision at the infrared image. In order to reduce infrared image noise, we use adaptive piecewise linear
transformation algorithm for infrared image enhancement, and objective evaluation of the enhanced images, at the same
time also to discuss real-time of the algorithm, and verify the feasibility of applying this algorithm.
A new real-time low-light-level (lll) image enhancement algorithm which applies to FPGA, is proposed in this paper. In
real-time Lll image processing, the time and space domain noise is effects of real-time Lll image system precision
primary factors, Seems particularly important how about to reduce Lll image noise and improve the precision at the lll
image. In order to reduce lll image noise, we use the time domain recursion and the good results obtained.er
Multi-frame infrared image restoration is concerned with the improvement of imagery acquired in the presence of varying degradations. The degradations can arise from a variety of factors: common examples include undersampling of the image data, uncontrolled platform or scene motion, system aberrations and instabilities, noise characteristic of the infrared detector. In this paper, the mathematic models of infrared image blur and sampling and noise models are discussed. The multi-frame infrared image restoration problem is discussed, too. We show the origin and restoration
infrared images which are used in the application of multi-frame infrared image restoration. By assessing subjectively
and objectively to restoration images, we have verified this kind of model and the feasibility of the multi-frame infrared
image restoration.
A new algorithm which is suitable for FPGA to the real-time infrared image enhancement is proposed in this paper. In
order to reduce Infrared image noise, we use the accumulation of the combining sequential neighbor frames, and use the
nonlinear expanding of gray histogram to enhance contrast ratio. This kind of algorithm has considered infrared image
characteristic and vision characteristic of the human eye synthetically, and guarantee real-time character of image
process, at the same time, also give consideration to the advantage of the FPGA design. This method can be realized
easily on hardware without damaged enhancement result. Finally, quality of enhanced image is evaluated through a
model. It has verified the enhancement result of this kind of algorithm, and offered reliable assurance for further
treatment of the infrared image. Use in the image system of the infrared video, the effect of image Enhancement is
obvious.
Reasons that thermal imaging systems consume power have been analyzed, and a low-power design scheme of thermal
imaging systems has been presented with multiple working temperature points. Transient response performance of α-si
microbolometer detectors is simulated firstly when the working temperature varies in the range from -40°C to +60°C.
Simulating results show that α-si microbolometer detectors have coherent response performance in a large range of
working temperature, which lay basis for designing uncooled thermal imaging system with multiple working
temperatures. Different from traditional thermal imaging systems, this thermal imaging system has three working
temperature with an accuracy range of less than ±0.01°C. When working, the temperature control circuit will switch
between the working temperatures according to the variety of the environmental temperature. To evaluate this thermal
imaging system, we measure its power consumption and NETD in the environmental temperature range from -40°C to
+60°C. The measurement results are that the total power is less than 2500mW and the NETD is less than 120mk. This
indicates that the thermal imaging system has nearly the same imaging quality and obviously lower power, compared
with traditional thermal imaging systems.
Iterative infrared image restoration is concerned with the improvement of infrared imagery acquired in the presence of
varying degradations. The degradations can arise from a variety of factors: common examples include undersampling of
the infrared image data, uncontrolled platform or scene motion, system aberrations and instabilities, noise characteristic
of the infrared detector. In this paper, the mathematic models of infrared image blur and sampling and noise models are
discussed. The iterative infrared image restoration problem is discussed, too. We show the origin and restoration infrared
images which are used in the application of iterative infrared image restoration. By assessing subjectively and
objectively to restoration infrared images, we have verified this kind of model and the feasibility of the iterative infrared
image restoration.
Recent advances in MEMS and focal plane array (FPA) technologies have led to the development of manufacturing
microbolometers monolithically on a readout integrated circuit (ROIC). Since the response of microbolometer detectors
depends on the modification of temperature in micromachined bridge structures, it is useful to model and simulate
thermally the corresponding structures in order to predict their performance parameters. In this work, finite element
methods are performed to simulate the transient temperature field of thermistor films of microbolometer detectors. The
varisized supporting legs' impacts on the performance of detectors are discussed and the transient response for three
microbolometer configurations was investigated. At the same time, variation of the operation temperature's impacts on
total noise, noise equivalent to temperature difference (NETD) and detectivity (D*) are also discussed in details. These
performance analyses are helpful for optimum design of microbolometer infrared detectors' structure and rational choice
of operation temperature of infrared focal plane arrays.
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