We aim to study the short-wave infrared (SWIR), medium-wave infrared (MWIR), and long-wave infrared (LWIR) imaging ability based on optical readout bimaterial microcantilever focal plane array (FPA) uncooled infrared imaging system. First, the principle of the bimaterial microcantilever sensing and the fabrication of the microcantilever array are introduced. Second, the optical-thermal-mechanical sensing theories based on the FPA are given. Finally, an optical readout microcantilever FPA infrared imaging system is developed for SWIR, MWIR, and LWIR imaging experiments. The experimental results show that the system can acquire the clear images of the SWIR, MWIR, and LWIR targets.
The uncooled optical readout infrared imaging system altering the infrared image directly into a visible image is becoming a hotspot of research recent years. How to reduce the volume and improve the quality of infrared imaging is a key problem of the optical readout infrared thermal imaging system. In this paper, an reflective readout method of infrared imaging systems is presented, by which reduce the volume of the system for about 30%, improve the uniformity of the infrared image, the minimum detectable angle can be decreased by 1.3×10-5deg than knife-edge filter method. The result of experiment is basically consistent with the theory analysis, experimental results indicate that the NETD of this system can be reach 173mK. Compared with traditional methods, the reflective optical readout method can effectively improve image quality.
Compared with the traditional infrared imaging technology, the new type of optical-readout uncooled infrared imaging technology based on MEMS has many advantages, such as low cost, small size, producing simple. In addition, the theory proves that the technology’s high thermal detection sensitivity. So it has a very broad application prospects in the field of high performance infrared detection. The paper mainly focuses on an image capturing and processing system in the new type of optical-readout uncooled infrared imaging technology based on MEMS. The image capturing and processing system consists of software and hardware. We build our image processing core hardware platform based on TI’s high performance DSP chip which is the TMS320DM642, and then design our image capturing board based on the MT9P031. MT9P031 is Micron’s company high frame rate, low power consumption CMOS chip. Last we use Intel’s company network transceiver devices-LXT971A to design the network output board. The software system is built on the real-time operating system DSP/BIOS. We design our video capture driver program based on TI's class–mini driver and network output program based on the NDK kit for image capturing and processing and transmitting. The experiment shows that the system has the advantages of high capturing resolution and fast processing speed. The speed of the network transmission is up to 100Mbps.
In the space limited infrared imaging system based MEMS, the adjustment of optical readout part is inconvenient. This paper proposed a method of wave-front coding to extend the depth of focus/field of the optical readout system, to solve the problem above, and to reduce the demanding for precision in processing and assemblage of the optical readout system itself as well. The wave-front coded imaging system consists of optical coding and digital decoding. By adding a CPM (Cubic Phase Mask) on the pupil plane, it becomes non-sensitive to defocussing within an extended range. The system has similar PSFs and almost equally blurred intermediate images can be obtained. Sharp images are supposed to be acquired based on image restoration algorithms, with the same PSF as a decoding core.We studied the conventional optical imaging system, which had the same optical performance with the wave-front coding one for comparing. Analogue imaging experiments were carried out. And one PSF was used as a simple direct inverse filter, for imaging restoration. Relatively sharp restored images were obtained. Comparatively, the analogue defocussing images of the conventional system were badly destroyed. Using the decrease of the MTF as a standard, we found the depth of focus/field of the wave-front coding system had been extended significantly.
Annular sub-aperture stitching method was developed for testing large-aperture aspheric surfaces without using of any compensating element for measurement. It is necessary to correct measurement of aspheric optical aberrations and create mathematical description to describe wave-front aberrations. Zernike polynomials are suitable to describe wave aberration functions and data fitting of experimental measurements for the annular sub-aperture stitching system. This paper uses Zernike polynomials to describe the wave-front aberrations of full wave-front and reconstructed wave-front by annular sub-aperture stitching algorithm. At the same time, the imaging quality of the aspheric optical element can be contrasted. The stitching result shows good agreement with the full aperture result.
Recent years, the MEMS-based optical readout infrared imaging technology is becoming a research hotspot.
Studies show that the MEMS-based optical readout infrared imager features a high frame rate. Considering the
high data Throughput and computing complexity of denoising algorithm It's difficult to ensure real-time of the
image processing. In order to improve processing speed and achieve real-time, we conducted a study of denoising
algorithm based on parallel computing using FPGA (Field Programmable Gate Array). In the paper, we analyze the
imaging characteristics of MEMS-based optical readout infrared imager and design parallel computing methods for
real-time denoising using the hardware description language. The experiment shows that the parallel computing
denoising algorithm can improve infrared image processing speed to meet real-time requirement.
The uncooled infrared imaging based on MEMS has more and more broad space for development in recent years. An
uncooled thermal detector array was designed and set up using bi-material micro-cantilever structures, which can bend
with the temperature change. The effective image points of objects' infrared images which are read out by an optical
method from this thermal detector array are discrete. For this reason, the output image should be filtered based on the
gray mean value of square window, firstly. Then, each point of image can be decided to assign zero or restore the initial
gray, according to the threshold of gray value summation of the filtered image's single direction template.
Comprehensive two directions' data that is in horizontal and vertical, the final result is achieved. The experimental
results demonstrate, this algorithm can remove noise well without losing the details of objects' effective image points.
The development of the un-cooled infrared imaging technology from military necessity. At present, It is widely
applied in industrial, medicine, scientific and technological research and so on. The infrared radiation temperature
distribution of the measured object's surface can be observed visually. The collection of infrared images from our
laboratory has following characteristics: Strong spatial correlation, Low contrast , Poor visual effect; Without color
or shadows because of gray image , and has low resolution; Low definition compare to the visible light image;
Many kinds of noise are brought by the random disturbances of the external environment. Digital image processing
are widely applied in many areas, it can now be studied up close and in detail in many research field. It has become
one kind of important means of the human visual continuation. Traditional methods for image enhancement cannot
capture the geometric information of images and tend to amplify noise. In order to remove noise and improve
visual effect. Meanwhile, To overcome the above enhancement issues. The mathematical model of FPA unit was
constructed based on matrix transformation theory. According to characteristics of FPA, Image enhancement
algorithm which combined with mathematical morphology and edge detection are established. First of all, Image
profile is obtained by using the edge detection combine with mathematical morphological operators. And then,
through filling the template profile by original image to get the ideal background image, The image noise can be
removed on the base of the above method. The experiments show that utilizing the proposed algorithm can enhance
image detail and the signal to noise ratio.
The progress of MEMS-based uncooled infrared focal plane arrays (IRFPAs) are one of the most successful
examples of integrated MEMS devices. We report on the fabrication and performance of a MEMS IRFPA based on
bimaterial microcantilever. The IR images of objects obtained by these FPAs are readout by an optical method.
However, it is difficult to avoid unwanted shape distortions in fabrication, which can degrade image quality in
many ways. In this paper, the actual manufacturing errors of FPA are widely and deeply analyzed. There are
basically two kinds of manufacturing error. The limitations of both kind of error are given. It is alse pointed out
that the detecting sensitivity has its special complexity if the shape of the FPA is not ideal flat. To overcome the
difficulties in readout process caused by manufacturing errors, a novel holographic compensating illumination
technology was given. The possibilities of actualizing this technology are analyzed in many aspects. And a model
of computer generated holographic compensation is given as a further development to be actualized in future The
experiment shows that it is a feasible way to improve system performance, especially when it is too difficult to
perfect the techniques of an FPA fabrication.
Micro-electro-mechanical system (MEMS) thermal transducer is a promising technological platform for uncooled IR
imaging. We fabricated MEMS infrared focal plane arrays (FPA) based on bi-material micro-cantilever and built an
optical-readout infrared imaging system. However as a result of some factors there are a great many of noise in the
infrared images. This paper presents a meaningful real-time denoising method base on double buffering. The advantages
of this method are not only solving the problem of fluency for real-time infrared image processing, but also improving
the noise problem impacting on the quality of infrared imaging. We have applied it to optical-readout infrared imaging
system successfully. We present this method and our results in the paper.
MEMS thermal transducer is a promising technological platform for uncooled IR imaging. We fabricated MEMS IR
FPA based on bi-material micro-cantilever and structured an uncooled MEMS IR System. In addition we obtained IR
images of room temperature objects by it. Considering simplicity, low cost and efficiency the FPA readout is performed
using an optical readout scheme in this system. The problem is some 'holes' will appear in the infrared images when
some pixels of the FPA can not be detected by the readout. This paper present an algorithm based on the space pixel
point. The algorithm can judge the characteristics of these 'holes' by using the follow parameters Average gray, Discrete
and Regional gradient. After finding the 'holes' we can inpaint these 'holds' by the method of Regional growth. We have
applied it to image output successfully. We present this algorithm and our results in the paper.
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