Color night vision technology can effectively improve the detection and identification probability. Current color
night vision method based on gray scale modulation fusion, spectrum field fusion, special component fusion and
world famous NRL method, TNO method will bring about serious color distortion, and the observers will be visual
tired after long time observation. Alexander Toet of TNO Human Factors presents a method to fuse multiband night
image a natural day time color appearance, but it need the true color image of the scene to be observed. In this paper
we put forward a color night vision method based on the correlation between natural color image and dual band
night image. Color display is attained through dual-band low light level images and their fusion image. Actual color
image of the similar scene is needed to obtain color night vision image, the actual color image is decomposed to
three gray-scale images of RGB color module, and the short wave LLL image, long wave LLL image and their
fusion image are compared to them through gray-scale spatial correlation method, and the color space mapping
scheme is confirmed by correlation. Gray-scale LLL images and their fusion image are adjusted through the
variation of HSI color space coefficient, and the coefficient matrix is built. Color display coefficient matrix of LLL
night vision system is obtained by multiplying the above coefficient matrix and RGB color space mapping matrix.
Emulation experiments on general scene dual-band color night vision indicate that the color display effect is
approving. This method was experimented on dual channel dual spectrum LLL color night vision experimental
apparatus based on Texas Instruments digital video processing device DM642.
In low level light (LLL) color night vision technology, dual spectrum images with respective special information were
acquired, and target identification probability would be effectively improved through dual spectrum image fusion. Image
registration is one of the key technologies during this process. Current dual spectrum image registration methods mainly
include dual imaging channel common optical axis scheme and image characteristic pixel searching scheme. In dual
imaging channel common optical axis scheme, additional prismatic optical components should be used, and large
amount of radiative energy was wasted. In image characteristic pixel searching scheme, complicated arithmetic made it
difficult for its real time realization. In this paper, dual channel dual spectrum LLL color night vision system structure
feature and dual spectrum image characteristics was studied, dual spectrum image gray scale symbiotic matrix
2-dimensional histogram was analysed, and a real time image registration method including electronic digital shifting,
pixel extension and extraction was put forward. By the analysis of spatial gray-scale relativity of fusion image,
registration precision is quantitatively expressed. Emulation experiments indicate that this arithmetic is fast and exact for
our dual channel dual spectrum image registration. This method was realized on dual spectrum LLL color night vision
experimental apparatus based on Texas Instruments digital video processing device DM642.
It is very important for mobile robot to correctly and fleetly locate. With the development of the theory and arithmetic of
computer vision, vision navigation has become an important research direction in airmanship of mobile robot. In the
paper, localization based on landmark is researched by using the camera of mobile robot on the basis of traditional
localization method. A novel mobile robot localization based on vision is presented by using multi-sensor data fusion. It
is showed from experiment data that the new localization method has better performance.
During the rehabilitation process of the post-stroke patients is conducted, their movements need to be localized and learned so that incorrect movement can be instantly modified or tuned. Therefore, tracking these movement becomes vital and necessary for the rehabilitative course. In the technologies of human movement tracking, the position prediction of human movement is very important. In this paper, we first analyze the configuration of the human movement system and choice of sensors. Then, The Kalman filter algorithm and its modified algorithm are proposed and to be used to predict the position of human movement. In the end, on the basis of analyzing the performance of the method, it is clear that the method described can be used to the system of human movement tracking.
Torsion micro-mirror is the key structure of MEMS optical devices such as MEMS optical switches, MEMS variable optical attenuator, MEMS scanning micro-mirror array and so on. In this paper, after testing a silicon-based non-silicon micro-mirror fabricated by bulk micromachining, some important measurement data has been achieved. It is clear that this silicon-based non-silicon micro-mirror scheme can has just less than 15 degree rotation at 20V driving voltage while the beam thickness is just 0.5 m m . In order to improving the stability, reliability and optical properties of the micro-mirror, a new scheme has been put forward and the fabricating process using surface-micromachining has been simulated. It is shown that the new scheme will improve the characteristics of the micro-mirror effectively.
Advanced observing and collimating technology demands excellent image detectors. While improving the performance of single image detector, methods of extending the observing ability through new pattern based on existing image detectors should be studied. Multi-band image color fusion bends itself to synthesize natural scene color image through different band mono-chromic information . Real-time image matching is the choke point of this technology. The accuracy and validity of traditional image correlation-matching algorithm are degraded by the presence of the gray change, object variation and image noise. For it uses the method of adding the difference of the pixels' gray value according to the corresponding position as degree of mismatching. In addition, natural scene different band mono-chromic image spectrum respond characteristics vary sharply. We studied image features of low-light and infrared images; founded the arithmetic model of different band image matching; put forward image margin correlation matching based on margin pixel detecting; and realized it on Altera EP1S80 developing system. The result shows that this new algorithm is effective to different band image matching.