Abstract: One of the key technologies of the digital camera nighttime visibility meter is to process the image information of the target light source and black body captured by the CCD at high speed and in real time. A miniaturized and portable embedded visibility measurement system based on TMS320DM642 was designed and implemented in hardware and software, and applied to digital camera night visibility measurement. The CCD video stream of 25 frames/s is collected by CCD, digitized and sent to the DSP processor, and the image segmentation and positioning algorithm of the target light source and the black body is realized by the DSP, and the nighttime visibility of the digital camera is measured. The experimental results show that the embedded system designed can better measure the nighttime visibility.
Key words: DSP; image processing; night visibility; embedded system
0 Preface
Visibility is an important parameter in meteorological observation, and it has important application value for aerospace, railway, highway and so on. The digital camera method is a new method for detecting visibility based on the visibility definition and the human visual threshold effect. The basic idea is to obtain the visibility value by directly processing the image of the selected object taken by the camera (CCD) and analyzing the brightness information. This paper studies the nighttime visibility measurement method of dual-source camera method, and designs a DSP-based miniaturized embedded system, from hardware and software design.
The system was studied to achieve the calculation of nighttime visibility. Experimental results show that the system can be used for observation of nighttime visibility.
1 Digital camera method to detect the principle of night visibility
The principle of nighttime visibility detection using the dual light source method is shown in Figure 1.
The dual light source method is a method based on the Beer-Lambert law to obtain the visibility of the light source and the black body by image gray information, and then invert the atmospheric extinction coefficient to calculate the visibility. The obtained atmospheric extinction coefficient is: 
Where: the brightness of the light source 1, 2, the black body 1, 2; D1 and D2 are the distance of the light source 1, 2 from the camera, respectively.
Then, according to the human eye visual threshold effect, the visibility value is D=ln(1/0.02)/σ.
2 embedded system hardware design
2.1 System overall design
The system is mainly composed of a target light source and a black body, a camera and a signal processing platform. The signal processing platform completes the image acquisition, segmentation and visibility calculation functions of the signal. This paper designs a real-time image acquisition and processing platform based on TMS320DM642 and CY37064P100, TVP5150PBS, SAA7121 and DMT32240T035_01WN. The platform performs image acquisition and segmentation positioning processing, calculation of the brightness of the target light source and the target black body, and the visibility value. Figure 2 is a block diagram of the system module.
The PAL camera provides a video stream of 25 frames per s. The CCD captures the image and converts the input video stream into 8-bit ITU-R BT.656 format video data through a video decoding chip, and obtains the visibility value through DSP image processing. Then, the serial communication circuit extended by the DM642 communicates with the LCD screen with the serial port, and the visibility value is displayed on the liquid crystal screen. At the same time, the video encoding chip converts the video data of the BT.656 format processed by the DSP into a video signal of the PAL system, and displays the processed target light source and the image of the target black body through the monitor.
2.2 Embedded Signal Processing System Hardware Design
2.2.1 Video Acquisition Module
The 8-bit analog industrial camera directly captures the PAL video image and sends it to the video decoder. After decoding, the ITU-R BT.656 format data is output. The decoder uses a high-performance, small-package (32-pin TQFP), low-power (less than 150 mW) TVP5150PBS to convert PAL video signals into digital color difference signals (YUV 4:2:2). FIG. 3 is a diagram of a video decoding module and a DSP interface.
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