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Volume 17Issue 4
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ZHANG Zhen-hai, LI Ke-jie, GAO Jun-xiao, DUAN Xing-guang. Research and Implementation of Algorithm for Image Enhancement and Unwrapped Distortion Correction for SLVF Panoramic Night Vision Image[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2008, 17(4): 423-428.
Citation: ZHANG Zhen-hai, LI Ke-jie, GAO Jun-xiao, DUAN Xing-guang. Research and Implementation of Algorithm for Image Enhancement and Unwrapped Distortion Correction for SLVF Panoramic Night Vision Image[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2008, 17(4): 423-428.

Research and Implementation of Algorithm for Image Enhancement and Unwrapped Distortion Correction for SLVF Panoramic Night Vision Image

  • Based on digital signal processor(DSP) and field programmable gate array(FPGA) techniques, the architecture of super large view field(SLVF) panoramic night vision image processing hardware platform was established. The panoramic unwrapping and correcting algorithm, up to a full 360°, based on coordinate rotation digital computer (CORDIC) and night vision image enhancement algorithm, based on histogram equalization theory and edge detection theory, was presented in this paper, with the purpose of processing night vision dynamic panoramic annular image. The annular image can be unwrapped and corrected to conventional rectangular panorama by the panoramic image processing algorithm, which uses the pipelined CORDIC configuration to realize a trigonometric function generator with high speed and high precision. Histogram equalization algorithm can perfectly enhance the contrast of the night vision image. Edge detection algorithm can be propitious to find and detect small dim dynamic targets in night vision circumstances. After abundant experiment, the algorithm for panoramic image processing and night vision image enhancement is successfully implemented in FPGA and DSP. The panoramic night vision image system is a compact device, with no external rotating parts. And the system can reliably and dynamically detect 360° SLVF panoramic night vision image.
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