| Citation: | Jianying FAN, Mingyang MA, Shoubo ZHAO. Research on High Reflective Imaging Technology Based on Compressed Sensing[J]. Journal of Electronics & Information Technology, 2020, 42(4): 1013-1020. doi: 10.11999/JEIT190512
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When imaging a highly reflective object, the light intensity reflected easily exceeds the maximum quantized value of the light intensity received by the sensor, which causes image distortion of the captured image in the saturated region of light intensity and seriously affects the quality of information transmission. In order to improve the data loss in the high-reflection imaging saturation region, a compression-sensing of high-reflection imaging method based on the new sampling theory of compressed sensing is proposed. A specific measurement matrix is used to conduct linear sampling of the target image, and the single light intensity sampling value of the CCD image sensor is combined with the distribution data in the measurement matrix, and the integrated data is restored and reconstructed with the algorithm to achieve the imaging of the measured target in the high-light environment. The peak signal to noise ratio and gray histogram are used as objective evaluation criteria. Experiments show that this imaging method is robust and feasible, with the proportion of saturated pixels in histogram detection 0% and the peak signal to noise ratio 58.37 dB, realizing the imaging without saturated light in the high-light environment, providing a new direction for the application of compressed sensing in imaging.
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