The color correction method based on dark channel prior and sub-region correction for EMCCD

Jie Xu; Chunye Xu; Fang Dai; Wanyu Liang; Qiyue Na

doi:10.1117/12.2564995

17 April 2020 The color correction method based on dark channel prior and sub-region correction for EMCCD

Jie Xu, Chunye Xu, Fang Dai, Wanyu Liang, Qiyue Na

Proceedings Volume 11455, Sixth Symposium on Novel Optoelectronic Detection Technology and Applications; 114554W (2020) https://doi.org/10.1117/12.2564995
Event: Sixth Symposium on Novel Photoelectronic Detection Technology and Application, 2019, Beijing, China

Abstract

For a large amount of near-infrared information is introduced to EMCCD, which leads to color distortion in the green plant area during R, G, B channel image fusion. In this paper, an algorithm combing dark channel prior and sub-region correction is proposed. First, the results of dark channel prior and sub-region extraction of green plant areas are analyzed and compared, we find that both of them have shortcomings. Second, on the basis of the preliminary dark channel extraction, binaryzation parameters are determined by analyzing the brightness mean values of various scenes in R, G, B and gray channel, so as to realize the extraction of green plant areas. Finally, the color correction is carried out in different regions and the image is converted from RGB color space to HIS color space. To make full use of the infrared information in the system, the I channel is replaced by gray channel. It is proved that the correction algorithm proposed in this paper can effectively correct the color biased image acquired by EMCCD system.

Citation Download Citation

Jie Xu, Chunye Xu, Fang Dai, Wanyu Liang, and Qiyue Na "The color correction method based on dark channel prior and sub-region correction for EMCCD", Proc. SPIE 11455, Sixth Symposium on Novel Optoelectronic Detection Technology and Applications, 114554W (17 April 2020); https://doi.org/10.1117/12.2564995

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KEYWORDS

Electron multiplying charge coupled devices

Feature extraction

Image segmentation

Detection and tracking algorithms

Image processing

Vegetation

Algorithms

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