水下视频图像清晰化方法

doi:10.13229/j.cnki.jdxbgxb20190344

Abstract

Abstract:

The general method to sharp the underwater video image is vulnerable to provoking issues such as image distortion, noise amplification, and the flicker and jump of adjacent frames in video playback. To overcome these disadvantages, a single color method based on color space as well as the underwater image sharpening method and an underwater video sharpening method based on spatiotemporal information fusion are proposed. In the process of clearing the single underwater image, the phenomenon that the transmittance is estimated to be large in traditional method is polished, and the combination of dark channel prior and color saturation is adopted in order to polish the background light. For the phenomenon of flicker and jump in adjacent frames in video playback, the time and space information are fused, and the more stable transmittance is estimated by interpolation and averaging. The experimental results show that the proposed underwater video sharpening method works effectively in the clearing of underwater video images, resulting in well-processed continuity and smoothness of the video.

Key words: information processing technology, underwater video image, color space, space-time information, background light, transmittance

CLC Number:

TP391.4

Yan-fen CHENG,Li-juan YAO,Qiao YUAN,Xian-qiao CHEN. Clearing strategy of underwater video image[J].Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 668-677.

Figures/Tables 10

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Table 1

Objective evaluation of underwater single image"

组别	评价指标	算法
组别	评价指标	He	CLAHE	MSRCR	本文
1	$g ˉ$	2.304 8	6.768 3	3.067 8	3.859 9
	$H$	14.635 0	17.723 0	14.059 2	16.644 7
	$E A V$	8.746 4	25.462 4	12.248 6	14.522 4
2	$g ˉ$	3.732 4	10.973 7	5.076 0	5.739 3
	$H$	15.132 0	17.053 3	14.955 3	15.689 7
	$E A V$	18.503 8	55.968 3	24.998 4	33.231 6

Table 1

Table 2

Objective evaluation of underwater video"

组别	方法	评价指标	第99帧	第103帧	第105帧
1	文献[5]	$g ˉ$	1.407 0	2.740 2	3.272 8
		$H$	14.059 4	14.310 6	14.246 5
		$E A V$	6.524 0	11.089 6	13.080 5
	逐帧处理	$g ˉ$	1.247 7	1.605 7	1.848 5
		$H$	14.519 9	14.990 1	15.212 2
		$E A V$	6.278 7	7.483 7	8.508 5
	本文算法	$g ˉ$	1.207 5	1.538 2	1.776 6
		$H$	14.352 9	14.846 0	15.046 3
		$E A V$	6.217 0	7.417 2	8.391 8
	方法	评价指标	第50帧	第59帧	第70帧
2	文献[5]	$g ˉ$	4.628 5	4.467 7	4.266 9
		$H$	13.282 8	13.291 2	13.584 1
		$E A V$	16.887 7	15.506 4	14.705 5
	逐帧处理	$g ˉ$	7.182 6	6.643 3	6.714 7
		$H$	14.768 2	14.747 9	14.850 5
		$E A V$	26.987 0	23.520 6	23.724 2
	本文算法	$g ˉ$	6.635 8	6.294 8	6.261 9
		$H$	14.459 6	14.355 0	14.442 4
		$E A V$	24.070 9	21.966 8	21.806 7

Table 2

References 13

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