贝叶斯框架下去雾算法的优化
首发时间:2018-05-22
摘要:近年来,由于雾霾天气的频繁出现,图像的户外视觉系统受到了严重的影响,导致图像质量严重退化,影响了图像的特征判断和识别。在交通运输、室外监控、侦查、导航、遥感遥测等方面带来了很大的不变。因此,对图像去雾技术的深入研究,有很大的应用前景。本文提出了大气光图来替换单一的大气光值,提高区域的去雾效果。实验表明该方法能有效提高有雾图像的清晰度和对比度,处理效果自然,视觉效果明显改善。
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Optimization of Fog Algorithm in Bayesian Framework
Abstract:In recent years, due to the frequent occurrence of haze weather, the outdoor visual system of the image has been seriously affected, resulting in serious degradation of image quality, which affects the image feature judgment and recognition.It has brought great changes in transportation, outdoor monitoring, reconnaissance, navigation, remote sensing and telemetry.Therefore, the research on image defogging technology has great application prospect.In this paper, the atmospheric light map is proposed to replace the single atmospheric light value and improve the effect of haze removal.Experiments show that this method can effectively improve the sharpness and contrast of fog images, and the processing effect is natural and the visual effect is improved obviously.
Keywords: Haze image Airlight map Bayes framework
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