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Improved Haze Removal Method using Proportionate Fusion of Color Attenuation Prior and Edge Preserving

机译:改进的雾霾去除方法使用彩色衰减的比例蚀刻和边缘保留

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Nowadays, fog and haze are becoming a global challenge. Images captured under the hazy condition have poor contrast and corrupted colour. Such images limit the visibility and thus hinder the way for the computer vision purposes like video observation, entity recognition. Such hazy images affect the usual working in the transportation sector e.g. trains, ships etc. One of the prominent factors affecting the outdoor vision applications is poor vision and thus, it may result in an intangible loss like safety. The image captured shows this behaviour because of the air light. This paper analyses the widely used techniques for haze removal from images alias color attenuation prior based haze removal and haze removal with edge preserving. Also, the paper proposes the better haze removing techniques using fusion based approach which gives better quality haze removal compared to the bench mark haze removal techniques. Experimental results tested with NIQE have proved the worth of proposed methods.
机译:如今,雾和阴霾正成为全球挑战。在朦胧条件下捕获的图像具有差对比度和损坏的颜色。这样的图像限制了可视性,从而阻碍了视频观察,实体识别等计算机视觉目的的方式。这种朦胧的图像影响了在运输领域的常用工作。火车,船只等。影响户外视觉应用的突出因素之一是视觉差,因此可能导致类似安全的无形损失。由于空气光,图像捕获的图像显示了这种行为。本文分析了广泛使用的雾霾从图像中移除的雾化技术,并用边缘保留了雾化的雾霾去除和雾度去除。此外,本文提出了采用基于熔融的方法更好的雾度去除技术,其提供了与稳压雾霾去除技术相比更好的质量雾度去除。用NIQE测试的实验结果证明了所提出的方法。

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