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Improving image quality in poor visibility conditions using a physical model for contrast degradation

机译:使用可降低对比度的物理模型改善可见性差的情况下的图像质量

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In daylight viewing conditions, image contrast is often significantly degraded by atmospheric aerosols such as haze and fog. This paper introduces a method for reducing this degradation in situations in which the scene geometry is known. Contrast is lost because light is scattered toward the sensor by the aerosol particles and because the light reflected by the terrain is attenuated by the aerosol. This degradation is approximately characterized by a simple, physically based model with three parameters. The method involves two steps: first, an inverse problem is solved in order to recover the three model parameters; then, for each pixel, the relative contributions of scattered and reflected flux are estimated. The estimated scatter contribution is simply subtracted from the pixel value and the remainder is scaled to compensate for aerosol attenuation. This paper describes the image processing algorithm and presents an analysis of the signal-to-noise ratio (SNR) in the resulting enhanced image. This analysis shows that the SNR decreases exponentially with range. A temporal filter structure is proposed to solve this problem. Results are presented for two image sequences taken from an airborne camera in hazy conditions and one sequence in clear conditions. A satisfactory agreement between the model and the experimental data is shown for the haze conditions. A significant improvement in image quality is demonstrated when using the contrast enhancement algorithm in conjuction with a temporal filter.
机译:在白天观看条件下,大气雾剂(例如雾霾和雾气)通常会大大降低图像对比度。本文介绍了一种在场景几何已知的情况下减少这种退化的方法。对比度丢失是因为光被气溶胶颗粒向传感器散射,并且由于地形反射的光被气溶胶衰减。这种退化大致由具有三个参数的基于物理的简单模型来表征。该方法包括两个步骤:首先,解决反问题以恢复三个模型参数;然后,对于每个像素,估计散射和反射通量的相对贡献。简单地从像素值中减去估计的散射贡献,然后按比例缩放其余部分以补偿气溶胶衰减。本文介绍了图像处理算法,并对所得增强图像中的信噪比(SNR)进行了分析。分析表明,SNR随范围呈指数下降。提出了一种时间滤波器结构来解决这个问题。呈现了在朦胧条件下从机载相机拍摄的两个图像序列和在清晰条件下拍摄的一个图像序列的结果。对于雾度条件,显示了模型与实验数据之间令人满意的一致性。当将对比度增强算法与时间滤波器结合使用时,可以显示图像质量的显着改善。

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