Dark Channel Prior and Global Contrast Stretching based Hybrid Defogging Image Technique

V. Trivedi, P. Shukla, H. Gupta
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引用次数: 1

Abstract

Since the foggy images undergo from low contrast and resolution due to diffusion of light and poor visibility conditions. So, Fog elimination is extremely preferred in both estimation picture making and computer vision applications. Proposed technique uses a Dark Channel Prior with contrast stretching to remove fog and improve the contrast of fog free image, respectively. Using Dark Channel Prior method one can directly take away the thickness of the haze and recover a high quality haze free image. Contrast Stretching is applied in the resulted image of dark channel prior method to improve the contrast of image. The noise that affect foggy image can also be ease by using the median low pass filter. By using this technique the visual quality and color of the foggy image can be correct effectively. Experiments are conducted on PSNR and RMSE parameters. Experimental Result shows that proposed method contains least average RMSE values and Higher PSNR values among other methods.
基于暗通道先验和全局对比度拉伸的混合图像去雾技术
由于光的扩散和能见度差,雾天图像的对比度和分辨率较低。因此,雾消除在估计图像制作和计算机视觉应用中都是非常优选的。该技术采用暗通道先验和对比度拉伸分别去除无雾图像的雾和提高无雾图像的对比度。使用暗通道先验方法可以直接去除雾的厚度,恢复高质量的无雾图像。对暗通道先验法得到的图像进行对比度拉伸,提高了图像的对比度。影响雾状图像的噪声也可以通过使用中值低通滤波器来缓解。利用该技术可以有效地保证雾天图像的视觉质量和色彩的准确性。对PSNR和RMSE参数进行了实验。实验结果表明,该方法具有最小的平均RMSE值和较高的PSNR值。
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