基于改进图像增强算法的单幅图像去雾

B. Xie, Jianhao Shen, Junxia Yang, Zhiming Lv
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引用次数: 0

摘要

在烟、雾、霾等恶劣天气下获取的图像往往受到较大程度的干扰。因此,除雾已成为许多领域的一项具有挑战性的任务。本文将四叉树大气光估计模型与引导滤波算法相结合,提出了一种图像增强算法,该算法可以显著提高图像对比度并保留细节。该方法可以显著改善无先验信息的彩色图像和灰度图像。多尺度分解模块为后续的平滑模块和增强模块提供基础图像和细节图像。通过上述大气光强估计算法和透射率估计算法,可以显著提高图像恢复的精度。利用引导滤波算法对残差图像进行处理,保存图像的细节信息。最后,通过颜色校正算法得到最终图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single Image Dehazing based upon Modified Image Enhancement Algorithm
The images acquired in the bad weather such as smoke, fog and haze are often disturbed to a large extent. Therefore, dehazing has become a challenging task in many fields. By combining the quadtree atmospheric light estimation model with the guided filtering algorithm, this paper proposes an image enhancement algorithm, which can significantly improve the image contrast and preserve the details. This method can significantly improve color image and gray image without prior information. The multi-scale decomposition module provides basic image and detail image for the subsequent smoothing module and enhancement module. Through the atmospheric light intensity estimation algorithm and transmittance estimation algorithm described above, the accuracy of image restoration can be significantly improved. The details of the image can be saved by processing the residual image by guided filtering algorithm. Finally, the final image can be obtained by color correction algorithm.
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