Traditional dehazing methods based on restoration are prone to color distortion and noise amplification when dealing with hazy image with large sky area. To improve dehazing effect, we propose a dehazing algorithm based on image structure–texture decomposition and reconstruction. Hazy image is decomposed into high-frequency texture layer and low-frequency structure layer by total variation. Discrete cosine transform is used to generate an image mask to separate sky area and non-sky area. The texture layer is denoised by the mask, and the structure layer is dehazed by dark channel prior. The media transmission is corrected by color attenuation prior. Finally, the denoised texture layer and the dehazed structure layer are reconstructed to obtain the dehazed image. A no-reference image quality assessment is also proposed to evaluate the dehazed images. Experiment results show that, compared with the state-of-the-art methods, our algorithm has better dehazing effect on non-sky area, and the sky area after dehazing is smooth without color distortion and noise.

传统的基于复原的去雾方法在处理大天空区域的模糊图像时容易出现颜色失真和噪声放大。为了提高去雾效果，我们提出了一种基于图像结构——纹理分解和重构的去雾算法。模糊图像通过全变分解为高频纹理层和低频结构层。离散余弦变换用于生成图像蒙版以分离天空区域和非天空区域。纹理层通过掩模去噪，结构层通过暗通道先验去雾。媒体传输通过之前的颜色衰减进行校正。最后对去噪纹理层和去雾结构层进行重构，得到去雾图像。还提出了一种无参考图像质量评估来评估去雾图像。实验结果表明，与最先进的方法相比，我们的算法对非天空区域的去雾效果更好，去雾后的天空区域平滑，没有颜色失真和噪声。