Abstract: The image obtained by the traditional dark channel prior image defogging fog method is dark and the quality is not high.To solve this problem,a telegraph equation model containing bidirectional diffusion and adaptive shock filtering is established.The edge detector is combined with impulse filtering and the weight coefficient is adaptively selected from the gradient feature of the image to form the sharpening term,so that the image can be enhanced adaptively according to the characteristics of different regions.Adding fidelity items to ensure that the enhanced image preserves the main features of the original image and prevents distortion of the image.On this basis,the finite difference method is used to solve the model numerically to obtain the enhanced image.Experimental results on foggy images show that,compared with the defogging algorithm based on dark channel prior theory and the enhancement algorithm based on adaptive impulse filtering,the proposed algorithm has obvious visual enhancement effect,which can improve the image brightness,reduce the noise effect and improve the image quality.

Key words: foggy image enhancement, telegraph equation, dark channel prior, bidirectional diffusion, adaptive shock filtering, edge detector

摘要： 由传统暗原色先验图像去雾方法得到的图像偏暗,质量不高。为此,建立包含双向扩散和自适应冲击滤波的电报方程模型。将边缘检测器与冲击滤波相结合,权重系数由图像的梯度特征自适应选取以构成锐化项,使图像根据不同区域的特征自适应地增强。加入保真项确保增强图像保留原图像的主要特征,防止图像失真。在此基础上,用有限差分法对模型进行数值求解从而得到增强图像。对雾天图像进行的实验结果表明,相对基于暗原色先验理论的去雾算法、基于自适应冲击滤波的增强算法,该算法在视觉上有明显的增强效果,能够提高图像亮度,降低噪声影响,改善图像质量。

关键词: 雾天图像增强, 电报方程, 暗原色先验, 双向扩散, 自适应冲击滤波, 边缘检测器

CLC Number: 

• TP391.41