Abstract:

For haze removal in color image, a fast algorithm based on Principle Component Analysis (PCA) and atmospheric scattering model was proposed for color image haze removal. Firstly, the principal components of three color channels were extracted from original color image, and the three color channels were reconstructed by use of maximum principal component, and the Minimum Reconstruction Map (MRM) was obtained by taking the minimum gray value in three color channels. Then, the MRM was filtered by median filter to improve the accuracy of estimation of the global atmosphere light, then the global atmosphere light was estimated in MRM. Finally, according to the atmospheric scattering model to obtain media transmittance and the sence radiance of the haze removal image. The experimental results showed that the proposed algorithm achieved better visual recovery results, in comparison with dark channel prior haze removal algorithm and contrast limited adaptive histogram equalization algorithm. The results domonstrate that the proposed algorithm improves the operation efficiency, it is simple and easy to implement, and can quickly remove haze in color image.

Key words: color image haze removal, Principal Component Analysis (PCA), reconstruction of maximum principal component, minimum reconstruction map, atmospheric scattering model

摘要：

为去除彩色图像中的雾霾,提出了一种基于主分量分析(PCA)和大气散射模型的快速去除彩色图像雾霾的算法。首先,提取彩色图像三个颜色通道的主分量,并用最大主分量重构三个颜色通道,并在重构后的三个颜色通道中取最小灰度值构成最小重构映射(MRM);然后,用中值滤波器对MRM滤波,以提高估计全局大气光的准确性,接着在MRM中估计全局大气光;最后,根据大气散射模型求解介质透过率和场景辐射度(去除雾霾后的图像)。实验结果表明,所提算法在视觉效果上取得了较好的复原结果,与暗原色去雾算法和对比度受限自适应直方图均衡算法相比,所提算法运算效率更高,同时该算法简单、易于实现,能较快去除彩色图像中的雾霾。

关键词: 去除彩色图像雾霾, 主分量分析, 最大主分量重构, 最小重构映射, 大气散射模型