基于模糊同组划分的多尺度彩色图像增强算法

现有多尺度Retinex彩色图像增强算法采用同定权值进行加权来融合各个单尺度Retinex算法的增强结果,无法充分体现各个单尺度算法在细节增强和颜色保持上的优势,且噪声信号往往随着图像的增强而放大.针对这些问题,提出一种基于模糊同组划分的多尺度Retinex彩色图像增强算法.算法首先采用模糊同组技术将像素点划分为噪声点、细节点和平滑区域点3类,并对噪声点采用矢量中值滤波进行去除.然后采用不同尺度的Retinex算法增强图像,并通过细节区域和平滑区域所占局部窗口的面积比例来融合各个单尺度增强结果.最后通过颜色恢复和动态截取拉伸操作,进一步减少图像颜色失真,扩大动态范围.实验表明,所提出的方法相比其他算法具有更好的彩色图像增强效果,具有实际应用价值.

Multi-scale color image enhancement algorithm based on fuzzy peer groups

The advantages of different single scale Retinex algorithms in detail enhancement and chromaticity preservation can not be utilized sufficiently by existing multi-scale Retinex algorithm due to using fixed weighted value.Moreover,the noisy pixels are often enhanced in the enhancement process.Aiming at these disadvantages,we propose an improved algorithm based on fuzzy peer group.First,the pixels are classified into noisy ones,detail ones and smooth ones using fuzzy peer group technique and the noisy pixels are suppressed with the vector median filter.Then the image is enhanced with different scale Retinex algorithms and the results are fused according to the proportions occupied by different pixels in local window.Finally,further operations of color restoration,dynamic truncation and stretch are carried out to solve the problems of color distortion and narrow dynamic range.Experiment results show that the proposed algorithm outperforms other methods,and can be applied in engineering application and has practical application values.