基于Retinex理论的图像去雾去噪算法

Image dehazing and detuning algorithm based on Retinex theory

利用基于Retinex理论的去雾算法对图像进行去雾处理,图像会出现颜色失真,细节信息不明显等问题,为了更好地实现动态范围压缩和颜色恒定,提出了一种基于Retinex理论的图像去雾去噪算法。该方法大致可分为3部分:求取光照强度,增强图像细节和线性加权融合。首先利用MSR算法求取图像的光照分量和反射分量,然后利用拉普拉斯金字塔对反射分量进行处理,增强图像的细节部分。最后进行彩色校正重建清晰图像。通过与其它去雾算法进行性能对比,实验结果表明,该算法具有较高的可靠性和有效性,能高效地去雾并增强图像的边缘和细节部分,得到细节清晰的高质量图像。

The image is defogged by using the defogging algorithm based on the Retinex theory,there will be problems such as image color distortion and inconspicuous detail information.In order to achieve better dynamic range compression and color constant,an image de-fogging algorithm based on Retinix theory is proposed.The method can be roughly divided into three parts:obtaining light intensity,enhancing image detail and linear weighted fusion.Firstly,the MSR algorithm is used to obtain the illumination component and the reflection component of the image,and then the Laplacian pyramid is used to process the reflection component to enhance the detail part of the image.Finally,color correction is performed to reconstruct a clear image.Compared with other defogging algorithms,the experimental results show that the algorithm has high reliability and effectiveness.Specifically,the algorithm can effectively defog and enhance the edges and details of the image,and obtain high-quality images with clear details.