基于域滤波的自适应Retinex图像增强

为了提高低照度图像的亮度和对比度,提出了一种新的基于Retinex理论的彩色图像增强方法。首先,基于Retinex理论,提出对HSV空间V分量进行域滤波估计图像光照分量,然后将V分量与光照分量相除得到反射分量的方法。之后,采用自适应Gamma校正对光照分量进行亮度提升,然后采用CLAHE对其进行对比度增强。最后,将亮度校正光照分量与反射分量相乘得到增强后的V分量,并将增强后的图像转化为RGB空间图像,达到彩色图像增强的目的。本算法可以获得更自然的增强效果,能抑制亮度较大像素点的增强,很好地突出图像中的细节信息,克服了图像增强中增强图像对比度低、颜色失真、过增强及光照突变处出现光晕现象等缺点。本算法对多种图像有效,例如高动态(HDR)图像、非均匀光照图像及低曝光图像。通过验证,本算法得到的结果相比于传统方法视觉效果更佳。

Adaptive Retinex image enhancement based on domain transform filter

In order to improve the brightness and contrast of low illumination images, we propose a new color image enhancement method based on Retinex theory. Firstly, we evaluate the illumination image of the V component by domain transform filtering in the HSV space based on the Retinex theory. We divide the V component by illumination to get the reflection image. Then, we enhance the illumination image by the adaptive Gamma correction and increase the contrast of the illumination image by the CLAHE. Finally, we multiply the enhanced illumination image by the reflection image and then transform the enhanced image into RGB space. The proposed method can achieve more natural enhancement effect, suppress strong light enhancement and highlight image details. Furthermore, the proposed method overcomes the drawbacks of low contrast, color distortion, over enhancement and halo artifact, which exist in the former methods. It can also deal with many kinds of images, such as high dynamic range images (HDR), non-uniform illumination images and low exposure images. Experimental results demonstrate that the proposed method can achieve better visual quality than traditional methods.