结合小波变换和CLAHE的图像增强算法

Image enhancement algorithm based on wavelet transform and CLAHE

针对降质图像可能存在的对比度低、光照不均、轮廓信息模糊等问题,提出一种结合小波变换和限制对比度自适应直方图均衡(CLAHE)的图像增强算法。首先,将原图像进行HSI变换得到亮度分量I,并引入基于限制对比度直方图均衡化算法对I进行亮度均衡处理得到I′;然后对I和I′进行小波分解得到对应的低频分量和不同尺度的高频分量,并采用引导滤波对高频分量进行去噪处理;提出基于区域特性测量的高频融合规则和基于图像可见度的低频融合规则,对两者的高频分量和低频分量分别进行融合;最后利用小波逆变换得到增强的亮度分量IL,并将亮度分量IL与分量H,S进行HSI逆变换得到增强图像。实验结果表明,该算法能有效提升图像的亮度和对比度,可以获得更好的图像视觉效果,并具有良好的图像保真和细节增强能力。

In view of the low contrast,uneven illumination and fuzzy contour information in degraded images,an image enhancement algorithm based on wavelet transform and CLAHE(contrast limited adaptive histogram equalization)is proposed.The original image is subjected to HSI transformation to obtain brightness components I.By introducing CLAHE algorithm,bright equalization processing for I is implemented to obtain I′.The I and I′are subjected to wavelet decomposition to obtain the corresponding low⁃frequency components and the high⁃frequency components with different scales.The guided filtering is used to carry out denoising processing for the high⁃frequency components.The high⁃frequency fusion rules based on regional characteristic measurement and the low⁃frequency fusion rules based on image visibility are proposed to fuse the high⁃frequency components and low⁃frequency components of the two respectively.The wavelet inverse transformation is adopted to obtain the enhanced brightness component IL.The HSI inverse transformation of brightness component IL and components H and S is carried out to obtain the enhanced image.The experimental results show that the algorithm can effectively improve the image brightness and contrast,obtain better image visual effect,and has good image fidelity and detail enhancement ability.