中国激光, 2015, 42 (2): 0209001, 网络出版: 2015-01-19
基于小波变换的低照度图像自适应增强算法 下载: 643次
Adaptive Enhancement Algorithm for Low Illumination Images Based on Wavelet Transform
图像处理 低照度图像 小波变换 双边滤波 模糊增强 Retinex理论 image processing low illumination images wavelet transform bilateral filtering fuzzy enhancement Retinex theory
摘要
提出了一种基于小波变换的低照度图像快速、自适应增强算法。将RGB 图像转到HSV 空间,并对亮度V 图像利用离散小波变换(DWT)将图像的高、低频子带分离。在小波变换的低频子带上利用双边滤波对图像的照射光分量进行快速估计与去除,而在高频子带上利用模糊变换实现边缘、纹理信息的增强与去噪处理。对处理后的V图像,基于提出的直方图目标函数,利用鲍威尔与模拟退火相结合的优化算法,实现了对比度的快速、自适应增强处理。将增强后的V 图像与H、S 颜色分量合成为清晰化的彩色图像。实验结果表明,该算法能快速、有效实现低照度图像的清晰化处理。
Abstract
A fast and adaptive enhancement algorithm for low illumination images based on wavelet transform is presented. RGB color image is converted to HSV color space, and the luminance component V is decomposed to low frequency sub-band and high frequency sub-bands by discrete wavelet transform (DWT). The illumination component is estimated and removed using bilateral filtering from the low frequency subband quickly, and the high frequency sub- bands corresponding to the image edges and texture are enhanced and de- noised using transform of fuzzy set. Based on the proposed histogram objective function, the contrast of the resulted V image is enhanced adaptively and quickly by employing the optimization method combining the Powell with the simulated annealing algorithm. The visibility improved color image is generated by combining the enhanced V image with H and S chrominance components. The experimental results show that the proposed algorithm can improve the visibility of low illumination images quickly and effectively.
李庆忠, 刘清. 基于小波变换的低照度图像自适应增强算法[J]. 中国激光, 2015, 42(2): 0209001. Li Qingzhong, Liu Qing. Adaptive Enhancement Algorithm for Low Illumination Images Based on Wavelet Transform[J]. Chinese Journal of Lasers, 2015, 42(2): 0209001.