基于稀疏表示和色彩传递的图像融合与彩色化

针对红外图像和微光图像的特点,提出一种基于稀疏表示和色彩传递的双波段图像融合与彩色化方法。该方法首先采用改进的基于K_SVD的分块稀疏表示获得红外与微光图像的稀疏融合图像,然后在YUV空间采用基于色彩传递的自然感彩色夜视处理技术,对红外与微光图像进行彩色化融合,最后用稀疏融合图像的灰度值代替彩色融合图像的Y分量,从而实现双波段图像的融合与彩色化。实验表明,本文提出的彩色融合算法能够综合红外与微光特征信息,且使图像具有最佳的亮度对比和细节信息,图像色彩更易于人眼观察。

Image fusion and colorization based on sparse representation and colour transfer

Considering the features of infrared image and low-light-level image, an image fusion and colorization method based on sparse representation and colour transfer is proposed in this paper. Firstly, the blocked sparse representation method based on K_SVD is used to extract image features and then the grayscale fused image with the max fusion rule is gained. Secondly, the colour is transferred by matching the statistics of target image and the reference image in the YUV colour space. Finally, the final color fusion image is obtained by replacing the luminance component with the grayscale fused image during the color transfer process. The experimental results show that the proposed algorithm can integrate the features of infrared image and low-light-level image well. And this method can obtain the perfect contrast and detail information, and the colour of the fusion image is comfortable for human eyes.