关键词: 多聚焦图像融合, 超分辨率, 平稳小波变换

Abstract: Aiming at the problems of edge blurring and image distortion of traditional wavelet transform in image fusion, a multi-focus image fusion algorithm based on super-resolution is proposed in this paper. All source images are processed by double cubic interpolation in single frame super-resolution to enhance the source image contrast and other details. The source images used in this paper are two images in the same scene which are processed by left and right focusing respectively. Stationary Wavelet Transform（SWT） is implemented for these high resolution source images, and the source images are divided into four sub-bands. To solve the problems of source image detail information confusion and structural information redundancy contained in these subbands, Principal Component Analysis（PCA） is adopted to select the maximum signal-to-noise ratio of each subband of the source image for image fusion. Inverse Stationary Wavelet Transform（ISWT） is used to reconstruct the fusion subband and obtain high quality fusion images. In order to evaluate the quality of fused image, two measurement methods, no reference image and full reference image, are selected to detect the quality of fused image. The experimental results show that the proposed algorithm overcomes the shortcomings of traditional wavelet transform algorithm in image fusion, and has the advantages of clear edge, good visual perception, good clarity and low distortion.

Key words: multi-focus image fusion, super resolution, stationary wavelet transform