A new multifocus image fusion based on spectrum comparison

作者：Zhang, Xiaoli; Li, Xiongfei^*; Feng, Yuncong

来源：Signal Processing, 2016, 123: 127-142.

DOI：10.1016/j.sigpro.2016.01.006

• Multifocus image fusion
• Global focus detection
• Saliency comparison
• Bayesian prediction

In this paper, a spectrum comparison based multifocus image fusion algorithm is proposed. A distinctive feature of the proposed algorithm is that it constructs a global focus detection algorithm, which makes it get free of block artifacts and reduces the loss of contrast in the fused image. In this algorithm, source images are first transformed into Fourier space, in which we adopt the Bayesian prediction algorithm to smooth the log spectrum of each source image. By comparing the difference between the original log spectrum and its smoothed version, we can get the saliency region of each source image. Then image segmentation based on Sobel operator is employed to identify the smooth regions that may be affected by edges or textures, finally a sigmoid function is utilized to map the saliency comparison results to focus detection results in which affected smooth regions are treated in a different way. Experimental results demonstrate the superiority of the proposed method in terms of subjective and objective evaluation.

• 出版日期2016-6
• 单位吉林大学