Smoothness Measure for Image Fusion in Discrete Cosine Transform

The aim of image fusion is to generate high-quality images using information from source images. The fused image contains more information than any of the source images. Image fusion using transforms is more effective than spatial methods. Statistical measures such as mean, contrast, and variance, are used in Discrete Cosine Transform (DCT) for image fusion. In this paper, we use statistical measures, such as the smoothness of a block in the transform domain, to select appropriate blocks from multiple images to obtain a fused image. Smoothness captures important blocks in images and duly eliminates noisy blocks. Furthermore, we compare and analyze all statistical measures in the DCT domain. Experimental results establish the superiority of our proposed method over state-of-the-art techniques for image fusion.

@article{Vadhi2016,
  title     = {Smoothness Measure for Image Fusion in Discrete Cosine Transform},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {5},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Radhika Vadhi and Veera Swamy Kilari and Srinivas Kumar Samayamantula},
  doi       = {10.14569/IJACSA.2016.070516},
  url       = {https://doi.org/10.14569/IJACSA.2016.070516}
}