Int J Performability Eng ›› 2022, Vol. 18 ›› Issue (12): 885-892.doi: 10.23940/ijpe.22.12.p6.885892

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CNN and PCA in Image Fusion: A Comparative Statistical Analysis

Ashi Agarwal*   

  1. ABES Engineering College, Ghaziabad, 201009, India
  • Submitted on ; Revised on ; Accepted on
  • Contact: * E-mail address:

Abstract: In technical terms, an image is the visual representation of a thing or person created using optical technology (such as a mirror or lens) or a technological apparatus. 2 distinct domains of multiresolution image fusion, i.e., PCA and CNN, are discussed in this study. Multiresolution image fusion techniques amalgamate more than two images covering optical unclear and blurred parts to produce an image covering all the focused areas or information. Based on the study, in both PCA and CNN. PCA is more straightforward among all image fusion approaches; meanwhile, according to the study conducted in this paper, it produces less effective results. On the other hand, CNN gives more effective results, but it is complex to handle. Also, the boundary pixels of the fused image has some mismatching problems, i.e., unrecognizable pixels. The effectiveness of the results is measured based on some statistical image quality parameters.

Key words: CNN, image fusion, multi-focus image fusion, mean square error, PCA, PSNR, SNR