A fuzzy convolutional neural network for enhancing multi-focus image fusion
The images captured by the cameras contain distortions, misclassified pixels, uncertainties
and poor contrast. Therefore, the multi-focus image fusion (MFIF) integrates various input
image features to produce a single fused image using all its objects in focus. However, it is
computationally complex, which leads to inconsistency. Hence, the MFIF method is
employed to generate the fused image by integrating the fuzzy sets (FS) and convolutional
neural network (CNN) to detect focused and unfocused parts in both source images. It is …
and poor contrast. Therefore, the multi-focus image fusion (MFIF) integrates various input
image features to produce a single fused image using all its objects in focus. However, it is
computationally complex, which leads to inconsistency. Hence, the MFIF method is
employed to generate the fused image by integrating the fuzzy sets (FS) and convolutional
neural network (CNN) to detect focused and unfocused parts in both source images. It is …
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