Multifocus image fusion using te-cnn technique

Abstract

A combination of two or more images is called an image fusion which produce an image that teaches more about computer perspective or human perception. The multi-focus image fusion technique in this paper uses CNN (Convolutional Neural Networks) to create a focus pixel-level maps on dynamic neural networks from multicolored images. This proposed CNN technique is entirely new approach when compared to the other integration methods which are utilized the same CNN method. In this proposed approach, the binary division is completely accessed to generate the focus maps. The result of this implementation prepares high-resolution pure images, view maps using bright field data. Also, produces exact focus maps next to a clear visual image. These mixing methods produce a proportional measurement. The deep learning method is used to perform the pixel separation for multi focus image fusion technique. The deep learning algorithm creates the datasets which are necessary to perform the image fusion in multi focus images by using focus maps and focus images.