Time Complexity of Image Fusion through Deep Learning Techniques
The advent of image analysis and research in the field of image research comes with many scientific
protocol. The investigation of image and their properties has very complex task to understand in
microscopic view. The pixel has the smallest size which is elementary part of the image study. Image fusion
is the most emerging field of this analysis. The Information of any kind whether it is image or data must be
clear on receiver side. The image fusion is the technique which collect the images at various angle and
integrated the image to make a perfect image which reflect the non-degradable or near to original image.
Simply the integrated images much give the full-fledged information of the need area which can’t possible
in single shot of image. This paper demonstrate the three techniques which are Compressive Bilateral
Filter (CBF), ConvSR and Weighted least squares (WLS) of image fusion experimented through MATLAB.
The three technique is belong to the deep learning techniques. This paper investigate the time of execution
of fusion process of images. The exploration provide the comparative time differences of three techniques
in fusion process. This paper include the twenty one images pairs. The pairing of image fused through the
said techniques provide the single image which consist the both image features with non-degradation.