Fusion Images Techniques for Motion Pixel in A blurred Image

Abstract

     Fusing digital images is an essential step in digital image processing, as it allows for integrating information from two or more images into a single image of high quality and clarity. This work fused images resulting from motion blur (left and right) with blur block sizes of 3, 5, 7, 9, and 11. The image resulting from the blur towards the right was combined with the image resulting from the blur towards the left for the same degree of blur using traditional techniques such as addition, multiplication, and new suggested techniques, namely absolute real standard deviation, binary standard deviation, real Covariance, and binary Covariance. The data examined by quality assessment methods with the reference depends on Mutual Information, Correlation Coefficient, Structural Similarity Index metric, Structural Content, Normalized Cross Correlation, and without references like Blind Reference, less Spatial Image Quality Evaluator, Naturalness Image Quality Evaluator, Perception-based Image Quality Evaluator, and Entropy. The best combination method was binary covariance and standard binary division.