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The limited depth of field in optical lenses and camera leads to output images having nonuniform focus. Fusing the focussed regions from many images of the identical scene results in an output image with uniform focus. Generally, the methods suggested for image fusion (IF) suffers from computational complexity. In this context, we suggest a new hybrid multifocus IF model using a single optimum Gabor filter. Another important contribution of this paper is that the Gabor filter is capable of distinguishing the clear and the blurry pixels. The key concept is to decompose inputs into blocks. Each of the blocks/patches is convolved with the single optimum Gabor filter for extracting the Gabor energy feature vector. A new patch is created for fusion based on the Gabor energy feature value of each pixel in the patch. The parameters of the single Gabor filter are optimized using a relatively new optimization technique termed squirrel search algorithm (SSA). The application of optimal Gabor filter to the multifocus image fusion problem is new. The suggested technique is tested with standard images having focus on distinct objects. The outcomes reveal that the suggested technique provides improved performance, it outperforms state-of-the-art classic fusion approaches in both objective and subjective assessments.

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