The key aim of Multi-focus Image Fusion (MFIF) is to gather all the necessary and useful information as well as features from the source images and then merge that information to develop a fused image. This fused image is having more information and better image quality than the source images. There exist a number of MFIF techniques in spatial as well as transform domain. However, since the source images have low resolution, high level of noise and are blurred, it becomes quite difficult for the traditional MFIF techniques to provide a fused image with high image quality. Thus, to fuse the source images efficiently, a hybrid MFIF method is proposed which consists of Neutrosophic Set and Stationary Wavelet Transform. Various state-of-the-art MFIF techniques have been used to compare the performance of the Neutrosophic Stationary Wavelet Transform (NSWT) technique. To evaluate the proposed technique, quantitative as well as qualitative evaluation has been done on two different datasets. To quantitatively evaluate the proposed method based on the NSWT, two different types of evaluation metrics are used namely ”reference-based” and ”reference-less”. From the experimental results and comparison with the existing state-of-the-art techniques it has been found that the NSWT has achieved better quantitative and qualitative results that in turn helpful in extending the Depth-of-Field of the imaging system. The achieved fusion results has shown the effectiveness of the proposed MFIF technique.