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Edge Preserving Image Fusion using Intensity Variation Approach

In this article, a novel edge preserving image fusion method is proposed by merging multiple images captured from different imaging sensors. The objective of this paper is to highlight the informative contents of multiple images into a single fused image. Fusion of data from multiple sensors is a difficult task as the imaging modality are different and sensors capturing the data may be affected by sensors noise. As the images captured from multiple sensors possess uncertainty within a pixel due to the multi-valued level of brightness. It is obvious that a deterministic method of fusion may not give a better results. Hence, it is required to explore the use of fuzzy sets theoretic approaches in this regard. The proposed scheme follow three stages. In the first stage of the algorithm, a resultant image is obtained by setting the maximum value between the pixel intensity of visible and infrared sub-images considered within a small spatial neighborhood. The edges of the visible image are preserved in the second stage of the algorithm using a Fuzzy edge technique. Finally the fused image is obtained by combining the obtained resultant image and the edges of the visible image. In order to evaluate the performance of the proposed method quantitatively, and qualitatively experiments were carried out on publicly available benchmark database, "TNO-database". The proposed method is compared with those of eight state-of-the-arts techniques. The experimental results of the proposed method attained state-of-the-art performance in objective assessment and visual quality assessment.