Abstract
Image fusion is an important technique aiming to generate a composite image from multiple images of the same scene. Infrared and visible images can provide the same scene information from different aspects, which is useful for target recognition. But the existing fusion methods cannot well preserve the thermal radiation and appearance information simultaneously. Thus, we propose an infrared and visible image fusion method by hybrid image filtering. We represent the fusion problem with a divide and conquer strategy. A Gaussian filter is used to decompose the source images into base layers and detail layers. An improved co-occurrence filter fuses the detail layers for preserving the thermal radiation of the source images. A guided filter fuses the base layers for retaining the background appearance information of the source images. Superposition of the fused base layer and fused detail layer generates the final fusion image. Subjective visual and objective quantitative evaluations comparing with other fusion algorithms demonstrate the better performance of the proposed method.
Highlights
Image fusion is an important technique of image enhancement that extracts different salient feature information from numerous images into one full enhanced image for increasing the amount of information and utilization of the image
Image fusion technology has been applied in several aspects such as multifocus, medical, remote sensing, infrared, and visible images [1], especially in the merging of infrared and visible images. e image generated by the infrared image according to the principle of thermal imaging has high contrast and mainly provides the saliency target information of the fused image, and the visible image mainly includes the accurate background information. e saliency target in the infrared image is important for target recognition, while the background texture data in the visible image are the key to environmental analysis and detail judgment
In order to evaluate the performance of the proposed method, the classical and recent proposed fusion algorithms are used for comparison. e experimental results are assessed with subjective evaluation and objective evaluation
Summary
Image fusion is an important technique of image enhancement that extracts different salient feature information from numerous images into one full enhanced image for increasing the amount of information and utilization of the image. E image generated by the infrared image according to the principle of thermal imaging has high contrast and mainly provides the saliency target information of the fused image, and the visible image mainly includes the accurate background information. Infrared and visible image fusion provides more comprehensive information, which has important practical significance in military and civilian fields [2]. E spatial domain-based approaches mainly generate weights according to the characteristics of the original spatial information of the pixels or regions in the source image. E transform domain-based method mainly includes two parts: image decomposition and fusion rules. Multiscale decomposition tools decompose the source images into different scale spaces for obtaining layers with different feature information. E transform domain-based methods have become a research hotspot for its good adaptability to the human visual system. A large number of transform coefficients resulting in the complexity of parameter optimization compromise the fusion performance
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