Method based on bitonic filtering decomposition and sparse representation for fusion of infrared and visible images

摘要

Infrared and visible images fusion based on edge-preserving can improve the fused result in a clear outline. However, there exists the performance degradation caused by some edges in the data which are smaller than the level of the noise with traditional edge-preserving decomposition. To remedy such deficiency, a method based on bitonic filtering decomposition and sparse representation is proposed for fusion of infrared and visible images. The bitonic filtering decomposition and sparse representation (BFSR) method consists of three steps: multi-scale bitonic filtering decomposition, mergence of base layers and detail layers, and reconstruction of the fused result. Compared with traditional image fusion based on edge-preserving, data-level-sensitive parameters are not included in the BFSR method, which can locally adapt to the signal and noise levels in an image. Moreover, the sparsity of images for fusing details is used in the BFSR method, which can analyse the explanatory factors hidden behind the data. As demonstrated in the experimental results, the proposed BFSR method achieves much fusion performance compared with other commonly used image fusion methods.