A fusion method for visible and infrared images based on contrast pyramid with teaching learning based optimization

• This paper presents an optimized method for visible and infrared images fusion employing TLBO method.
• Fusion coefficients are non-linear adjusted adaptively by fitness function.
• Proposed method outperforms other methods in both visual effect and objective evaluation.

This paper proposes a novel image fusion scheme based on contrast pyramid (CP) with teaching learning based optimization (TLBO) for visible and infrared images under different spectrum of complicated scene. Firstly, CP decomposition is employed into every level of each original image. Then, we introduce TLBO to optimizing fusion coefficients, which will be changed under teaching phase and learner phase of TLBO, so that the weighted coefficients can be automatically adjusted according to fitness function, namely the evaluation standards of image quality. At last, obtain fusion results by the inverse transformation of CP. Compared with existing methods, experimental results show that our method is effective and the fused images are more suitable for further human visual or machine perception.