This paper describes the main results of a recent investigation of wavelet-based algorithms for fusion of visible and infrared surveillance image sequences used in various scenarios. The concept of adaptive image fusion where the fusion engine adapts to multiple streams of input images and tries to achieve optimal fusion performance under real-time constraints is discussed. A wavelet-based intra-fusion adaptive framework is presented and the design of a system that uses this framework is outlined. The effect of several key wavelet transform parameters, such as the type of wavelet transform, the mother wavelets, the levels of decomposition, the wavelet coefficients used in the fusion process, the fusion rule, etc., which all affect the performance of an adaptive wavelet-based fusion system and the quality of the fused result, are studied in this work.