Image fusion is the process of integrating several source images into a single image that provides more reliable information along with reduced redundancy. In this paper, a hybrid image fusion algorithm for multi focus and multi modality images is presented by exploiting the advantages of both the transform as well as spatial domain techniques. In the initial image fusion framework, the source images are decomposed only once using cascaded wavelet transform and the transformed coefficients are combined according to the fusion rules. Inverse cascaded wavelet transform is applied for obtaining the initial fused image. Further, Roberts operator is used for extracting the edge information and decision rule is introduced for choosing the edges from the focused part. The extracted edge information from the focused part replaces the existing edge information in the initial fused image for enhancing the reliability of the fused image. Experiments on various types of images such as multifocus as well as multimodality images are conducted to examine the performance of the proposed algorithm. Experimental results have shown that the proposed algorithm outperforms the well known techniques in terms of both visual perception and quantitative evaluation. Furthermore, the proposed algorithm achieves a good balance between enhancing fusion quality meanwhile reducing the computational cost. © 2017, Springer Science+Business Media, LLC.