Résumé:
Multimodal image fusion through wavelet transform represents an advanced image processing method. Its aim is to combine data from various imaging sources such as optical, infrared, radar, etc., with the aim of generating a richer, more comprehensive and informative composite image that is more powerful than conventional images. original.
The main objective of this dissertation is to participate in the state of the art relating to the fusion of multimodal medical images in particular by using fusion algorithms based on the double tree complex wavelet transform (DTCWT) and the transform discrete wavelet (DWT). After having exposed the advantages of the DWT and DTCWT transform we carried out several tests on multimodal images (medical and multifocus) using several fusion rules. The results obtained showed the effectiveness of the fusion algorithms used in terms of visual quality and in terms of quantitative measurements
