A Robust Technique for Feature-based Image Mosaicing using Image Fusion

Abstract

Since last few decades, image mosaicing in real time applications has been a challenging field for image processing experts. It has wide applications in the field of video conferencing, 3D image reconstruction, satellite imaging and several medical as well as computer vision fields. In this paper, we have proposed a feature based image mosaicing technique using image fusion. Initially, the input images are stitched together using the popular stitching algorithms i.e. Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF). To extract the best features from the stitching results, the blending process is done by means of Discrete Wavelet Transform (DWT) using the maximum selection rule for both approximate as well as detail-components. The SIFT provides scale as well as rotational invariance property. The SURF provides better computation speed and illumination invariance. The robustness and quality of the above mosaicing techniques are tested by means of three-dimensional rotational images.