A Novel Multimodality Image Fusion Method Using Region Consistency Rule

Authors:
Tanish Zaveri;Mukesh Zaveri
Affiliations:
EC Department, Nirma University, Ahmedabad, India;Computer Engineering Department, Sardar Vallabhbhai National Institute of Technology Surat, India
Venue:
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Year:
2009

Citing 3
Cited 1

Normalized Cuts and Image Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multifocus image fusion using region segmentation and spatial frequency

Image and Vision Computing
Region Based Image Fusion for Detection of Ewing Sarcoma

ICAPR '09 Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition

Similarity-based multimodality image fusion with shiftable complex directional pyramid

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes an efficient region based image fusion scheme using discrete wavelet transform. This paper also proposes two new fusion rules namely mean, max and standard deviation (MMS) and region consistency rule. The proposed algorithm identifies the given images are multisensor or multifocus automatically. It allows best suitable algorithm for segmenting the input source images. Proposed method is applied on large number of registered images of various categories of multifocus and multimodality images and results are compared using standard reference based and nonreference based image fusion parameters. It is evident from simulation results of our proposed algorithm that it preserves more information compared to earlier reported pixel based and region based methods.