A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
A new automated quality assessment algorithm for image fusion
Image and Vision Computing
Survey of clustering algorithms
IEEE Transactions on Neural Networks
Similarity-based multimodality image fusion with shiftable complex directional pyramid
Pattern Recognition Letters
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This paper proposes a novel region based image fusion scheme based on high boost filtering concept using discrete wavelet transform. In the recent literature, region based image fusion methods show better performance than pixel based image fusion method. Proposed method is a novel idea which uses high boost filtering concept to get an accurate segmentation using discrete wavelet transform. This concept is used to extract regions from input registered source images which are then compared with different fusion rules. The new MMS fusion rule is also proposed to fuse multimodality images. The different fusion rules are applied on various categories of input source images and resultant fused image is generated. 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 has been observed from simulation results that our proposed algorithm is consistent and preserves more information compared to earlier reported pixel based and region based methods.