Pixel-level image fusion

Infrared and visible image fusion methods and applications: A survey

A new 1D chaotic system for image encryption

Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multi-modal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. This review article provides a factual listing of methods and summarizes the broad scientific challenges faced in the field of medical image fusion. We characterize the medical image fusion research based on (1) the widely used image fusion methods, (2) imaging modalities, and (3) imaging of organs that are under study. This review concludes that even though there exists several open ended technological and scientific challenges, the fusion of medical images has proved to be useful for advancing the clinical reliability of using medical imaging for medical diagnostics and analysis, and is a scientific discipline that has the potential to significantly grow in the coming years.

Medical Image Fusion: A survey of the state of the art

2D Sine Logistic modulation map for image encryption

Multimodal medical image fusion, as a powerful tool for the clinical applications, has developed with the advent of various imaging modalities in medical imaging. The main motivation is to capture most relevant information from sources into a single output, which plays an important role in medical diagnosis. In this paper, a novel fusion framework is proposed for multimodal medical images based on non-subsampled contourlet transform (NSCT). The source medical images are first transformed by NSCT followed by combining low- and high-frequency components. Two different fusion rules based on phase congruency and directive contrast are proposed and used to fuse low- and high-frequency coefficients. Finally, the fused image is constructed by the inverse NSCT with all composite coefficients. Experimental results and comparative study show that the proposed fusion framework provides an effective way to enable more accurate analysis of multimodality images. Further, the applicability of the proposed framework is carried out by the three clinical examples of persons affected with Alzheimer, subacute stroke and recurrent tumor.

Directive Contrast Based Multimodal Medical Image Fusion in NSCT Domain

http://eee.sutech.ac.ir/sites/eee.sutech.ac.ir/files/Groups/com/DrDanyali/7-A%20new%20robust%20reference%20watermarking%20scheme%20based%20on%20DWT-SVD.pdf

A new robust reference watermarking scheme based on DWT-SVD

A new contrast based multimodal medical image fusion framework

Discrete fractional wavelet transform and its application to multiple encryption

Multi-modal medical image fusion, as a powerful tool for the clinical applications, has developed with the advent of various imaging modalities in medical imaging. The main motivation is to capture most relevant information from sources into a single output, which plays an important role in medical diagnosis. In this paper, a novel framework for medical image fusion based on framelet transform is proposed considering the characteristics of human visual system (HVS). The core idea behind the proposed framework is to decompose all source images by the framelet transform. Two different HVS inspired fusion rules are proposed for combining the low- and high-frequency coefficients respectively. The former is based on the visibility measure, and the latter is based on the texture information. Finally, the fused image is constructed by the inverse framelet transform with all composite coefficients. Experimental results highlight the expediency and suitability of the proposed framework. The efficiency of the proposed method is demonstrated by the different experiments on different multi-modal medical images. Further, the enhanced performance of the proposed framework is understood from the comparison with existing algorithms.

Gaurav Bhatnagar

Papers

Directive Contrast Based Multimodal Medical Image Fusion in NSCT Domain

A new robust reference watermarking scheme based on DWT-SVD

A new contrast based multimodal medical image fusion framework

Discrete fractional wavelet transform and its application to multiple encryption

Human visual system inspired multi-modal medical image fusion framework