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Hybrid Multi Resolution Method of Image Fusion for Medical Image Processing


Affiliations
1 VELTECH Dr. RR and Dr. SR Technical University, Chennai, India
 

Image fusion is a process of combining multiple input images of the same scene into a single fused image, which preserves relevant information and also retains the important features from each of the original images and makes it more suitable for human and machine perception. The reason for going onto image fusion is that, in the medical image processing, different sources of images produce complementary information and so one has to fuse all the sources of images to get more details required for the diagnosis of the patients. In this method the raw data is the MR scan image of a patient’s brain which is observed at different angles or resolutions. The images possess both different as well as common information with respect to each other. Thus when these images are fused together the redundant images are neglected and the complementary images are added thereby producing an accurate diagnosis with a single image.

Keywords

Image Fusion, Transform, Segmentation, Filter Bank, NSCT.
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  • Hybrid Multi Resolution Method of Image Fusion for Medical Image Processing

Abstract Views: 203  |  PDF Views: 4

Authors

P. Selvaperumal
VELTECH Dr. RR and Dr. SR Technical University, Chennai, India

Abstract


Image fusion is a process of combining multiple input images of the same scene into a single fused image, which preserves relevant information and also retains the important features from each of the original images and makes it more suitable for human and machine perception. The reason for going onto image fusion is that, in the medical image processing, different sources of images produce complementary information and so one has to fuse all the sources of images to get more details required for the diagnosis of the patients. In this method the raw data is the MR scan image of a patient’s brain which is observed at different angles or resolutions. The images possess both different as well as common information with respect to each other. Thus when these images are fused together the redundant images are neglected and the complementary images are added thereby producing an accurate diagnosis with a single image.

Keywords


Image Fusion, Transform, Segmentation, Filter Bank, NSCT.