Fusion of Medical Images in Wavelet Domain: A Discrete Mathematical Model

Satya Prakash Yadav, Sachin Yadav


Introduction: Image compression is a great instance for operations in the medical domain that leads to better understanding and implementations of treatment, especially in radiology. Discrete wavelet transform (dwt) is used for better and faster implementation of this kind of image fusion.

Methodology: To access the great feature of mathematical implementations in the medical domain we use wavelet transform with dwt for image fusion and extraction of features through images.

Results: The predicted or expected outcome must help better understanding of any kind of image resolutions and try to compress or fuse the images to decrease the size but not the pixel quality of the image.

Conclusions: Implementation of the dwt mathematical approach will help researchers or practitioners in the medical domain to attain better implementation of the image fusion and data transmission, which leads to better treatment procedures and also decreases the data transfer rate as the size will be decreased and data loss will also be manageable.

Originality: The idea of using images may decrease the size of the image, which may be useful for reducing bandwidth while transmitting the images. But the thing here is to maintain the same quality while transmitting data and also while compressing the images.

Limitations: As this is a new implementation, if we have committed any mistakes in image compression of medical-related information, this may lead to treatment faults for the patient. Image quality must not be reduced with this implementation.


Discrete Wavelet Transform; Image Fusion; Scaling Function; Wavelet Function;

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