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

Satya Prakash Yadav, Sachin Yadav


Introduction: As per “Hong ZHENG, Dequen ZHENG Yanxianag HU, Sheng Li. Study on the Optimal Parameters of Image Fusion Based on Wavelet Transform[J]. Journal of Computational Information Systems (2010)” Image compression is a great instance of operations in the domain of medical which leads to better understanding and implementations of treatment especially in radiology. Discrete wavelet transform also termed as 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 be capable of 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 DWT a mathematical approach will help the researchers or practitioners in the medical domain for 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 also we can manage the data loss.

Originality: The kind of thought of implementing the fuse to the images may decrease the size of the image which may useful for reducing the bandwidth while transmitting the images. But the thing here is to maintain the same quality while transmission of data and also while compressing the images. Limitations: As this is new to implementation, if we have done any wrong in image compression of medical related information, this may lead to treatment faults of the patient. Image quality must not be reduced with this implementation.


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


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