fusion of medical images in wavelet domain

Abstract

Image compression is a major example of medical operations since it leads to better newlineknowledge and delivery of treatment, especially in the field of radiology. The most newlinerecent image formats are presented by mathematical methods which require a lot of newlineinformation representation. Discrete as well as Continuous Wavelet Transform that newlinedecomposes the original image to Low Pass and High Pass sub-band region is an newlineimportant tool which provides sufficient information to represent the original image newlinewith a significant reduction in computation time and is considerably easier to newlineimplement. Thanks to the practicality of the discrete wavelet transformation, we can newlineobtain reasonable frequency resolution for low frequency components in image newlinecompression and poor temporal resolution for high frequency components. newlineThis work presents a new approach to multi-resolution analysis and is most commonly newlineused in the science of image fusion, capturing features of an image not only in specific newline(low-high) resolution but with multiple orientations. We use WT, DWT and CWT for newlineimage fusion and image extraction to access the role of mathematical implementations newlinein the medical domain. The expected or planned results must be able to better newlineunderstand every form of image resolution and should attempt to compress or fuse the newlineimages to decrease their size but not their pixel quality. Implementation of the newlinemathematical method would allow the medical researchers and practitioners to better newlineunderstand the image fusion and transmission that leads to better care and also newlinedecreases the transfer rate of data as the size decreases and the loss of data can also be newlinecontrolled. The concept of introducing image fusion will decrease the image size that newlinecan be useful when transmitting images in rising bandwidth. The goal is to retain the newlinesame quality during the data transmission and the compression of images. Because this newlineis a new implementation, if the encoding of medical information images is incorrect, newlinethen it may lead to treatment errors