EFFICIENT MEDICAL IMAGE FUSION BASED ON DENOISING AND FILTERING USING HYBRID FILTERS
Author’s Name : Theres Paul | T B Dharmaraj
Volume 05 Issue 03 Year 2018 ISSN No: 2349-3828 Page no: 23-28
Image fusion is to automatically transfer the meaningful information contained in multiple source images to a single fused image without introducing information loss. Medical images are often corrupted by noise in acquisition or transmission, and the noise signal is easily mistaken for a useful characterization of the image, making the fusion effect drop significantly. The main aim of Medical Image fusion is in having better quality of fused image for the diagnostic purposes. Modified image fusion framework is the combination of Butterworth High pass filter and Cross Bilateral filter. Input source images are sharpened by using high order and low cut off frequency Butterworth filter. Sharpened source images are the inputs of cross bilateral filter. A multiscale alternating sequential filter is exploited to extract the useful characterizations (e.g., details and edges) from noisy input medical images by the process of feature extraction. Then, a bilateral filter – based filtering to guide the fusion of main features of input images. The modified image fusion framework is effective in preserving brightness, fine details, information content, texture and contrast of image.
Feature Extraction, Butterworth Filter, Cross Bilateral Filter, Multistate Alternating Sequential Filter, Medical Image Fusion
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