PERFORMANCE ENHANCEMENT OF MEDICAL IMAGE FUSION BASED ON DWT AND SHARPENING WIENER FILTER

(Received: 7-Jan.-2021, Revised: 28-Feb.-2021 , Accepted: 16-Mar.-2021)

Authors Nada Jasim Habeeb,

Keywords #Image fusion #Multimodal medical images #SWT #PCA #DT-CWT #DWT #Focus operators

Abstract The fusion of multimodal medical images plays an important role in data integration and improving image quality. It has a fundamental role in the accuracy of medical analysis and diagnosis. Despite the recent technological development, medical images may be exposed to blur and noise from various sources. This will affect the accuracy of the medical analysis. Therefore, de-blurring or noise removal from medical images is essential in this field. Discrete Wavelet Transform, DWT, is generally utilized in image fusion spatially in the fusion of the multimodal images. It produces a good image representation. The drawback of DWT-based image fusion is the blur presented in the fused image due to the limited directionality of wavelets. To solve this problem, Sharpening Wiener Filter and DWT-based image fusion for multimodal medical images are proposed. The proposed fusion method is evaluated using some of focus operators that were used to measure the amount of focus in the test images. The results showed that the proposed fusion gives good values of focus operators compared with the values of focus operators of image fusion techniques that are based on wavelet domain.

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