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2019 | OriginalPaper | Buchkapitel

Early Started Hybrid Denoising Technique for Medical Images

verfasst von : Khakon Das, Mausumi Maitra, Punit Sharma, Minakshi Banerjee

Erschienen in: Recent Trends in Signal and Image Processing

Verlag: Springer Singapore

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Abstract

We propose an Early Started Hybrid Denoising Technique for brain images using modified Haar wavelet transform. To enhance the quality of the images, image fusion is used by combining two brain images obtained using positron emission tomography (PET) and computed tomography (CT) scan. Modified wavelet transform using lifting and in-place calculation has been proposed in the paper which has been shown efficient with respect to denoising parameters. The proposed algorithm is applied on the fused images, and the results show reduced noise parameters and enhanced denoised images. The peak signal-to-noise ratio (PSNR) and other statistical results like Universal Image Quality Index (UIQI) and Mutual Information (MI) are better for the fused images using modified Haar wavelet transform.

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Metadaten
Titel
Early Started Hybrid Denoising Technique for Medical Images
verfasst von
Khakon Das
Mausumi Maitra
Punit Sharma
Minakshi Banerjee
Copyright-Jahr
2019
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-8863-6_14

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