Deblurring of MRI Image Using Blind and Non-Blind Deconvolution Methods

Sugandha Agarwal¹, O.P. Singh¹ and Deepak Nagaria²

¹Amity School of Engineering and Technology, Amity University, Lucknow.

²Electronics and Communication Department, BIET, Jhansi.

Corresponding Author E-mail: sugandhaa7@gmail.com

Abstract: For effectual analysis and diagnosis of medical images, image deblurring is the essential step. While acquiring, medical images usually get corrupted by noise and blur. The paper aims to improve the clarity and quality of blurred and noisy MRI (Magnetic Resonance Image) due to various causes such as Gaussian blurring, out of focus blur, motion artifacts, turbulence, and etc.Several procedures are available for denoising and deblurring image, but they lack uniqueness.    Blind and non-blind deconvolution is utilized in this work to restore the original uncorrupted image. Deconvolution algorithms are analyzed both theoretically and experimentally for deblurring of MRI images. The performance evaluation is conducted using PSNR (Peak Signal to Noise Ratio), SNR (Signal to Noise Ratio) and MSE (Mean Square Error) on the basics of all the above mentioned parameters it was inferred that blind deconvolution algorithm produced more accurate result both analytically and experimentally.

Keywords: Blind deconvolution; Non- blind deconvolution; PSF (Point Spread Function); PSNR (Peak Signal to Noise Ratio); SNR (Signal to Noise Ratio) and MSE (Mean Square Error)

[ HTML Full Text]

Back to TOC