Gaussian Noise Removal in an Image using Fast Guided Filter and its Method Noise Thresholding in Medical Healthcare Application

• Published in: Journal of medical systems Vol. 43; no. 8; pp. 280 - 9
• Main Authors: Majeeth, S. Shaik, Babu, C. Nelson Kennedy
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2019; Springer Nature B.V
• Subjects: Algorithms; Computer applications; Delivery of Health Care; Diagnostic Imaging; Discrete Wavelet Transform; Health Informatics; Health Sciences; Image & Signal Processing; Image filters; Medical imaging; Medicine; Medicine & Public Health; Noise; Noise reduction; Normal Distribution; Random noise; Signal-To-Noise Ratio; Statistics for Life Sciences; Wavelet Analysis; Wavelet transforms; Wearable Computing Techniques for Smart Health; Wiener filtering; Fast guided filter; Method noise; Wavelet thresholding
• ISSN: 0148-5598; 1573-689X; 1573-689X
• DOI: 10.1007/s10916-019-1376-4

A new denoising algorithm using Fast Guided Filter and Discrete Wavelet Transform is proposed to remove Gaussian noise in an image. The Fast Guided Filter removes some part of the details in addition to noise. These details are estimated accurately and combined with the filtered image to get back the final denoised image. The proposed algorithm is compared with other existing filtering techniques such as Wiener filter, Non Local means filter and bilateral filter and it is observed that the performance of this algorithm is superior compared to the above mentioned Gaussian noise removal techniques. The resultant image obtained from this method is very good both from subjective and objective point of view. This algorithm has less computational complexity and preserves edges and other detail information in an image.