Image Denoising using Hybrid Filter in Presence of Multiple Noises and Graphical User Interface for Medical Image Enhancement

• Published in: I-manager's Journal on Image Processing Vol. 2; no. 4; pp. 10 - 18
• Main Authors: Karnam, Gopi, Ramashri, T.
• Format: Journal Article
• Language: English
• Published: Nagercoil iManager Publications 15.12.2015
• ISSN: 2349-4530; 2349-6827
• DOI: 10.26634/jip.2.4.3686

In the field of image processing, the filtering algorithms are functional over the noisy images to eliminate the noise and protect the image details. In medical diagnosis, removing noise is a very challenging issue, as images are corrupted by multiple noises. Medical images like CT, MRI, and PET have information about the heart, nerves and brain. These images are to be precise and free from noise. This paper presents an efficient method for noise reduction, contrast enhancement for medical images. The projected method uses Hybridization of adaptive median filter with the wiener filter for denoising multiple noises. Wiener filter have enhanced stability between smoothness and precision. It also shows the GUI representation of Image smoothing, Histogram Equalization. The method is experimented on the MRI (Magnetic Resonance Image) and performance is evaluated in terms of the Peak Signal to Noise Ratio (PSNR), Correlation coefficient, Mean Absolute Error (MAE) and Mean Square Error (MSE). The proposed technique removes the Gaussian noise, Impulse noise and Blurredness in the images and improve the quality of images. The result shows that, the hybrid filter outperforms most of the basic algorithms for reduction of multiple noises in medical images. Finally, the results proved that the exploitation of hybrid filter gives the appropriate and consistent results on the test images and provide precision to picture while preserving its information.