Medical Image De-Noising Schemes Using Different Wavelet Threshold Techniques
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 11
Abstract
In recent years most of researcher’s has done tremendous work in the field of medical image applications such as Magnetic Resonance Imaging (MRI), Ultra Sound, CT scan but still there are many research and experiments in medical imaging field and diagnosing of human health by Health Care Institutes. There is a growing interest for medical imaging de-noising as a hot area of research and also imaging equipment as a device. It is used for better image processing and highlighting the important features. These images are affected with random noise during acquisition, analyzing and Transmission process. This results in blurry image visible in low contrast. Wavelet transforms have effective method to separate the noise from the original medical image by using threshold techniques without affecting the important data of an image. Wavelet transform enables us to use the forward wavelet transform to represent sub-band of the original image in decomposition process then reconstructing this sub band coefficients to original image using inverse wavelet transform. In this work, the quality of medical image has been evaluated using filter assessment parameters like Variance, standard deviation, the squared difference error between original medical image & de-noised image (MSE) and the ratio between original image & noisy image. From numerical results, we can see that the algorithm is efficient de-noising of noisy medical image. When, investigating with Baye’s threshold techniques it achieved the Best value of peak signal to noise ratio (PSNR). For best medical image de-noising, the wavelet based de-noising algorithm has been investigated and results of Baye’s techniques and hard & soft threshold methods have been compared.
Authors and Affiliations
Nadir Mustafa, Saeed Khan, Jiang Li, Mohamed Elsir
Keywords
Related Articles
- EP ID EP138311
- DOI 10.14569/IJACSA.2015.061108
- Views 99
- Downloads 0
Convolutional Neural Networks in Predicting Missing Text in Arabic
Missing text prediction is one of the major concerns of Natural Language Processing deep learning community’s at-tention. However, the majority of text prediction related research is performed in other languages but not...
Rule Adaptation in Collaborative Working Environments using RBAC Model
Collaborative Working Environments (CWEs) are getting prominence these days. With the increase in the use of collaboration tools and technologies, a lot of sharing and privacy issues have also emerged. Due to its dynamic...
Smart Coaching : Enhancing Weightlifting and Preventing Injuries
Getting injured is one of the most devastating and dangerous challenges that an athlete can go through and if it is a big injury it could end his/her athletic career. In this paper, we propose a system to automate the id...
The Impact of Motivator and Demotivator Factors on Agile Software Development
Since the last decade, Agile software development has emerged as a widely utilized software development method keeping in view the developing countries of South Asia. The literature reports significant challenges and bar...
Security Issues of a Recent RFID Multi Tagging Protocol
RFID is now a widespread method used for identifying people and objects. But, not all communication protocols can provide the same rigorous confidentiality to RFID technology. In return, unsafe protocols put individuals...