A Wavelet Based Unsharp Masking Algorithm for Enhancing Lung Images
Archana J.N.1, Aishwarya P.2
1Archana J.N*, Research Scholar , Bharathiar University, Coimbatore, India.
2Aishwarya P, Department of Computer Science, Atria Institute of Technology, Bangalore, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2597-2602 | Volume-8 Issue-12, October 2019. | Retrieval Number: K20910981119/2019©BEIESP | DOI: 10.35940/ijitee.K2091.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Low contrast and poor quality are the often cited problems in the generation of medical images. In this paper the lung images are sharpened using a technique called Unsharp Masking for contrast enhancement. A simple algorithm using wavelet based unsharp masking is developed in order to improve the quality of the visual data and provide insights to the physician for better and faster diagnosis of diseases. The proposed algorithm and the sharpened images with increasing level of intensity are illustrated. Experimental results shows that in addition to enhancing the details of the image, the proposed algorithm also preserves the edge features of the lung images effectively.
Keywords: Lung Image, Haar Transform, Laplacian, Unsharp Masking, Wavelet Transform.
Scope of the Article: Image Processing and Pattern Recognition