CT Scan and X-Ray Medical Images Compression using WDR and PCA techniques: A Performance Analysis
S. Saradha Rani1, G Sasibhushana Rao2, B. Prabhakara Rao3
1S. Saradha Rani, Department of ECE, GITAM (Deemed To Be University), Visakhapatnam (Andhra Pradesh), India.
2G. Sasibhushana Rao, Department of ECE, AU College of Engineering, AU, Visakhapatnam (Andhra Pradesh), India.
3B. Prabhakara Rao, Department of ECE, JNT University, Kakinada (Andhra Pradesh), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 2048-2051 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2717037619/19©BEIESP
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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: Image compression which is a subset of data compression plays a crucial task in medical field. The medical images like CT, MRI, PET scan and X-Ray imagery which is a huge data, should be compressed to facilitate storage capacity without losing its details to diagnose the patient correctly. Now a days artificial neural network is being extensively researched in the domain of image processing. This paper examines the performance of two techniques namely Principle Component Analysis (PCA) and Wavelet difference reduction (WDR). Wavelet difference reduction method is a wavelet coding technique. The potential of the techniques to compress the medical image and achieving good quality, is measured by MSE and PSNR quality metrics. The investigation is carried on CT scan of lower abdomen and X-ray scan of Rib Cage medical images.
Keywords: Image Compression, PCA, Wavelet, WDR.
Scope of the Article: Image Processing and Pattern Recognition