Vlsi Implementation of Image Fusion Using Pca Algorithm With Maximum Selection Rule
Surya Prasada Rao Borra1, Rajesh Kumar Panakala2, P. Rajesh Kumar3
1Surya Prasada Rao Borra, Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada (Andhra Pradesh), India.
2Rajesh Kumar Panakala, Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada (Andhra Pradesh), India.
3P. Rajesh Kumar, University College of Engineering, Andhra University, (Andhra Pradesh), India.
Manuscript received on 13 May 2019 | Revised Manuscript received on 19 May 2019 | Manuscript Published on 23 May 2019 | PP: 1960-1965 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F13520476S519/2019©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: Nowadays, medical diagnosis is achieved by using the Digital Image Processing (DIP) techniques. Because, the role of DIP is more important in the medical field to identify the activities of the patients related to various diseases. Magnetic Resonance Imaging (MRI) and Computer Tomography (CT) scan images are used to identify the tissues in various organs of the human body. In brain medical imaging, the brain structural information without functional data will be given by MRI scan. But, CT scan image includes the functional data with brain activity. To improve the low dose CT scan, Principal Component Analysis (PCA) algorithm is used in this paper which is implemented on FPGA. The Maximum Selection Rule (MSR) is used to select the high frequency component from the image. Application Specified Integrated Chips (ASIC) and Field Programmable Gate Array (FPGA) performances analysed for the different methods. In 180nm technology, PCA-IF architecture achieved 5.145mm2 area, 298.25mW power, and 124ms delay.
Keywords: Application Specified Integrated Chips, Field Programmable Gate Array, Principle Component Analysis, Maximum Selection Rule.
Scope of the Article: Algorithm Engineering