Medical Fusion Image Using Wavelet Transformation
S. V. Jagadeesh Chandra1, A. Narendra Babu2, G. Srinivasa Rao3, Sk. Gousiya Begum4, V. Sai Nageswara Rao5, B. Nagababu6, B. Prem Kumar7
1S. V. Jagadeesh Chandra, Department of Electronics & Communication Engg, Lakireddy Balireddy College of Engineering, Mylavaram, Andhra Pradesh, India.
2A. Narendra Babu, Department of Electronics & Communication Engg, Lakireddy Balireddy College of Engineering, Mylavaram, Andhra Pradesh, India.
3G. Srinivasa Rao, Department of Electronics & Communication Engg, Lakireddy Balireddy College of Engineering, Mylavaram, Andhra Pradesh, India.
4Gousiya Begum, Department of Electronics & Communication Engg, Lakireddy Balireddy College of Engineering, Mylavaram, Andhra Pradesh, India.
5V. Sai Nageswara Rao, Department of Electronics & Communication Engg, Lakireddy Balireddy College of Engineering, Mylavaram, Andhra Pradesh, India.
6B. Nagababu, Department of Electronics & Communication Engg, Lakireddy Balireddy College of Engineering, Mylavaram, Andhra Pradesh, India.
7B. Prem Kumar, Department of Electronics & Communication Engg, Lakireddy Balireddy College of Engineering, Mylavaram, Andhra Pradesh, India.
Manuscript received on 27 May 2019 | Revised Manuscript received on 05 June 2019 | Manuscript published on 30 June 2019 | PP: 1864-1866 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6877058719/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Medical Image Fusion is the process which deals with enhancing multiple images like Computed Tomography scan, Magnetic Resonance Imaging scan by fusing them into a single or multiple imaging modalities by reducing randomness in them using Wavelet Transformation technique. The main objective is to improve the understanding of medical images with the help of Discrete Wavelet Transformation technique. DWT uses mainly fusion rules involving pixel averaging, minimum-maximum and maximum-minimum methods. The basic wavelets are Coiflets, Haar, Daubechies, Bi- orthogonal wavelets. The final performance of the fusion is then measured on the parameters such as increasing the size of the fused image without reducing the resolution.
Keywords: Wavelets; Medical Image Fusion; Discrete Wavelet Transformation; Pixel Averaging; Coiflets.
Scope of the Article: Aggregation, Integration, and Transformation