Interpolation of the Histogramed MR Brain Images for Resolution Enhancement
A. Charles Stud1, N. Ramamurthy2
1A.Charles Stud, Research Scholar, ECE department, JNT University Anantapur, Ananthapuramu, Andhra Pradesh, India.
2N. Ramamurthy, Professor of ECE department, G.Pullaiah College of Engineering & Technology, Kurnool, Andhra Pradesh, India.
Manuscript received on 20 August 2019. | Revised Manuscript received on 11 September 2019. | Manuscript published on 30 September 2019. | PP: 1253-1256 | Volume-8 Issue-11, September 2019. | Retrieval Number: J94250881019/2019©BEIESP | DOI: 10.35940/ijitee.J9425.0981119
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: Magnetic resonance imaging (MRI) is an incredible testing method which provides appropriate anatomical images of the body. For the diagnosis, high resolution MR images are essential to extract the detailed information about the diseases. However, with the measured MR images it’s a challenging issue in extracting the detailed information associated to disease for the posterior analysis or treatment. Usually to improve the resolution of the MR image, histogram equalization process has to be applied. In this paper, interpolation method is applied to improve the resolution of MR brain images for the histogram-ed images. And for the assessment of the skillfulness of introduced method, performance metrics such as peak signal to noise ratio (PSNR) and absolute mean brightness error (AMBE) are measured. The peak of signal for the enhanced images through interpolation will be much better and may have the good variation to the mean brightness error. With this there can be potential to the artificial intelligence for better diagnosis in complex decisive instances.
Keywords: Histogram Equalization, Interpolation, MR images, Resolution Enhancement
Scope of the Article: Image Processing and Pattern Recognition