Spatial Correlation Based Contrast Enhancement for Retinal Images
M. Nagraju Naik1, Venkata Subba Reddy K2
1Dr. M. Nagraju Naik, Department of Electronics and Communications Engineering, CMR College of Engineering & Technology, Kandlakoya, Medchal, Hyderabad, Telangana, India.
2Venkata Subba Reddy K, Department of Electronics and Communications Engineering, SSJ Engineering College, Hyderabad, Telangana, India.
Manuscript received on 05 March 2019 | Revised Manuscript received on 12 March 2019 | Manuscript Published on 20 March 2019 | PP: 130-134 | Volume-8 Issue- 4S2 March 2019 | Retrieval Number: D1S0027028419/2019©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: A Novel Contrast Enhancement Approach is proposed in this paper to enhance the quality of low contrast retinal images such that the automatic diagnosis of Diabetic Retinopathy results in more accurate results. Unlike the conventional approaches, this approach considers the spatial correlations between image pixels along with image pixel intensities. Due to the consideration of spatial correlations, the pixel intensities in the output image are not only linear combinations of input pixels but also relate to the neighboring pixel intensities. Extensive simulations are carried out over the proposed approach through the standard fundus image datasets such as DRIVE and DIARETDB1. Further the proposed approach is compared with conventional approaches and the performance enhancement is measured through the performance metrics like contrast improvement index and linear index of fuzziness and observed that the proposed approach outperforms the conventional approaches.
Keywords: Diabetic Retinopathy, Contrast Enhancement, Histogram, CLAHE, DRIVE, CII, LIF.
Scope of the Article: Communications