A New Method of Correcting Uneven Illumination Problem in Fundus Images

Document type: Conference Papers
Peer reviewed: Yes
Author(s): A.M. Aibinu, Muhammad Imran Iqbal, M. Nilsson, M.J.E. Salami
Title: A New Method of Correcting Uneven Illumination Problem in Fundus Images
Conference name: International Conference on Robotics, Vision, Information, and Signal Processing
Year: 2007
City: Penang, Malaysia
Organization: Blekinge Institute of Technology
Department: School of Engineering - Dept. of Signal Processing (Sektionen för teknik – avd. för signalbehandling)
School of Engineering S- 372 25 Ronneby
+46 455 38 50 00
Authors e-mail: muhammad.imran.iqbal@bth.se
Language: English
Abstract: Recent advancements in signal and image processing have reduced the time of diagnoses, effort and pressure on the screeners by providing auto diagnostic tools for different diseases. The success rate of these tools greatly depend on the quality of acquired images. Bad image quality can significantly reduce the specificity and the sensitivity which in turn forces screeners back to their tedious job of manual diagnoses. In acquired fundus images, some areas appear to be brighter than the other, that is areas close to the center of the image are always well illuminated, hence appear very bright while areas far from the center are poorly illuminated hence appears to be very dark. Several techniques including the simple thresholding, Naka Rushton (NR) filtering technique and histogram equalization (HE) method have been suggested by various researchers to overcome this problem. However, each of these methods has limitations at their own and hence the need to develop a more robust technique that will provide better performance with greater flexibility. A new method of compensating uneven (irregular) illumination in fundus images termed global-local adaptive histogram equalization using partially-overlapped windows (GLAPOW) is proposed in this paper. The developed algorithm has been tested and the results obtained show superior performance when compared to other known techniques for uneven illumination correction.
Subject: Signal Processing\Detection and Classification
Medical Sciences
Keywords: Fundus Image, Overlap Technique, Adaptive Histogram Equalization, Median filtering, Windowing.