Non-Invasive Contrast Normalisation and Denosing Technique for the Retinal Fundus Image

Toufique Ahmed Soomro () and Junbin Gao
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Toufique Ahmed Soomro: Charles Sturt University
Junbin Gao: The University of Sydney Business School, The University of Sydney

Annals of Data Science, 2016, vol. 3, issue 3, No 3, 265-279

Abstract: Abstract Diabetic retinopathy (DR) causes vision loss insufficiency due to impediment rising from high sugar level conditions disturbing the retina. The progression of DR occurs in the foveal avascular zone due to loss of tiny blood vessels of the capillary network. Due to image acquisition process of the fundus camera, the colour retinal fundus image suffers from varying contrast and noise problems, varying contrast and noise problem in fundus image can be overcome. The technique has been implemented. The technique is based on the Retinex algorithm along with stationary wavelet transform. The technique has been applied on 36 high-resolution fundus image database contain the 18 bad quality images and 18 good quality images. The RETinex and stationary wavelet transform (RETSWT) is developed with the denoising technique Based on stationary wavelet transform. RETSWT achieves an average PSNR improvement of 2.39 dB the contrast improvement factor of 5.5 for good quality images while it achieves an average PSNR improvement of 2.20 dB for bad quality images with contrast improvement factor of 5.31. The RETSWT image enhancement method potentially reduces the need for the invasive fluorescein angiogram in DR assessment.

Keywords: Eye related disease; Image enhancement; Contrast; PSNR (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s40745-016-0079-7

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