Retinal Image Enhancement based on Contrast, Luminosity Adjustment and MSC
A. Anilet Bala1, Pranav Pranshu Kanwar2, Shipra Das3, Debottama Das4
1A. Anilet Bala, Assistant Professor, Department of Electronics and Communication, SRM Institute of Science and Technology, SRM University, Kattankulathur, Chennai (Tamil Nadu), India.
2Pranav Pranshu Kanwar, UG Scholar, Department of Electronics and Communication, SRM Institute of Science and Technology, SRM University, Kattankulathur, Chennai (Tamil Nadu), India.
3Shipra Das, UG Scholar, Department of Electronics and Communication, SRM Institute of Science and Technology, SRM University, Kattankulathur, Chennai (Tamil Nadu), India.
4Debottama Das, UG Scholar, Department of Electronics and Communication, SRM Institute of Science and Technology, SRM University, Kattankulathur, Chennai (Tamil Nadu), India.
Manuscript received on 04 June 2019 | Revised Manuscript received on 29 June 2019 | Manuscript Published on 04 July 2019 | PP: 538-541 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A10990681S419/2019©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: Retinal images have been widely used by ophthalmologists for detecting the retinal diseases before-hand and diagnosing them suitably. Old age macular degeneration, diabetic retinopathy and glaucoma are some examples of these diseases. However, poor quality of the image due to inadvertent circumstances limits the ability of the ophthalmologists to study the image. This paper hereby proposes an algorithm that is used to obtain clearer images by performing contrast and luminosity adjustment that enhances the basic quality of the clicked image. Following this, Multi-dictionary Sparse Coding (MSC) is carried out on the image to obtain the retinal vessel structures and miniscule details. Amount of Image enhancement is calculated by measuring the improvement after each stage of operation on the image. The image’s quality is found to be much better compared to the other methods and thus can be suggested to the ophthalmologists for conducting the further medical studies conveniently.
Keywords: Retinal Image Enhancement, Multi-Dictionary Sparse Coding (MSC), Contrast-Luminosity Adjustment, Dictionary Learning, Sparse Coding.
Scope of the Article: Image Security