Retinal Image Enhancement Based on Contrast, Luminosity Adjustment and MSC
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.