Diabetic Retinopathy (DR) is a major cause of blindness in diabetic patients. The
increasing population of diabetic patients and difficulty to diagnose it at an early stage are limiting
the screening capabilities of manual diagnosis by ophthalmologists. Color fundus images are
widely used to detect DR lesions due to their comfortable, cost-effective and non-invasive acquisition
procedure. Computer Aided Diagnosis (CAD) of DR based on these images can assist ophthalmologists
and help in saving many sight years of diabetic patients. In a CAD system, preprocessing
is a crucial phase, which significantly affects its performance. Commonly used preprocessing
operations are the enhancement of poor contrast, balancing the illumination imbalance due to
the spherical shape of a retina, noise reduction, image resizing to support multi-resolution, color
normalization, extraction of a field of view (FOV), etc. Also, the presence of blood vessels and optic
discs makes the lesion detection more challenging because these two artifacts exhibit specific
attributes, which are similar to those of DR lesions. Preprocessing operations can be broadly
divided into three categories: 1) fixing the native defects, 2) segmentation of blood vessels, and 3)
localization and segmentation of optic discs. This paper presents a review of the state-of-the-art
preprocessing techniques related to three categories of operations, highlighting their significant aspects
and limitations. The survey is concluded with the most effective preprocessing methods,
which have been shown to improve the accuracy and efficiency of the CAD systems.
