AN EFFICIENT IMAGE COMPRESSIONS COMPARATIVE ANALYSIS FOR FUNDUS IMAGES

Image compression approaches are used for images that are not easy to analyze or are not able to compress in efficient manner. Such robust algorithms are particularly significant for systems conveying and archiving necessary information or statistics, because the compression of fundus images is necessary to gather the medical data about the patient's health. So this paper deals with the comparative analysis of four efficient image compression techniques named as discrete wavelet transform (DWT), Adaptive dictionary algorithms, Super spatial prediction and Chain codes. The image compression comparison is done in terms of peak signal to noise ratio and mean square error rate which are used to check the robustness of compressing the fundus images and shows that which is the most efficient for the compressions. The whole scenario is implemented using MATLAB 2016a environment