Design And Implementation Of Image Compression Based On JPEG 2000 AND SOM Techniques

Abstract

Telemedicine is the practice of providing therapeutic services to patients remotely through newlinethe use of electronic systems that enable two-way, real-time contact between patients and newlinemedical professionals. Telemedicine often takes the form of a phone call. This occurs when a newlinepatient calls their primary care physician for advice on non-urgent medical issues that do not newlinerequire the doctor to see the patient in person. Telemedicine is used to supplement in-person newlineconsultations rather than taking their place where it is clinically warranted. An interface newlinebetween the hardware, software, and a communication channel is what makes up the newlineTelemedicine system. The ultimate goal of the system is to bridge the gap between two newlinegeographical sites in order to share information. The improvements in information and newlinetechnology that have taken place recently have made it possible to handle medical newlineinformation in more effective ways. Digital images are one of the most essential components newlineinside that data, which is utilised for a variety of purposes including surgical and diagnostic newlineplans. This data is produced by hospitals and medical facilities, which generate a great newlinequantity of data. Patients and medical professionals alike can benefit tremendously from the newlinestraightforward nature of storing and sharing digital medical photos. Since there are so many newlineimages, it is important to compress them in order to reduce the inherent redundancy of the newlineimage and present it in a more condensed form. This is done in hopes of facilitating the newlineeffective transmission as well as storage of images. For this study, a high-resolution chest Xray newlineimage from NIH Chest X-ray Dataset on Kaggle and a leg fracture image are taken newlineas input and then image compression operation was performed using Self-organizing Maps newline(SOM) algorithm at different bits per code vector, as well as JPEG 2000 technique. After newlineapplying above procedures, compressed image of various sizes is obtained along with their newlineperformance evaluation measures namely, MSE, RMSE, and PSNR. newline