PROBABILISTIC RUN-LENGTH ENCODING FOR EFFICIENT MEDICAL IMAGE COMPRESSION USING VLSI ENVIRONMENT
Dr. K. Radhika, Sk. Ayisha, C.Abhinaya C.Abhinaya, Sk.Noorulla Sk.Noorulla, T.Manjula T.Manjula · Journal of Emerging Technologies and Innovative Research · 2025
— Images are one of the most widely used forms of data representation. As a result, organizations and individuals often need to store and share vast quantities of images. However, one major challenge is the potentially large file size of digital images. With advancements in image acquisition technologies and the growing demand for high-quality, high-resolution images, file sizes have increased significantly. Consequently, image compression has become an essential aspect of image processing. The primary goal of image compression is to reduce the file size as much as possible without sacrificing image quality, achieving an optimal balance. Various compression techniques have been developed to meet this goal, but the "best" method often depends on the specific characteristics of the image being compressed. This paper focuses on converting images into binary format and applying the Run-Length Encoding (RLE) algorithm for compressing binary images. While RLE is a simple and effective compression method.