An Analysis of the Effectiveness of Different Image Compression Methods

Image compression presents compelling solutions across various domains, including image analysis, biomedical image processing, and wireless systems, emerging as a pivotal application in today's digital landscape. Its significance is particularly pronounced in the efficient transmission and storage of large data images in diverse applications such as big data and medical fields. Amidst these applications, Dynamic Magnetic Resonance Imaging (MRI) has garnered increasing attention due to its exclusive soft tissue contrast and diagnostic capabilities using magnetic and radio waves, avoiding X-ray radiations and producing detailed 3D anatomical images. This survey delves into the realm of image compression, specifically focusing on dynamic MRI images. The goal is to provide a comprehensive overview of different image compression schemes, aiming to design an efficient compression system tailored for dynamic MRI images. The paper explores various compression schemes, ranging from standalone implementations to hybrids incorporating two or more algorithms. Additionally, the author presents a comparative analysis of these surveyed compression schemes, paving the way for future research endeavors in the domain of image compression for dynamic MRI images.