Light-field enables us to observe scenes from free view-points. However, it generally consists of 4-D enormous data, which are not suitable for storing or transmitting without effective compression. Image acquisition, transmission, interpretation and visualization have witnessed a lot of research interest and have manifold applications in real life. Light field Images popularly known as Plenoptic Images are light rays travelling in every direction. The data sets generated using plenoptic images are large in size and consume a lot of storage space. This paper studies the general process of image acquisition, light field images and various datasets. Image compression will help the users or professionals to not only achieve storage efficiency but also aid in transmission of Images. In this paper, we study efficient compression of multi-focus images synthesized from dense light-field by using DWT instead of DCT-based compression in order to suppress degradation such as block noise. Quality of reconstructed light-field is evaluated by PSNR for analyzing characteristics of residuals. This paper presents the modeling, design and implementation of two IP cores that are compliant with the CCSDS 121.0-B-2 and CCSDS 123.0-B-1 lossless satellite image compression standards. This paper provides a comparative study of various image compression techniques/algorithms and evaluates them on parameters like peak signal to noise ratio (PSNR), mean square error (MSE), Structural Similarity Index (SSI) and compression ratio (CR). © 2020, Springer Science+Business Media, LLC, part of Springer Nature.