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@article{166498,
        author = {Mrs. D.JENI JEBA SEELI and Dr.K.K.Thanammal},
        title = {Analytical Study of Hybrid Techniques for Image Compression and Decompression },
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {2},
        pages = {985-988},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=166498},
        abstract = {Due to its ability to facilitate cloud-based medical and diagnostic data interchange, telemedicine has grown in importance among healthcare facilities, hospitals, and research organizations. Transmitting medical data over channels with constrained bandwidth might be laborious due to the volume of data generated by IoT. Thus, before being transmitted, information needs to be compressed. Currently available techniques compress data greatly, however the resulting restored data quality is very poor. It is crucial to achieve the appropriate quality because images and data are crucial for clinical and diagnostic purposes. In order to preserve both the efficiency of the compression and the desired quality of the returned information, this work aims to provide a hybrid medical information compression technique. This work attempts to demonstrate the value of the hybrid medical image compression method for raising the standard of the medical image while simultaneously offering effective compression ratios. Both the increased security of asymmetric algorithms and the speed and simplicity of symmetric algorithms are incorporated into the hybrid approach.},
        keywords = {Hybrid Compression, Medical Image, Lossy Compression, Lossless Compression},
        month = {July},
        }