Abstract

In this paper, a new technique for storing medical images securely in cloud environments for telemedicine applications by implementing the CS-based method is suggested. The main problem here lies in the development of a compression algorithm that can provide minimal storage needs while maintaining the good quality of the images used for making diagnoses. The proposed method uses a combination of data encryption together with compression based on the CS approach, with the application of dictionary coding, sparse reconstruction, and lossy compression of images. The results of the experiments indicate substantial superiority of the suggested method over the conventional image compression algorithms like JPEG and JPEG2000, demonstrating compression 2ratios (CR) between 1.166 and 1.703 and high peak signal-to-noise ratios (PSNR) compared to JPEG's 38.522 dB (40.322 dB). Furthermore, the method under consideration is characterized by high-security properties, which include NPCR = 99.8% and UACI = 34%. This guarantees the safety of encryption even in the case when keys differ from each other. Besides, the proposed technique proves to be quite efficient in terms of runtime, where the client side requires 120 ms to perform, while the cloud side needs 300 ms. The research findings prove that the suggested approach can be applied successfully in the field of telemedicine, providing an ideal trade-off between compressibility and security. Further work may involve improving the computational efficiency of the algorithm, along with widening its applicability to other medical imaging applications.