Image data play important role in various real-time online and offline applications. Biomedical field has adopted the imaging system to detect, diagnose, and prevent several types of diseases and abnormalities. The biomedical imaging data contain huge information which requires huge storage space. Moreover, currently telemedicine and IoT based remote health monitoring systems are widely developed where data is transmitted from one place to another. Transmission of this type of huge data consumes more bandwidth. Along with this, during this transmission, the attackers can attack the communication channel and obtain the important and secret information. Hence, biomedical image compression and encryption are considered the solution to deal with these issues. Several techniques have been presented but achieving desired performance for combined module is a challenging task. Hence, in this work, a novel combined approach for image compression and encryption is developed. First, image compression scheme using wavelet transform is presented and later a cryptography scheme is presented using confusion and diffusion schemes. The outcome of the proposed approach is compared with various existing techniques. The experimental analysis shows that the proposed approach achieves better performance in terms of autocorrelation, histogram, information entropy, PSNR, MSE, and SSIM.

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