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Due to the fast development of communication networks and digital technologies, several multimedia data are developed and transmitted over the networks (Hanis and Amutha 2018). In addition, the technologies like tele-radiology, tele-surgery and tele-medicine are enormously created for clinical usage. The patient information is exposed to network transmission with the aforementioned technologies. Particularly, medical images like X-ray, Computerized Tomography (CT), and Magnetic Resonance Imaging (MRI) with higher redundancy, data storage and pixel correction are tampered and attacked easily by unauthorized users. So, protecting the information from the unauthorized person is a primary objective that leads to the development of several data encryption algorithms. Usually, the encryption algorithms are categorized into two types such as transform domain encryption algorithms and spatial domain encryption algorithms (Hua and Zhou 2016; Duseja and Deshmukh 2019). Due to the intrinsic properties of digital image such as high information redundancy, high data capacity and strong inter-pixel correlation, the conventional encryption algorithms are ineffective in image encryption (Tong et al. 2016; Lv et al. 2018; Gupta et al. 2019). Additionally, multimedia based applications like commercial, military, medical, and political fields requires large bandwidth for data communication (Wang et al. 2019). So, the combination of compression and encryption is useful for real time applications, where the compression saves the bandwidth and the encryption protects the privacy of the data (Li and Lo 2017; Ge et al. 2019). However, the combination of image compression and encryption makes the operation difficult (Pavithra and Chandrasekaran 2021). The several researches are done on the joint operation of image compression and encryption to achieve better data transmission such as sine chaotification (Liu et al. 2019), 2 dimensional logistic adjusted sine map (Feng et al. 2019), Convolutional Neural Network (CNN) (Chen et al. 2019), cross-coupled chaotic maps (Patro et al. 2020), 5 dimensional chaotic map (Kaur et al. 2020), phase-truncated short-time fractional Fourier transform (Yu et al. 2020), Knuth–Durstenfeld algorithm (Wang et al. 2020), etc.
In the aforementioned algorithms, complexity and time consumption of the compression and encryption of the images are higher. So, the motivation of this research is to propose a hybrid algorithm for ensuring high security, fast speed, and a promising compression ratio for protecting the content of the image and to diminish the amount of data required for transmission. The major contributions of the research article are listed below;
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Initially, IWT is applied on the digital images: cameraman, Lena, circuit, Barbara, peppers, aerial, X-ray, CT, MRI medical images, etc. for data compression. The coefficients of IWT are similar to the input images, hence it is very easy to compress the images that significantly reduces complexity of the system.
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In addition, the Deoxyribonucleic Acid (DNA) and Hyperchaotic sequences are utilized to encrypt the images, and a Hybrid Hyperchaotic system (FOHCNN and FOFDMCC) is used to generate the pseudorandom sequences. The image pixel intensity value is transformed into serial binary digital streams and then the bit-streams are scramble by hyperchaotic sequence. The complementation and DNA algebraic sequence are applied between DNA and Hyperchaotic sequence to attain significant encryption performance.
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In the experimental segment, a few performance measures such as Number of Changing Pixel Rate (NPCR), Unified Averaged Changed Intensity (UACI), and correlation coefficient are utilized to analyze the performance of the proposed image compression and encryption model.
This research paper is prepared as follows; Section 2 reviews recent research papers on “image compression and encryption”. Section 3 details about the proposed model with mathematical expressions and the simulation result of the proposed model is denoted in the Section 4. Section 5 details about the conclusion of the research work.