Secured Compression for 2D Medical Images Through the Manifold and Fuzzy Trapezoidal Correlation Function

Abstract

In biomedical imaging, the imaging of secured storage and maintaining medical images like MRI, CT, and ultrasound scans are challenging with ever-growing tremendous image data. This article has proposed a systematic approach for secured compression of the image data that would compress the image data at multiple levels at each instance that would substitute with a smaller size data block through dictionary mechanism. The resultant image is encrypted through a 256-bit symmetric key dynamically generated through the hashing-based technique for multiple rounds. In each round, a 16-bit key sequence obtained from the hashing-based technique is an integral part of the 256-bit key used in the encryption process, and the same key sequence is being used in the decryption phase. Finally, the resultant image is stored for future reference for further medical examinations. In reconstructing the original image, the same approach is performed in reverse order to get back the original image without any significant impact on the image standard through the Fuzzy Trapezoidal correlation method. The proposed mechanism is being practically implemented over the medical images, and the outcome seems to be very pleasing compared to the counterparts. It is observed on implementation. The medical images are compressed to 58% of their original size without significant impact on the quality of the image that is being reconstructed. The approximated entropy in the majority of the cases is less than zero has proven the proposed mechanism is robust for secured compression of the medical images for secured storage.

Keywords

• Lossless compression
• Image encryption
• Image decryption
• Fuzzy trapezoidal
• Correlation function

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