Selective Image Encryption of Medical Images Based on Threshold Entropy and Arnold Cat Map
Kiran Kiran · Bioscience Biotechnology Research Communications · 2020
In medical image applications, selective image encryption plays an important role as it reduces computational cost and time.Lot of existing full image encryption algorithms may be more complex and uses traditional techniques.Effective method has been developed for protection of medical images.Combination of threshold entropy and Arnold Cat Map (ACM) are used in the algorithm to encrypt only selected part of medical image.Threshold entropy value used for separating the significant and insignificant blocks in the original image.In order to reduce the blocking artifacts after the partition of medical image, neglect the insignificant pixels present in the image sub blocks based on the thresholding of Lower four binary planes.At last Least significant Bit (LSB) embedding algorithm employed to achieve lossless encryption.The proposed technique is achieves the low computational complexity and also fast execution time.