Abstract
Recently, medical color images significantly affect the efficient diagnosis process and investigation of critical diseases besides mitigating the misdiagnosis problems. Surplus, the theft problem of medical identity and information has been a severe privacy apprehension in the healthcare realm. This paper introduces an efficient digital multi-level security system for medical color images based on fusion, watermarking, and encryption techniques through utilizing singular value decomposition (SVD), discrete wavelet transform (DWT), chaotic encryption process, and wavelet-based fusion algorithm. The fundamental concept of the suggested system is to isolate the three RGB color components of the medical image. Afterward, a fusion process is introduced to fuse every separated color component with a grayscale image. After that, every fused image is encrypted with a chaotic encryption scheme. Finally, the SVD and DWT are utilized to embed the resulting three encrypted fused images into the three RGB components of the original (host) medical color image to obtain the watermarked medical color image. Thus, the proposed system can effectively distribute medical data amongst two different remote organizations in smart telemedicine systems. The performance evaluation of the suggested system is examined by numerous color medical images and diverse severe attacking scenarios on the transmitted medical color images. The simulation tests reveal that the watermarked medical color images resulted from the suggested system are robust against channel assaults like a blur, Gaussian, compression, wrap, cropping, and rotation. Also, the simulation outcomes verified that the suggested system could recognize the recovered watermarks although the presence of different multimedia attacks on the watermarked images. More tests and outcomes prove that the suggested security system is adequate and robust against channel attacks contrasted with previous security systems. The suggested security system achieves high PSNR values and superior quality results. Also, it introduces high correlation outcomes in the presence of channel attacks and provides less computational processing time.