LWT-DCT-SVD and DWT-DCT-SVD based watermarking schemes with their performance enhancement using Jaya and Particle swarm optimization and comparison of results under various attacks

BacterialWmark: telemedicine watermarking technique using bacterial foraging for smart healthcare system

“…The overhead of the proposed technique increased due to the use of multiple keys and pseudovector generation. Reference 2 proposes a robust method by comparing two optimization techniques. Reference 3 proposes a medical image watermarking with its authentication using a feature extraction technique.…”

“…1 This type of medical data can be in any form, such as audio, video, and image. 2 Copyright protection of these data is the need of the hour. Watermarking is one of the methods to protect the copyright of critical medical information.…”

“…Other radiologists and medical professionals in the same area exchange this information for clinical evaluation 1 . This type of medical data can be in any form, such as audio, video, and image 2 . Copyright protection of these data is the need of the hour.…”

Robust, imperceptible and optimized watermarking of DICOM image using Schur decomposition, LWT-DCT-SVD and its authentication using SURF

“…The discrete cosine transform coefficient has only real values, unlike the discrete Fourier transform. DCT has the ability to compress an image’s pixels information into a small number of DCT coefficient values, resulting in data consolidation into less values [ 7 ]. The 2D DCT and inverse DCT of an N × N image are defined as shown in Eq.…”

“… Singular value decomposition (SVD), Genetic algorithm (GA) Host image of size 256 × 256: Lena; Watermark image of size: 32 × 32 (grey-level) Correlation coefficient (CC), PSNR Rotation, Average filter, Scaling, Gaussian noise, Gamma correction, Histogram, Median filter In the proposed method, GA is utilized to obtain multiple scaling factors (SF) for achieving the highest possible robustness without degrading image quality. [ 7 ] This paper provides a comparison between PSO and JAYA as well as between LWT and DWT LWT, DWT, DCT, SVD, PSO, JAYA Host grayscale image: 512 × 512; Watermark grayscale: 256 × 256 PSNR, SSIM, Normalized correlation coefficient (NCC), Mean square error (MSE) JPEG compression, Gaussian noise, Median filter, Salt and Pepper, Low pass filter, Sharpening, Gamma correction, Scaling, Translation The proposed work has been tested under different attacks and found robust and imperceptible. [ 8 ] To improve the watermarked image’s integrity and perceived quality and to enhance the security of watermarking DWT, SVD, Quantization, Shore, Lena, Baboon, Pepper, Dark cloud: 200 × 200 PSNR, Bit error rate (BER) JPEG compression, Gaussian noise, Median filter, Cropping The enhanced perceptual quality of the watermarked images and the proposed scheme preserve high PSNR.…”