Quality analysis of distributed max-plus algebra based morphological wavelet transform

Abstract

This proposed technique employs a disseminated data embedding watermarking strategy that is based on a morphological wavelet transform and uses Max-plus algebra to achieve high image quality, big data capacity, and reasonable operational cost. Previously, we had to use a simple MMT watermarking methodology and estimated that using image quality parameters, primarily considering the diagonal component (HH). For embedding watermarks after the decomposition process carried through MMT, the presented distributed data embedding strategy, however, emphasises on middle frequency signal-groups. We have used hypothesized watermarking technique to process five benchmark images during the experiments to examine the scheme’s capability. The PSNR and the SSIM values are elevated by the proposed approach. The combined (high and low) frequency’s PSNR value is preferable towards the high frequency’s. It is also remarked that the middle-frequency SSIM value is higher than the high-frequency value.