Gaussian Iterated Map-Lyrebird Optimization Algorithm (GIM-LOA) and SPIHT Encoding Based Blind Dual Watermarking Scheme for Image

A prominent area of study in digital Multimediaresearch is the Digital Watermarking (DWM) method, which has shown promise as a copyright protection tool. Blind watermarking schema and non-blind Water mark schema are the two classifications under which watermarking algorithms fall. The dual blind WaterMark (WM) technique in this work employs the Stucki Kernel halftone (SKH) algorithm, Set Partitioning in Hierarchical Trees (SPIHT), and selfrecoveries in images to detect tampering. and the Gaussian Iterated Map-Lyrebird Optimization Algorithm (GIM-LOA). SPHIT is used to rebuild the image. SPHIT can produce a bitstreams at desired rates including coefficientsof Wavelet Transforms. In the event that the received bit stream is interrupted, sound progressive transmission can be used to reconstruct the image. GIM-LOA is introduced for watermark bit mapping in an iteration-based method, utilizing its members' searching skills in water embedding. Each lyrebird, as a member of the LOA, determines the values of the Watermark bits according to its bit position. Updating the optimal bit solution should also be made easier by comparing the Objective Function (OF) values and authentication bit are generated using recovery bits prior to inserting the watermark, shuffle the WM components using GIM-LOA and Arnold Cat Mapping (ACM) and thus improving security and quality of the image recovery. The suggested algorithm performs better than current methods in terms of many statistical metrics and security elements of Tampering Detection (TD) techniques, and it is protected against various attacks.