{"title":"Haar Wavelet Transform and Multiobjective Cost Function for Video Watermarking","authors":"A. U. Wagdarikar","doi":"10.46253/j.mr.v2i4.a4","DOIUrl":null,"url":null,"abstract":"Generally, Watermarking is the process of hiding the concealed message into multimedia sources, like image, video and audio. Video watermarking is mostly concentrated in the robustness of the system rather than other steganography. In this paper, the multiobjective cost function is proposed for video watermarking. At first, the cover image (video frame) is subjected into cost function computation. Subsequently, the cost function is recently proposed and modeled by various constraints, like energy, intensity, coverage, edge, as well as brightness. Then, the Haar Wavelet Transform is applied to the original frame, which attains a wavelet coefficient on the basis of the video frame. Concurrently, by exploiting the bit plane technique the concealed message is partitioned into binary images. In the embedding phase, the message bit is embedded into the wavelet coefficients according to the cost value. The concealed message is retrieved in the extraction phase. At last, the simulation results are examined, and performance is evaluated by exploiting metrics like Peak Signal Noise Ratio (PSNR) and correlation coefficients.","PeriodicalId":167187,"journal":{"name":"Multimedia Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimedia Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46253/j.mr.v2i4.a4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Generally, Watermarking is the process of hiding the concealed message into multimedia sources, like image, video and audio. Video watermarking is mostly concentrated in the robustness of the system rather than other steganography. In this paper, the multiobjective cost function is proposed for video watermarking. At first, the cover image (video frame) is subjected into cost function computation. Subsequently, the cost function is recently proposed and modeled by various constraints, like energy, intensity, coverage, edge, as well as brightness. Then, the Haar Wavelet Transform is applied to the original frame, which attains a wavelet coefficient on the basis of the video frame. Concurrently, by exploiting the bit plane technique the concealed message is partitioned into binary images. In the embedding phase, the message bit is embedded into the wavelet coefficients according to the cost value. The concealed message is retrieved in the extraction phase. At last, the simulation results are examined, and performance is evaluated by exploiting metrics like Peak Signal Noise Ratio (PSNR) and correlation coefficients.