LBP Based Watermarked Image Resolution Enhancement


Authors : Harit Kumar Pandey, Abhishek Saxena.

Volume/Issue : Volume 3 - 2018, Issue 6 - June

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/ZUdVfQ

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

In this paper we use a watermark pattern of the fragile image with recovery capacity based on the local binary model (LBP). The local binary pattern operator used to remove confined spatial characteristics. A local binary model is utilized to speak to the restricted connections of a pixel with its neighborhood pixels.Every pixel estimated by the LBP administrator acquires its own particular neighborhood twofold model as a portrayal of nearby spatial relationships. We use the LBP administrator to create integrated authentication data in each 3 × 3 pixel image block for the detection and restoration of the alteration. The retrieval data is gotten by ascertaining the average value of each picture block and then the average value is changed over into a paired string that is embedded in eight adjacent LSB pixels of each picture obstruct for picture. On paper we consider the contribution as 256 × 256 and the image size 1024 × 1024, one of the advantages over other existing systems is that it can also process the image in color. The quality is figured utilizing the PSNR, yet in the proposed plot, the PSNR at the pinnacle point is additionally computed to get a superior outcome.

Keywords : Authentication, signal, noise, information hiding, integrity, Local Binary Pattern (LBP),PSNR (Peak Signal to Noise Ratio).

CALL FOR PAPERS


Paper Submission Last Date
30 - April - 2024

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe