Lossless data embedding -- new paradigm in digital watermarking
type: Item
instance of: scholarly article
title: Lossless data embedding -- new paradigm in digital watermarking
zbMATH Open document ID: 1001.68910
DOI: 10.1155/S1110865702000537
author: Jessica Fridrich
author: Miroslav Goljan
author: Rui Du
published in: EURASIP Journal on Applied Signal Processing
publication date: 2002-08-12T00:00:00Z
review text: Summary: One common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small and perceptual models are used to minimize its visibility, the distortion may not be acceptable for medical imagery (for legal reasons) or for military images inspected under nonstandard viewing conditions (after enhancement or extreme zoom). In this paper, we introduce a new paradigm for data embedding in images (lossless data embedding) that has the property that the distortion due to embedding can be completely removed from the watermarked image after the embedded data has been extracted. We present lossless embedding methods for the uncompressed formats (BMP, TIFF) and for the JPEG format. We also show how the concept of lossless data embedding can be used as a powerful tool to achieve a variety of nontrivial tasks, including lossless authentication using fragile watermarks, steganalysis of LSB embedding, and distortion-free robust watermarking.
Mathematics Subject Classification ID: 68U99
Mathematics Subject Classification ID: 68U10
Mathematics Subject Classification ID: 68P25
zbMATH DE Number: 1779613
zbMATH Keywords: steganography
zbMATH Keywords: watermarked image
zbMATH Keywords: robust watermarking
MaRDI profile type: Publication
full work available at URL: s1110865702000537
OpenAlex ID: W2123218196
description: scientific article; zbMATH DE number 1779613