Reversible Data Hiding in Color Image With Grayscale Invariance

Different from all the previous reversible data hiding schemes, a completely novel one for the color image is proposed, which reversibly embeds messages into the color host image without modifying its corresponding gray version. The property of grayscale invariance is valuable, because many applications and image processing algorithms for color images are based on the corresponding gray versions, such as black and white printing, producing reading materials for color blind people, single-channel image processing, and so on. Thus, in terms of these applications and image processing algorithms, the presented scheme will make the generated color marked image be free for its further uses. In this paper, the unchanged gray version is utilized efficiently in both the embedding processes and the extracting processes. Messages are embedded into the red and blue channels of color image, and then the green channel is adjusted adaptively to remove the offsets from the gray version caused by modifying its red and blue channels. To return the adjusted green channel, error correcting bits guaranteeing the reversibility are regarded as one part of payloads to be recursively embedded. Therefore, the reversibility and the property of grayscale invariance are both achieved.

I. Introduction

Data hiding embeds messages into digital multimedia such as image, audio, video etc through an imperceptible way. Such technology plays the important role in protecting the privacy, which can be roundly classified as robust watermarking [1] having the ability to resist many attacks, fragile watermarking [2], [3] being fragile to any modifications, and steganography [4] with the strong undetectability. From the application side, robust watermarking, steganography and fragile watermarking are mainly used for copyright protection, covert communication and integrity authentication respectively. A review of data hiding techniques and a few emerging innovative solutions using data hiding are well introduced in [5].