Histogram-based near-lossless data hiding and its application to image compression

Abstract

This paper proposes a near-lossless data hiding (DH) method for images where the proposed method can improve the image compression efficiency. The proposed method firstly quantizes an image in accordance with a user-given maximum allowed error. This method, then, embeds data to the quantized image based on histogram shifting (HS). Even this method uses HS-based DH which requires to memorize the shifted bins for data extraction, the method, under some conditions, takes data out from the marked image by just applying re-quantization as least significant bitplane (LSB) substitution-based DH. So the proposed method is based on unification of HS- and LSB substitution-based DH. In the method, lossless compression of the marked image can achieve better compression efficiency than lossy compression of the original image. Experimental results show the effectiveness of the proposed method.