# An Adaptive Reversible Data Hiding Scheme Using AMBTC and Quantization Level Difference  
[PERSON]  
1 School of Information, Zhejiang University of Finance & Economics, Hangzhou 310018, China; [EMAIL_ADDRESS]  
[PERSON]  
2 Department of Computer Science and Information Engineering, Feng Chia University, Taichung 407032, Taiwan; [EMAIL_ADDRESS] (C.-C.C.); [EMAIL_ADDRESS] (Z.-M.W.)  
[PERSON]  
4 Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan 41170,  
compressed images and an index mapping mechanism. [PERSON] et al. [6] proposed a data hiding method based on DWT. Their method hides a secret image inside a cover image by using two secret keys. [PERSON] [11] et al. proposed a scheme to hide the secret information in the DCT coefficient domain. In this scheme, the image is divided into 8 \(\times\) 8 blocks, where if two successive coefficients of the medium-frequency components are zero, the information is hidden in each block.  
Block truncation coding (BTC) [12] is another efficient lossy block-based image compression technique. In recent years, many researchers have studied data hiding based on BTC and made improvements, such as absolute block truncation coding (AMBTC) [13], ordered dither block truncation coding (ODBTC) [14], error Diffusion Block truncation coding (EDBTC) [15], etc. BTC is characterized by low complexity and low memory, and thus it has become an ideal data hiding domain. [PERSON] and [PERSON] [16] presented a data hiding method in which each secret bit is embedded into the bitmap of the BTC compression codes. [PERSON] [17] proposed a data hiding method for halftone compressed images based on ODBTC and exploiting modification direction (EMD). [PERSON] et al. [18] introduced a data hiding scheme based on error-diffused BTC to embed an extremely large amount of watermarks without obviously damaging image quality. These methods are irreversible, and the host image is permanently altered and it cannot be recovered accurately after data extraction. However, in some applications such as medical image sharing, military image processing, remote sensing and multimedia archive management, the recovery of a host image is essential [19]. To address this problem, a reversible data hiding scheme [20] were proposed that can extract the hidden data and produce a lossless recovery of the cover image. As [PERSON] et al. mentioned [1], the key property of reversible data hiding is not only the secret data but also the host image can be accurately recovered in the recorder.  
In 2008, [PERSON] et al. [21] presented a reversible data hiding method aimed at BTC-compressed color images. In 2011, [PERSON] et al. [22] introduced a reversible image hiding based on the BTC-compressed approach. In this scheme, the histogram shifting and bitmap flipping technique were used to hide secret bits. In 2013, [PERSON] et al. [23] introduced another reversible data hiding method for BTC-compressed using the joint neighbor coding technique. In 2015, [PERSON] et al. [24] presented a reversible data hiding scheme for AMBTC-compressed images by combining secret bits with bitmap bits one by one.  
In this paper, we propose an adaptive reversible data hiding scheme that is based on an AMBTC compression domain and quantization level difference. In this scheme, the cover image is compressed into corresponding quantizers and a bitmap image by absolute moment block truncation coding (AMBTC). Subsequently, a certain amount of the data bits will be embedded into this pixel according to the value of QLD. The rest of this paper consists of four sections: AMBTC's and [PERSON] et al.'s methods are introduced in Section 2; the proposed algorithm is illustrated in Section 3; detailed experimental description and comparative analysis are provided in Section 4; and finally, the conclusions are offered in Section 5.