Zhenxing Qian

Reference Sharing Mechanism for Watermark Self-Embedding

This paper proposes two novel self-embedding watermarking schemes based upon a reference sharing mechanism, in which the watermark to be embedded is a reference derived from the original principal content in different regions and shared by these regions for content restoration. After identifying tampered blocks, both the reference data and the original content in the reserved area are used to recover the principal content in the tampered area. By using the first scheme, the original data in five most significant bit layers of a cover image can be recovered and the original watermarked image can also be retrieved when the content replacement is not too extensive. In the second scheme, the host content is decomposed into three levels, and the reference sharing methods with different restoration capabilities are employed to protect the data at different levels. Therefore, the lower the tampering rate, the more levels of content data are recovered, and the better the quality of restored results.

Watermarking With Flexible Self-Recovery Quality Based on Compressive Sensing and Compositive Reconstruction

This paper proposes a novel watermarking scheme with flexible self-recovery quality. The embedded watermark data for content recovery are calculated from the original discrete cosine transform (DCT) coefficients of host image and do not contain any additional redundancy. When a part of a watermarked image is tampered, the watermark data in the area without any modification still can be extracted. If the amount of extracted data is large, we can reconstruct the original coefficients in the tampered area according to the constraints given by the extracted data. Otherwise, we may employ a compressive sensing technique to retrieve the coefficients by exploiting the sparseness in the DCT domain. This way, all the extracted watermark data contribute to the content recovery. The smaller the tampered area, the more available watermark data will result in a better quality of recovered content. It is also shown that the proposed scheme outperforms previous techniques in general.

Reversible Data Hiding in Encrypted JPEG Bitstream

This correspondence proposes a framework of reversible data hiding (RDH) in an encrypted JPEG bitstream. Unlike existing RDH methods for encrypted spatial-domain images, the proposed method aims at encrypting a JPEG bitstream into a properly organized structure, and embedding a secret message into the encrypted bitstream by slightly modifying the JPEG stream. We identify usable bits suitable for data hiding so that the encrypted bitstream carrying secret data can be correctly decoded. The secret message bits are encoded with error correction codes to achieve a perfect data extraction and image recovery. The encryption and embedding are controlled by encryption and embedding keys respectively. If a receiver has both keys, the secret bits can be extracted by analyzing the blocking artifacts of the neighboring blocks, and the original bitstream perfectly recovered. In case the receiver only has the encryption key, he/she can still decode the bitstream to obtain the image with good quality without extracting the hidden data.

Image self-embedding with high-quality restoration capability

In this paper, we present a new fragile watermarking method aimed at providing improved restoration capability. A mechanism of block classification is used to compress the original image according to the DCT coefficients, in which blocks corresponding to different types are encoded to variable lengths. The compressed bits are expanded as reference bits, and then embedded into the entire image along with some authentication bits generated from each block. On the receiving side, the authentication bits are extracted to localize the tampered areas, and the reference bits are used to reconstruct a reference image for restoring the contents of the tampered regions. Results show that the proposed method provides a better restoration quality.

Efficient reversible data hiding in encrypted images

This paper proposes a novel scheme of reversible data hiding in encrypted images based on lossless compression of encrypted data. In encryption phase, a stream cipher is used to mask the original content. Then, a data hider compresses a part of encrypted data in the cipher-text image using LDPC code, and inserts the compressed data as well as the additional data into the part of encrypted data itself using efficient embedding method. Since the majority of encrypted data are kept unchanged, the quality of directly decrypted image is satisfactory. A receiver with the data-hiding key can successfully extract the additional data and the compressed data. By exploiting the compressed data and the side information provided by the unchanged data, the receiver can further recover the original plaintext image without any error. Experimental result shows that the proposed scheme significantly outperforms the previous approaches.

Reversible Data Hiding in Encrypted Images With Distributed Source Encoding

This paper proposes a novel scheme of reversible data hiding in encrypted images using distributed source coding. After the original image is encrypted by the content owner using a stream cipher, the data-hider compresses a series of selected bits taken from the encrypted image to make room for the secret data. The selected bit series is Slepian-Wolf encoded using low-density parity check codes. On the receiver side, the secret bits can be extracted if the image receiver has the embedding key only. In case the receiver has the encryption key only, he/she can recover the original image approximately with high quality using an image estimation algorithm. If the receiver has both the embedding and encryption keys, he/she can extract the secret data and perfectly recover the original image using the distributed source decoding. The proposed method outperforms the previously published ones.

Reversible fragile watermarking for locating tampered blocks in JPEG images

This paper proposes a novel fragile watermarking scheme for JPEG image authentication. The watermark is generated by folding the hash results of quantized coefficients, and each block is used to carry two watermark bits using a reversible data-hiding method. Because modification to the cover is small, the visual quality of watermarked image is satisfactory. On the receiver side, one may attempt to extract the watermark and recover the original content. By measuring mismatch between the watermark data extracted from the received image and derived from the recovered content, the blocks containing fake content can be located accurately, while the original information in the other blocks is retrieved without any error as long as the tampered area is not extensive.

Scalable Coding of Encrypted Images

Recent studies have shown that sparse representation can be used effectively as a prior in linear inverse problems. However, in many multiscale bases (e.g., wavelets), signals of interest (e.g., piecewise-smooth signals) not only have few significant coefficients, but also those significant coefficients are well-organized in trees. We propose to exploit this, named sparse-tree, prior for linear inverse problems with limited numbers of measurements. In particular, we present the tree-based majorize-maximize (TMM) algorithm for signal reconstruction in this setting. Our numerical results show that TMM provides significantly better reconstruction quality compared to the majorize-maximize (MM) algorithm that relies only on the sparse prior.This paper proposes a novel scheme of scalable coding for encrypted images. In the encryption phase, the original pixel values are masked by a modulo-256 addition with pseudorandom numbers that are derived from a secret key. After decomposing the encrypted data into a downsampled subimage and several data sets with a multiple-resolution construction, an encoder quantizes the subimage and the Hadamard coefficients of each data set to reduce the data amount. Then, the data of quantized subimage and coefficients are regarded as a set of bitstreams. At the receiver side, while a subimage is decrypted to provide the rough information of the original content, the quantized coefficients can be used to reconstruct the detailed content with an iteratively updating procedure. Because of the hierarchical coding mechanism, the principal original content with higher resolution can be reconstructed when more bitstreams are received.

Compressing Encrypted Image Using Compressive Sensing

This work proposes a novel scheme of compressing and decompressing encrypted image based on compressive sensing. An original image is encrypted as a set of coefficients by a secret orthogonal transform. Since the image has sparse representation in conventional transform domain and can be recovered from a small quantity of measurements, the encrypted image data are compressed into a series of measurement data. Using signal recovery method of compressive sensing, a receiver can reconstruct the principal content of original image. This way, the quality of reconstructed image is dependent on the compression rate and the smoothness of original content.

Self-embedding watermark with flexible restoration quality

A novel self-embedding watermarking scheme is proposed, in which the reference data derived from the most significant bits (MSB) of host image and the localization data derived from MSB and reference data are embedded into the least significant bits (LSB) of the cover. At authentication side, while the localization data are used to detect the blocks containing substitute information, the reference data extracted from other regions and the spatial correlation are exploited to recover the principal content in tampered area by a pixel-by-pixel manner. In this scheme, the narrower the tampered area is, the higher quality of recovered content can be obtained.