SimYing Ong

A Scalable Reversible Data Embedding Method with progressive quality degradation functionality

This paper proposes a novel reversible information hiding method aiming to achieve scalable carrier capacity while progressively distorting the image quality. Unlike the conventional methods, the proposed method HAM (Histogram Association Mapping) purposely degrades the perceptual quality of the input image through data embedding. To the best of our knowledge, there is no method that attempts to significantly increase the carrier capacity while introducing (tolerating) intentional perceptual degradation for avoiding unauthorized viewing. HAM eliminates the expensive pre-processing step(s) required by the conventional histogram shifting data embedding approach and improves its carrier capacity. In particular, the host image is divided into non-overlapping blocks and each block is classified into two classes. Each class undergoes different HAM process to embed the external data while distorting quality of the image to the desired level. Experiments were conducted to measure the performances of the proposed method by using standard test images and CalTech 101 dataset. In the best case scenario, an average of ~2.88 bits per pixel is achieved as the effective carrier capacity for the CalTech 101 dataset. The proposed method is also compared with the conventional methods in terms of carrier capacity and scalability in perceptual quality degradation.

Reversible Data Embedding Using Reflective Blocks with Scalable Visual Quality Degradation

In this paper, a reversible data hiding method with scalable visual quality degradation functionality is proposed. An image is first divided into blocks and each pixel in a block is associated with unique mirror value(s). The original pixel value is modified to its associated value(s) to encode external payload. A block is further categorized as reflective and non-reflective block, depending on the range of pixel values in it. The number of bits embedded into a block can be controlled to achieve different level of image quality degradation. To further intensify the distortion, pixels grouped in block of predefined size is permuted where scalability in quality degradation is achieved by changing the block size. Basic performance of the proposed method is verified through experiments using standard test images. In the best case scenario, an image can hold up to 2.26 bits per pixel of external payload.

Beyond format-compliant encryption for JPEG image

In this work, a format-compliant encryption method with the data embedding feature for JPEG compressed image is proposed. First, DC coefficients are encoded based on the regions induced by the textural information carried by AC coefficients. Second, AC coefficients are scanned in eight different orders and the order that results in the smallest bitstream size is selected. Next, AC coefficients from each block are extracted in the form of Run/Size and Value, and manipulated to significantly increase the scope of permutation. Then the virtual queue decomposition is proposed to embed external information. All the processes are completely reversible where the embedded information can be extracted and the original content can be perfectly reconstructed from its processed counterpart. The performance of the proposed method is verified through experiments using various standard test images and the UCID dataset. The proposed method is also compared against the conventional format-compliant encryption methods, where its superiority in terms of robustness against sketch attacks, suppression of bitstream size increment, and data embedding are highlighted. In the best case scenario, the proposed method is able to generate an encrypted image of the same size as the original image (e.g., 512×512) with more than 5800 bits of additionally embedded information while achieving a compression gain of 1%. HighlightsSignificantly increase the scope of permutation for DCT coefficients.Robust against sketch attacks.Offer extra feature of data embedding to format-compliant encryption.Design VQD (virtual queue decomposition) data representation scheme where carrier capacity can be increased without giving any impact to bitstream size.Design an adaptive scanning order to suppress the bitstream size increment.

Scrambling-embedding for JPEG compressed image

This paper proposes a novel reversible unified information hiding method for the JPEG compressed image, aiming to achieve scrambling and external data insertion simultaneously. The properties of DC coefficients, energy of AC coefficient block, and run of zero AC coefficients are exploited. Two techniques are proposed to degrade the perceptual quality while manipulating the DCT coefficients for data embedding. Most of the existing unified information hiding methods are designed to operate in the spatial domain and their direct application to the compressed domain such as JPEG will lead to large bitstream size increment. Thus, the proposed techniques aim to minimize the bitstream size increment while offering comparable performance with respect to the current state-of-the-art methods. Experiments are conducted to measure the performance of the proposed unified method by using the UCID (Uncompressed Color Image Database) database and standard test images. Results suggest that the effective data payload ranging from 32 to 10238 bits and SSIM value ranging from 0.0548 to 0.9432 are achieved for the UCID database. The proposed method are also compared with the conventional methods in terms of effective data payload, image quality degradation, bitstream size increment and robustness against multiple sketch attacks. HighlightsDegrade image quality while embedding external data in a JPEG compressed image under a single framework.Achieve scrambling-embedding using the properties derived from the components (i.e., DC coefficient and AC coefficient) of a JPEG compressed image.Minimize the bitstream size increment caused by scrambling-embedding, which is inevitable for the conventional methods.Achieve scalability in both image quality degradation and data payload.Achieve complete reversibility.

Progressive quality degradation in JPEG compressed image using DC block orientation with rewritable data embedding functionality

This paper proposes a novel block rotational method to degrade quality and embed external data in JPEG compressed image. The orientation of each non-overlapping DC coefficients block is exploited to embed information while introducing distortion. To achieve progressive quality degradation, size of DC coefficients block is manipulated and the proposed embedding process is applied recursively by shrinking block size in each iteration. Markers are added into the blocks as pre-processing steps to ensure that the original orientation always yields the smallest difference. A post-processing is also proposed to erase the marker introduced for recovering image at higher quality, making the proposed method a rewritable method but not complete reversible. Experiments are conducted to verify the basic performance of the proposed method and comparisons with the conventional methods are also carried out.

Rotational based rewritable data hiding in JPEG

This paper proposes a novel rotational method on AC coefficient pairs to embed data into a JPEG compressed image. The purpose is to improve the carrier capacity while maintaining its original feature in controlling quality degradation. The proposed method exploits two properties in the quantized AC coefficients, namely, large magnitude and short run of zeros for low frequency subbands, and vice versa. The coefficients are first grouped into pairs and then rotated to the left or right directions to create distinctive states, where each can be utilized to represent external data. The AC coefficients are not modified and no additional AC coefficients are introduced for data embedding. However, preprocessing is needed so that all blocks satisfy the properties assumed to ensure correct data extraction and image recovery. The proposed method is rewritable because the host image can be re-utilized without causing further distortion. Experiments were conducted to verify the basic performance of the proposed method. On average, the proposed method is able to embed up to ~9318 bits in the test images of quality factor 80.

Reversible data hiding by adaptive modification of prediction errors

Histogram Shifting (HS) is one of the most popular reversible data hiding techniques that has received tremendous attention from the research community in recent years. While histogram shifting offers many advantages, it suffers from relatively low payload, which restricts its applications significantly. In this work, a new reversible data hiding technique based on the modification of the histogram of prediction errors is proposed. The proposed method employs an adaptive strategy to vacate multiple bins as the embedding venues in order to increase the effective payload. The histogram bins are shifted dynamically based on their magnitudes. To maintain high quality for the output image, the distance of shifting is minimized for smaller prediction errors. On the other hand, the distance of shifting is allowed to be larger for larger prediction errors, which are of lower occurrences, to create more space for embedding. The proposed data hiding method is able to reversibly hide larger number of bits into the host image while achieving comparable output image quality when compared to the conventional histogram shifting based methods. The experimental results suggest that, on average, the proposed method is able to embed 0.247bpp into various standard test images, while still maintaining the visual quality at satisfactory level of ~48.9 dB.

Fast recovery of unknown coefficients in DCT-transformed images

Abstract The advancement of cryptography and cryptanalysis has driven numerous innovations over years. Among them is the treatment of cryptanalysis on selectively encrypted content as a recovery problem. Recent research has shown that linear programming is a powerful tool to recover unknown coefficients in DCT-transformed images. While the time complexity is polynomial, it is still too high for large images so faster methods are still desired. In this paper, we propose a fast hierarchical DCT coefficients recovery method by combining image segmentation and linear programming. In theory the proposed method can reduce the overall time complexity by a linear factor which is the number of image segments used. Our experimental results showed that, for 100 test images of different sizes and using a naive image segmentation method based on Otsu’s thresholding algorithm, the proposed method is faster for more than 92% cases and the maximum improvement observed is more than 19 times faster. While being mostly faster, results also showed that the proposed method can roughly maintain the visual quality of recovered images in both objective and subjective terms.

Reversible multiple messages embedding using reflective blocks

This paper proposes three multiple messages embedding (MME) methods as extension for reversible data embedding using reflective blocks [1]. MME is realized by exploiting the data representation scheme in [1] while maintaining the reversibility and scalability of [1]. In particular, Method I utilizes block range to embed multiple messages while Method II utilizes bit representation to realize MME. Both of these methods can each embed a maximum of 9 messages in a host image. Method III is the hybrid of Method I and II, and it can embed up to 37 messages in a host image. Experimental results show the average embedding capacity for each individual embedding channel.

Reversible and tunable scrambling-embedding method

This paper proposes a reversible unified method to scramble an image and embed information into it using row and column rotation methods. Each row (column) is divided into groups and rotated to the left (bottom) to distort the image. Unique states are derived during the rotation process and utilized to embed external information. In the decoding process, the pixel correlations in the vertical and horizontal directions are exploited to reconstruct the original image and extract the embedded information. The proposed method is able to control the output image quality to achieve its intended distortion using the control parameters. Experiments are conducted to verify the basic performance of the proposed method. Our previously proposed method is adopted to further improve the proposed method in terms of payload and quality degradation of the output image. It is verified that the original image can be perfectly reconstructed and the proposed method itself is able to achieve an average effective payload up to ~9015.0 bits. SSIM and PSNR values are measured to determine the range of achievable distortion using different parameters.