Dual image based reversible data hiding method using neighbouring pixel value differencing

Abstract

Dual image based reversible data hidings are recently proposed where dual copies of a cover image are used to embed the secret data. In this paper, a novel reversible data hiding method based on neighbouring pixel value differencing is proposed to increase embedding capacity with a good image quality. The mean value of neighbouring pixels and the difference values are used to decide the size of embedding bits per the sub-block. The receiver can extract the secret data and recover the cover image from dual stegoimages. The experimental results show that the proposed method has a higher capacity and still a good image quality where it could embed 767,922 bits and maintain 45.58 and 45.33?dB for dual images.     

New splitting algorithms for geometric transformations of digital images and their error analysis

For digital images and patterns under the nonlinear geometric transformation, T: (ξ, η) → (x, y), this study develops the splitting algorithms (i.e., the pixel‐division algorithms) that divide a 2D pixel into N × N subpixels, where N is a positive integer chosen as N = 2 ^k(k ≥ 0) in practical computations. When the true intensity values of pixels are known, this method makes it easy to compute the true intensity errors. As true intensity values are often unknown, the proposed approaches can compute the sequential intensity errors based on the differences between the two approximate intensity values at N and N/2. This article proposes the new splitting–shooting method, new splitting integrating method, and their combination. These methods approximate results show that the true errors of pixel intensity are O(H), where H is the pixel size. Note that the algorithms in this article do not produce any sequential errors as N ≥ N₀, where N₀ (≥2) is an integer independent of N and H. This is a distinctive feature compared to our previous papers on this subject. The other distinct feature of this article is that the true error bound O(H) is well suited to images with all kinds of discontinuous intensity, including scattered pixels. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 323–335, 2011     

Reversible Data Hiding in Encrypted Images Based on Prediction and Adaptive Classification Scrambling

Reversible data hiding in encrypted images (RDH-EI) technology is widely used in cloud storage for image privacy protection. In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling. First, the prediction error image is obtained by a novel prediction method before encryption. Then, the image pixel values are divided into two categories by the threshold range, which is selected adaptively according to the image content. Multiple high-significant bits of pixels within the threshold range are used for embedding data and pixel values outside the threshold range remain unchanged. The optimal threshold selected adaptively ensures the maximum embedding capacity of the algorithm. Moreover, the security of encrypted images can be improved by the combination of XOR encryption and classification scrambling encryption since the embedded data is independent of the pixel position. Experiment results demonstrate that the proposed method has higher embedding capacity compared with the current state-ofthe-art methods for images with different texture complexity.     

Dynamic selective information hiding based on search order coding with low bit rate

Abstract

A low bit rate information hiding scheme is important for efficient communication. According to our observation, in a search order coding based (SOC based) hiding method, the case distribution generated from different images and from different secret strings is different. Based on this characteristic, we designed a dynamic selective, SOC based, information hiding scheme to achieve a desirable compression effect. That is, depending on different case distributions, we used different coding modes to reduce the bit rate more effectively. The main concept of our design is to let the two cases that occur most frequently use one-bit indicators and to let the remaining two cases use four-bit indicators to indicate the following coding types. The experimental results showed that the proposed scheme has a lower bit rate than other SOC based information hiding schemes. As a result, the proposed information hiding scheme is more practical for real world applications.     

Bit rate reduction techniques for absolute moment block truncation coding

Abstract

Block Truncation Coding uses a two‐level moment preserving quantizer that adapts to local properties of the images. It has the features of low computation load and low memory requirement while its bit rate is only 2.0 bits per pixel. A more efficient algorithm, the absolute moment BTC (AMBTC) has been extensively used in the field of signal compression because of its simple computation and better MSE performance. We propose postprocessing methods to further reduce the entropy of two output data of AMBTC, including the bit map and two quantization data (a, b). A block of a 2×4 bit map is packaged into a byte‐oriented symbol. The entropy can be reduced from 0.965 bpp to 0.917 bpp on average for our test images. The two subimages of quantization data (a, b) are postprocessed by the Peano Scan. This postprocess can further reduce differential entropy about 0.4 bit for a 4×4 block. By applying arithmetic coding, the total bit reduction is about 0.3～0.4 bpp. The bit rate can reach 1.6～1.7 bpp with the same quality as traditional AMBTC.     

Coverless Information Hiding Based on the Molecular Structure Images of Material

The traditional information hiding methods embed the secret information by modifying the carrier, which will inevitably leave traces of modification on the carrier. In this way, it is hard to resist the detection of steganalysis algorithm. To address this problem, the concept of coverless information hiding was proposed. Coverless information hiding can effectively resist steganalysis algorithm, since it uses unmodified natural stego-carriers to represent and convey confidential information. However, the state-of-the-arts method has a low hidden capacity, which makes it less appealing. Because the pixel values of different regions of the molecular structure images of material (MSIM) are usually different, this paper proposes a novel coverless information hiding method based on MSIM, which utilizes the average value of sub-image’s pixels to represent the secret information, according to the mapping between pixel value intervals and secret information. In addition, we employ a pseudo-random label sequence that is used to determine the position of sub-images to improve the security of the method. And the histogram of the Bag of words model (BOW) is used to determine the number of sub-images in the image that convey secret information. Moreover, to improve the retrieval efficiency, we built a multi-level inverted index structure. Furthermore, the proposed method can also be used for other natural images. Compared with the state-of-the-arts, experimental results and analysis manifest that our method has better performance in anti-steganalysis, security and capacity.     

Wavelet-based distortion measure for binary images

Abstract

This paper proposes an objective distortion measure for binary images. Whereas most previously proposed measures decide the distortion weight of a distorted pixel based on the relationship with the neighbouring pixels in the spatial domain, we observe the characteristics of distorted pixels in multi-spectral spatial-frequency bands. Similarities between the binary wavelet transform and the human visual system are utilised to obtain the distortion weight. When we decide the distortion weight of a distorted pixel, we consider flatness, edge orientation and texture complexity of the distorted pixel at each level of binary wavelet decomposition. Experimental results on various sample images show that the proposed measure is more adequate to human than previously proposed measures.     

A colour image retrieval scheme based on Z-scanning technique

Abstract

This paper proposes a new colour image retrieval scheme using Z-scanning technique for content-based image retrieval (CBIR). In recent years, the CBIR is a popular research topic for image retrieval. This paper proposes a scheme which employs the Z-scanning technique to extract directional intensity features for measuring the similarity between query and database images. In the multiple channel images, each colour channel can be processed individually or combined into a grey channel Y. In order to extract the features by Z-scanning technique from all images, each channel of all images must be divided into several N×N blocks. In each block, F pairs of pixels are scanned by a ‘Z’ direction to obtain the texture features. Each colour channel can be obtained an M×M Z-scanning co-occurrence matrix (ZSCM) for storing the probability of each relationship of all closest blocks. At the similarity measure stage, the ZSCMs of query image and database images are compared to measure their similarity. The experimental results show that the proposed scheme is beneficial for image retrieval when the images include the same texture or object. On the other hand, the proposed scheme also can get better retrieval results and more efficiency than colour correlogram (CC) technique for colour texture images. Another technique uses motif co-occurrence matrix (MCM) as the feature in similarity measurement. The experimental results show the proposed ZSCM can get better retrieval results and higher recall and precision values than the CC and MCM techniques for public image databases.     

Measurement of large,discontinuous displacement from digital images

One main limitation of conventional digital image correlation (DIC) methods is their incapacity to treat with large, discontinuous displacements. This paper seeks to resolve this issue using a variational method. Specifically, the objective function is written in a form of L¹-norm instead of L²-norm for discontinuity preservation. This convex, non-differentiable objective function is resolved by a proximal gradient method. Then, the entire correlation process is embedded into a multi-level image pyramid, enabling large displacements to be measured accurately. The proposed method is first validated on images with prescribed small displacements; its performance to treat with discontinuous, large displacements is then examined. The results show that the proposed method exhibits an acceptable performance when measuring some extreme displacements up to 16.5 pixels in a 500 × 500 pixels resolution image. Concerning subpixel accuracy, the errors can be lessened to a very low level with optimised parameters even for a dense correlation at each pixel. Good performance is also demonstrated in forms of noise proof and illumination fluctuation tolerance. Finally, an application is conducted on an experiment concerned with cracking in desiccated soils, in which the proposed method succeeds in tracking the nucleation and propagation processes of multiple cracks.     

Tritium digital autoradiography with a Medipix2 hybrid silicon pixel detector

We report on the first measurements of ³H beta autoradiography obtained using a room temperature hybrid pixel detector, consisting of the Medipix2 single particle counting read-out chip bump-bonded to a 300 μm thick silicon pixel detector. This system has 256×256 square pixels of 55 μm pitch for a total sensitive area of 14×14 mm². Each pixel contains a double threshold discriminator and a 13-bit counter. Using a detection threshold equivalent to less than 6 keV and a background count rate of 5×10⁻³ counts mm⁻² s⁻¹, with exposures up to several hours, real-time images have been obtained of tritium-labeled solution drops spotted on a thin mylar foil placed in contact with the continuous top electrode of the silicon detector, in open air condition.     

A Parallel Fringe-scanning Algorithm for Phase-shifting Interferometry

Abstract

In connection with digital interferometry, the evaluation of phase-shifted interferograms can be speeded up by a digital image processor. A special parallel algorithm has been designed for scanning the saw-tooth shaped fringes. It is shown that the number of image passes (TC cycles) for a 2 ^j × 2 ^j pixel image is reduced to j instead of 2^j. Fringe scanning of a saw-tooth phase image and a pseudocoloured display of the continuous phase is obtained after 1·4s for 512 × 512 points.     

High-speed use of CCD area sensors as high energy particle detectors

A position sensitive detector for minimum ionizing particles is described. It is based on charge coupled devices (CCDs) area image sensors with single pixel sizes of 22 × 22 μm². The operating frequency is 6.75 MHz and the total readout time for 2.3 × 10⁵ pixels is about 40 ms. The devices are operated close to room temperature.     

The new block pixel sort algorithm for TVC-encrypted medical image

To transfer the medical image from one place to another place or to store a medical image in a particular place with secure manner has become a challenge. In order to solve those problems, the medical image is encrypting and compressing before sending or saving at a place. In this paper, a new block pixel sort algorithm has been proposed for compressing the encrypted medical image. The encrypted medical image acts as an input for this compression process. During the compression, encrypted secret image E₁₂(;) is compressed by the pixel block sort encoding (PBSE). The image is divided into four identical blocks, similar to 2×2 matrix. The minimum occurrence pixel(s) are found out from every block and the positions of the minimum occurrence pixel(s) are found using the verdict occurrence process. The pixel positions are shortened with the help of a shortening process. The features (symbols and shortened pixel positions) are extracted from each block and the extracted features are stored in a particular place, and the values of these features put together as a compressed medical image. The next process of PBSE is pixel block short decoding (PBSD) process. In the decoding process, there are nine steps involved while decompressing the compressed encrypted medical image. The feature extraction value of compressed information is found out from the feature extraction, the symbols are split and the positions are shortened in a separate manner. The position is retrieved from the rescheduled process and the symbols and reconstructed positions of the minimum occurrence pixels are taken block wise. Every symbol is placed based on the position in each block: if the minimum occurrence pixel is ‘0’, then the rest of the places are automatically allocated as ‘1’ or if the minimum occurrence pixel is ‘1’ the remaining place is automatically allocated as ‘0’. Both the blocks are merged as per order 2×2. The final output is the reconstructed encrypted medical image. From this compression method, we can achieve the high compression ratio, minimum time, less compression size and lossless compression, which are the things experimented and proved.     

Advances in Fabrication of TES μ-Calorimeter Arrays and Associated Filter Structures for AC-Biased Read Out

In this paper we describe microfabrication developments for a 1024 pixel calorimeter array, to be used in future X-ray spectroscopic space missions. We report on an optimization study of high packing factor, mushroom shaped, Cu/Bi absorbers, for which a sputter deposition technique into a new type of photoresist mould has been developed. We have fabricated a prototype 32×32 array where 98 representable pixels are potentially functioning TESs. To gain more control on the detector pixel performance a new procedure was developed to couple absorber and thermometer, utilizing a thin insulating layer. Advances are reported in the fabrication of superconducting LC resonating circuits, needed for frequency domain multiplexed read out. A quality factor Q∼4000 @ 2.6 MHz has been measured, which was limited by critical current in the circuit.      

A simple segmentation method for DNA microarray spots by kernel density estimation

The DNA microarray analysis is one of the most important areas in biomedical research. For the accurate analysis of microarray data the process of segmentation, classification of pixels as foreground or background, should be done accurately. In this paper we suggest a kernel density estimation approach for the segmentation of the microarray spot. We estimate the density of n pixel intensities for a given target area by the kernel density estimation, and the resulting kernel density estimate gives bimodal density by appropriate choice of the smoothing parameter. We suggest two modes of the kernel density estimate for n pixel intensities as estimates of the foreground (mode with larger value) and the background (mode with smaller value) intensity, respectively. The segmentation method proposed in this paper is easy and simple to use, robust to the shape of spot, and very accurate. This research was supported by Korea Science and Engineering Foundation grant (R14-2003-002-01000-0).     

Reversible Data Hiding in Classification-Scrambling Encrypted-Image Based on Iterative Recovery

To improve the security and quality of decrypted images, this work proposes a reversible data hiding in encrypted image based on iterative recovery. The encrypted image is firstly generated by the pixel classification scrambling and bit-wise exclusive-OR (XOR), which improves the security of encrypted images. And then, a pixel-type-mark generation method based on block-compression is designed to reduce the extra burden of key management and transfer. At last, an iterative recovery strategy is proposed to optimize the marked decrypted image, which allows the original image to be obtained only using the encryption key. The proposed reversible data hiding scheme in encrypted image is not vulnerable to the ciphertext-only attack due to the fact that the XOR-encrypted pixels are scrambled in the corresponding encrypted image. Experimental results demonstrate that the decrypted images obtained by the proposed method are the same as the original ones, and the maximum embedding rate of proposed method is higher than the previously reported reversible data hiding methods in encrypted image.     

CdSe/CdS core/shell quantum dots as sensitizer of a photorefractive polymer composite

Abstract

CdSe/CdS core/shell, tri-n-octylphosphine oxide passivated, quantum dots are used to sensitize a photorefractive polymer composite. The composite also consists of poly(N-vinylcarbazole) as the nominally charge transporting matrix and an electro-optic chromophore. The efficacy of sensitization and consequent photorefractive performance is investigated using transmission spectroscopy and ellipsometry, two-beam coupling and degenerate four-wave mixing experiments. The photorefractive nature of the photo-induced grating is confirmed by the observation of asymmetric two-beam coupling. Four-wave mixing reveals record diffraction efficiencies for a nano-particle-sensitized photorefractive polymer at the field levels applied (1.3% at 70 V.μm^?1). A recently developed analytical technique is used to extract space-charge field rise time values from degenerate four-wave mixing transients. In turn, analysis of the dependence of the rise time on applied field is used to determine the zero-field charge dissociation efficiency to be 3.6 × 10^?5 ± 0.5 × 10^?5. It is further shown that the magnitude of this parameter accounts for most of the difference in photorefractive response rate between the present material and a similar C₆₀ sensitized composite.     

Image segmentation via local higher order statistics

The aim of this work is to present a method for the segmentation of images based on local higher order statistics. The algorithm can be applied for the separation of objects from a texture background and the segmentation of textures. The proposed technique makes no use of a data bank and its complexity is O(??) where ?? is the number of pixels. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol 13, 215–223, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10069     

3D Pixel Mechanical Metamaterials

Metamaterials have unprecedented properties that facilitate the development of advanced devices and machines. However, their interconnected building structures limit their applications, especially in the fields that require large deformation, rich programmability and efficient shape‐reconfigurability. To break this limit and exploit more potentialities of metamaterials, an innovative material design strategy is proposed, named mechanical pixel (MP) array design. Similar to a screen that displays images by adjusting the colors of pixels, the metamaterials can form and reconfigure 3D morphologies by tuning the heights (lengths) of the MPs in the array. The strategy is demonstrated in a multistable metamaterial by experimental tests, theoretical analysis, and numerical simulations. Using this strategy, a large macroscopic shear deformation is obtained, and remarkable enhancements in the mechanical programmability, shape‐reconfigurability and adaptability, and reusable shock‐resistance are exhibited. Moreover, mechanical design and property prediction for the metamaterials are both greatly simplified due to the pixelated design. For a piece of the 3D pixel metamaterial with m n‐unit MPs, the number of programmable displacement–force curves increases from n+1 to 2^m?n+1, and the number of stable morphologies grows from n+1 to at least (n+1)^m. This strategy can be used to enhance the merits and further excavate the potential of versatile metamaterials.