Steganographic capacity estimation for the statistical restoration framework

Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.To deal with the illuminant selection step, we hypothesize that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to how the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation.The implementation of this selection criterion strongly relies on the use of a diagonal model for illuminant change. Then, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimized to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimize different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D.Several research lines remain still open, such as, measuring the effects of using the computed sharp sensors on the category hypothesis; or inserting spatial contextual information to improve category hypothesis. Finally, to explore how individual sensors can be adjusted to the colours in a scene.

We propose a new watermarking method based on quantization index modulation. A concept of initial data loss is introduced in order to increase capacity of the watermarking channel under high intensity additive white Gaussian noise. According to the concept some samples in predefined positions are ignored even though this produces errors in the initial stage of watermark embedding. The proposed method also exploits a new form of distribution of quantized samples where samples that interpret “0” and “1” have differently shaped probability density functions. Compared to well-known watermarking schemes, this provides an increase of capacity under noise attack and introduces a distinctive feature. Two criteria are proposed that express the feature numerically. The criteria are utilized by a procedure for estimation of a gain factor after possible gain attack. Several state-of-the-art quantization-based watermarking methods were used for comparison on a set of natural grayscale images. The superiority of the proposed method has been confirmed for different types of popular attacks.

We propose a system in which the watermark message is embedded into audio signal by means of Quantization Index Modulation (QIM) scheme. However, the method is sensitive to gain scaling attack. We use a value-metric scaling invariant method called Rational Dither Modulation (RDM) to cope with this problem. At the same time, we exploit the psychoacoustic model to improve the audio signal's perceptual quality after the watermark embedding procedure. In comparison of the traditional QIM which use a fixed quantization step, our method adjusts the quantization step with psychoacoustic model adaptively. Experimental results show that our watermarking scheme is robust against common signal processing attacks while keeping the watermarked audio a high perceptual quality.

A natural color mapping method has been previously proposed that matches the statistical properties (mean and standard deviation) of night-vision (NV) imagery to those of a daylight color image (manually selected as the "target" color distribution). Thus the rendered NV image appears to resemble the target image in terms of colors. However, in this prior method the colored NV image may appear unnatural if the target image's "global" color statistics are too different from that of the night vision scene (e.g., it would appear to have too much green if much more foliage was contained in the target image). Consequently, a new "local coloring" method is presented in the current paper, and functions to render the NV image segment-by-segment by using a histogram matching technique. Specifically, a false-color image (source image) is formed by assigning multi-band NV images to three RGB (red, green and blue) channels. A nonlinear diffusion filter is then applied to the false-colored image to reduce the number of colors. The final grayscale image segments are obtained by using clustering and merging techniques. The statistical matching procedure is merged with the histogram matching procedure to assure that the source image more closely resembles the target image with respect to color. Instead of using a single target color image, the mean, standard deviation and histogram distribution of a set of natural scene images are used as the target color properties for each color scheme. Corresponding to the source region segments, the target color schemes are grouped by their scene contents (or colors) such as green plants, roads, ground/earth. In our experiments, five pairs of night-vision images were initially analyzed, and the images that were colored (segment-by-segment) by the proposed "local coloring" method are shown to be much more natural, realistic, and colorful when compared with those produced by the "global-coloring" method.

Carrier frequencies beyond 300 GHz have recently received attention primarily due to the potential for impressive capacity for future multi-gigabit wireless communication systems. In this context, this paper considers the different attenuation factors at the THz band and estimates the available bandwidth and the corresponding maximum data rate in the THz band. Results show that capacity values beyond 1Tbps can be achieved under certain conditions for the transmitted power, antenna gains and weather conditions.

Carbon dioxide (CO2) injection in deep saline formations causes pressure increase which may be detrimental to the mechanical integrity of the storage reservoir. Injection induced pressure build‐up is a limiting factor for CO2 injection rates and storage capacity. In this study, we extend a semi‐analytical solution (based on one‐dimensional, two‐phase, two‐component radial flow) for application to estimate pressure build‐up and maximum injection rate of CO2 at a field site (South Scania, Sweden) using the method of superposition of image well solutions to account for the straight‐line boundaries imposed by three fault zones. The semi‐analytical approach for estimating pressure build‐up is validated by comparison to numerical simulations based on TOUGH2‐ECO2N. We analyze injection pressure sensitivity due to uncertainty in reservoir parameters as well as boundary conditions. Maximum injection rates and pressure limited capacity estimates are presented. This work demonstrates the use of semi‐analytical solutions to analyze pressure limitation on storage capacity for realistic reservoirs with irregular (non‐circular) boundaries. It is also shown that the semi‐analytical approach can also be used to evaluate the benefit of having multiple injection wells in terms of increasing the injection‐pressure‐limited storage capacity. The methodology presented in this study is useful for screening analysis of storage sites as well as for operation design and optimization where pressure build‐up as a limiting factor influences the objective function.

Carbon-ion radiotherapy (CIRT) is known as a promising treatment for liver tumors. However, no method has been established for estimating post-therapeutic residual liver reserve capacity (pRLRC). We previously introduced the estimation method of pRLRC using 99 mTc-galactosyl human serum albumin (99 mTc-GSA) scintigraphy (Yamazaki method). In this study, we developed "Yamazaki-variant" method for pRLRC using dose distribution data of CIRT planning. The purpose of this study was to compare pRLRC calculated by Yamazaki method and Yamazaki-variant in CIRT patients for liver tumors, and to provide the clinical advantages in both methods in terms of estimating ability of pRLRC. Patients who received CIRT for liver tumors in our hospital and underwent 99 mTc-GSA scintigraphy before and 3months after CIRT, and contrast-enhanced liver MRI within 1month before CIRT were included. A total of 71 patients, 21 additional to the 50 previously reported, were evaluated. The maximal removal rate of 99 mTc-GSA (GSA-Rmax) was analyzed and the GSA-Rmax of the estimated residual liver (GSA-RL) was calculated using fusion images of MRI and SPECT by Yamazaki method. In Yamazaki-variant, multiple simulations were performed using the dose distribution of the CIRT planning and SPECT fusion images to obtain higher diagnostic accuracy of GSA-RL. Two of these estimates, Validation 1 and Validation 2 by Yamazaki-variant, were used as validation data. GSA-RL and Validation 1 and 2 were compared with GSA-Rmax 3months after CIRT (post-GSA-Rmax) using linear regression analysis. GSA-RL, Validation 1 and 2 were calculated as 0.448 ± 0.214, 0.413 ± 0.199 and 0.435 ± 0.208 mg/min, respectively. Post-GSA-Rmax was 0.428 ± 0.220 mg/min. The relationship between post-GSA-Rmax and each parameter was y = 0.02 + 0.90x (R2 = 0.78) for GSA-RL, y = 0.02 + 0.94x (R2 = 0.79) for Estimation 1, y = 0.02 + 0.99x (R2 = 0.80) for Estimation 2, respectively (P <.0001). Both Yamazaki method and Yamazaki-variant showed comparable accurate estimation ability for post-GSA-Rmax. The estimation of pRLRC by Yamazaki method and Yamazaki-variant was in good agreement with post-therapeutic liver reserve capacity after CIRT, and there was no difference in the accuracy of the estimation. The usefulness of Yamazaki method, which is simpler and more clinically applicable, was confirmed. This study is registered in UMIN Clinical Trials Registry (UMIN-CTR) as UMIN study ID: UMIN000038328 and UMIN000049770, UMIN000038174.

We present a method to compute the steganographic capacity for images, with odd-even based hiding in the quantized discrete cosine transform domain. The method has been generalized for varying orders of co-occurrence statistics for statistical restoration based steganography. We further utilize this capacity estimate to hide the maximum possible data per individual frequency stream, while ensuring that the first order histograms of individual frequency coefficients remain matched. We also show that certain frequency components are more useful for steganalysis after first order statistical restoration is performed for a certain band of select frequencies.

In this paper, we suggest an adaptive watermarking method to improve both transparence and robustness of quantization index modulation (QIM) scheme. Instead of a fixed quantization step size, we apply a step size adapted to image content in each 8times8 block to make a balance of the robustness extraction and the transparence of embedding. The modified steps are determined by the contrast masking thresholds of Watson's perceptual model. From normalized cross correlation between the original watermark and the detected watermark, we observe that it is robust to attacks of additive white Gaussian noise, salt & pepper noise, JPEG compression than the original QIM.

This paper presents a novel approach for blind audio watermarking. The proposed scheme utilizes the flexibility of discrete wavelet packet transformation (DWPT) to approximate the critical bands and adaptively determines suitable embedding strengths for carrying out quantization index modulation (QIM). The singular value decomposition (SVD) is employed to analyze the matrix formed by the DWPT coefficients and embed watermark bits by manipulating singular values subject to perceptual criteria. To achieve even better performance, two auxiliary enhancement measures are attached to the developed scheme. Performance evaluation and comparison are demonstrated with the presence of common digital signal processing attacks. Experimental results confirm that the combination of the DWPT, SVD, and adaptive QIM achieves imperceptible data hiding with satisfying robustness and payload capacity. Moreover, the inclusion of self-synchronization capability allows the developed watermarking system to withstand time-shifting and cropping attacks.

In this paper, we propose a new digital watermarking algorithm named spatial unified key insertion (SUKI) for few-color images. By performing the adaptive threshold halftoning and contour shaping and modification, we can embed a binary logo into a digital image with superior JPEG compression resistance ability. The bit error rate (BER) of JPEG attack is equal to zero for all testing images with quality factor≥80. The BER is much lower than the traditional watermarking algorithms, such as spread spectrum watermarking and quantization index modulation watermarking. The payload is considerably high and there are no "salt-and-peppers" artifacts in the watermarked images. No additional color is introduced and the palette keeps unchanged after watermark embedding. The proposed algorithm can be applied to natural images with distinct boundaries by segmenting the images into different parts.