Showing papers in "electronic imaging in 2008"

Image restoration by sparse 3D transform-domain collaborative filtering

Abstract: We propose an image restoration technique exploiting regularized inversion and the recent block-matching and 3D filtering (BM3D) denoising filter. The BM3D employs a non-local modeling of images by collecting similar image patches in 3D arrays. The so-called collaborative filtering applied on such a 3D array is realized by transformdomain shrinkage. In this work, we propose an extension of the BM3D filter for colored noise, which we use in a two-step deblurring algorithm to improve the regularization after inversion in discrete Fourier domain. The first step of the algorithm is a regularized inversion using BM3D with collaborative hard-thresholding and the seconds step is a regularized Wiener inversion using BM3D with collaborative Wiener filtering. The experimental results show that the proposed technique is competitive with and in most cases outperforms the current best image restoration methods in terms of improvement in signal-to-noise ratio.

A Reversible Data Hiding Method for Encrypted Images

Abstract: Since several years, the protection of multimedia data is becoming very important The protection of this multimedia data can be done with encryption or data hiding algorithms To decrease the transmission time, the data compression is necessary Since few years, a new problem is trying to combine in a single step, compression, encryption and data hiding So far, few solutions have been proposed to combine image encryption and compression for example Nowadays, a new challenge consists to embed data in encrypted images Since the entropy of encrypted image is maximal, the embedding step, considered like noise, is not possible by using standard data hiding algorithms A new idea is to apply reversible data hiding algorithms on encrypted images by wishing to remove the embedded data before the image decryption Recent reversible data hiding methods have been proposed with high capacity, but these methods are not applicable on encrypted images In this paper we propose an analysis of the local standard deviation of the marked encrypted images in order to remove the embedded data during the decryption step We have applied our method on various images, and we show and analyze the obtained results

Revisiting weighted stego-image steganalysis

Abstract: This paper revisits the steganalysis method involving a Weighted Stego-Image (WS) for estimating LSB replacement payload sizes in digital images. It suggests new WS estimators, upgrading the method's three components: cover pixel prediction, least-squares weighting, and bias correction. Wide-ranging experimental results (over two million total attacks) based on images from multiple sources and pre-processing histories show that the new methods produce greatly improved accuracy, to the extent that they outperform even the best of the structural detectors, while avoiding their high complexity. Furthermore, specialised WS estimators can be derived for detection of sequentially-placed payload: they offer levels of accuracy orders of magnitude better than their competitors.

Stereoscopic image quality metrics and compression

Abstract: We are interested in metrics for automatically predicting the compression settings for stereoscopic images so that we can minimize file size, but still maintain an acceptable level of image quality. Initially we investigate how Peak Signal to Noise Ratio (PSNR) measures the quality of varyingly coded stereoscopic image pairs. Our results suggest that symmetric, as opposed to asymmetric stereo image compression, will produce significantly better results. However, PSNR measures of image quality are widely criticized for correlating poorly with perceived visual quality. We therefore consider computational models of the Human Visual System (HVS) and describe the design and implementation of a new stereoscopic image quality metric. This, point matches regions of high spatial frequency between the left and right views of the stereo pair and accounts for HVS sensitivity to contrast and luminance changes at regions of high spatial frequency, using Michelson's Formula and Peli's Band Limited Contrast Algorithm. To establish a baseline for comparing our new metric with PSNR we ran a trial measuring stereoscopic image encoding quality with human subjects, using the Double Stimulus Continuous Quality Scale (DSCQS) from the ITU-R BT.500-11 recommendation. The results suggest that our new metric is a better predictor of human image quality preference than PSNR and could be used to predict a threshold compression level for stereoscopic image pairs.

Camera identification from cropped and scaled images

Abstract: In this paper, we extend our camera identification technology based on sensor noise to a more general setting when the image under investigation has been simultaneously cropped and scaled. The sensor fingerprint detection is formulated using hypothesis testing as a two-channel problem and a detector is derived using the generalized likelihood ratio test. A brute force search is proposed to find the scaling factor which is then refined in a detailed search. The cropping parameters are determined from the maximum of the normalized cross-correlation between two signals. The accuracy and limitations of the proposed technique are tested on images that underwent a wide range of cropping and scaling, including images that were acquired by digital zoom. Additionally, we demonstrate that sensor noise can be used as a template to reverse-engineer in-camera geometrical processing as well as recover from later geometrical transformations, thus offering a possible application for re-synchronizing in digital watermark detection.

Realization of correlation attack against the fuzzy vault scheme

Abstract: User privacy and template security are major concerns in the use of biometric systems. These are serious concerns based on the fact that once compromised, biometric traits can not be canceled or reissued. The Fuzzy Vault scheme has emerged as a promising method to alleviate the template security problem. The scheme is based on binding the biometric template with a secret key and scrambling it with a large amount of redundant data, such that it is computationally infeasible to extract the secret key without possession of the biometric trait. It was recently claimed that the scheme is susceptible to correlation based attacks which assume the availability of two fuzzy vaults created using the same biometric data (e.g. two impressions of the same fingerprint) and suggests that correlating them would reveal the biometric data hidden inside. In this work, we implemented the fuzzy vault scheme using fingerprints and performed correlation attacks against a database of 400 fuzzy vaults (200 matching pairs). Given two matching vaults, we could successfully unlock 59% of them within a short time. Furthermore, it was possible to link an unknown vault to a short list containing its matching pair, for 41% of all vaults. These results prove the claim that the fuzzy vault scheme without additional security measures is indeed vulnerable to correlation attacks.

Technology-assisted dietary assessment

Abstract: Dietary intake provides valuable insights for mounting intervention programs for prevention of disease. With growing concern for adolescent obesity, the need to accurately measure diet becomes imperative. Assessment among adolescents is problematic as this group has irregular eating patterns and have less enthusiasm for recording food intake. Preliminary studies among adolescents suggest that innovative use of technology may improve the accuracy of diet information from young people. In this paper, we propose a novel food record method using a mobile device that will provide an accurate account of daily food and nutrient intake among adolescents. Our approach includes the use of image analysis tools for identification and quantification of food consumption. Images obtained before and after food is consumed can be used to estimate the diet of an individual. In this paper we describe our initial results and indicate the potential of the proposed system.

Measuring Stereoscopic Image Quality Experience with Interpretation Based Quality Methodology

Abstract: Stereoscopic technologies have developed significantly in recent years. These advances require also more understanding of the experiental dimensions of stereoscopic contents. In this article we describe experiments in which we explore the experiences that viewers have when they view stereoscopic contents. We used eight different contents that were shown to the participants in a paired comparison experiment where the task of the participants was to compare the same content in stereoscopic and non-stereoscopic form. The participants indicated their preference but were also interviewed about the arguments they used when making the decision. By conducting a qualitative analysis of the interview texts we categorized the significant experiental factors related to viewing stereoscopic material. Our results indicate that reality-likeness as well as artificiality were often used as arguments in comparing the stereoscopic materials. Also, there were more emotional terms in the descriptions of the stereoscopic films, which might indicate that the stereoscopic projection technique enhances the emotions conveyed by the film material. Finally, the participants indicated that the three-dimensional material required longer presentation time, as there were more interesting details to see.

A Fast Non-Local Image Denoising Algorithm

Abstract: In this paper we propose several improvements to the original non-local means algorithm introduced by Buades et al. which obtains state-of-the-art denoising results. The strength of this algorithm is to exploit the repetitive character of the image in order to denoise the image unlike conventional denoising algorithms, which typically operate in a local neighbourhood. Due to the enormous amount of weight computations, the original algorithm has a high computational cost. An improvement of image quality towards the original algorithm is to ignore the contributions from dissimilar windows. Even though their weights are very small at first sight, the new estimated pixel value can be severely biased due to the many small contributions. This bad influence of dissimilar windows can be eliminated by setting their corresponding weights to zero. Using the preclassification based on the first three statistical moments, only contributions from similar neighborhoods are computed. To decide whether a window is similar or dissimilar, we will derive thresholds for images corrupted with additive white Gaussian noise. Our accelerated approach is further optimized by taking advantage of the symmetry in the weights, which roughly halves the computation time, and by using a lookup table to speed up the weight computations. Compared to the original algorithm, our proposed method produces images with increased PSNR and better visual performance in less computation time. Our proposed method even outperforms state-of-the-art wavelet denoising techniques in both visual quality and PSNR values for images containing a lot of repetitive structures such as textures: the denoised images are much sharper and contain less artifacts. The proposed optimizations can also be applied in other image processing tasks which employ the concept of repetitive structures such as intra-frame super-resolution or detection of digital image forgery.

Large holographic displays as an alternative to stereoscopic displays

Abstract: 3D displays comprise stereoscopic displays and holographic displays. Eye convergence and accommodation are important depth cues for human vision. Stereoscopic displays provide only convergence information whereas holographic displays also provide accommodation information. Due to the inherently better 3D quality we consider holographic displays as the preferred alternative to stereoscopic displays. Our new approach to holographic displays omits unnecessary wavefront information and significantly reduces the requirements on the resolution of the spatial light modulator and the computation effort compared to conventional holographic displays. We verified our concept with holographic display prototypes and measurements. SeeReal's approach makes holographic displays feasible as a consumer product for mass-market applications.

Further study on YASS: steganography based on randomized embedding to resist blind steganalysis

Abstract: We present further extensions of yet another steganographic scheme (YASS), a method based on embedding data in randomized locations so as to resist blind steganalysis. YASS is a JPEG steganographic technique that hides data in the discrete cosing transform (DCT) coefficients of randomly chosen image blocks. Continuing to focus on JPEG image steganography, we present, in this paper, a further study on YASS with the goal of improving the rate of embedding. Following are the two main improvements presented in this paper: (i) a method that randomizes the quantization matrix used on the transform domain coefficients, and (ii) an iterative hiding method that utilizes the fact that the JPEG "attack" that causes errors in the hidden bits is actually known to the encoder. We show that using both these approaches, the embedding rate can be increased while maintaining the same level of undetectability (as the original YASS scheme). Moreover, for the same embedding rate, the proposed steganographic schemes are more undetectable than the popular matrix embedding based F5 scheme, using features proposed by Pevny and Fridrich for blind steganalysis.

MPEG recompression detection based on block artifacts

Abstract: With sophisticated video editing technologies, it is becoming increasingly easy to tamper digital video without leaving visual clues. One of the common tampering operations on video is to remove some frames and then re-encode the resulting video. In this paper, we propose a new method for detecting this type of tampering by exploring the temporal patterns of the block artifacts in video sequences. We show that MPEG compression introduces different block artifacts into various types of frames and that the strength of the block artifacts as a function over time has a regular pattern for a given group of pictures (GOP) structure. When some frames are removed from an MPEG video file and the file is then recompressed, the block artifacts introduced by the previous compression would remain and affect the average of block artifact strength of the recompressed one in such a way that depends on the number of deleted frames and the type of GOP used previously. We propose a feature curve to reveal the compression history of an MPEG video file with a given GOP structure, and use it as evidence to detect tampering. Experimental results evaluated on common video benchmark clips demonstrate the effectiveness of the proposed method.

Laser-plasma scanning 3D display for putting digital contents in free space

Abstract: We present a novel 3D display that can show any 3D contents in free space using laser-plasma scanning in the air. The laser-plasma technology can generate a point illumination at an arbitrary position in the free space. By scanning the position of the illumination, we can display a set of point illuminations in the space, which realizes 3D display in the space. This 3D display has been already presented in Emerging Technology of SIGGRAPH2006, which is the basic platform of our 3D display project. In this presentation, we would like to introduce history of the development of the laser-plasma scanning 3D display, and then describe recent development of the 3D contents analysis and processing technology for realizing an innovative media presentation in a free 3D space. The one of recent development is performed to give preferred 3D contents data to the 3D display in a very flexible manner. This means that we have a platform to develop an interactive 3D contents presentation system using the 3D display, such as an interactive art presentation using the 3D display. We would also like to present the future plan of this 3D display research project.

Performance evaluation of 3D-TV systems

Abstract: The image quality circle is a commonly accepted framework to model the relation between the technology variables of a display and the resulting image quality. 3D-TV systems, however, go beyond the concept of image quality. Research has shown that, although 3D scenes are clearly more appreciated by subjects, the concept 'image quality' does not take this added value of depth into account. Concepts as 'naturalness' and 'viewing experience' have turned out to be more useful when assessing the overall performance of 3D displays. In this paper, experiments are described that test 'perceived depth', 'perceived image quality' and 'perceived naturalness' in images with different levels of blur and different depth levels. Results show that naturalness incorporates both blur level as well as depth level, while image quality does not include depth level. These results confirm that image quality is not a good measure to assess the overall performance of 3D displays. Naturalness is a more promising concept.

Sensor calibration and simulation

Abstract: We describe a method for simulating the output of an image sensor to a broad array of test targets. The method uses a modest set of sensor calibration measurements to define the sensor parameters; these parameters are used by an integrated suite of Matlab software routines that simulate the sensor and create output images. We compare the simulations of specific targets to measured data for several different imaging sensors with very different imaging properties. The simulation captures the essential features of the images created by these different sensors. Finally, we show that by specifying the sensor properties the simulations can predict sensor performance to natural scenes that are difficult to measure with a laboratory apparatus, such as natural scenes with high dynamic range or low light levels.

Textural features based universal steganalysis

Abstract: This paper takes the task of image steganalysis as a texture classification problem. The impact of steganography to an image is viewed as the alteration of image texture in a fine scale. Specifically, stochastic textures are more likely to appear in a stego image than in a cover image from our observation and analysis. By developing a feature extraction technique previously used in texture classification, we propose a set of universal steganalytic features, which are extracted from the normalized histograms of the local linear transform coefficients of an image. Extensive experiments are conducted to make comparison of our proposed feature set with some existing universal steganalytic feature sets on gray-scale images by using Fisher Linear Discriminant (FLD). Some classical non-adaptive spatial domain steganographic algorithms, as well as some newly presented adaptive spatial domain steganographic algorithms that have never been reported to be broken by any universal steganalytic algorithm, are used for benchmarking. We also report the detection performance on JPEG steganography and JPEG2000 steganography. The comparative experimental results show that our proposed feature set is very effective on a hybrid image database.

Integral photography using hexagonal fly's eye lens and fractional view

Abstract: We have developed a new integral photography (IP) system that incorporates a hexagonal fly's eye lens sheet to create a fractional view. In a fractional view, the ratio between the lens and pixel pitches of the IP image is intentionally chosen to be a non-integer so that the directions of all the rays emitted from each pixel on the LCD panel located behind the sheet become quasi-random. Creating a fractional view simultaneously increases the effective number of individual views and the resolution of each view. Furthermore, initial production costs can be decreased because the fractional view can be created using inexpensive off-the-shelf lens sheets together with a variety of common flat panel displays that have different pixel pitches. The difference in pitch is compensated for using computer software. The problem is that fractional views were originally only used with lenticular-lens based displays that have a horizontal parallax; therefore, some extension is necessary if fractional views are to be used with displays that have a full parallax. Furthermore, a typical flat panel display, such as an LCD, consists of RGB subpixels that are in positions that are slightly shifted relative to each other. We have developed a way of extending existing fractional views in order to cope with the full parallax obtained by a fly's eye lens sheet and the pixel shift. We demonstrated that good binocular vision can be obtained when using two hexagonal fly's eye lens sheets that were made without any relation to an LCD.

A generalization of non-local means via kernel regression

Abstract: The Non-Local Means (NLM) method of denoising has received considerable attention in the image processing community due to its performance, despite its simplicity. In this paper, we show that NLM is a zero-th order kernel regression method, with a very specific choice of kernel. As such, it can be generalized. The original method of NLM, we show, implicitly assumes local constancy of the underlying image data. Once put in the context of kernel regression, we extend the existing Non-Local Means algorithm to higher orders of regression which allows us to approximate the image data locally by a polynomial or other localized basis of a given order. These extra degrees of freedom allow us to perform better denoising in texture regions. Overall the higher order method displays consistently better denoising capabilities compared to the zero-th order method. The power of the higher order method is amply illustrated with the help of various denoising experiments.

Video fingerprinting: features for duplicate and similar video detection and query-based video retrieval

Abstract: A video "fingerprint" is a feature extracted from the video that should represent the video compactly, allowing faster search without compromising the retrieval accuracy. Here, we use a keyframe set to represent a video, motivated by the video summarization approach. We experiment with different features to represent each keyframe with the goal of identifying duplicate and similar videos. Various image processing operations like blurring, gamma correction, JPEG compression, and Gaussian noise addition are applied on the individual video frames to generate duplicate videos. Random and bursty frame drop errors of 20%, 40% and 60% (over the entire video) are also applied to create more noisy "duplicate" videos. The similar videos consist of videos with similar content but with varying camera angles, cuts, and idiosyncrasies that occur during successive retakes of a video. Among the feature sets used for comparison, for duplicate video detection, Compact Fourier-Mellin Transform (CFMT) performs the best while for similar video retrieval, Scale Invariant Feature Transform (SIFT) features are found to be better than comparable-dimension features. We also address the problem of retrieval of full-length videos with shorter-length clip queries. For identical feature size, CFMT performs the best for video retrieval.

Two Fibonacci P-code based image scrambling algorithms

Abstract: Image scrambling is used to make images visually unrecognizable such that unauthorized users have difficulty decoding the scrambled image to access the original image. This article presents two new image scrambling algorithms based on Fibonacci p-code, a parametric sequence. The first algorithm works in spatial domain and the second in frequency domain (including JPEG domain). A parameter, p, is used as a security-key and has many possible choices to guarantee the high security of the scrambled images. The presented algorithms can be implemented for encoding/decoding both in full and partial image scrambling, and can be used in real-time applications, such as image data hiding and encryption. Examples of image scrambling are provided. Computer simulations are shown to demonstrate that the presented methods also have good performance in common image attacks such as cutting (data loss), compression and noise. The new scrambling methods can be implemented on grey level images and 3-color components in color images. A new Lucas p-code is also introduced. The scrambling images based on Fibonacci p-code are also compared to the scrambling results of classic Fibonacci number and Lucas p-code. This will demonstrate that the classical Fibonacci number is a special sequence of Fibonacci p-code and show the different scrambling results of Fibonacci p-code and Lucas p-code.

Camera identification from printed images

Abstract: In this paper, we study the problem of identifying digital camera sensor from a printed picture. The sensor is identified by proving the presence of its Photo-Response Non-Uniformity (PRNU) in the scanned picture using camera ID methods robust to cropping and scaling. Two kinds of prints are studied. The first are postcard size (4" by 6") pictures obtained from common commercial printing labs. These prints are always cropped to some degree. In the proposed identification, a brute force search for the scaling ratio is deployed while the position of cropping is determined from the cross-correlation surface. Detection success mostly depends on the picture content and the quality of the PRNU estimate. Prints obtained using desktop printers form the second kind of pictures investigated in this paper. Their identification is complicated by complicated geometric distortion due to imperfections in paper feed. Removing this distortion is part of the identification procedure. From experiments, we determine the range of conditions under which reliable sensor identification is possible. The most influential factors in identifying the sensor from a printed picture are the accuracy of angular alignment when scanning, printing quality, paper quality, and size of the printed picture.

Integrated daylight harvesting and occupancy detection using digital imaging

Abstract: This paper describes a proof-of-concept implementation that uses a high dynamic range CMOS video camera to integrate daylight harvesting and occupancy sensing functionalities. It has been demonstrated that the proposed concept not only circumvents several drawbacks of conventional lighting control sensors, but also offers functionalities that are not currently achievable by these sensors. The prototype involves three algorithms, daylight estimation, occupancy detection and lighting control. The calibrated system directly estimates luminance from digital images of the occupied room for use in the daylight estimation algorithm. A novel occupancy detection algorithm involving color processing in YCC space has been developed. Our lighting control algorithm is based on the least squares technique. Results of a daylong pilot test show that the system i) can meet different target light-level requirements for different task areas within the field-of-view of the sensor, ii) is unaffected by direct sunlight or a direct view of a light source, iii) detects very small movements within the room, and iv) allows real-time energy monitoring and performance analysis. A discussion of the drawbacks of the current prototype is included along with the technological challenges that will be addressed in the next phase of our research.

Disparity manipulation for stereo images and video

Abstract: We develop a general framework for disparity manipulation and morphing for stereo images and video. The framework consists of three parts: disparity map generation, disparity map manipulating/editing, and stereo image synthesis. We first discuss disparity map generation techniques for different original input data types, including monoscopic images, monoscopic video, stereo image pairs, and stereo video. Then, we describe three methods for user manipulation of the disparity map. In the first, the user employs an interactive object-selecting tool by inputting seed points near the desired object boundary. Given the selected objects, the user defines input-output disparity mapping curves for each object. In the second method, the user arbitrary manipulates a 3D disparity surface and our system calculates the new 3D surface after the user editing. A third method provides conversions between the two common stereo camera capture setups: "toein" and "off-axis" (we present their mathematical description). We show several morphed disparity map examples for each disparity manipulation method. Finally, we describe disparity-based image rendering to synthesize new stereo image pairs from given original stereo image pairs based on a morphed disparity map. The synthesis method includes image warping, data-filling and disparity map smoothing procedures.

An investigation of multispectral imaging for the mapping of pigments in paintings

Abstract: Compared with colorimetric imaging, multispectral imaging has the advantage of retrieving spectral reflectance factor of each pixel of a painting. Using this spectral information, pigment mapping is concerned with decomposing the spectrum into its constituent pigments and their relative contributions. The output of pigment mapping is a series of spatial concentration maps of the pigments comprising the painting. This approach was used to study Vincent van Gogh's The Starry Night. The artist's palette was approximated using ten oil pigments, selected from a large database of pigments used in oil paintings and a priori analytical research on one of his self portraits, executed during the same time period. The pigment mapping was based on single-constant Kubelka-Munk theory. It was found that the region of blue sky where the stars were located contained, predominantly, ultramarine blue while the swirling sky and region surrounding the moon contained, predominantly, cobalt blue. Emerald green, used in light bluish-green brushstrokes surrounding the moon, was not used to create the dark green in the cypresses. A measurement of lead white from Georges Seurat's La Grande Jatte was used as the white when mapping The Starry Night. The absorption and scattering properties of this white were replaced with a modern dispersion of lead white in linseed oil and used to simulate the painting's appearance before the natural darkening and yellowing of lead white oil paint. Pigment mapping based on spectral imaging was found to be a viable and practical approach for analyzing pigment composition, providing new insight into an artist's working method, the possibility for aiding in restorative inpainting, and lighting design.

Anisotropic local high-confidence voting for accurate stereo correspondence

Abstract: We present a local area-based, discontinuity-preserving stereo matching algorithm that achieves high quality results near depth discontinuities as well as in homogeneous regions. To address the well-known challenge of defining appropriate support windows for local stereo methods, we use the anisotropic Local Polynomial Approximation (LPA) - Intersection of Confidence Intervals (ICI) technique. It can adaptively select a nearoptimal anisotropic local neighborhood for each pixel in the image. Leveraging this robust pixel-wise shape-adaptive support window, the proposed stereo method performs a novel matching cost aggregation step and an effective disparity refinement scheme entirely within a local high-confidence voting framework. Evaluation using the benchmark Middlebury stereo database shows that our method outperforms other local stereo methods, and it is even better than some algorithms using advanced but computationally complicated global optimization techniques.

Real-time people counting system using a single video camera

Abstract: There is growing interest in video-based solutions for people monitoring and counting in business and securityapplications. Compared to classic sensor-based solutions the video-based ones allow for more versatile function-alities, improved performance with lower costs. In this paper, we propose a real-time system for people countingbased on single low-end non-calibrated video camera.The two main challenges addressed in this paper are: robust estimation of the scene background and the num-ber of real persons in merge-split scenarios. The latter is likely to occur whenever multiple persons move closely,e.g. in shopping centers. Several persons may be considered to be a single person by automatic segmentationalgorithms, due to occlusions or shadows, leading to under-counting. Therefore, to account for noises, illumina-tion and static objects changes, a background substraction is performed using an adaptive background model(updated over time based on motion information) and automatic thresholding. Furthermore, post-processingof the segmentation results is performed, in the HSV color space, to remove shadows. Moving objects aretracked using an adaptive Kalman “lter, allowing a robust estimation of the objects future positions even underheavy occlusion. The system is implemented in Matlab, and gives encouraging results even at high frame rates.Experimental results obtained based on the PETS2006 datasets are presented at the end of the paper.Keywords: Video analysis, video surveillance, background estimation, segmentation, object tracking

Time-multiplexing display module for high-density directional display

Abstract: The new high-density directional (HDD) display using the time-multiplexing technique is proposed to reduce the complexity of the multi-projection system used for the HDD display. The HDD display is a natural three-dimensional display which has been developed to solve the visual fatigue problem caused by the accommodation-vergence conflict. The proposed HDD display consists of multiple time-multiplexing display modules. Each module consists of an LED array, a DMD, lenses, and an aperture array. A number of directional images are displayed by the DMD at a high frame rate and the LED's emit light one after another in synchronization with the DMD. The apertures are arranged twodimensionally, and their horizontal positions are different. The LED's are arranged in a same way. All directional images displayed by the DMD pass through different apertures. Multiple modules are arranged two-dimensionally with the different horizontal positions and all images are combined by a common lens. A vertical diffuser is used as a display screen to cancel the difference of the vertical display directions. All directional images are superimposed on the vertical diffuser, and are given the different horizontal display directions. Each module generates 15 directional images at a frame rate of 60 Hz. Four modules are combined to display 60 directional images in the different horizontal directions with the angle pitch of 0.31°.

Influence of embedding strategies on security of steganographic methods in the JPEG domain

Abstract: In this paper, we study how specific design principles and elements of steganographic schemes for the JPEG format influence their security. Our goal is to shed some light on how the choice of the embedding operation and domain, adaptive selection channels, and syndrome coding influence statistical detectability. In the experimental part of this paper, the detectability is evaluated using a state-of-the-art blind steganalyzer and the results are contrasted with several adhoc detectability measures, such as the embedding distortion. We also report the first results of our steganalysis of the recently proposed YASS algorithm and compare its security to other steganographic methods for the JPEG format.

Digital Camera Workflow for High Dynamic Range Images Using a Model of Retinal Processing

Abstract: We propose a complete digital camera workflow to capture and render high dynamic range (HDR) static scenes, from RAW sensor data to an output- referred encoded image. In traditional digital camera processing, demosaicing is one of the first operations done after scene analysis. It is followed by rendering operations, such as color correction and tone mapping. Our approach is based on a model of retinal processing of the human visual system (HVS). In the HVS, rendering operations, including adaptation, are performed directly on the cone responses, which corresponds to a mosaic image. Our workflow conforms more closely to the retinal processing model, performing all rendering before demosaicing.. This reduces the complexity of the computation, as only one third of the pixels are processed. This is especially important as our tone mapping operator applies local and global tone corrections, which is usually needed to well render high dynamic scenes. Our algorithms efficiently process HDR images with different keys and different content.

Adaptive DCT-based filtering of images corrupted by spatially correlated noise

Abstract: Majority of image filtering techniques are designed under assumption that noise is of special, a priori known type and it is i.i.d., i.e. spatially uncorrelated. However, in many practical situations the latter assumption is not true due to several reasons. Moreover, spatial correlation properties of noise might be rather different and a priori unknown. Then the assumption that noise is i.i.d. under real conditions of spatially correlated noise commonly leads to considerable decrease of a used filter effectiveness in comparison to a case if this spatial correlation is taken into account. Our paper deals with two basic aspects. The first one is how to modify a denoising algorithm, in particular, a discrete cosine transform (DCT) based filter in order to incorporate a priori or preliminarily obtained knowledge of spatial correlation characteristics of noise. The second aspect is how to estimate spatial correlation characteristics of noise for a given image with appropriate accuracy and robustness under condition that there is some a priori information about, at least, noise type and statistics like variance (for additive noise case) or relative variance (for multiplicative noise). We also present simulation results showing the effectiveness (the benefit) of taking into consideration noise correlation properties.