Showing papers on "Discrete cosine transform published in 2004"

Feature-Based steganalysis for JPEG images and its implications for future design of steganographic schemes

Abstract: In this paper, we introduce a new feature-based steganalytic method for JPEG images and use it as a benchmark for comparing JPEG steganographic algorithms and evaluating their embedding mechanisms. The detection method is a linear classifier trained on feature vectors corresponding to cover and stego images. In contrast to previous blind approaches, the features are calculated as an L1 norm of the difference between a specific macroscopic functional calculated from the stego image and the same functional obtained from a decompressed, cropped, and recompressed stego image. The functionals are built from marginal and joint statistics of DCT coefficients. Because the features are calculated directly from DCT coefficients, conclusions can be drawn about the impact of embedding modifications on detectability. Three different steganographic paradigms are tested and compared. Experimental results reveal new facts about current steganographic methods for JPEGs and new de-sign principles for more secure JPEG steganography.

Transform-domain Wyner-Ziv codec for video

Abstract: In current interframe video compression systems, the encoder performs predictive coding to exploit the similarities of successive frames. The Wyner-Ziv Theorem on source coding with side information available only at the decoder suggests that an asymmetric video codec, where individual frames are encoded separately, but decoded conditionally (given temporally adjacent frames) could achieve similar efficiency. We propose a transformdomain Wyner-Ziv coding scheme for motion video that uses intraframe encoding, but interframe decoding. In this system, the transform coefficients of a Wyner-Ziv frame are encoded independently using a scalar quantizer and turbo coder. The decoder uses previously reconstructed frames to generate side information to conditionally decode the Wyner-Ziv frames. Simulation results show significant gains above DCT-based intraframe coding and improvements over the pixel-domain Wyner-Ziv video coder.

Statistical tools for digital forensics

Abstract: A digitally altered photograph, often leaving no visual clues of having been tampered with, can be indistinguishable from an authentic photograph. As a result, photographs no longer hold the unique stature as a definitive recording of events. We describe several statistical techniques for detecting traces of digital tampering in the absence of any digital watermark or signature. In particular, we quantify statistical correlations that result from specific forms of digital tampering, and devise detection schemes to reveal these correlations.

Efficient, low-complexity image coding with a set-partitioning embedded block coder

Abstract: We propose an embedded, block-based, image wavelet transform coding algorithm of low complexity. It uses a recursive set-partitioning procedure to sort subsets of wavelet coefficients by maximum magnitude with respect to thresholds that are integer powers of two. It exploits two fundamental characteristics of an image transform-the well-defined hierarchical structure, and energy clustering in frequency and in space. The two partition strategies allow for versatile and efficient coding of several image transform structures, including dyadic, blocks inside subbands, wavelet packets, and discrete cosine transform (DCT). We describe the use of this coding algorithm in several implementations, including reversible (lossless) coding and its adaptation for color images, and show extensive comparisons with other state-of-the-art coders, such as set partitioning in hierarchical trees (SPIHT) and JPEG2000. We conclude that this algorithm, in addition to being very flexible, retains all the desirable features of these algorithms and is highly competitive to them in compression efficiency.

Feature-based steganalysis for JPEG images and its implications for future design of steganographic schemes

Abstract: In this paper, we introduce a new feature-based steganalytic method for JPEG images and use it as a benchmark for comparing JPEG steganographic algorithms and evaluating their embedding mechanisms. The detection method is a linear classifier trained on feature vectors corresponding to cover and stego images. In contrast to previous blind approaches, the features are calculated as an L 1 norm of the difference between a specific macroscopic functional calculated from the stego image and the same functional obtained from a decompressed, cropped, and recompressed stego image. The functionals are built from marginal and joint statistics of DCT coefficients. Because the features are calculated directly from DCT coefficients, conclusions can be drawn about the impact of embedding modifications on detectability. Three different steganographic paradigms are tested and compared. Experimental results reveal new facts about current steganographic methods for JPEGs and new design principles for more secure JPEG steganography.

A face and palmprint recognition approach based on discriminant DCT feature extraction

Abstract: In the field of image processing and recognition, discrete cosine transform (DCT) and linear discrimination are two widely used techniques. Based on them, we present a new face and palmprint recognition approach in this paper. It first uses a two-dimensional separability judgment to select the DCT frequency bands with favorable linear separability. Then from the selected bands, it extracts the linear discriminative features by an improved Fisherface method and performs the classification by the nearest neighbor classifier. We detailedly analyze theoretical advantages of our approach in feature extraction. The experiments on face databases and palmprint database demonstrate that compared to the state-of-the-art linear discrimination methods, our approach obtains better classification performance. It can significantly improve the recognition rates for face and palmprint data and effectively reduce the dimension of feature space.

Perception-motivated high dynamic range video encoding

Abstract: Due to rapid technological progress in high dynamic range (HDR) video capture and display, the efficient storage and transmission of such data is crucial for the completeness of any HDR imaging pipeline. We propose a new approach for inter-frame encoding of HDR video, which is embedded in the well-established MPEG-4 video compression standard. The key component of our technique is luminance quantization that is optimized for the contrast threshold perception in the human visual system. The quantization scheme requires only 10--11 bits to encode 12 orders of magnitude of visible luminance range and does not lead to perceivable contouring artifacts. Besides video encoding, the proposed quantization provides perceptually-optimized luminance sampling for fast implementation of any global tone mapping operator using a lookup table. To improve the quality of synthetic video sequences, we introduce a coding scheme for discrete cosine transform (DCT) blocks with high contrast. We demonstrate the capabilities of HDR video in a player, which enables decoding, tone mapping, and applying post-processing effects in real-time. The tone mapping algorithm as well as its parameters can be changed interactively while the video is playing. We can simulate post-processing effects such as glare, night vision, and motion blur, which appear very realistic due to the usage of HDR data.

Flipping structure: an efficient VLSI architecture for lifting-based discrete wavelet transform

Abstract: In this paper, an efficient very large scale integration (VLSI) architecture, called flipping structure, is proposed for the lifting-based discrete wavelet transform. It can provide a variety of hardware implementations to improve and possibly minimize the critical path as well as the memory requirement of the lifting-based discrete wavelet transform by flipping conventional lifting structures. The precision issues are also analyzed. By case studies of the JPEG2000 default lossy (9,7) filter, an integer (9,7) filter, and the (6,10) filter, the efficiency of the proposed flipping structure is demonstrated.

Compressing historical information in sensor networks

Abstract: We are inevitably moving into a realm where small and inexpensive wireless devices would be seamlessly embedded in the physical world and form a wireless sensor network in order to perform complex monitoring and computational tasks. Such networks pose new challenges in data processing and dissemination because of the limited resources (processing, bandwidth, energy) that such devices possess. In this paper we propose a new technique for compressing multiple streams containing historical data from each sensor. Our method exploits correlation and redundancy among multiple measurements on the same sensor and achieves high degree of data reduction while managing to capture even the smallest details of the recorded measurements. The key to our technique is the base signal, a series of values extracted from the real measurements, used for encoding piece-wise linear correlations among the collected data values. We provide efficient algorithms for extracting the base signal features from the data and for encoding the measurements using these features. Our experiments demonstrate that our method by far outperforms standard approximation techniques like Wavelets. Histograms and the Discrete Cosine Transform, on a variety of error metrics and for real datasets from different domains.

Blocking artifacts suppression in block-coded images using overcomplete wavelet representation

Abstract: It is well known that at low-bit-rate block discrete cosine transform compressed image exhibits visually annoying blocking and ringing artifacts. In this paper, we propose a noniterative, wavelet-based deblocking algorithm to reduce both types of artifacts. The algorithm exploits the fact that block discontinuities are constrained by the dc quantization interval of the quantization table, as well as the behavior of wavelet modulus maxima evolution across wavelet scales to derive appropriate threshold maps at different wavelet scales. Since ringing artifacts occur near strong edges, which can be located either along block boundaries or within blocks, suppression of block discontinuities does not always reduce ringing artifacts. By exploiting the behavior of ringing artifacts in the wavelet domain, we propose a simple yet effective method for the suppression of such artifacts. The proposed algorithm can suppress both block discontinuities and ringing artifacts effectively while preserving true edges and textural information. Simulation results and extensive comparative study with both iterative and noniterative methods reported in the literature have shown the effectiveness of our algorithm.

MPEG Video Encryption Algorithms

Abstract: Multimedia data security is important for multimedia commerce. Previous cryptography studies have focused on text data. The encryption algorithms developed to secure text data may not be suitable to multimedia applications because of the large data size and real time constraint. For multimedia applications, light weight encryption algorithms are attractive. We present four fast MPEG video encryption algorithms. These algorithms use a secret key to randomly change the sign bits of Discrete Cosine Transform (DCT) coefficients and/or the sign bits of motion vectors. The encryption is accomplished by the inverse DCT (IDCT) during the MPEG video decompression processing. These algorithms add a small overhead to MPEG codec. Software implementations are fast enough to meet the real time requirement of MPEG video applications. The experimental results show that these algorithms achieve satisfactory results. They can be used to secure video-on-demand, video conferencing, and video email applications.

No reference PSNR estimation for compressed pictures

Abstract: Many user-end applications require an estimate of the quality of coded video or images without having access to the original, i.e. a no-reference quality metric. Furthermore, in many such applications the compressed video bitstream is also not available. This paper describes methods for using the statistical properties of intra coded video data to estimate the quantization error caused by compression without accessing either the original pictures or the bitstream. We derive closed form expressions for the quantization error in coding schemes based on the discrete cosine transform and block based coding. A commonly used quality metric, the peak signal to noise ratio (PSNR) is subsequently computed from the estimated quantization error. Since quantization error is the most significant loss incurred during typical coding schemes, the estimated PSNR, or any PSNR-based quality metric may be used to gauge the overall quality of the pictures.

Image enhancement in the JPEG domain for people with vision impairment

Abstract: An image enhancement algorithm for low-vision patients was developed for images compressed using the JPEG standard. The proposed algorithm enhances the images in the discrete cosine transform domain by weighting the quantization table in the decoder. Our specific implementation increases the contrast at all bands of frequencies by an equal factor. The enhancement algorithm has four advantages: 1) low computational cost; 2) suitability for real-time application; 3) ease of adjustment by end-users (for example, adjusting a single parameter); and 4) less severe block artifacts as compared with conventional (post compression) enhancements. Experiments with visually impaired patients show improved perceived image quality at moderate levels of enhancement but rejection of artifacts caused by higher levels of enhancement.

Scalable variable complexity approximate forward DCT

Abstract: The discrete cosine transform (DCT) is one of the major components in most of image and video compression systems. The variable complexity algorithm framework has been applied successfully to achieve complexity savings in the computation of the inverse DCT in decoders. These gains can be achieved due to the highly predictable sparseness of the quantized DCT coefficients in natural image/video data. With the increasing demand for instant video messaging and two-way video transmission over mobile communication systems running on general-purpose embedded processors, the encoding complexity needs to be optimized. In this paper, we focus on complexity reduction techniques for the forward DCT, which is one of the more computationally intensive tasks in the encoder. Unlike the inverse DCT, the forward DCT does not operate on sparse input data, but rather generates sparse output data. Thus, complexity reduction must be obtained using different methods from those used for the inverse DCT. In the literature, two major approaches have been applied to speed up the forward DCT computation, namely, frequency selection, in which only a subset of DCT coefficients is computed, and accuracy selection, in which all the DCT coefficients are computed with reduced accuracy. These two approaches can achieve significant computation savings with minor output quality degradation, as long as the coding parameters are such that the quantization error is larger than the error due to the approximate DCT computation. Thus, in order to be useful, these algorithms have to be combined using an efficient mechanism that can select the "right" level of approximation as a function of the characteristics of the input and the target rate, a selection that is often based on heuristic criteria. In this paper, we consider two previously proposed fast, variable complexity, forward DCT algorithms, one based on frequency selection, the other based on accuracy selection. We provide an explicit analysis of the additional distortion that each scheme introduces as a function of the quantization parameter and the variance of the input block. This analysis then allows us to improve the performance of these algorithms by making it possible to select the best approximation level for each block and a target quantization parameter. We also propose a hybrid algorithm that combines both forms of complexity reduction in order to achieve overall better performance over a broader range of operating rates. We show how our techniques lead to scalable implementations where complexity can be reduced if needed, at the cost of small reductions in video quality. Our hybrid algorithm can speed up the DCT and quantization process by close to a factor of 4 as compared to fixed-complexity forward DCT implementations, with only a slight quality degradation in PSNR.

Semi-fragile watermarking scheme for authentication of JPEG images

Abstract: With the increasing popularity of JPEG images, a need arises to devise effective watermarking techniques which consider JPEG compression as an acceptable manipulation. In this paper, we present a semi-fragile watermarking scheme which embeds a watermark in the quantized DCT domain. It is tolerant to JPEG compression to a pre-determined lowest quality factor, but is sensitive to all other malicious attacks, either in spatial or transform domains. Feature codes are extracted based on the relative sign and magnitudes of coefficients, and these are invariant due to an important property of JPEG compression. The employment of a nine-neighborhood mechanism ensures that non-deterministic block-wise dependence is achieved. Analysis and experimental results are provided to support the effectiveness of the scheme.

Rapid MR Imaging with "Compressed Sensing" and Randomly Under-Sampled 3DFT Trajectories

Abstract: M. Lustig, D. L. Donoho, J. M. Pauly Electrical Engineering, Stanford University, Stanford, CA, United States, Statistics, Stanford University, Stanford, CA, United States Introduction Recently a rapid imaging method was proposed [1] that exploits the fact that sparse or compressible signals, such as MR images, can be recovered from randomly under-sampled frequency data [1,2,3]. Because pure random sampling in 2D is impractical for MRI hardware, it was proposed to use randomly perturbed spirals to approximate random sampling. Indeed, pure 2D random sampling is impractical, however, randomly undersampling the phase encodes in a 3D Cartesian scan (Fig. 1) is practical, involves no overhead, is simple to implement and is purely random in two dimensions. Moreover, scan-time reduction in 3D Cartesian scans is always an issue. We provide a method to evaluate the effective randomness of a randomly under-sampled trajectory by analyzing the statistics of aliasing in the sparse transform domain. Applying this method to MR angiography, where images are truly sparse, we demonstrate a 5fold scan time reduction, which can be crucial in time-limited situations or can be used for time resolved imaging Theory Medical images in general, and specifically angiograms, often have a sparse representation using a linear transform (wavelets, DCT, finite differences, etc.)[1]. Under-sampling the Fourier domain results in aliasing. When the under-sampling is random, the aliasing is incoherent and acts as additional noise interference in the image, but more importantly, as incoherent interference of the sparse transform coefficients. Therefore, it is possible to recover the sparse transform coefficients using a non-linear reconstruction scheme [1-4] and consequently, recover the image itself. The interference in the sparse domain is a generalization of a point-spread function (PSF) and is computed by I(n,m)= where xn is the n th

Super-resolution reconstruction of compressed video using transform-domain statistics

Abstract: Considerable attention has been directed to the problem of producing high-resolution video and still images from multiple low-resolution images. This multiframe reconstruction, also known as super-resolution reconstruction, is beginning to be applied to compressed video. Super-resolution techniques that have been designed for raw (i.e., uncompressed) video may not be effective when applied to compressed video because they do not incorporate the compression process into their models. The compression process introduces quantization error, which is the dominant source of error in some cases. In this paper, we propose a stochastic framework where quantization information as well as other statistical information about additive noise and image prior can be utilized effectively.

Low-power multiplierless DCT architecture using image correlation

Abstract: Low-power design is one of the most important challenges to maximize battery life in portable devices and to save the energy during system operation. In this paper, we propose a low-power DCT (discrete cosine transform) architecture using a modified multiplierless CORDIC (coordinate rotation digital computer) arithmetic. The switching power consumption is reduced during DCT: the proposed architecture does not perform arithmetic operations of unnecessary bits during the CORDlC calculations. The experiment results show that we can reduce up to 26.1% power dissipation without compromise of the final DCT results. Also, the speed of the proposed architecture is increased about 10%. The proposed low-power DCT architecture can be applied to consumer electronics and portable multimedia systems requiring high throughput and low-power.

A novel DCT-based approach for secure color image watermarking

Abstract: We focus on visually meaningful color image watermarks, we construct a new digital watermarking scheme based on the discrete cosine transformation. The proposed method uses the sensitivity of human eyes to adoptively embed a watermark in a color image. In addition, to prevent tampering or unauthorized access, a new watermark permutation function is proposed, which causes a structural noise over the extracted watermark. Also, we have proposed a procedure to eliminate this noise to decrease false positives and false negatives in the extracted watermark. The experimental results show that embedding the color watermark adapted to the original image produces the most imperceptible and the most robust watermarked image under geometric and volumetric attacks.

MDCT analysis of sinusoids: exact results and applications to coding artifacts reduction

Abstract: Although widely used in many coding applications, the Modified Discrete Cosine Transform (MDCT) has the drawback of being sensitive to time shifts. With the popular choice of a sine window, we show that it is possible to compute an explicit formulation of this time dependency. Starting from the exact MDCT of a pure sine and a simple interpretation in terms of combined modulations, we propose a regularization method that computes a "pseudo-spectrum" for the set of MDCT coefficients. This pseudo-spectrum is shown to provide, at a low computational cost, a good approximation of the local spectrum of the signal, with an improved behavior with respect to frequency and phase than the classical MDCT spectrum, ie. the absolute value of the coefficients. Amongst other applications, this procedure can be used to reduce some of the artifacts that appear in MDCT-based audio coders at low bit-rates.

Design and Analysis of a High-Rate Acoustic Link for Underwater Video Transmission

Abstract: A high bit rate acoustic link for underwater video transmission is examined. Currently, encoding standards support video transmission at bit rates as low as 64 kbps. While this rate is still above the limit of commercially available acoustic modems, prototype acoustic modems based on phase coherent modulation/detection have demonstrated successful transmission at 30 kbps over a deep water channel. The key to bridging the remaining gap between the bit-rate needed for video transmission and that supported by the acoustic channel lies in two approaches: use of efficient image/video compression algorithms and use of high-level bandwidth-efficient modulation methods. An experimental system, based on discrete cosine transform (DCT) and Huffman entropy coding for image compression, and variable rate M-ary quadrature amplitude modulation (QAM) was implemented. Phase-coherent equalization is accomplished by joint operation of a decision feedback equalizer (DFE) and a second order phase locked loop (PLL). System performance is demonstrated experimentally, using transmission rate of 25000 symbols/sec at a carrier frequency of 75 kHz over a 10 m vertical path. Excellent results were obtained, thus demonstrating bit rates as high as 150 kbps, which are sufficient for real-time transmission of compressed video. As an alternative to conventional QAM signaling, whose high-level constellations are sensitive to phase distortions induced by the channel, M-ary differential amplitude and phase shift keying (DAPSK) was used. DAPSK does not require explicit carrier phase synchronization at the receiver, but instead relies on simple differentially coherent detection. Receiver processing includes a linear equalizer whose coefficients are adjusted using a modified linear least square (LMS) algorithm. Simulation results confirm good performance of the differentially coherent equalization scheme employed. Thesis Supervisor: Milica Stojanovic Title: Principal Scientist, MIT Sea Grant College Program

Low power design of DCT and IDCT for low bit rate video codecs

Abstract: This paper examines low power design techniques for discrete cosine transform (DCT) and inverse discrete cosine transform (IDCT) circuits applicable for low bit rate wireless video systems. The techniques include skipping DCT computation of low energy macroblocks, skipping IDCT computation of blocks with all coefficients equal to zero, using lower precision constant multipliers, gating the clock, and reducing transitions in the data path. The proposed DCT and IDCT circuits reduce power dissipation by, on average, 94% over baseline reference circuits.

A hidden Markov model framework for traffic event detection using video features

Abstract: A novel approach for highway traffic event detection in video is presented. The proposed algorithm extracts event features directly from compressed video and detects traffic event using a Gaussian mixture hidden Markov model (GMHMM). First, an invariant feature vector is extracted from discrete cosine transform (DCT) domain and macro-block vectors after MPEG video stream is parsed. The extracted feature vector accurately describes the change of traffic state and is robust towards different camera setups and illumination situations, such as sunny, cloud, and night. Six traffic patterns are studied and a GMHMM is trained to model these patterns in offline stage. Then, Viterbi algorithm is used to determine the most likely traffic condition. The proposed algorithm is efficient both in terms of computational complexity and memory requirement. The experimental results prove the system has a high detection rate. The presented model based system can be easily extended for detection of similar traffic events.

Simultaneous storage of medical images in the spatial and frequency domain: A comparative study

Abstract: Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient.

New cost-effective VLSI implementation of a 2-D discrete cosine transform and its inverse

Abstract: This paper first reviewed the two-dimensional discrete cosine transform (2-D DCT) and inverse DCT (IDCT) architectures. Then a new VLSI architecture, namely the transpose free row column decomposition method (TF-RCDM), for 2-D DCT/IDCT is proposed. The new RCDM architecture replaces the transpose circuits with permutation networks and parallel memory modules. As results, the timing overhead of I/O operations is eliminated and the hardware complexity is largely reduced. An accuracy testing system is designed to find the optimum word-length parameters. Based on the accuracy testing system, the proposed architecture has achieved the smallest word-length among the reported 2-D DCT architectures. Synthesis results showed that with 0.25-/spl mu/m CMOS technology library, the area was about 1.5 mm/sup 2/ and the speed was about 125 MHz.