Showing papers in "IEEE Signal Processing Magazine in 2003"
TL;DR: The goal of this article is to introduce the concept of SR algorithms to readers who are unfamiliar with this area and to provide a review for experts to present the technical review of various existing SR methodologies which are often employed.
Abstract: A new approach toward increasing spatial resolution is required to overcome the limitations of the sensors and optics manufacturing technology. One promising approach is to use signal processing techniques to obtain an high-resolution (HR) image (or sequence) from observed multiple low-resolution (LR) images. Such a resolution enhancement approach has been one of the most active research areas, and it is called super resolution (SR) (or HR) image reconstruction or simply resolution enhancement. In this article, we use the term "SR image reconstruction" to refer to a signal processing approach toward resolution enhancement because the term "super" in "super resolution" represents very well the characteristics of the technique overcoming the inherent resolution limitation of LR imaging systems. The major advantage of the signal processing approach is that it may cost less and the existing LR imaging systems can be still utilized. The SR image reconstruction is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, including medical imaging, satellite imaging, and video applications. The goal of this article is to introduce the concept of SR algorithms to readers who are unfamiliar with this area and to provide a review for experts. To this purpose, we present the technical review of various existing SR methodologies which are often employed. Before presenting the review of existing SR algorithms, we first model the LR image acquisition process.
3,491 citations
Journal Article•
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TL;DR: This work presents a brief review of particle filtering theory and shows how it can be used for resolving many problems in wireless communications, and demonstrates its application to blind equalization, blind detection over flat fading channels, multiuser detection, and estimation and detection of space-time codes in fading channels.
Abstract: Recent developments have demonstrated that particle filtering is an emerging and powerful methodology, using Monte Carlo methods, for sequential signal processing with a wide range of applications in science and engineering. It has captured the attention of many researchers in various communities, including those of signal processing, statistics and econometrics. Based on the concept of sequential importance sampling and the use of Bayesian theory, particle filtering is particularly useful in dealing with difficult nonlinear and non-Gaussian problems. The underlying principle of the methodology is the approximation of relevant distributions with random measures composed of particles (samples from the space of the unknowns) and their associated weights. First, we present a brief review of particle filtering theory; and then we show how it can be used for resolving many problems in wireless communications. We demonstrate its application to blind equalization, blind detection over flat fading channels, multiuser detection, and estimation and detection of space-time codes in fading channels.
786 citations
TL;DR: This article emphasizes the processing that is done on the luminance components of the video, and provides an overview of the techniques used for bit-rate reduction and the corresponding architectures that have been proposed.
Abstract: Throughout this article, we concentrate on the transcoding of block-based video coding schemes that use hybrid discrete cosine transform (DCT) and motion compensation (MC). In such schemes, the frames of the video sequence are divided into macroblocks (MBs), where each MB typically consists of a luminance block (e.g., of size 16 /spl times/ 16, or alternatively, four 8 /spl times/ 8 blocks) along with corresponding chrominance blocks (e.g., 8 /spl times/ 8 Cb and 8 /spl times/ 8 Cr). This article emphasizes the processing that is done on the luminance components of the video. In general, the chrominance components can be handled similarly and will not be discussed in this article. We first provide an overview of the techniques used for bit-rate reduction and the corresponding architectures that have been proposed. Then, we describe the advances regarding spatial and temporal resolution reduction techniques and architectures. Additionally, an overview of error resilient transcoding is also provided, as well as a discussion of scalable coding techniques and how they relate to video transcoding. Finally, the article ends with concluding remarks, including pointers to other works on video transcoding that have not been covered in this article, as well as some future directions.
736 citations
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TL;DR: The sliding DFT process for spectrum analysis was presented and shown to be more efficient than the popular Goertzel (1958) algorithm for sample-by-sample DFT bin computations and a modified slide DFT structure is proposed that provides improved computational efficiency.
Abstract: The sliding DFT process for spectrum analysis was presented and shown to be more efficient than the popular Goertzel (1958) algorithm for sample-by-sample DFT bin computations. The sliding DFT provides computational advantages over the traditional DFT or FFT for many applications requiring successive output calculations, especially when only a subset of the DFT output bins are required. Methods for output stabilization as well as time-domain data windowing by means of frequency-domain convolution were also discussed. A modified sliding DFT algorithm, called the sliding Goertzel DFT, was proposed to further reduce the computational workload. We start our sliding DFT discussion by providing a review of the Goertzel algorithm and use its behavior as a yardstick to evaluate the performance of the sliding DFT technique. We examine stability issues regarding the sliding DFT implementation as well as review the process of frequency-domain convolution to accomplish time-domain windowing. Finally, a modified sliding DFT structure is proposed that provides improved computational efficiency.
630 citations
TL;DR: The SR image reconstruction method estimates an HR image with finer spectral details from multiple LR observations degraded by blur, noise, and aliasing, and the major advantage of this approach is that it may cost less and the existing LR imaging systems can still be utilized.
Abstract: The spatial resolution that represents the number of pixels per unit area in an image is the principal factor in determining the quality of an image. With the development of image processing applications, there is a big demand for high-resolution (HR) images since HR images not only give the viewer a pleasing picture but also offer additional detail that is important for the analysis in many applications. The current technology to obtain HR images mainly depends on sensor manufacturing technology that attempts to increase the number of pixels per unit area by reducing the pixel size. However, the cost for high-precision optics and sensors may be inappropriate for general purpose commercial applications, and there is a limitation to pixel size reduction due to shot noise encountered in the sensor itself. Therefore, a resolution enhancement approach using signal processing techniques has been a great concern in many areas, and it is called super-resolution (SR) (or HR) image reconstruction or simply resolution enhancement in the literature. In this issue, we use the term “SR image reconstruction” to refer to a signal processing approach toward resolution enhancement, because the term “super” very well represents the characteristics of the technique overcoming the inherent resolution limitation of low-resolution (LR) imaging systems. The term SR was originally used in optics, and it refers to the algorithms that mainly operate on a single image to extrapolate the spectrum of an object beyond the diffraction limit (SR restoration). These two SR concepts (SR reconstruction and SR restoration) have a common focus in the aspect of recovering high-frequency information that is lost or degraded during the image acquisition. However, the cause of the loss of high-frequency information differs between these two concepts. SR restoration in optics attempts to recover information beyond the diffraction cutoff frequency, while the SR reconstruction method in engineering tries to recover high-frequency components corrupted by aliasing. We hope that readers do not confuse the super resolution in this issue with the term super resolution used in optics. SR image reconstruction algorithms investigate the relative motion information between multiple LR images (or a video sequence) and increase the spatial resolution by fusing them into a single frame. In doing so, it also removes the effect of possible blurring and noise in the LR images. In summary, the SR image reconstruction method estimates an HR image with finer spectral details from multiple LR observations degraded by blur, noise, and aliasing. The major advantage of this approach is that it may cost less and the existing LR imaging systems can still be utilized. Considering the maturity of this field and its various prospective applications, it seems timely and appropriate to discuss and adjust the topic of SR in the special issue of the magazine, since we do not have enough materials for ready disposal. This special section contains five articles covering various aspects of SR techniques. The first article, “Super-Resolution Image Reconstruction: A Technical Overview” by Sungcheol Park, Minkyu Park, and Moon Gi Kang, provides an introduction to the concepts and definitions of the SR image reconstruction as well as an overview of various existing SR algorithms. Advanced issues that are currently under investigation in this area are also discussed. The second article, “High-Resolution Images from Low-Resolution Compressed Video,” by Andrew C. Segall, Rafael Molina, and Aggelos K. Katsaggelos, considers the SR techniques for compressed video. Since images are routinely compressed prior to transmission and storage in current acquisition systems, it is important to take into account the characteristics of compression systems in developing the SR techniques. In this article, they survey models for the compression system and develop SR techniques within the Bayesian framework. The third article, by Deepu Rajan, Subhasis Chaudhuri, and Manjunath V. Joshi, titled “Multi-Objective Super-Resolution Technique: Concept and Examples,”
422 citations
TL;DR: The two key components that are necessary for successful SR restoration are described: the accurate alignment or registration of the LR images and the formulation of an SR estimator that uses a generative image model together with a prior model of the super-resolved image itself.
Abstract: Super-resolution (SR) restoration aims to solve the following problem: given a set of observed images, estimate an image at a higher resolution than is present in any of the individual images. Where the application of this technique differs in computer vision from other fields is in the variety and severity of the registration transformation between the images. In particular this transformation is generally unknown, and a significant component of solving the SR problem in computer vision is the estimation of the transformation. The transformation may have a simple parametric form, or it may be scene dependent and have to be estimated for every point. In either case the transformation is estimated directly and automatically from the images. We describe the two key components that are necessary for successful SR restoration: the accurate alignment or registration of the LR images and the formulation of an SR estimator that uses a generative image model together with a prior model of the super-resolved image itself. As with many other problems in computer vision, these different aspects are tackled in a robust, statistical framework.
296 citations
Journal Article•
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TL;DR: The presented book the authors offer here is not kind of usual book, but the book that it is proffer is the soft file of the book, which will precisely be profitable.
Abstract: The presented book we offer here is not kind of usual book. You know, reading now doesn't mean to handle the printed book in your hand. You can get the soft file of digital halftoning in your gadget. Well, we mean that the book that we proffer is the soft file of the book. The content and all things are same. The difference is only the forms of the book, whereas, this condition will precisely be profitable.
215 citations
TL;DR: The attainment of super resolution (SR) from a sequence of degraded undersampled images could be viewed as reconstruction of the high-resolution (HR) image from a finite set of its projections on a sampling lattice as an optimization problem whose solution is obtained by minimizing a cost function.
Abstract: The attainment of super resolution (SR) from a sequence of degraded undersampled images could be viewed as reconstruction of the high-resolution (HR) image from a finite set of its projections on a sampling lattice. This can then be formulated as an optimization problem whose solution is obtained by minimizing a cost function. The approaches adopted and their analysis to solve the formulated optimization problem are crucial, The image acquisition scheme is important in the modeling of the degradation process. The need for model accuracy is undeniable in the attainment of SR along with the design of the algorithm whose robust implementation will produce the desired quality in the presence of model parameter uncertainty. To keep the presentation focused and of reasonable size, data acquisition with multisensors instead of, say a video camera is considered.
204 citations
TL;DR: An overview of the most recent progress achieved in the design of an efficient BCI system in multimedia applications is provided, with an emphasis on signal processing aspects.
Abstract: This article raises various issues in the design of an efficient BCI system in multimedia applications. The main focus is on one specific modality, namely an electroencephalography (EEG)-based BCI. In doing so, we provide an overview of the most recent progress achieved in this field, with an emphasis on signal processing aspects.
156 citations
TL;DR: This survey surveys the field of super resolution (SR) processing for compressed video and develops and presents all techniques within the Bayesian framework, and surveys models for the acquisition and compression systems.
Abstract: Surveys the field of super resolution (SR) processing for compressed video The introduction of motion vectors, compression noise, and additional redundancies within the image sequence makes this problem fertile ground for novel processing methods In conducting this survey, though, we develop and present all techniques within the Bayesian framework This adds consistency to the presentation and facilitates comparison between the different methods The article is organized as follows We define the acquisition system utilized by the surveyed procedures Then we formulate the HR problem within the Bayesian framework and survey models for the acquisition and compression systems This requires consideration of both the motion vectors and transform coefficients within the compressed bit stream We survey models for the original HR image intensities and displacement values We discuss solutions for the SR problem and provide examples of several approaches
139 citations
TL;DR: The current status of universal multimedia access (UMA) technologies is discussed and future directions in this area are investigated and key developments and trends from the last few years have set the scene for ubiquitous multimedia consumption.
Abstract: The previous decade has seen a variety of trends and developments in the area of communications and thus multimedia access. While individual, isolated developments produced small advances on the status quo, their combination and cross-fertilization resulted in today's complex but exciting landscape. In particular, we are beginning to see delivery of all types of data for all types of users in all types of conditions. This article discusses the current status of universal multimedia access (UMA) technologies and investigates future directions in this area. Key developments and trends from the last few years have set the scene for ubiquitous multimedia consumption. In summary, these are: wireless communications and mobility; standardized multimedia content; interactive versus passive consumption; and the Internet and the World Wide Web (WWW).
TL;DR: Methods that support UMA and the tools provided by MPEG-7 to achieve this are discussed, including segmentation and summarization of audio video (AV) content, and finally, transcoding of AV content.
Abstract: With the growing ubiquity and mobility of multimedia-enabled devices, universal multimedia access (UMA) is emerging as one of the important components for the next generation of multimedia applications. The basic concept underlying UMA is universal or seamless access to multimedia content, by automatic selection and adaptation of content based on the user's environment. UMA promises an integration of these different perspectives into a new class of content adaptive applications that could allow users to access multimedia content without concern for specific coding formats, terminal capabilities, or network conditions. We discuss methods that support UMA and the tools provided by MPEG-7 to achieve this. We also discuss the inclusion of metadata in JPEG 2000 encoded images. We present these methods in the typical order that they may be used in an actual application. Therefore, we first discuss the (personalized) selection of desired content from all available content, followed by the organization of related variations of a single piece of content. Then, we discuss segmentation and summarization of audio video (AV) content, and finally, transcoding of AV content.
TL;DR: UMA is one of the use cases that has led to the creation of a new part in MPEG-21 dealing with digital item adaptation and an overview of MPEG- 21 related activities and an outlook on future developments is given.
Abstract: The lack of interoperable (and thus standardized) solutions is stalling the deployment of advanced multimedia packaging and distribution applications although most of the individual technologies are indeed already present. This motivated MPEG (ISO/IEC JTCl SC29 WGI I) in June 2000 to start working on the definition of enabling normative technology for the multimedia applications of the 21st century: MPEG-21 "Multimedia Framework." MPEG-21's approach is to define a framework to support transactions that are interoperable and highly automated, specifically taking into account digital rights management (DRM) requirements and targeting multimedia access and delivery using heterogeneous networks and terminals. This article first outlines the context and background of the MPEG-21 initiative. Then, an overview of MPEG-21 technology is given. Subsequently, it is discussed how MPEG-21 can provide solutions for universal multimedia access (UMA). UMA is also one of the use cases that has led to the creation of a new part in MPEG-21 dealing with digital item adaptation. Finally, this article concludes with an overview of MPEG-21 related activities and an outlook on future developments.
TL;DR: The basic spatial and spectral characteristics of blue- and green-noise halftoning models are reviewed, and some of the earlier work done to improve error diffusion as a noise generator is reviewed.
Abstract: In this article, we review the spatial and spectral characteristics of blue- and green-noise halftoning models. In the case of blue noise, dispersed-dot dither patterns are constructed by isolating minority pixels as homogeneously as possible, and by doing so, a pattern composed exclusively of high-frequency spectral components is produced. Blue-noise halftoning is preferred for display devices that can accommodate isolated dots such as various video displays and some print technologies such as ink-jet. For print marking engines that cannot support isolated pixels, dispersed-dot halftoning is inappropriate. For such cases, clustered-dot halftoning is used to avoid dot-gain instability. Green-noise halftones are clustered-dot, blue-noise patterns. Such patterns enjoy the blue-noise properties of homogeneity and lack low-frequency texture but have clusters of minority pixels on blue-noise centers. Green noise is composed exclusively of midfrequency spectral components. In addition to the basic spatial and spectral characteristics of the halftoning models, this article also reviews some of the earlier work done to improve error diffusion as a noise generator. We also discuss processes to generate threshold arrays to achieve blue and green noise with the computationally efficient process of ordered dither.
TL;DR: This work develops a unified framework for explaining, analyzing, and extending signal processing methods based on GMANOVA and shows the applicability of this framework to a number of detection and estimation problems in signal processing and communications and provides new and simple ways to derive numerous existing algorithms.
Abstract: Generalized multivariate analysis of variance (GMANOVA) and related reduced-rank regression are general statistical models that comprise versions of regression, canonical correlation, and profile analyses as well as analysis of variance (ANOVA) and covariance in univariate and multivariate settings. It is a powerful and, yet, not very well-known tool. We develop a unified framework for explaining, analyzing, and extending signal processing methods based on GMANOVA. We show the applicability of this framework to a number of detection and estimation problems in signal processing and communications and provide new and simple ways to derive numerous existing algorithms. Many of the methods were originally derived "from scratch", without knowledge of their close relationship with the GMANOVA model. We explicitly show this relationship and present new insights and guidelines for generalizing these methods. Our results could inspire applications of the general framework of GMANOVA to new problems in signal processing. We present such an application to flaw detection in nondestructive evaluation (NDE) of materials. A promising area for future growth is image processing.
TL;DR: Two methods for simultaneously generating the super-resolved depth map and the image from LR observations are described, which avoids correspondence and warping problems inherent in current SR techniques involving the motion cue in the LR observations and uses a more natural depth-related defocus as a natural cue in real aperture imaging.
Abstract: Described methods for simultaneously generating the super-resolved depth map and the image from LR observations. Structural information is embedded within the observations and, through the two formulations of DFD and SFS problems, we were able to generate the super-resolved images and the structures. The first method described here avoids correspondence and warping problems inherent in current SR techniques involving the motion cue in the LR observations and uses a more natural depth-related defocus as a natural cue in real aperture imaging. The second method, while again avoiding the correspondence problems, also demonstrates the usefulness of the generalized interpolation scheme leading to more flexibility in the final SR image, in the sense that the LR image can be viewed at SR with an arbitrary light source position. The quality of the super-resolved depth and intensity maps has been found to be quite good. The MAP-MRF framework that was used in both methods models both the surface normal and the intensity field as separate MRFs, and this helps in regularizing the solution.
TL;DR: B batch processing algorithms for blind equalization using higher-order statistics for mitigation of the ISI induced by single-input, single-output channels as well as of both the ISI and MAI induced by multiple- input, multiple- output channels are reviewed.
Abstract: Statistical signal processing has been one of the key technologies in the development of wireless communication systems, especially for broadband multiuser communication systems which severely suffer from intersymbol interference (ISI) and multiple access interference (MAI). This article reviews batch processing algorithms for blind equalization using higher-order statistics for mitigation of the ISI induced by single-input, single-output channels as well as of both the ISI and MAI induced by multiple-input, multiple-output channels. In particular, this article reviews the typical inverse filter criteria (IFC) based algorithm, super-exponential algorithm, and constant modulus algorithm along with their relations, performance, and improvements. Several advanced applications of these algorithms are illustrated, including blind channel estimation, simultaneous estimation of multiple time delays, signal-to-noise ratio (SNR) boost by blind maximum ratio combining, blind beamforming for source separation in multipath, and multiuser detection for direct sequence/code division multiple access (DS/CDMA) systems in multipath.
TL;DR: Explored the basic theory of recursive digital oscillators with a bent towards the practical, and from there looked at some common oscillators, adding some mechanisms for controlling their amplitude and adjusting their frequency.
Abstract: Explored the basic theory of recursive digital oscillators with a bent towards the practical, and from there looked at some common oscillators. Then the article added some mechanisms for controlling their amplitude and adjusting their frequency. A brief example of how these oscillators and their control mechanisms may be used to make FSK modulators is given.
TL;DR: A designed system to be as "student friendly" as possible is presented, built around ImageJ, a freely available, full-featured, and user-friendly program for image analysis.
Abstract: Image processing (IP) can be taught very effectively by complementing the basic lectures with computer laboratories where the participants can actively manipulate and process images. This offering can be made even more attractive by allowing the students to develop their own IP code within a reasonable time frame. A designed system to be as "student friendly" as possible is presented. The software is built around ImageJ, a freely available, full-featured, and user-friendly program for image analysis. The students can walk away from the course with an IP system that is operational. Using the ImageAccess interface layer, they can easily program both ImageJ plug-ins and Internet applets. The system that we have described may also appeal to practitioners as it offers simple, full-proof way of developing professional level IP software.
TL;DR: Two improved general purpose computational techniques are focused on, including the factorization algorithm by Lindsey-Fox (L-F), which makes use of the fast Fourier transform to factor polynomials with random coefficients of degrees as high as 1 million.
Abstract: In this article, we discuss the current status of polynomial factoring (root finding) algorithms with some historical and mathematical background including size limits, convergence, accuracy and speed. The methods of root approximation versus root refinement are also examined. We then focus on two improved general purpose computational techniques, and in particular the factorization algorithm by Lindsey-Fox (L-F), which makes use of the fast Fourier transform to factor polynomials with random coefficients of degrees as high as 1 million. Computer simulations give insight that result in significant improvements in traditional approaches to an ancient problem.
TL;DR: The best halftone reproductions, however, are obtained by iterative techniques that minimize the (squared) error between the output of the cascade of the printer and visual models in response to the halftones image and theoutput of the visual model in Response to the original continuous-tone image.
Abstract: D igital halftoning is the process of generating a pattern of pixels with a limited number of colors that, when seen by the human eye, is perceived as a continuous-tone image. Digital halftoning is used to display continuous-tone images in media in which the direct rendition of the tones is impossible. The most common example of such media is ink or toner on paper, and the most common rendering devices for such media are, of course, printers. Halftoning works because the eye acts as a spatial low-pass filter that blurs the rendered pixel pattern, so that it is perceived as a continuous-tone image. Although all halftoning methods rely, at least implicitly, on some understanding of the properties of human vision and the display device, the goal of model-based halftoning techniques is to exploit explicit models of the display device and the human visual system (HVS) to maximize the quality of the displayed images. This is illustrated in Figure 1. Based on the type of computation involved, halftoning algorithms can be broadly classified into three categories [1]: point algorithms (screening or dithering), neighborhood algorithms (error diffusion), and iterative algorithms [least squares and direct binary search (DBS)]. All of these algorithms can incorporate HVS and printer models. The best halftone reproductions, however, are obtained by iterative techniques that minimize the (squared) error between the output of the cascade of the printer and visual models in response to the halftone image and the output of the visual model in response to the original continuous-tone image.
TL;DR: A rebuttal to the article by C. Herley, "Why watermarking is nonsense" is presented with the intention of starting a discussion open to all the readers, on the controversial points raised by that article.
Abstract: We focus on the emerging, nonsecurity-oriented applications of digital watermarking and data hiding in general. Then we consider a more technical topic, i.e., we compare, at a very general level, the two most important approaches to the watermarking problem proposed so far, namely, spread spectrum (SS) and quantization index modulation (QIM) random-binning-like watermarking. A rebuttal to the article by C. Herley, "Why watermarking is nonsense" (IEEE Signal Processing Magazine, vol. 19, no. 5, pp. 10-11, Sept. 2002), is also presented with the intention of starting a discussion open to all the readers, on the controversial points raised by that article.
TL;DR: The DVD-Audio specification allows for up to 24-b PCM data and uses the Meridian lossless packing (MLP) algorithm to provide up to six channels of high-quality, multichannel audio at sampling rates of up to 96 kHz for six channels or 192 kHz for two channels.
Abstract: Highlights the latest developments in consumer audio and specifically in DVD-Audio and SACD. The DVD-Audio specification allows for up to 24-b PCM data and uses the Meridian lossless packing (MLP) algorithm to provide up to six channels of high-quality, multichannel audio at sampling rates of up to 96 kHz for six channels or 192 kHz for two channels. Super-audio CD (SACD), introduced in March 1999, integrates a variety of new technologies, such as the hybrid disc, direct stream digital (DSD), and direct stream transfer coding.
TL;DR: Dirty-paper coding makes an analogy to the problem of writing on dirty paper, where the reader cannot nominally distinguish dirt from ink, and in the field of information hiding, theoretical bounds as well as practical watermarking schemes have been found.
Abstract: Dirty-paper coding makes an analogy to the problem of writing on dirty paper, where the reader cannot nominally distinguish dirt from ink. There are many scenarios where this result may be applied. In the field of information hiding (or watermarking), theoretical bounds as well as practical watermarking schemes have been found. Another important application of dirty-paper coding is for a multiuser channel wherein a multiple-antenna transmitter is communicating with multiple users.
TL;DR: A class of digital filters, called interpolated finite impulse response (IFIR) filters that can implement narrowband lowpass FIR filter designs with a significantly reduced computational workload relative to traditional FIR filters are described.
Abstract: The article describes a class of digital filters, called interpolated finite impulse response (IFIR) filters that can implement narrowband lowpass FIR filter designs with a significantly reduced computational workload relative to traditional FIR filters. Topics discussed include: optimum expansion factor choice, number of FIR filter taps estimation, IFIR filter performance modeling, passband ripple considerations, implementation, and filter design.
TL;DR: The design principles of color error diffusion that differentiate it from grayscale error diffusion are discussed, focusing oncolor error diffusion halftoning systems using the red, green, and blue (RGB) space for convenience.
Abstract: Grayscale halftoning converts a continuous-tone image (e.g., 8 bits per pixel) to a lower resolution (e.g., 1 bit per pixel) for printing or display. Grayscale halftoning by error diffusion uses feedback to shape the quantization noise into high frequencies where the human visual system (HVS) is least sensitive. In color halftoning, the application of grayscale error-diffusion methods to the individual colorant planes fails to exploit the HVS response to color noise. Ideally the quantization error must be diffused to frequencies and colors, to which the HVS is least sensitive. Further it is desirable for the color quantization to take place in a perceptual space so that the colorant vector selected as the output color is perceptually closest to the color vector being quantized. This article discusses the design principles of color error diffusion that differentiate it from grayscale error diffusion, focusing on color error diffusion halftoning systems using the red, green, and blue (RGB) space for convenience.
TL;DR: The lessons that have been learned in two areas of error-diffusion research: threshold modulation and error stability are described, important in understanding how to improve and extend the algorithm.
Abstract: Many modifications to error diffusion have been proposed to improve the algorithm and to extend its application to print media and to color. In this article, we describe some of the lessons that have been learned in two areas of error-diffusion research: threshold modulation and error stability. Both of these areas are important in understanding how to improve and extend the algorithm. Many suggested modifications have been made over the years to eliminate these unwanted textures. One method to improve the algorithm involves different ways of calculating and distributing the errors. Some of the modified algorithms have even proposed amplifying or suppressing the errors. Strange effects can occur, however, when the errors are amplified or if negative components are introduced. The stability analysis presented in this article will illustrate these instabilities and explain their relationship to changes in the error distribution.
TL;DR: An overview of some of the latest developments in high-quality DSD generation is concluded with a basic introduction in signal processing for super audio.
Abstract: Super-audio compact disc (SACD), conceived and developed by Philips and Sony, is viewed as the successor of the standard CD. In March 1999 the standard was set, and Scarlet Book version 1.0 was released. Since then, the format changed from an audiophile release format to a mass-consumer format. Not only does SACD provide an enhanced listening performance to the end-user, it also provides strong copy protection for the music industry. These aspects, in combination with a basic introduction in signal processing for super audio, are discussed The article is concluded with an overview of some of the latest developments in high-quality DSD generation.
TL;DR: In this paper, the problem of optimizing halftoning for compression is investigated and watermarking and steganography for halftone images arc relatively new areas that are motivated by the proliferation of networking and the exchange of digital data.
Abstract: Compression is routinely used in printing pipelines. While both lossless and lossy compression methods exist for compressing halftones, dispersed types of halftones remain difficult to compress given their very nature. In recent years researchers have started looking at the problem of designing halftoners that generate both good quality and compressible halftones. We believe that the problem of optimizing halftoning for compression is a very interesting and useful area. Watermarking and steganography for halftone images arc relatively new areas that are motivated by the proliferation of networking and the exchange of digital data. We have described a number of approaches in watermarking halftones and embedding halftones into each other. Certainly many more aspects of this problem can and will be considered in the future.