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Jan P Allebach - One of the best experts on this subject based on the ideXlab platform.
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Quantization of accumulated diffused Errors in Error Diffusion
IEEE Transactions on Image Processing, 2005Co-Authors: Tichiun Chang, Jan P AllebachAbstract:Due to its high image quality and moderate computational complexity, Error Diffusion is a popular halftoning algorithm for use with inkjet printers. However, Error Diffusion is an inherently serial algorithm that requires buffering a full row of accumulated diffused Error (ADE) samples. For the best performance when the algorithm is implemented in hardware, the ADE data should be stored on the chip on which the Error Diffusion algorithm is implemented. However, this may result in an unacceptable hardware cost. In this paper, we examine the use of quantization of the ADE to reduce the amount of data that must be stored. We consider both uniform and nonuniform quantizers. For the nonuniform quantizers, we build on the concept of tone-dependency in Error Diffusion, by proposing several novel feature-dependent quantizers that yield improved image quality at a given bit rate, compared to memoryless quantizers. The optimal design of these quantizers is coupled with the design of the tone-dependent parameters associated with Error Diffusion. This is done via a combination of the classical Lloyd-Max algorithm and the training framework for tone-dependent Error Diffusion. Our results show that 4-bit uniform quantization of the ADE yields the same halftone quality as Error Diffusion without quantization of the ADE. At rates that vary from 2 to 3 bits per pixel, depending on the selectivity of the feature on which the quantizer depends, the feature-dependent quantizers achieve essentially the same quality as 4-bit uniform quantization.
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block interlaced pinwheel Error Diffusion
Journal of Electronic Imaging, 2005Co-Authors: Pingshan Li, Jan P AllebachAbstract:Error Diffusion is a popular halftoning algorithm that in its most widely used form, is inherently serial. As a serial algorithm, Error Diffusion offers limited opportunity for large-scale parallelism. In some implementations, it may also result in excessive bus traffic between the on-chip processor and the off-chip memory used to store the modified continuous-tone image and the halftone image. We introduce a new Error Diffusion algorithm in which the image is processed in two groups of interlaced blocks. Within each group, the blocks may be processed entirely independently. In the first group, the Error Diffusion proceeds along an outward spiral from the center of the block. Errors along the boundaries of blocks in the first group are diffused into neighboring blocks in the second group, within which the Error Diffusion spirals inward. A tone-dependent Error Diffusion training framework is used to eliminate artifacts associated with the spiral scan paths. We demonstrate image quality that is close to that achieved by conventional line-by-line Error Diffusion.
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Clustered-minority-pixel Error Diffusion
Journal of The Optical Society of America A-optics Image Science and Vision, 2004Co-Authors: Pingshan Li, Jan P AllebachAbstract:We present a clustered-minority-pixel Error-Diffusion halftoning algorithm for which the quantizer threshold is modified on the basis of the past output and a dot activation map. Dot area, dot shape, and dot distribution are more controllable than with other clustered-dot halftone algorithms such as Levien’s algorithm. This method also effectively reduces structured mazelike artifacts in midtones that occur in Levien’s algorithm. The dot distribution is further improved by using different Error-Diffusion weights for different input gray levels.
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tone dependent Error Diffusion
IEEE Transactions on Image Processing, 2004Co-Authors: Pingshan Li, Jan P AllebachAbstract:We present an enhanced Error Diffusion halftoning algorithm for which the filter weights and the quantizer thresholds vary depending on input pixel value. The weights and thresholds are optimized based on a human visual system model. Based on an analysis of the edge behavior, a tone dependent threshold is designed to reduce edge effects and start-up delay. We also propose an Error Diffusion system with parallel scan that uses variable weight locations to reduce worms.
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memory efficient Error Diffusion
IEEE Transactions on Image Processing, 2003Co-Authors: Tichiun Chang, Jan P AllebachAbstract:Because of its good image quality and moderate computational requirements, Error Diffusion has become a popular halftoning solution for desktop printers, especially inkjet printers. By making the weights and thresholds tone-dependent and using a predesigned halftone bitmap for tone-dependent threshold modulation, it is possible to achieve image quality very close to that obtained with far more computationally complex iterative methods. However, the ability to implement Error Diffusion in very low cost or large format products is hampered by the requirement to store the tone-dependent parameters and halftone bitmap, and also the need to store Error information for an entire row of the image at any given point during the halftoning process. For the first problem, we replace the halftone bitmap by deterministic bit flipping, which has been previously applied to halftoning, and we linearly interpolate the tone-dependent weights and thresholds from a small set of knot points. We call this implementation a reduced lookup table. For the second problem, we introduce a new serial block-based approach to Error Diffusion. This approach depends on a novel intrablock scan path and the use of different parameter sets at different points along that path. We show that serial block-based Error Diffusion reduces off-chip memory access by a factor equal to the block height. With both these solutions, satisfactory image quality can only be obtained with new cost functions that we have developed for the training process. With these new cost functions and moderate block size, we can obtain image quality that is very close to that of the original tone-dependent Error Diffusion algorithm.
Vishal Monga - One of the best experts on this subject based on the ideXlab platform.
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hardcopy image barcodes via block Error Diffusion
IEEE Transactions on Image Processing, 2005Co-Authors: N Dameravenkata, Vishal Monga, B L EvansAbstract:Error Diffusion halftoning is a popular method of producing frequency modulated (FM) halftones for printing and display. FM halftoning fixes the dot size (e.g., to one pixel in conventional Error Diffusion) and varies the dot frequency according to the intensity of the original grayscale image. We generalize Error Diffusion to produce FM halftones with user-controlled dot size and shape by using block quantization and block filtering. As a key application, we show how block-Error Diffusion may be applied to embed information in hardcopy using dot shape modulation. We enable the encoding and subsequent decoding of information embedded in the hardcopy version of continuous-tone base images. The encoding-decoding process is modeled by robust data transmission through a noisy print-scan channel that is explicitly modeled. We refer to the encoded printed version as an image barcode due to its high information capacity that differentiates it from common hardcopy watermarks. The encoding/halftoning strategy is based on a modified version of block-Error Diffusion. Encoder stability, image quality versus information capacity tradeoffs, and decoding issues with and without explicit knowledge of the base image are discussed.
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ICASSP (3) - Tone dependent color Error Diffusion
2004 IEEE International Conference on Acoustics Speech and Signal Processing, 2004Co-Authors: Vishal Monga, Brian L. EvansAbstract:Conventional grayscale Error Diffusion halftoning produces worms and other objectionable artifacts. Tone dependent Error Diffusion (Li, P. and Allebach, J.P. Proc. SPIE Color Imaging, vol.4663, p.310-21, 2002) reduces these artifacts by controlling the Diffusion of quantization Errors based on the input graylevel. Li and Allebach designed Error filter weights and thresholds for each (input) graylevel with optimization based on a human visual system (HVS) model. We extend tone dependent Error Diffusion to color. In color Error Diffusion, what color to render becomes a major concern in addition to finding optimal dot patterns. We present a visually optimum design approach for input level (tone) dependent Error filters (for each color plane). The resulting halftones reduce traditional Error Diffusion artifacts and achieve greater accuracy in color rendition.
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color Error Diffusion halftoning
IEEE Signal Processing Magazine, 2003Co-Authors: N Danteravenkata, B L Evans, Vishal MongaAbstract: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.
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Variations on Error Diffusion: Retrospectives and future trends
electronic imaging, 2003Co-Authors: Brian L. Evans, Vishal Monga, Niranjan Damera-venkataAbstract:Grayscale Error Diffusion introduces nonlinear distortion (directional artifacts and false textures), linear distortion (sharpening), and additive noise. Since Error Diffusion is 2-D sigma-delta modulation (Anastassiou, 1989), Kite et al . linearize Error Diffusion by replacing the thresholding quantizer with a scalar gain plus additive noise. Sharpening is proportional to the scalar gain. Kite et al . derive the sharpness control parameter value in threshold modulation (Eschbach and Knox, 1991) to compensate linear distortion. These unsharpened halftones are particularly useful in perceptually weighted SNR measures. False textures at mid-gray (Fan and Eschbach, 1994) are due to limit cycles, which can be broken up by using a deterministic bit flipping quantizer (Damera-Venkata and Evans, 2001). We review other variations on grayscale Error Diffusion to reduce false textures in shadow and highlight regions, including green noise halftoning Levien, 1993) and tone-dependent Error Diffusion (Li and Allebach, 2002). We then discuss color Error Diffusion in several forms: color plane separable (Kolpatzik and Bouman, 1992); vector quantization (Shaked et al . 1996); green noise extensions (Lau et al . 2000); and matrix-valued Error filters (Damera-Venkata and Evans, 2001). We conclude with open research problems.
B L Evans - One of the best experts on this subject based on the ideXlab platform.
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hardcopy image barcodes via block Error Diffusion
IEEE Transactions on Image Processing, 2005Co-Authors: N Dameravenkata, Vishal Monga, B L EvansAbstract:Error Diffusion halftoning is a popular method of producing frequency modulated (FM) halftones for printing and display. FM halftoning fixes the dot size (e.g., to one pixel in conventional Error Diffusion) and varies the dot frequency according to the intensity of the original grayscale image. We generalize Error Diffusion to produce FM halftones with user-controlled dot size and shape by using block quantization and block filtering. As a key application, we show how block-Error Diffusion may be applied to embed information in hardcopy using dot shape modulation. We enable the encoding and subsequent decoding of information embedded in the hardcopy version of continuous-tone base images. The encoding-decoding process is modeled by robust data transmission through a noisy print-scan channel that is explicitly modeled. We refer to the encoded printed version as an image barcode due to its high information capacity that differentiates it from common hardcopy watermarks. The encoding/halftoning strategy is based on a modified version of block-Error Diffusion. Encoder stability, image quality versus information capacity tradeoffs, and decoding issues with and without explicit knowledge of the base image are discussed.
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color Error Diffusion halftoning
IEEE Signal Processing Magazine, 2003Co-Authors: N Danteravenkata, B L Evans, Vishal MongaAbstract: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.
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adaptive threshold modulation for Error Diffusion halftoning
IEEE Transactions on Image Processing, 2001Co-Authors: N Dameravenkata, B L EvansAbstract:Grayscale digital image halftoning quantizes each pixel to one bit. In Error Diffusion halftoning, the quantization Error at each pixel is filtered and fed back to the input in order to diffuse the quantization Error among the neighboring grayscale pixels. Error Diffusion introduces nonlinear distortion (directional artifacts), linear distortion (sharpening), and additive noise. Threshold modulation, which alters the quantizer input, has been previously used to reduce either directional artifacts or linear distortion. This paper presents an adaptive threshold modulation framework to improve halftone quality by optimizing Error Diffusion parameters in the least squares sense. The framework models the quantizer implicitly, so a wide variety of quantizers may be used. Based on the framework, we derive adaptive algorithms to optimize 1) edge enhancement halftoning and 2) green noise halftoning. In edge enhancement halftoning, we minimize linear distortion by controlling the sharpening control parameter. We may also break up directional artifacts by replacing the thresholding quantizer with a deterministic bit flipping (DBF) quantizer. For green noise halftoning, we optimize the hysteresis coefficients.
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modeling and quality assessment of halftoning by Error Diffusion
IEEE Transactions on Image Processing, 2000Co-Authors: T D Kite, B L Evans, Alan C BovikAbstract:Digital halftoning quantizes a graylevel image to one bit per pixel. Halftoning by Error Diffusion reduces local quantization Error by filtering the quantization Error in a feedback loop. In this paper, we linearize Error Diffusion algorithms by modeling the quantizer as a linear gain plus additive noise. We confirm the accuracy of the linear model in three independent ways. Using the linear model, we quantify the two primary effects of Error Diffusion: edge sharpening and noise shaping. For each effect, we develop an objective measure of its impact on the subjective quality of the halftone. Edge sharpening is proportional to the linear gain, and we give a formula to estimate the gain from a given Error filter. In quantifying the noise, we modify the input image to compensate for the sharpening distortion and apply a perceptually weighted signal-to-noise ratio to the residual of the halftone and modified input image. We compute the correlation between the residual and the original image to show when the residual can be considered signal independent. We also compute a tonality measure similar to total harmonic distortion. We use the proposed measures for edge sharpening, noise shaping, and tonality to evaluate the quality of Error Diffusion algorithms.
Yuk-hee Chan - One of the best experts on this subject based on the ideXlab platform.
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Optimizing the Error Diffusion Filter for Blue Noise Halftoning With Multiscale Error Diffusion
IEEE Transactions on Image Processing, 2013Co-Authors: Yik-hing Fung, Yuk-hee ChanAbstract:A good halftoning output should bear a blue noise characteristic contributed by isotropically-distributed isolated dots. Multiscale Error Diffusion (MED) algorithms try to achieve this by exploiting radially symmetric and noncausal Error Diffusion filters to guarantee spatial homogeneity. In this brief, an optimized Diffusion filter is suggested to make the Diffusion close to isotropic. When it is used with MED, the resulting output has a nearly ideal blue noise characteristic.
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green noise digital halftoning with multiscale Error Diffusion
IEEE Transactions on Image Processing, 2010Co-Authors: Yik-hing Fung, Yuk-hee ChanAbstract:Multiscale Error Diffusion (MED) is superior to conventional Error Diffusion algorithms as it can eliminate directional hysteresis completely and possesses a good blue noise characteristic. However, due to its filter design, it is not suitable for systems with poor isolated dot generation and instable dot gain. In this paper, we propose a MED algorithm to produce halftones of desirable green noise characteristics. This algorithm allows one to adjust the desirable cluster size freely through a single parameter and supports a linear relationship between the cluster size and the input gray level. With a close-to-isotropic Diffusion filter, the algorithm can effectively remove pattern artifacts, eliminate directional artifacts and preserve original image details. Analysis and simulation results show that it provides better performance in terms of various aspects including dot distribution, anisotropy and output image quality as compared with other conventional green noise Error Diffusion algorithms.
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Reducing the Complexity of Multiscale Error Diffusion
TENCON 2006 - 2006 IEEE Region 10 Conference, 2006Co-Authors: Yuk-hee ChanAbstract:Multiscale Error Diffusion (MED) is superior to conventional Error Diffusion algorithms as it can eliminate directional hysteresis completely. However, the complexity of this frame-oriented process is much higher and makes it not suitable for real-time applications. In this paper, a fast MED algorithm is proposed. The complexity of this algorithm is remarkably reduced as compared with conventional MED algorithms. It also supports parallel processing.
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feature preserving multiscale Error Diffusion for digital halftoning
Journal of Electronic Imaging, 2004Co-Authors: Yuk-hee Chan, Sinming CheungAbstract:Multiscale Error Diffusion is superior to conventional Error Diffusion methods in digital halftoning as it can eliminate directional hysteresis completely. However, there is a bias to favor a particular type of dots in the course of the halftoning process. A new multiscale Error Diffusion method is proposed to improve the Diffusion perfor- mance by reducing the aforementioned bias. The proposed method can eliminate the pattern noise in flat regions and the boundary effect found in some other conventional multiscale Error Diffusion methods. At the same time, it can preserve the local features of the input image in the output. This is critical to quality, especially when the resolution of the output is limited by the physical constraints of the display unit. © 2004 SPIE and IS&T. (DOI: 10.1117/1.1758728)
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Preserving image features in digital halftoning with a multiscale Error Diffusion technique
2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628), 2002Co-Authors: Yuk-hee Chan, Sinming CheungAbstract:Multiscale Error Diffusion is superior to conventional Error Diffusion methods in digital halftoning as it can completely eliminate directional hysteresis. However, there is a bias to favor a particular type of dot in the course of the halftoning process. A new multiscale Error Diffusion method is proposed to improve the Diffusion performance by reducing the aforementioned bias. The proposed method can also eliminate the boundary effect found in conventional multiscale Error Diffusion methods and preserve the local features of the input image in the output. This is critical to the quality when the resolution of the output is limited by the physical constraints of the display unit.
Gonzalo R. Arce - One of the best experts on this subject based on the ideXlab platform.
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color extended visual cryptography using Error Diffusion
IEEE Transactions on Image Processing, 2011Co-Authors: Inkoo Kang, Gonzalo R. ArceAbstract:Color visual cryptography (VC) encrypts a color secret message into color halftone image shares. Previous methods in the literature show good results for black and white or gray scale VC schemes, however, they are not sufficient to be applied directly to color shares due to different color structures. Some methods for color visual cryptography are not satisfactory in terms of producing either meaningless shares or meaningful shares with low visual quality, leading to suspicion of encryption. This paper introduces the concept of visual information pixel (VIP) synchronization and Error Diffusion to attain a color visual cryptography encryption method that produces meaningful color shares with high visual quality. VIP synchronization retains the positions of pixels carrying visual information of original images throughout the color channels and Error Diffusion generates shares pleasant to human eyes. Comparisons with previous approaches show the superior performance of the new method.
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halftone visual cryptography via Error Diffusion
IEEE Transactions on Information Forensics and Security, 2009Co-Authors: Zhongmin Wang, Gonzalo R. Arce, G Di CrescenzoAbstract:Halftone visual cryptography (HVC) enlarges the area of visual cryptography by the addition of digital halftoning techniques. In particular, in visual secret sharing schemes, a secret image can be encoded into halftone shares taking meaningful visual information. In this paper, HVC construction methods based on Error Diffusion are proposed. The secret image is concurrently embedded into binary valued shares while these shares are halftoned by Error Diffusion-the workhorse standard of halftoning algorithms. Error Diffusion has low complexity and provides halftone shares with good image quality. A reconstructed secret image, obtained by stacking qualified shares together, does not suffer from cross interference of share images. Factors affecting the share image quality and the contrast of the reconstructed image are discussed. Simulation results show several illustrative examples.
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Color extended visual cryptography using Error Diffusion
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Inkoo Kang, Gonzalo R. Arce, Heung-kyu LeeAbstract:This paper introduces a color visual cryptography encryption method that produces meaningful color shares via visual information pixel (VIP) synchronization and Error Diffusion halftoning. VIP synchronization retains the positions of pixels carrying visual information of original shares throughout the color channels and Error Diffusion generates shares pleasant to human eyes. Comparisons with previous approaches show the superior performance of the new method.
