Error Diffusion Research Articles

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

In this paper, we propose a novel error diffusion halftoning algorithm for the conversion of cyan, magenta and yellow (CMY) ink amounts to a multi-bit halftone image. We adopt the idea of allowing multiple drops of colorants in order to achieve print results with better saturation, which is implemented by modifying the classic Floyd-Steinberg error diffusion algorithm. For better halftone texture and more efficient use of colorants, we add a dot-off-dot feature to the classic Floyd-Steinberg error diffusion. Blending-in the original input image with its DBS screened multilevel halftone image as a preprocessing step to dot-off-dot error diffusion is proposed as a measure to reduce halftone artifacts. Digitally simulated halftone images will be presented to illustrate the better halftone texture that can be achieved by applying the proposed algorithm.

Error diffusion method with optimized weighting coefficients for binary hologram generation.

The error diffusion method can effectively reduce quality degradation by propagating thresholding errors to neighboring pixels in the conversion of a gray-scale hologram to a binary hologram. In previous works, the four weighting coefficients in error diffusion are mostly set as the Floyd-Steinberg coefficient, which was determined empirically and originally proposed for photograph processing. In this work, we point out that the Floyd-Steinberg coefficients can be suboptimal for hologram error diffusion binarization. Furthermore, the weighting coefficients are optimized for each different hologram adaptively. Compared with conventional coefficients, our optimized coefficients can better preserve the fidelity of a reconstructed image after a hologram is binarized.

Improved branch‐cut phase unwrapping strategy based on dynamic adjacent table

Phase unwrapping (PU) is a key step of interferometric SAR signal processing. The accuracy of the unwrapping phase directly affects the accuracy of the digital elevation model (DEM). The traditional path-integral methods and global-planning methods cannot take into account both PU accuracy and processing efficiency, and causes PU error diffusion and large-area PU holes. To solve these problems, this study proposed an improved PU strategy based on dynamic adjacent table. For the problem of unwrapping holes that appears in traditional path-integral methods, this study introduces improved local quality maps to guide the path-integral operation, which effectively realises the phase compensation of the PU holes. For the low efficiency of the traditional branch-cut algorithm, this study implements the real-time integration path optimisation planning by further introducing the dynamic adjacent table and greatly reduces the data volume of the adjacent table. Thus, the efficiency of PU was greatly improved. Finally, the proposed method was validated by the airborne dual-antenna interferometric SAR experimental data.

Watermarking in dot-diffusion halftones using adaptive class-matrix and error diffusion

Digital halftoning deals with transforming a gray or color image into its binary version which is useful in printing applications. Dot diffusion is one of the prominent halftone methods which can yield superior image quality with parallel processing capabilities. In this paper, a rapid watermarking algorithm is proposed for dot-diffusion halftone images using adaptive class-matrix selection and modified error diffusion kernels. To process the image using an adaptive class matrix, the processing order of the class matrix is reversed and transposed, and for error diffusion the coefficients are replaced with different weights. For decoding, an effective strategy is proposed based on a correlation analysis and halftone statistics. The proposed strategy can successfully embed and decode the binary watermark from a single dot-diffused halftone image. From the experimental results, the proposed method is found to be effective in terms of good decoding accuracy, imperceptibility and robustness against various printed distortions.

Improvement of display performance of electrowetting displays by optimized waveforms and error diffusion

AbstractThe electrowetting display (EWD) has a low gray level, and there are some phenomena that affect the display quality, such as oil backflow and charge trapping. In this paper, an error diffusion algorithm based on pixel neighborhood gray information and direct current (DC)‐balanced driving waveform are proposed for display quality of EWD. The proposed algorithm and driving waveform are implemented in the proposed driving system based on Digital Visual Interface (DVI) video codec system and field‐programmable gate array (FPGA) control system. The experiment results show that the driving waveform suppresses the oil backflow, charge trapping and keeps DC balance, and the proposed error diffusion preserves the edges and richness of image. The whole driving system successfully plays video in real time with computer and improves the display quality of EWD.

Digital Material Design Using Tensor-Based Error Diffusion for Additive Manufacturing

Recent multi-material additive manufacturing (AM) technologies enable the fabrication of an object with accurate deposition of different types of materials. Hence, in addition to geometric shapes, it is possible to use different material compositions to optimize the mechanical properties of a component for given design requirements. However, current AM processes have a limitation on the number of materials that can be deposited during the fabrication process. Due to the constraint, it is critical to optimize the material distribution using the limited base materials; however, an extremely large design space exists in a design domain that is enabled by the AM technologies. In this paper, we introduce a digital material design framework to generate digital material compositions that can be printed and be able to achieve the desired behavior. We take analog material composition as the input and perform the analog-to-digital conversion using an exemplar-based approach based on a pre-computed material library. The patterns in the library are constructed with different combinations of the given base materials, and their mechanical properties are computed using finite element simulation. Accordingly, the design goal of the analog-to-digital conversion is to find material composition in the design domain with matching mechanical properties. A tensor-based error diffusion algorithm has been developed to reduce the approximation error during the conversion effectively. Experimental tests based on the design framework have been performed. The test results demonstrate that our framework can quickly find effective solutions for various multi-material design problems.

Two-in-One Image Steganography Using Error Diffusion

Image steganography is a technique for concealing a secret message in a cover image unobtrusively. The resultant images are called the stego images. In this paper, we propose a method for concealing a secret image into a cover image of the same size, where the most significant bits (MSBs) of the secret image are embedded in the least significant bits (LSBs) of the cover image after the reversal of the order of the bit sequences. Such a symmetric relationship between MSBs and LSBs derives a complementary between the stego and extracted secret images. We also propose a method for improving the image quality of both stego and extracted secret images by using an error diffusion technique. Experimental results show that the proposed method works well for both grayscale and color images, and the proposed error diffusion method can suppress the noises like false contours caused in the embedding process visually and quantitatively.

Data Compaction of Neural Networks by Error Diffusion Type Quantization

Data Compaction of Neural Networks by Error Diffusion Type Quantization

Improved single-random-phase holographic encryption using double-phase method

An improved single-random-phase holographic encryption (SRPHE) is proposed by using double-phase method and demonstrated by a spatial light modulator (SLM). Different from the conventional SRPHE using Fresnel diffraction and the bidirectional error diffusion method, the proposed SRPHE employees the angular spectrum diffraction and double-phase method to generate a phase-only hologram, and the phase-only hologram is encrypted into ciphertext by multiplying a single random phase mask. When the ciphertext is modulated by the conjugate of the random phase mask and loaded to a SLM, the decrypted image can be achieved successfully. The improved SRPHE has two advantages of better quality of the decrypted image, and lower time-cost of hologram generation, which is compared with the conventional SRPHE. Numerical simulations and optical reconstruction results have been carried out to verify the validity of the proposed SRPHE.

Optimised halftoning and inverse halftoning of dermoscopic images for supporting teledermoscopy system

Telemedicine systems require reliable, small size, and secure transmission. In teledermoscopy, the transmission of the traditional large size dermoscopic images leads to heavy consumption of storage space and bandwidth congestion, which impairs the efficient use of the transmission channel bandwidth. Furthermore, halftoning and inverse halftoning have a great practical impact in the reduction of the images' size. For teledermoscopy, the present work optimises the error filter during the error diffusion process to generate the halftone dermoscopic images with small size. The proposed inverse halftone optimises two parameters during the integration between the regularised inverse filter and the DLPA-ICI (directional local polynomial approximation and the intersection of confidence intervals) estimator's kernel. The optimised kernel parameter determines the best window size of the kernel in the restored image estimation. The experimental results included comparative studies in terms of several image quality metrics and the average size reduction in percentage when using the genetic algorithm for optimisation with Jarvis error diffusion for halftone images generation. The achieved average size reduction is 92.15% using the proposed method compared to the average dermoscopic images' size in the test set on 900 images showing the superiority of the proposed method.

3D Tone-Dependent Fast Error Diffusion

As 3D printing becomes more prevalent, more attention is being paid to its ability to adequately reproduce the appearance of surfaces. Research into methods to accurately represent grayscale images through halftoning is well-developed in 2D printing, but work in the halftoning of surfaces in 3D printing is less developed. The halftoning method of tone-dependent fast error diffusion has been shown in 2D printing to be an effective means of achieving both high image quality and computational efficiency, making it an ideal algorithm to run in printing units where computational power is restricted. This work seeks to adapt tone-dependent fast error diffusion to halftone the surfaces of three-dimensional objects. Here, the ideal tone-dependent error diffusion parameters will be calculated for an image. Then, a surface traversal mechanism will be implemented to navigate the surface of a threedimensional object while error diffusion is applied to halftone it. The expected result is an algorithm that can halftone the surface of an object with quality approaching that of iterative methods, with a fraction of the processing that they require. Iterative methods currently produce the highest halftoning quality for 3D surfaces, but their use is limited due to the amount of computation they entail. The development of a tone-dependent fast error diffusion algorithm allows 3D halftoning to represent a continuoustone surface with comparably high quality, but the computation it requires is more appropriate for standard printers; thus, it improves on the quality of surface halftoning that most printing units can produce.

Vector Multilevel Tone-Dependent Error Diffusion in the YyCxCz Color Space

In this paper, we present a tone-dependent fast error diffusion algorithm for color images, in which the quantizer is based on a simulated linearized printer space and the filter weight function depends on the ratio of the luminance of the current pixel to the maximum luminance value. The pixels are processed according to a serpentine scan instead of the classic raster scan. We compare the results of our algorithm to those achieved using the fixed Floyd-Steinberg weights and processing the image according to a raster scan ordering.

基于邻域灰度信息误差扩散算法的电润湿电子纸研究

基于邻域灰度信息误差扩散算法的电润湿电子纸研究

Deep multispectral painting reproduction via multi-layer, custom-ink printing

We propose a workflow for spectral reproduction of paintings, which captures a painting's spectral color, invariant to illumination, and reproduces it using multi-material 3D printing. We take advantage of the current 3D printers' capabilities of combining highly concentrated inks with a large number of layers, to expand the spectral gamut of a set of inks. We use a data-driven method to both predict the spectrum of a printed ink stack and optimize for the stack layout that best matches a target spectrum. This bidirectional mapping is modeled using a pair of neural networks, which are optimized through a problem-specific multi-objective loss function. Our loss function helps find the best possible ink layout resulting in the balance between spectral reproduction and colorimetric accuracy under a multitude of illuminants. In addition, we introduce a novel spectral vector error diffusion algorithm based on combining color contoning and halftoning, which simultaneously solves the layout discretization and color quantization problems, accurately and efficiently. Our workflow outperforms the state-of-the-art models for spectral prediction and layout optimization. We demonstrate reproduction of a number of real paintings and historically important pigments using our prototype implementation that uses 10 custom inks with varying spectra and a resin-based 3D printer.

Improving the Visual Quality of Size-Invariant Visual Cryptography for Grayscale Images: An Analysis-by-Synthesis (AbS) Approach.

In visual cryptography (VC) for grayscale image, size reduction leads to bad perceptual quality to the reconstructed secret image. To improve the quality, the current efforts are limited to the design of VC algorithm for binary image, and measuring the quality with metrics that are not directly related to how the human visual system (HVS) perceives halftone images. We propose an analysis-by-synthesis (AbS) framework to integrate the halftoning process and the VC encoding: the secret pixel/block is reconstructed from the shares in the encoder and the error between the reconstructed secret and the original secret images is fed back and compensated concurrently by the error diffusion process. In doing so, the error between the reconstructed secret and original secret is pushed to high frequency band, thus producing visually pleasing reconstructed secret image. This framework is simple and flexible in that it can be combined with many existing size-invariant VC algorithms, including probabilistic VC, random grid VC and vector/block VC. More importantly, it is proved that this AbS framework is as secure as the traditional VC algorithms. Experimental results demonstrate the effectiveness of the proposed AbS framework.

Smartphone Heading Correction Based on Gravity Assisted and Middle Time Simulated-Zero Velocity Update Method.

Electronic appliances and ferromagnetic materials can be easily found in any building in urban environment. A steady magnetic environment and a pure value of geomagnetic field for calculating the heading of the smartphone in case of pedestrian walking indoors is hard to obtain. Therefore, an independent inertial heading correction algorithm without involving magnetic field but only making full use of the embedded Micro-Electro-Mechanical System (MEMS) Inertial measurement unit (IMU) device in the smartphone is presented in this paper. Aiming at the strict navigation requirements of pedestrian smartphone positioning, the algorithm focused in this paper consists of Gravity Assisted (GA) and Middle Time Simulated-Zero Velocity Update (MTS-ZUPT) methods. With the help of GA method, the different using-mode of the smartphone can be judged based on the data from the gravity sensor of smartphone. Since there is no zero-velocity status for handheld smartphone, the MTS-ZUPT algorithm is proposed based on the idea of Zero Velocity Update (ZUPT) algorithm. A Kalman Filtering algorithm is used to restrain the heading divergence at the middle moment of two steps. The walking experimental results indicate that the MTS-ZUPT algorithm can effectively restrain the heading error diffusion without the assistance of geomagnetic heading. When the MTS-ZUPT method was integrated with GA method, the smartphone navigation system can autonomously judge the using-mode and compensate the heading errors. The pedestrian positioning accuracy is significantly improved and the walking error is only 1.4% to 2.0% of the walking distance in using-mode experiments of the smartphone.

Direct binary search for improved coherent beam shaping and optical differentiation wavefront sensing.

Spatially dithered distributions of binary amplitude pixels are optimized using a full direct binary search, taking into account the experimental configuration for amplitude modulation of coherent waves. This design process is shown to yield a significant reduction of the noise induced by binarization and pixelation over the region of interest. We demonstrate this approach for beam shaping and optical differentiation wavefront sensing, where the region of interest is in an image plane of the pixel distribution, and in the far field of the pixel distribution, respectively. The observed reduction in error compared to a standard error diffusion algorithm is significant for both applications because it improves performance without the tighter fabrication tolerance and cost associated with smaller pixels.

Benchmarking modern algorithms to holographically create optical tweezers for laser-cooled atoms

ABSTRACTWe discuss and compare three methods to generate holograms for optical tweezers: simple rounding, Floyd–Steinberg error diffusion dithering and mixed-region amplitude freedom (MRAF). These schemes are optimized for producing large arrays of tightly focused luminous spots. The algorithms are compared in terms of their speed, efficiency and accuracy, for periodic arrangements of traps; an arrangement of particular interest for the trapping and manipulation of single laser-cooled atoms in the field of quantum computing. We simulate the image formation using each of a binary amplitude modulating digital mirror device (DMD) and a phase modulating spatial light modulator (PSLM) as the display element. While a DMD allows for fast frame rates, the slower PSLM is more efficient and provides higher accuracy with a quasi-continuous variation of phase. We discuss the relative merits of each algorithm for use with both a DMD and a PSLM, allowing one to choose the ideal approach depending on the circumstances.

A Robust Image Steganography on Resisting JPEG Compression with No Side Information

ABSTRACTRobust JPEG steganographic algorithms are proposed to transmit covert message against JPEG compression. The existing robust JPEG steganographic algorithms are working with the side information about JPEG compression quality factor of a lossy channel. However, massive recent experimental results reveal that the performance of the present robust JPEG steganographic algorithms is poor if the side information is unknown. Thus, this paper proposes a new robust JPEG steganographic algorithm to satisfy the requirement. First, the error diffusion of steganographic embedding encoder is analyzed. Then, a new robust JPEG steganographic algorithm is proposed based on the analysis result. A series of experiments are conducted on 10,000 images from BOSSbase 1.01 image library. The results show that the proposed method can resist JPEG compression efficiently with acceptable resistance to steganalysis statistical detection.

Comparing noniterative methods for phase-only Fresnel holograms, with speckle reduction, using a low-resolution spatial-light modulator in mostly phase mode

We analyze 10 cases of noniterative methods for speckle noise reduction in phase-only hologram generation. The analyzed methods are bidirectional error diffusion, random phase-free, double-phase, random displaced phase distribution (RDPD), and complex field encoding (CFE). The first three methods have been used before in the Fresnel hologram display, whereas the last two methods have been used in the area of holographic memory recording and generation of optical fields, respectively. We study the last two methods as alternatives to the generation of a Fresnel hologram without random phase (RP) and compare their results with the first three methods. We found that the RDPD also suffers a high degradation of low frequencies, so we introduce a modification for reducing the degradation effect. This method allows control of the spread angle of the object wave propagation. We also found that the CFE achieves a precise reconstruction of the object in different planes without the addition of any RP, with a very high signal-to-noise-ratio (SNR). We compare the results of 10 cases and discuss the advantages of each one. We include the peak signal-to-noise-ratio and SNR measurements of each case. We present simulated and experimental results.