New halftoning method using adaptive cell

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.

Dot diffusion is an efficient approach which utilizes concepts of block-wise and parallel-oriented processing to generate halftones. However, the block-wise nature of processing reduces image quality much more significantly as compared to error diffusion. In this work, four types of filters with various sizes are employed in co-optimization procedures with class matrices of size 8 n 8 and 16 x 16 to improve the image quality. The optimal diffused weighting and area are determined through simulations. Many well-known halftoning methods, some of which includes direct binary search (DBS), error diffusion, ordered dithering, and prior dot diffusion methods, are also included for comparisons. Experimental results show that the proposed dot diffusion achieved quality close to some forms of error diffusion, and additionally, superior to the well-known Jarvis and Stucki error diffusion and Mese's dot diffusion. Moreover, the inherent parallel processing advantage of dot diffusion is preserved, allowing us to reap higher executing efficiency than both DBS and error diffusion.

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 performance 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.

The objective of this work is to reconstruct high quality gray-level images from halftone images, or the inverse halftoning process. We develop high performance halftone reconstruction methods for several commonly used halftone techniques. For better reconstruction quality, image classification based on halftone techniques is placed before the reconstruction process so that the halftone reconstruction process can be fine tuned for each halftone technique. The classification is based on enhanced 1D correlation of halftone images and processed with a three- layer back propagation neural network. This classification method reached 100 percent accuracy with a limited set of images processed by dispersed-dot ordered dithering, clustered-dot ordered dithering, constrained average, and error diffusion methods in our experiments. For image reconstruction, we apply the least-mean-square adaptive filtering algorithm which intends to discover the optimal filter weights and the mask shapes. As a result, it yields very good reconstruction image quality. The error diffusion yields the best reconstructed quality among the halftone methods. In addition, the LMS method generates optimal image masks which are significantly different for each halftone method. These optimal masks can also be applied to more sophisticated reconstruction methods as the default filter masks.

An analysis of the error diffusion method is presented which is based on the terminology of filter theory. The calculation of diffractive elements with the error diffusion method is shown. The stagnation of the iterative Fourier transform algorithm with a bandwidth constraint is overcome by error diffusion.

Halftoning is a crucial part of image reproduction in print. For large format prints, especially at higher resolutions, it is important to have very fast and computationally feasible halftoning methods of good quality. The authors have already introduced an approach to obtain image-independent threshold matrices generating both first- and second-order frequency modulated (FM) halftones with different clustered dot sizes. Predetermined and image-independent threshold matrices make the proposed halftoning method a point-by-point process and thereby very fast. In this article, they report a comprehensive quality evaluation of first-and second-order FM halftones generated by this technique and compare them with each other, employing several quality metrics. These generated halftones are also compared with error diffusion (ED) halftones employing two different error filters. The results indicate that the second-order FM halftoning with small clustered dot size performs best in almost all studied quality aspects than the first-and second-order FM halftoning with larger clustered dot size. It is also shown that the first- and second-order FM halftones with small clustered dot sizes are of almost the same quality as ED halftones using Floyd–Steinberg error filter and of higher quality than halftones generated by ED employing Jarvis, Judice, and Ninke error filter.

In the final optics assembly of Inertial Confinement Fusion (ICF) driver, Diffractive Optical Elements (DOEs) are applied to achieve some important functions, such as harmonic wave separation, beam sampling, beam smoothing and pulse compression etc. However, in order to optimize the system structure, decrease the energy loss and avoid the damage of laser induction or self-focusing effect, the number of elements used in the ICF system, especially in the final optics assembly, should be minimized. The multiple exposure method has been proposed, for this purpose, to fabricate BSG and CSG on one surface of a silica plate. But the multiple etch processes utilized in this method is complex and will introduce large alignment error. Error diffusion method that based on pulse-density modulation has been widely used in signal processing and computer generated hologram (CGH). In this paper, according to error diffusion method in CGH and partial coherent imaging theory, we present a new method to design coding mask of combine CSG-BSG element with error diffusion method. With the designed mask, only one exposure process is needed in fabricating combined element, which will greatly reduce the fabrication difficulty and avoid the alignment error introduced by multiple etch processes. We illustrate the designed coding mask for CSG-BSG element with this method and compare the intensity distribution of the spatial image in partial coherent imaging system with desired relief.

Several investigations has been conducted to determine the best way to improve the reconstruction of Kinoform images. Many of these investigations, however, forcused on the use of the iterative algorithm method, and little attention was paid to the use of the error-diffusion method. Most of the studies that have focused on the error-diffusion method examined its use in relation to binary-phase quantized holograms, not kinoform. Moreover, the relationship between an input object's position and the diffusion coefficients has not been reported. This is because the error-diffusion method reconstructed to separate the object as for the noise that originated in the quantization error. This paper discribes the application of a error-diffusion method that uses a complex number for the diffusion coefficient a kinoform. Results of Computer Simulation showd that the error diffusion method is superior to the iterative algorithm method for image reconstruction iterative algorithm because less processing. they also demonstrared that the restriction on the position of an object can be eased by changing the diffusion coefficient on the basis of that object's position.

This paper presents an hardware- and bandwidth-efficient high-performance 2D convolution accelerator for convolutional neural networks (CNNs) in IoT applications. The 2D convolution accelerator is made up of three main components including a dedicated Loader, a Circle Buffer, and a MAC (Multiplier-Accumulator) unit. The 2D convolution accelerator has a 2-stage pipeline structure that reduces latency, increases processing throughput, and reduces power consumption. The architecture proposed in the paper eliminates the reloading of both the weights as well as the input image data. The 2D convolution unit is configurable to support 2D convolution operations with different sizes of input image matrix and kernel filter. The architecture can reduce memory access time and power as well as execution time thanks to the efficient reuse of the preloaded input data, while simplifying hardware implementation. The 2D convolution unit has been simulated and implemented on Xilinx's FPGA platform to evaluate its superiority. Experimental results show that our design is 1.54× and 13.6× faster in performance than the design in [7] and [8], respectively, at lower hardware cost without using any FPGA's dedicated hardware blocks. By reusing preloaded data, our design achieves a bandwidth reduction ratio between 66.4% and 90.5%.

Watermarking in halftone images with parity-matched error diffusion

Error diffusion (ED) and pseudorandom encoding (PRE) methods of designing Fourier transform holograms are compared in terms of their properties and the optical performance of the resulting far-field diffraction patterns. Although both methods produce a diffuse noise pattern due to the error between the desired fully complex pattern and the encoded modulation, the PRE errors reconstruct uniformly over the nonredundant band-width of the discrete-pixel spatial light modulator, while the ED errors reconstruct outside the window of the designed diffraction pattern. Combining the two encoding methods produces higher-fidelity diffraction patterns than either method produces individually. For some designs the fidelity of the ED-PRE algorithm is even higher over the entire nonredundant bandwidth than for the previously reported [J. Opt. Soc. Am. A 16, 2425 (1999)] minimum-distance-PRE algorithm.

A method has been developed to induce symmetric edge enhancement in error diffusion with threshold modulation. The existing threshold modulation algorithm induces edge enhancement by subtracting a term proportional to the input image from the threshold. The edge enhancement that results in asymmetric due to the asymmetric shape of the error diffusion filter. The new method induces a symmetric edge enhancement by subtracting a term from the threshold that is proportional to a filtered version of the input image. The filtering is accomplished with a recursive filter, applied during the error diffusion algorithm, which cancels out the error diffusion filter and imposes a symmetric sharpening filter. The result is a symmetric edge enhancement that is more pleasing to the eye.

A digital micromirror device (DMD) provides 2D- and 3D-scene reconstruction by displaying diffractive and holographic optical elements. The highest frame rates (tens of thousands of Hz) can be achieved if the displayed optical elements are binarized. Except for DMD applications, hologram binarization is useful for display creation, image encryption, information compression and storage, fast 3D printing, etc. Error diffusion is one of the most qualitative implementations of hologram binarization. In this paper, three group's weighting matrices of error diffusion are analyzed: 16 standard, eight dot and six diagonal matrices. Thus, 30 error diffusion methods were used for optically recorded off-axis digital hologram binarization. The quality of the image reconstruction from the binarized holograms was compared. Direct applications of error diffusion with large weighting matrices and dot diffusion provide the highest reconstruction quality. Seven metrics were used as the error diffusion threshold. Twelve bypass directions of error diffusion were analyzed. In addition, the joint application of Otsu threshold and complex bypass directions allows us to improve the quality of hologram binarization by 15%.

This paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, then the MGD values are filled within a local window to merge text segments. If the value is above a threshold, the pixel is considered as potential text. Isolated segments are then eliminated in a non-text region filtering process. After the text segmentation, a conventional error diffusion method is applied to the background, while edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) then prevents the printing of successive dots around the text region boundaries. The method is extended to halftone color images to sharpen the text regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. However, edge enhancement unfortunately produces color distortion, as edge enhancement and color difference are trade-offs. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, an additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. In experiments, the text of a scanned image was sharper when using the proposed algorithm than with conventional error diffusion without changing the background.

Herbicide deposition rate can be affected by the leaf surface features of weeds and have a significant impact on the overall efficacy. In this paper, an orthogonal experiment was conducted to investigate the differences of droplet evaporation and spreading characteristics corresponding to weed leaf surface with hairy, waxy and rough (ridged) structures. Three weed species—Descurainia sophia, Lepidium lotifolium, and Lolium temulentum—were included in the study, representing these three leaf structures respectively. Glyphosate sprays with organic silicone surfactant in different concentrations were composed for the test. Single droplets with two diameters of 0.05 μL and 0.1 μL were deposited on the leaves to evaluate the evaporation and spreading characteristics. A digital camera was used and the evaporation duration and the maximum droplet coverage images could be captured and extracted from the recorded videos. The Image Processing Toolbox in Matlab was applied to segment the images for droplet and leaf background and the binary images’ pixel numbers were counted for coverage area calculation. The results revealed that the evaporation duration was reduced with the increase of the organic silicone concentration, while the spread area was expanded. The droplet spread more widely and evaporated faster on D. sophia leaves than on the leaves with L. lotifolium and L. temulentum surfaces. The spreading area and evaporation duration varied much faster on L. lotifolium leaves than on the leaves of other weed species. The droplet sizes affected spreading more significantly on L. temulentum leaf surface, as the spreading procedure of small size droplets was restrained by the groove structure. The results of this study would benefit the consideration of the farmers when selecting the proper nozzle code and the determining of the surfactant mixture in order to optimize the use of herbicides like glyphosate.