Efficient Halftoning Based on Multiple Look-Up Tables

This work employs the well known weighted least squares method to optimization to produce halftone images using improved K-means clustering theory. Our algorithm applies to both a printer model and a model for the human visual system (HVS). In this algorithm, the improved K-means clustering method is used to segment an image several regions. In the halftone process, each clustering uses the weighted least-squares model-based(WLSMB) algorithm by use of direct binary search iterative method to obtain halftone image. Analysis and simulation results show that the proposed algorithm produces better gray-scale halftone image quality when we increase the number of clustering with a certain range and outperforms least-squares model-based algorithm in the PSNR (Peak Signal Noise Ratio), WSNR (Weighted Signal Noise Ratio) criteria.

This paper presents a high-speed multiplier/squarer design over finite field GF(2m) for large m. We extended the look-up table (LUT) based multiplication algorithm introduced by Hasan to reduce the LUT generation time and then showed how to effectively add the squaring operation to the developed multiplier. The unified multiplication/squaring module is very suitable for applications like Elliptic Curve Cryptography (ECC) in which these two types of operations are operated alternately. Experimental results exhibit that using the proposed sub-group, multiple look-up tables (SG-MLUT) based scheme, up to 29% improvement in the total computation time of multiplication can be achieved in comparison with that using Hasan's algorithm. When employing the unified multiplier/squarer module instead of Hasan's design in ECC applications, we can gain further improvement in the scalar multiplication time because no LUT generation is needed using our design, and obtain about 24.5% reduction on the resulting area-time (AT) complexity.

A region based random multi-pixel search algorithm to improve the binary hologram reconstruction quality

We introduce a process for optically reconstructing full-color holographic images recorded by optical scanning holography. A complex RGB-color hologram was recorded and converted into a binary hologram using a direct binary search (DBS) algorithm. The generated binary hologram was then optically reconstructed using a spatial light modulator. The discrepancies between the reconstructed object sizes and colors due to chromatic aberration were corrected by adjusting the reconstruction parameters in the DBS algorithm. To the best of our knowledge, this represents the first optical reconstruction of a full-color hologram recorded by optical scanning holography.

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.

In railroad turnouts, geometries of tongue and crossing rails are very complex and their shapes are changing along the track. Therefore, wheels are subjected to not only tread and flange contacts, but also the back-of-flange and top-of-flange contacts in the case of spring switches of tram vehicles. For this reason, one needs to deal with significant jumps in contact points for solving wheel/rail contact problems in turnout, and an accurate prediction of jumps in contact points is one of the most important issues that need to be carefully handled in the dynamic simulation of vehicle/turnout interactions. In this investigation, a numerical procedure that can be used for solving such a complex wheel/rail contact problem in turnout is proposed. In particular, a combined nodal and non-conformal contact approach is developed such that significant jumps in contact points are detected using the nodal search, while the exact location of contact point is then determined with continuous surface parameterizations using non-conformal contact equations. With this combined nodal and non-conformal contact approach for the contact geometry analysis of vehicle/turnout interactions, multiple look-up contact tables can be generated in an efficient way without losing accuracy. Since detailed contact search is performed off-line to obtain look-up contact tables, significant changes in contact points in turnout can be efficiently predicted on-line with tabular data to be interpolated in a standard way. Several numerical examples are presented in order to demonstrate the use of the numerical procedure developed in this investigation.

In this paper, a halftoning-based watermarking method is presented. This method enables high pixel-depth watermark embedding, while maintaining high image quality. This technique is capable of embedding watermarks with pixel depths up to 3 bits without causing prominent degradation to the image quality. To achieve high image quality, the parallel oriented high-efficient direct binary search (DBS) halftoning is selected to be integrated with the proposed orientation modulation (OM) method. The OM method utilizes different halftone texture orientations to carry different watermark data. In the decoder, the least-mean-square-trained filters are applied for feature extraction from watermarked images in the frequency domain, and the naïve Bayes classifier is used to analyze the extracted features and ultimately to decode the watermark data. Experimental results show that the DBS-based OM encoding method maintains a high degree of image quality and realizes the processing efficiency and robustness to be adapted in printing applications.

Table-lookup-and-addition methods provide multiplierless function evaluation using multiple lookup tables and a multioperand adder. In spite of their high-speed operation, they are only practical in low-precision applications due to the fast increase in table size with precision width. In this brief, we present two methods for table size reduction by decomposing the original table of initial values into two or three tables with fewer entries and/or smaller bit width. The proposed table decompositions do not incur any extra rounding errors so that the original table can be completely recovered. Experimental results demonstrate significant saving of table sizes compared with the best of the prior designs of the multipartite methods.

Mobile advertising refers to communication in which mobile phones are used as a medium to efficiently attract potential customers. Among mobile advertising applications, barcodes are becoming a very powerful mobile commerce tool. By capturing a barcode with a camera scanner, people can easily access a wealth of information online. Barcodes have thus converted hard copies of newspapers, wallpapers, and magazines into crucial platforms for mobile commerce. However, although barcodes are frequently used for embedding information in printed matter, they have unsightly overt patterns. Concealing data in visually meaningful image barcodes (such as trademarks) instead of using extra barcode areas has the advantage of increasing the added value of using conventional barcode patterns, and thus it is desirable for future mobile advertising. This paper presents a novel data-hiding method for halftone images. Data-hiding and halftoning algorithms are integrated into the method to prevent extreme bi-level quantization in the halftoning process, for printing purposes. We first applied regular ordered dithering to divide the input continuous-tone image into discrete-parameter halftone cells. The hidden data message was embedded in the halftone cells by using a screen column-shift method. A modified direct binary search (DBS) optimization framework was then used to enhance the output image quality. Simulation results demonstrated that the proposed method outperformed a state-of-the-art method in terms of image quality and data capacity.

The motivation behind this paper is to encode a secret picture SI into n shares of halftone pictures in VC scheme. In this paper it proposes a strategy for encoding a shading picture into n significant halftone shares utilizing the scheme of halftone visual cryptography secret pixels encrypted into shares acquaint commotion with the halftone pictures, the perceptual mistakes between the halftone shares and the continuous-tone pictures are minimized as for a human visual framework (HVS) demonstrate. The secret picture can be effectively decoded without demonstrating any impedance with the share pictures. The security of our strategy is ensured by the properties of VC. The proposed technique can encoded the secret pixels into the shares using the method of direct binary search (DBS) halftoning strategy for color pictures. The mistake between the halftone shares and the continous-tone pictures are minimized as for a human visual framework (HVS) show The recreation comes about portray that our proposed technique can enhance altogether the halftone picture quality for the encoded offers of grayscale pictures and colors pictures also utilizing the strategy for DBS to enhance the nature of halftone picture and revealed secret picture.

Direct binary search is used to optimize spatially dithered distributions of transparent and opaque pixels for beam shaping, improving the performance of spatial gain precompensation for laser systems, and wavefront metrology by optical differentiation.

A model for directly predicting the actual printed image produced by an ink‐jet printer is proposed. The distribution of ink dots in the printed image is determined solely by the halftone image, while the greyscale values of the sampled pixels are influenced by the blending of multiple ink colours, creating a complex mapping relationship. This paper presents a method to accurately measure ink dot displacement by establishing a deviation transformation relationship for each step of the ink‐jet‐to‐measurement process, enabling precise positioning of the nozzle offset. By combining the ink dot displacement data with the halftone image, an actual ink dot distribution model is constructed. A neural network is employed to fit the mapping between the ink dot distribution of the halftone image and the pixel greyscale values of the printed sample, thereby achieving the prediction of the real printed image. The experimental results demonstrate that the model can accurately predict the post‐press image and reflect the printer defects.

Achromatic multilevel diffractive lenses (AMDLs) represent a breakthrough in flat optics by overcoming chromatic aberration with practical manufacturability. This review examines their evolution from concepts to state-of-the-art devices (2016–2025), analyzing design methods, fabrication, limitations, and applications. We trace the development from zone plates to free-form AMDLs, highlighting the shift from analytical to computational design. The review explores inverse optimization algorithms like direct binary search and global optimization for achieving broadband achromatic performance. Manufacturing advances are categorized, from lithography for centimeter-scale devices to emerging techniques such as 3D printing and laser direct writing. Theoretical analysis establishes fundamental trade-offs between lens diameter, numerical aperture, bandwidth, and efficiency. We compare AMDLs with achromatic metalenses to outline the advantages and trade-offs of each paradigm. Furthermore, we examine the integration of artificial intelligence in AMDL design, from correction algorithms to end-to-end optimization. This synergy of computational optics, advanced manufacturing, and machine learning enables compact, high-performance optical systems for consumer electronics, scientific instrumentation, and photonic technologies, providing engineers with key insights and future research directions.

A framework to jointly halftone and watermark a grayscale images is presented. The framework needs the definition of three components: a human visual system (HVS)-based error metric between the continuous-tone image and a halftone, a watermarking scheme with a corresponding watermark detection measure, and a search strategy to traverse the space of halftones. We employ the HVS-based error metric used in the direct binary search (DBS) halftoning algorithm, and we use a block-based spread spectrum watermarking scheme and the toggle and swap search strategy of DBS. The halftone is printed on a desktop printer and scanned using a flatbed scanner. The watermark is detected from the scanned image and a number of post-processed versions of the scanned image, including one restored in Adobe PhotoShop. The results show that the watermark is extremely resilient to printing, scanning, and post-processing; for a given baseline image quality, joint optimization is better than watermarking and halftoning independently. For this particular algorithm, the original continuous-tone image is required to detect the watermark.

Optimal sampling method is effective in generating phase-only hologram. In this approach, the intensity of a source image is multiplied with an optimal sampling lattice, and converted into a hologram. Subsequently, the phase component of the hologram is retained as a phase-only hologram. The optimal sampling lattice is optimized through direct binary search so that the reconstructed image is closest to a given training image. A hologram generated with this method is known as an optimal sampled phase-only hologram (OSPOH). The reconstructed image of an OSPOH is generally good, but its quality cannot be further improved by extending the optimization process. In this paper, an enhancement on the reconstructed image of OSPOH through time-division filtering is presented. Experiment results revealed that the proposed method can lead to significant enhancement on the reconstructed image.