Continuous-tone Images Research Articles

Reversible Data Hiding in Encrypted Color Halftone Images with High Capacity

In recent years, reversible data hiding (RDH) has become a research hotspot in the field of multimedia security that has aroused more and more researchers’ attention. Most of the existing RDH algorithms are aiming at continuous-tone images. For RDH in encrypted halftone images (RDH-EH), the original cover image cannot be recovered losslessly after the watermark is extracted. For some application scenarios such as medical or military images sharing, reversibility is critical. In this paper, a reversible data hiding scheme in encrypted color halftone images (RDH-ECH) is proposed. In the watermark embedding procedure, the cover image is copied into two identical images to increase redundancy. We use wet paper code to embed the watermark into the image blocks. Thus, the receiver only needs to process the image blocks by the check matrices in order to extract the watermarks. To increase embedding capacity, we embed three layers in the embedding procedure and combine the resulting images into one image for convenience of transmission. From the experimental results, it can be concluded that the original image can be restored entirely after the watermarks are extracted. Besides, for marked color halftone images, our algorithm can implement high embedding capacity and moderate visual quality.

Joint design of plane-dependent FM screens sets using DBS algorithm

Color Halftoning is a technique for generating a halftone image by using a limited number of colorants to simulate a continuous-tone image as perceived by a human viewer. This paper describes an algorithm to jointly design three screens for Cyan, Magenta and Yellow colorants using the Direct Binary Search algorithm. The results show that high-quality color halftone images can be obtained using the screens sets, and the computational complexity will be greatly reduced.

Sparsity-based inverse halftoning via semi-coupled multi-dictionary learning and structural clustering

Inverse halftoning is the restoration of a continuous-tone image from its halftone version, which is a critical process for halftone transform, digital archive management and high precision identification of halftone. In this paper, a novel inverse halftoning method based on semi-coupled multi-dictionary learning is proposed to address the cross-style image restoration from halftone images to continuous-tone images. By using semi-coupled multi-dictionary learning, multiple dictionary pairs and their corresponding mapping functions between continuous-tone image and its halftone version could be simultaneously learned. The learned multiple dictionary pairs can well represent the structure characteristics of halftone images and continuous-tone images, respectively. In addition, the mapping functions learned by semi-coupled manner can bridge the gap between the two different style images of halftone image and continuous-tone image. Unlike the existed methods, the proposed method could effectively relax the assumption of the same sparse coding coefficients in coupled dictionary learning. To obtain more accurate mapping functions, a structural clustering method for cross-style image patches is proposed by using SUSAN (smallest univalue segment assimilating nucleus) filtering and HOG (histogram of oriented gradient) features, which can capture the similar structure features from halftone images and continuous-tone images, and thus improve the classification accurate rate of halftone image patches. The experimental results demonstrate that the proposed method can restore higher quality continuous-tone images than that produced by the state-of-the-art methods, which not only reduce the screen noise in smooth regions, but also provide well fine details and clear edges.

AC coefficient and K‐means cuckoo optimisation algorithm‐based segmentation and compression of compound images

Compound images are containing palletise regions including text or graphics and continuous tone images. The compression of compound images is a challenging function and which is complicated to achieve it without degrading the quality of the images. This document is mainly used to improve the compression ratio and an efficient segmentation method is created to separate the background image, text and graphics from the compound images for to make the compression independently. The segmentation is performed through AC coefficient-based segmentation method resulting in smooth and non-smooth regions. The non-smooth region is again segmented by means of K-means cuckoo optimisation algorithm. In the second phase, the segmented background image, text and graphics were compressed by means of arithmetic coder, Huffman coder and JPEG coder, respectively. This proposed technique is implemented in the working platform of MATLAB and the results were analysed.

Edge-Preserving Error Diffusion for Multi-Toning Based on Dual Quantization

Digital multi-toning is a technique for converting a continuous-tone image into a multi-tone image for its reproduction with a multi-tone output device. It is becoming important as printers now have the ability to print dots of different intensities. Error Diffusion (ED) is an algorithm that has been shown to be effective for the multi-toning process and has been widely applied to digital printing tasks. However, in the actual printing process, conventional ED techniques for digital multi-toning are often unable to print a sufficiently good-quality image because of physical or mechanical dot gain. In particular, distortion of the contour of printed letters is noticeable. Black letters against a white background appear enlarged, whereas white letters on a black background appear faded. In this paper, we propose an edge-preserving ED algorithm to improve the quality of printed images. We prepare different quantization thresholds between the edge and other regions to allow for stable detection of the edge regions. In addition, we propose a multi-step edge-detection algorithm to avoid printed artefacts. Experimental results using printed images showed that the proposed algorithm improved the quality of printed images in comparison with conventional techniques.

On Large Local Error Accumulation in Multilevel Error Diffusion

Error diffusion is an often used method that transforms a continuous tone (multibit) image into an image of lower bit depth, most commonly into a binary output of black and white. The simplicity of the processing and the quality of the output have made error diffusion a frequently used tool. Part of the image quality is attributed to the minimization of quantization errors in the error-diffusion process. This article describes local instabilities in a color multilevel error-diffusion system that—in contrast—can lead to large local errors in the output, far exceeding the normally expected quantization errors. This can have serious negative effects specifically in connection with the design and incorporation of color calibration sheets.

Deep neural network for halftone image classification based on sparse auto-encoder

To restore high quality continuous tone images from each class of halftone images, halftone image fine classification is the key problem. In this paper, a novel feature learning method is proposed for classifying 14 kinds of halftone images produced by the most well-known halftoning algorithms. This study employs the stacked sparse auto-encoders (SAE) trained with unsupervised learning for extracting features of halftone images, and then uses softmax regression with supervised learning for fine-tuning the deep neural network and classifying halftone images. In order to reduce the run-time of deep neural network and improve the image correct classification rate, we propose an effective patch extraction method for testing halftone images by measuring the mean and variance of local entropy in a patch. Halftone image classification is determined by the classification results of all effective patches inside an image via majority voting (MV). The experimental results demonstrate that our proposed method achieves an average correct classification rate (ACCR) of over 99.44% for 14 kinds of halftone images on two public image sets. Compared with state-of-the-art LMS–Bayes and M10–ML methods, the proposed SAE-MV method can distinguish the most categories of halftone images and achieve competitive ACCR, meanwhile, demonstrate better generalization performance.

Extended visual cryptography for continuous-tone images: effect of the optimum tone mapping

Visual cryptography is a kind of cryptography that can be decrypted only by a human visual system when stacking transparencies. Extended visual cryptography allows to print meaningful images on transparencies which can conceal the existence of 'secret' in the transparencies. Many studies have tried to incorporate continuous-tone images into extended visual cryptography. However, most of them failed in preserving the image quality after the encryption. This paper introduces a scheme for extended visual cryptography for continuous-tone images. The scheme is based on parallel error diffusion that can quickly encrypt images with no pixel expansion. The most important feature of this scheme is the optimum tone mapping so that the resulting images may have very high contrast comparing with the conventional schemes. Some experimental results are shown to evaluate the effectiveness of the optimum tone mapping.

Halftone image encryption based on reversible pairwise swapping

As a special kind of binary image, halftone image is produced by digital halftoning and widely used in printing. In recent years, some consumer electronics apply halftone image for lost-cost liquid crystal display systems. However, few techniques are reported for securing the content of halftone images, although a variety of schemes have been developed for continuous-tone image encryption in literatures. This paper proposes an encryption scheme for digital halftone images based on the principle of reversible pairwise swapping. The encryption and decryption phases are symmetrical because of the reversibility. It also can be easily integrated into some emerging display technologies such as cholesteric liquid crystal display which is used in electronic paper book. This secure method is also applicable for binary image encryption. Extensive experimental results demonstrate the effectiveness and efficiency of the proposed method.

Scanned image descreening with image redundancy and adaptive filtering.

Currently, most electrophotographic printers use halftoning technique to print continuous tone images, so scanned images obtained from such hard copies are usually corrupted by screen like artifacts. In this paper, a new model of scanned halftone image is proposed to consider both printing distortions and halftone patterns. Based on this model, an adaptive filtering based descreening method is proposed to recover high quality contone images from the scanned images. Image redundancy based denoising algorithm is first adopted to reduce printing noise and attenuate distortions. Then, screen frequency of the scanned image and local gradient features are used for adaptive filtering. Basic contone estimate is obtained by filtering the denoised scanned image with an anisotropic Gaussian kernel, whose parameters are automatically adjusted with the screen frequency and local gradient information. Finally, an edge-preserving filter is used to further enhance the sharpness of edges to recover a high quality contone image. Experiments on real scanned images demonstrate that the proposed method can recover high quality contone images from the scanned images. Compared with the state-of-the-art methods, the proposed method produces very sharp edges and much cleaner smooth regions.

An error diffusion based method to generate functionally graded cellular structures

The spatial variation of cell size in a functionally graded cellular structure is achieved using error diffusion to convert a continuous tone image into binary form. Effects of two control parameters, greyscale value and resolution on the resulting cell size measures were investigated. Variation in cell edge length was greatest for the Voronoi connection scheme, particularly at certain parameter combinations. Relationships between these parameters and cell size were identified and applied to an example, where the target was to control the minimum and maximum cell size. In both cases there was an 8% underestimation of cell area for target regions.

Multi-objective hardware–software partitioning of embedded systems: A case study of JPEG encoder

Embedded systems have become integral parts of today's technology-based life, starting from various home appliances to satellites. Such a wide range of applications encourages for their economic design using optimization-based tools. The JPEG encoder is an embedded system, which is applied for obtaining high quality output from continuous-tone images. It has emerged in recent years as a problem of optimum partitioning of its various processes into hardware and software components. Realizing pairing and conflicting nature among its various cost terms, for the first time the JPEG encoder is formulated and partitioned here as a multi-objective optimization problem. A multi-objective binary-coded genetic algorithm is proposed for this purpose, whose effectiveness is demonstrated through the application to a real case study and a number of large-size hypothetical instances.

A PREDICTIVE CODING METHOD FOR LOSSLESS COMPRESSION OF IMAGES

Images are an important part of today's digital world. However, due to the large quantity of data needed to represent modern imagery the storage of such data can be expensive. Thus, work on efficient image storage (image compression) has the potential to reduce storage costs and enable new applications.This lossless image compression has uses in medical, scientific and professional video processing applications.Compression is a process, in which given size of data is compressed to a smaller size. Storing and sending images to its original form can present a problem in terms of storage space and transmission speed.Compression is efficient for storing and transmission purpose.In this paper we described a new lossless adaptive prediction based algorithm for continuous tone images. In continuous tone images spatial redundancy exists.Our approach is to develop a new backward adaptive prediction techniques to reduce spatial redundancy in a image.The new prediction technique known as Modifed Gradient Adjusted Predictor (MGAP) is developed. MGAP is based on the prediction method used in Context based Adaptive Lossless Image Coding (CALIC). An adaptive selection method which selects the predictor in a slope bin in terms of minimum entropy improves the compression performance.

WDCT-based Image Coding Algorithm with Down-Sampling and APDCT Interpolation

Abstract The DCT-based JPEG standard is the most commonly used lossy compression algorithm for still continuous-tone images due to its high effectiveness and low computational complexity. However, the visually disturbing blocking artifacts generate when image is compressed at low bit rates. With the frequency warping, the warped discrete cosine transform (WDCT) makes the signal energy distribution more suitable for image coding. In order to improve the coding performance at low bit rates, this paper presents an image coding frame based on down-sampling and all phase DCT (APDCT) interpolation. Experimental results show that, no matter for PSNR or subjective result, the proposed method obviously improves the performance of image coding at low bit rates, and reduces the blocking artifacts significantly.

Continuous Tone Colour Printing in Two and a Half Dimensions Through a Combination of 19<sup>th</sup> Century Analogue Methodologies and 3D Printing

This paper proposes a contemporary method of continuous tone colour printing based upon the Nineteenth Century printing process of Woodburytype as developed by Walter Bentley Woodbury in 1865. Woodburytype was the only truly continuous tone printing process yet invented, and died out in the late nineteenth century as more expedient and cost effective methods of printing prevailed, thus laying the path for current CMYK print technologies. Digital print itself, since its development as a range of colour printing technologies, has followed a route based on the half-tone dot and four colour separation predicated around CMYK. In recent years stochastic algorithms and dithering have allowed the lay down of multiple passes and colour sets to create a near continuous tone image. The downside of this approach is that in order to create a full colour subtractive image, the resultant prints have very little surface topography and a mechanical uniformity that demonstrates none of the surface characteristics, tactile qualities and rich tonal warmth of the 19th century photomechanical processes.Current research at the Centre for Fine Print Research (CFPR) at the University of the West of England, Bristol, is exploring the potential of CNC milled imagery, where the tonal range of each colour is assigned a physical height to produce a continuous tone topographic relief printing matrix, from which the colour image is cast in a silicone ink. A translucent image is cast from each of the colour matrices and each colour is assembled one on top of another resulting in a true four colour separation continuous tone print, where colour tone is created by physical depth of colour.

Direct Binary Search Based Algorithms for Image Hiding

Digital halftoning is an important process to convert a continuous-tone image into a binary image with pure black and white pixels. The Direct Binary Search (DBS) is one of the well-known halftoning methods that can generate high quality binary images. The main contribution of this paper is to present a DBS based halftoning method that conceals a binary image into two binary images. More specifically, three distinct gray scale images are given, such that one of them should be hidden in the other two gray scale images. Our DBS based halftoning method generates three binary images that reproduce the tone of the corresponding original three gray scale images. Quite surprisingly, the secret binary image can be seen by overlapping the other two binary images. In other words, the secret binary image is hidden in two public binary images. Also, it is very hard to guess the secret images using only one of the two public images, and both of these two public images are necessary to get the secret image. Another contribution of this paper is to extend our DBS based halftoning method to hide one image and more than one image into more than two images. The resulting images show that our DBS based halftoning method hides and recovers the original images. Hence, our DBS based halftoning technique can be used for watermarking as well as amusement purpose.

Towards optimized binary pattern generation for grayscale digital halftoning: A binary particle swarm optimization (BPSO) approach

Grayscale digital halftoning produces bi-level representation of original continuous tone images. This process plays pivotal role for devices like printers, plasma panels, LCD displays, etc. The bi-level images can be considered as binary images where ‘0’ and ‘1’ correspond to black and white, respectively. This paper investigates potential of binary particle swarm optimization (BPSO) to generate faithful binary halftone patterns. The cost function addresses important characteristics of original images and pleasant visual appearance of halftone images. The paper also shows the application of pattern look-up-table (p-LUT) approach to address the high processing time of BPSO optimization and simple gradient-based edge enhancement for improved edge retention. Results are evaluated subjectively by statistical measures and psychovisual test. Results are evaluated objectively using image quality evaluation metrics as well. The comparisons with state-of-the-art techniques are also drawn. The evaluation results along with the comparisons show the competitive potential of the presented technique.

Continuous-tone images obtained using three primary-color electrochromic cells containing gel electrolyte

We prepared solid-state electrochromic (EC) cells based on phthalate derivatives and containing a gel electrolyte. The cells showed vivid color changes via electrochemical reactions, i.e., from being water transparent to assuming one of the three primary colors (cyan, magenta, and yellow). Moreover, we obtained continuous-tone images by using the three primary-color EC cells. The formation of continuous-tone images by using the EC cells was realized by applying a rectangular-wave voltage with various duty ratios. In addition, according to a subtractive color-mixture process, we obtained multiple color representations, including intermediate red, green, and blue colors, by stacking two of the three primary-color EC cells.

Organic Electrochromic Materials and Device toward Color Electronic Paper

We prepared solid-state electrochromic (EC) cells based on phthalate derivatives and containing a gel electrolyte. The cells showed vivid color changes via electrochemical reactions, i.e., from being water transparent to assuming one of the three primary colors (cyan, magenta, and yellow). Moreover, we obtained continuous-tone images by using the three primary-color EC cells. The formation of continuous-tone images by using the EC cells was realized by applying a rectangular-wave voltage with various duty ratios. In addition, according to a subtractive color-mixture process, we obtained multiple color representations, including intermediate red, green, and blue colors, by stacking two of the three primary-color EC cells.

A Navel approach Image compression based on Luminance and Chrominance using Binary Wavelet Transform (BWT) and Raster Line Technique

In rapid development multimedia the Images are awesome use full, image coding is the key and most prevalent in mass communication and storage system. This paper represents image compression based on Luminance and Chrominance using Binary Wavelet Transform 1 and Raster Line technique is proposed. This 2-5 techniques. In a distributed environment large image files remain a major bottleneck within systems. Compression is an important component of the solutions available for creating file sizes of manageable and transmittable dimensions. Increasing the bandwidth is another method, but the cost sometimes makes this a less attractive solution. Platform portability and performance are important in the selection of the compression/decompression technique to be employed. Compression solutions today are more portable due to the change from proprietary high end solutions to accepted and implemented international standards. In most of the applications the exact restoration of stored image is not mandatory. This fact can help to make the storage more effective, and in this way we get the lossy compression methods. JPEG is evolving as the industry standard technique for the compression of continuous tone images. But this has a limitation for the color images that the application where the color integrity is important like correcting chromatic aberration is not suitable for JPEG data. In this paper a lossy image compression is proposed by considering the chrominance aberration correction. II.