LUT与Elman网络相结合的图像逆半调算法

为改进查找表逆半调算法中"未出现半调模式逆半调值"的估计精度,提出了一种查找表与Elman回归网络相结合的图像逆半调算法。该算法首先通过样本图集生成初步逆半调查找表,然后以Elman型回归网络为工具,构造、训练逆半调逼近模型,最后达到拟合"未出现半调模式逆半调值"的目的,产生完整查找表,支持逆半调处理。实验结果及性能分析表明,应用本文算法生成的逆半调重建图像在视觉效果及PSNR指标上表现良好,具有运行速度快、空间复杂度低的特点。     

基于B样条小波的彩色印刷扫描图像逆半调

彩色印刷是一种利用黄、品红、青、黑四色油墨叠印产生彩色图像的技术,逆半调是将半色调图像转换成连续调图像的过程,主要应用在电子出版和印刷图像电子化方面。选取LAB颜色空间作为逆半调处理的颜色空间,选择三阶B样条小波作为小波基,遵循小波分解、小波系数调整、小波重构的小波变换算法,对彩色印刷扫描图像进行逆半调处理,得到逆半调图像。实验结果表明,该算法避免了破坏彩色图像红、绿、蓝颜色通道的颜色相关性,对彩色印刷扫描图像的重建和印刷加网图像的恢复具有一定的理论意义和应用价值。     

查找表与神经网络相结合的图像逆半调算法

为提高查找表逆半调算法中“未出现半调模式逆半调值”的估计精度,本文提出了基于IRN神经网络的逆半调逼近模型,通过分析、训练和优化确定了合适的IRN网络结构、隐层数、隐层节点数。实验结果表明,应用该算法训练、拟合出的查找表数据在逆半调重建图像的视觉效果及PSNR指标上表现良好,而且算法执行速度快、空间复杂度低。     

多尺度框架误差分散逆半调方法研究

摘 要：通过分析现有基于滤波的误差分散逆半调方法,提出了一种多尺度逆半调框架。基于该框架,引入平稳小波变换,提出了一种新的逆半调算法。首先,对半调图进行3尺度离散平稳小波变换,通过分析各尺度图像的频谱特性,构造了HIST滤波器,并结合尺度间小波系数的相关性,采用不同策略分别抑制各尺度图像中的噪声,最后利用小波反变换得到逆半调图像。实验验证了多尺度逆半调框架的正确性,并且该算法所得逆半调图像具有良好的视觉效果,能保持图像边缘,峰值信噪比也有所提高。     

MSPRL：面向图像逆半色调的多尺度渐进式残差学习网络

目的 图像逆半色调的目的是从二值半色调图像中恢复出连续色调图像。半色调图像丢失了大量原始图像内容信息,因此逆半色调成为一个经典的图像重建病态问题。现有的逆半色调算法重建效果无法满足对图像细节和纹理的需求。此外,已有方法大多忽略了训练策略对模型优化的重要影响,导致模型性能较差。针对上述问题,提出一个逆半色调网络以提高半色调图像重建质量。方法 首先提出一个端到端的多尺度渐进式残差学习网络（multiscale progressivoly residual learning network,MSPRL）以恢复出更高质量的连续色调图像。该网络基于UNet架构并以多尺度图像作为输入;为充分利用不同尺度输入图像的信息,设计一个浅层特征提取模块以捕获多尺度图像的注意力信息;同时探讨不同学习策略对模型训练和性能的影响。结果 实验在7个数据集上与6种方法进行对比。在Place365和Kodak数据集上,相比性能第2的方法,峰值信噪比（peak signal-to-noise ratio,PSNR）分别提高0.12dB和0.18dB;在其他5个常用于图像超分辨率的测试数据集Set5、Set14、BSD100（Berkeley segmentation dataset 100）、Urban100和Manga109上,相比性能第2的方法,PSNR值分别提高0.11dB、0.25dB、0.08dB、0.39dB和0.35dB。基于本文的训练策略,重新训练的渐进式残差学习网络相比未优化训练模型在7个数据集上PSNR平均提高1.44dB。本文方法在图像细节和纹理重建上实现最优效果。实验表明选用合适的学习策略能够优化模型训练,对性能提升具有重要帮助。结论 本文提出的逆半色调模型,综合UNet架构和多尺度图像信息的优点,选用合适的训练策略,使得图像重建的细节与纹理更加清晰,视觉效果更加细致。本文算法代码公布在https://github.com/Feiyuli-cs/MSPRL。     

Digital halftoning by iterative isotropic error feedback

An error diffusion scheme for digital halftoning is proposed. The scheme is an iterative and isotropic error feedback process. Also, to compensate for the nonlinear tone reproduction by laser printers due to ink drop overlaps, we incorporate Pappas-Neuhoff's simplified printer model into the new error diffusion scheme. It appears that the proposed halftoning technique enhances the perceived tone continuity of halftone hard copies, and it alleviates the objectionable structured halftone textures of some existing methods. In addition, a mechanism is suggested to preview a halftone print on a gray-level CRT monitor. The user can interactively set the desired brightness of the halftone print and balance image contrast and tone continuity, which are two mutually exclusive subjective criteria for halftone reproduction.     

Thermodynamics-inspired inverse halftoning viamultiple halftone images

Based on an analogy between thermodynamics and Bayesian inference,inverse halftoning was formulated using multiple halftone images based on Bayesian inference using the maximizer of the posterior marginal(MPM) estimate.Applying Monte Carlo simulation to a set of snapshots of the Q-Ising model,it was demonstrated that optimal performance is achieved around the Bayes-optimal condition within statistical uncertainty and that the performance of the Bayes-optimal solution is superior to that of the maximum-a-posteriori(MAP) estimation which is a deterministic limit of the MPM estimate.These properties were qualitatively confirmed by the mean-field theory using an infinite-range model established in statistical mechanics.Additionally,a practical and useful method was constructed using the statistical mechanical iterative method via the Bethe approximation.Numerical simulations for a 256-grayscale standard image show that Bethe approximation works as good as the MPM estimation if the parameters are set appropriately.     

一种改进的查找表逆半调算法

边缘和平滑区域是图像的重要组成部分,人眼对边缘特征和平滑区域的噪声比较敏感。文中提供了一种改进的查找表逆半调算法,该算法在查找表逆半调算法的基础上考虑了边缘在图像处理中的作用,并对图像边缘分类,然后,按照半调图及图像边缘的类型重构连续色调图像。通过由误差分散类半调图构成的不同频率特征的训练集、测试集进行实验,表明当训练集为平滑图像集时基于边缘的查找表逆半调算法处理平滑图像,在主、客观评价方面的效果都好于查找表逆半调算法处理的图像;而改进的方法在处理细节图像时与查找表逆半调算法相比没有优势。     

Color recovery of black-and-white halftoned images via categorized color-embedding look-up tables

A new method of recovering the original colors of black-and-white (B&W) halftoned images with homogeneous dot patterns is proposed. The conventional inverse halftoning method, which uses a look-up table (LUT), can establish the relation between the halftoned patterns and the corresponding gray levels, while the conventional reversible color to gray conversion method can recover the original colors from a given color-embedded gray image. To accomplish our goal of original color recovery from B&W halftoned patterns, an approach of combining the conventional inverse halftoning and reversible color to gray conversion is presented in this paper. Differently from the conventional method of inverse halftoning via LUT, four LUTs categorized according to the red, green, blue, and gray reference colors are designed to more accurately map a specific B&W halftone pattern into the corresponding color-embedded gray level based on the observation that the shapes of the halftone patterns depend on input colors, thereby increasing the color recovery accuracy. Also, a color mapping method based on a linear regression which models the relation between the recovered colors and the original colors is introduced to adjust the initially recovered colors more closely to the original colors. Experimental results show that unknown original colors can be recovered from B&W halftoned images via the proposed method.     

A gradient-based adaptive error diffusion method with edge enhancement

This paper presents a gradient-based adaptive error diffusion method with edge enhancement effect while preserving the smoothness effect. The proposed method not only can modulate the threshold in halftoning dynamically but also can determine the weights of the error diffusion filter adaptively to diffuse the quantization error to neighboring pixels properly. Under six testing images, experimental results demonstrate that our proposed new error diffusion method has a good compromise between the edge enhancement effect in the halftone image and the image quality effect in the corresponding inverse halftone image when compared to the methods by Floyd–Steinberg, Eschbach and Knox, Hwang et al., Li, and Feng et al., but it has some execution-time degradation.     

A New Model-Based Digital Halftoning and Data Hiding Designed With LMS Optimization

This work employs the well known least-mean-square (LMS) method to design an adaptive filter to produce high-quality halftone images. The filter can be regarded as a transformation medium between original gray level images and corresponding halftone images. Experimental results indicate that the proposed LMS-designed halftoning offers the extra benefit of edge enhancement. Since a halftone image is typically used in printing, a modified printer model, which can coordinate with the proposed LMS-designed halftoning, is proposed to eliminate the harm caused by the dot-gain effect in printing. Moreover, two data hiding applications, the direct embedding LMS-designed halftone technique (DELDH) and the information sharing LMS-designed halftone technique (ISLDH), are proposed to demonstrate the performance of the proposed LMS-designed halftoning. The experimental results show that, both techniques can be used with the proposed modified printer model to achieve excellent image quality and decoded visual patterns     

基于Laplacian金字塔的逆有序抖动算法

针对有序抖动半调图,提出一种基于Laplacian金字塔的逆半调方法。采用分治策略,利用Laplacian金字塔变换将图像分成低频和高频区域,通过滤波器组抑制高频噪声,同时保持图像边缘,改善逆半调图像的质量。实验证明,该算法具有时空复杂度较低、峰值信噪比高等特点。     

基于空间信息的彩色逆半调图像评价方法

针对彩色逆半调图像提出一种基于空间信息的质量评价方法。首先,将图像变换到视觉均匀颜色空间S-CIELab空间,通过定义人眼感知色差图像和感知梯度图像,构造评价彩色逆半调图像质量的定量指标。仿真结果表明：该指标反映的结果符合人眼视觉特性,与人的主观评价结果基本一致,它为基于图像内容的彩色逆半调方法的设计提供了依据。     

Inverse error-diffusion using iterated conditional modes

Error-diffusion (ED) is one conventional halftoning technique that converts a gray-level image into a halftone. For further processing the ED halftones, it is often necessary to estimate the original image from the halftone: the inverse of ED. We propose to calculate iterated conditional modes (ICM) for the maximum a posteriori (MAP) solution of inverse ED. The ICM always searches for a better estimate in the valid image space. It requires only local computation and is applicable to any type of the MRF model used for the original gray-level images. Experimental results for common standard images are given to show that our ICM performs well and is more flexible than the descent-projection (DP) approach.     

基于偏微分方程的误差分散逆半调改进算法

结合误差分散半调噪声特征,提出一种基于偏微分方程的逆半调改进算法。通过研究偏微分方程的去噪原理,以3次B样条函数作为扩散函数,采用迭代求解偏微分方程的方法估计逆半调图像,计算每次迭代前后图像梯度模值的增量以确定平滑度的调节参数,解决偏微分方程在应用中的参数选择自适应问题。实验结果表明,该算法在图像整体平滑度和细节保持能力上都具有较好的效果。     

基于K-means聚类的数字半色调算法

数字半色调是在二值设备或多色二值设备上实现图像再现的一门技术,提出将K-means聚类法应用在数字半色调技术中。算法中应用人类视觉系统模型(HVS)和印刷模型最大限度减少原始灰度连续调图像和半色调图像之间的视觉误差;利用K-means聚类法将灰度图像划分成聚类分区,在每个聚类分区应用最小平方法(least-squares)最小化二值半色调图像和原始灰度级图像之间的平方误差,所构造的半色调算法与基于模型的最小平方法(LSMB)算法相比,随着聚类分区的增加,图像平滑且边缘清晰度增加,尤其是在图像细节部位。与LSMB算法比较,该算法的均方误差值有所降低,而权重信噪比和峰值信噪比提高了0.2～2 dB,模拟实验结果验证了算法的有效性。     

A fuzzy neural approach to design of a Wiener printer model incorporated into model-based digital halftoning

This paper presents the design of a Wiener model for a class of laser electrophotographic printers utilizing a fuzzy neural approach. The feasibility and effectiveness of incorporating the proposed spatial-based Wiener printer model into the framework of model-based digital halftoning is also investigated. The Wiener model comprises a two-dimensional FIR filter followed by a nonlinear static mapping. The nonlinear static mapping is synthesized based on a fuzzy neural network to account for the tone distortion commonly observed in a printing system. A set of systematic steps for parametric identification/optimization and evaluation of the Wiener printer model is proposed. Experimental results as well as a comparative study show that the Wiener model-based halftoning approach is superior (in terms of image quality) to conventional ones and comparable to the one utilizing a comprehensive printer model. Another comparative study reveals that the Wiener printer model, though computationally less efficient than the conventional dot-overlap model, consumes significantly less time to process an image than the comprehensive printer model does.     

图像逆半调及其质量评价综述

数字半调是数字印刷乃至现代印刷的核心技术之一。半调可使连续色调图像转换为二值图像。如需对半调图像作分类识别、图像压缩、图像增强等处理,就应先让半调图像重建为连续色调图像,即进行逆半调处理。首先介绍了半调图像的不同发展阶段;然后对已有的逆半调方法根据不同的图像恢复依据进行了分类介绍,并对重建的逆半调图像的质量进行了客观评价;最后总结了已有逆半调方法的不足,并指出了未来可改进的关键方向。     

An improved parallel contrast-aware halftoning

Digital image halftoning is a widely used technique. However, achieving high fidelity tone reproduction and structural preservation with low computational time cost remains a challenging problem. This paper presents a highly parallel algorithm to boost real-time application of serial structure-preserving error diffusion. The contrast-aware halftoning approach is one such technique with superior structure preservation, but it offers only a limited opportunity for graphics processing unit （GPU） accel- eration. Our method integrates contrast-aware halftoning into a new parallelizable error-diffusion halftoning framework. To eliminate visually disturbing artifacts resulting from parallelization, we propose a novel multiple quantization model and space-filling curve to maintain tone consistency, blue-noise property, and structure consistency. Our GPU implementation on a commodity personal computer achieves a real-time performance for a moderately sized image. We demonstrate the high quality and performance of the proposed approach with a variety of examples, and provide comparisons with state-of-the-art methods.     

一种非线性逆有序抖动的方法

针对有序抖动半调图,提出一种以非线性滤波技术为基础的快速、非迭代逆半调方法。它采用低通和非线性滤波的层叠,有效平滑了灰度变化平缓区域的半调噪声。通过分离边缘信息补偿非线性滤波损失的细节,以改善逆半调图像的质量。算法具有存储容量要求低,峰值信噪比高等特点。