An Optimized Implementation of a Novel Nonlinear Filter for Color Image Restoration

Image processing is becoming more popular because images are being used increasingly in medical diagnosis,biometric monitoring,and character recognition.But these images are frequently contaminated with noise,which can corrupt subsequent image processing stages.Therefore,in this paper,we propose a novel nonlinear filter for removing“salt and pepper”impulsive noise from a complex color image.The new filter is called the Modified Vector Directional Filter(MVDF).The suggested method is based on the traditional Vector Directional Filter(VDF).However,before the candidate pixel is processed by the VDF,theMVDF employs a threshold and the neighboring pixels of the candidate pixel in a 3×3 filter window to determine whether it is noise-corrupted or noise-free.Several reference color images corrupted by impulsive noise with intensities ranging from 3%to 20%are used to assess theMVDF’s effectiveness.The results of the experiments show that theMVDF is better than the VDF and the Generalized VDF(GVDF)in terms of the PSNR(Peak Signal-to-Noise Ratio),NCD(Normalized Color Difference),and execution time for the denoised image.In fact,the PSNR is increased by 6.554%and 12.624%,the NCD is decreased by 20.273%and 44.147%,and the execution time is reduced by approximately a factor of 3 for the MVDF relative to the VDF and GVDF,respectively.These results prove the efficiency of the proposed filter.Furthermore,a hardware design is proposed for the MVDF using the High-Level Synthesis(HLS)flow in order to increase its performance.This design,which is implemented on the Xilinx ZynqXCZU9EG Field-ProgrammableGate Array(FPGA),allows the restoration of a 256×256-pixel image in 2 milliseconds(ms)only.

An anti-aliasing filtering of quantum images in spatial domain using a pyramid structure

As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum domain.This paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial domain.It achieves the effect of anti-aliasing filtering on quantum images during the scaling process.First,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical images.Since aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of reduction.Subsequently,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing effect.The constructed pyramid model is then used to select an appropriate image for upscaling to the original image size.Finally,the complexity of the circuit is analyzed.Compared to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer outputs.Additionally,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.

Median Filtering Forensics Scheme for Color Images Based on Quaternion Magnitude-Phase CNN

In the paper,a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images.Compared with conventional convolutional neural network,color images can be processed in a holistic manner in the proposed scheme,which makes full use of the correlation between RGB channels.And due to the use of convolutional neural network,it can effectively avoid the one-sidedness of artificial features.Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection.

Narrow-band high-transmittance birefringent filter and its application in wide color gamut display

We propose a narrow-band birefringent filter and its application in wide color gamut.The birefringent filter consists of five phase retarders and two polarizers,and it has both narrow band and high transmittance.In the experiment,we fabricate the birefringent filter using quartz phase retarders and polarizers,and apply it in serval different displays.The color gamuts of displays are enhanced more than 30%NTSC(National Television System Committee),and the widest color gamuts that have been obtained are 126%NTSC in liquid crystal displays and 138%NTSC in organic light-emitting devices.Moreover,the deep blue light in spectrum of display can be reduced using the birefringent filter.The birefringent filter can be an efficient element to achieve wide color gamut display.

Selective removal technology using chemical etching and excimer assistance in precision recycle of color filter

Color filters are produced using semiconductor production techniques although problems with low yield remain to be addressed. This study presents a new means of selective removal using excimer irradiation, chemical etching, or electrochemical machining on the fifth generation TFT LCDs. The selective removal of microstructure layers from the color filter surface of an optoelectronic flat panel display, as well as complete removal of the ITO thin-films, RGB layer, or resin black matrix (BM) layer from the substrate is possible. Individual defective film layers can be removed, or all films down to the Cr layer or bare glass can be completely eliminated. Experimental results demonstrate that defective ITO thin-films, RGB layers, or the resin BM layer can now be recycled with a great precision. When the ITO or RGB layer proves difficult to remove, excimer light can be used to help with removal. During this recycling process, the use of 225 nm excimer irradiation before chemical etching, or electrochemical machining, makes removal of stubborn film residues easy, effectively improving the quality of recycled color filters and reducing fabrication cost.

Static filtering and collocation in successive steps for measurements with colored noises

The theory of static filtering in successive steps with colored noises is ample scope for its application in the procedure of GPS data processing. A majority of error and round-cycle distinctness in the measurements of GPS carrier phase can be eliminated through three times of differential calculations of stations, satellites and epochs, in which the cycle beatings became isolated values. The observation error of three-differentials in the intervals between epochs results in block diagonal matrixes in the covariance matrixes, so that the desired matrixes occupy too large memory and the processing time is too long. Therefore, by using the theory of static filtering in successive steps with colored noises, the interrelation can be eliminated and can save the processing time and memory.

Color reproduction for noisy CFA data using directional cycle-spinning

This paper addresses color filter array（CFA） color reproduction problem where the aim is to utilize an image captured by the CFA to produce an image with full color information.First,conventional subband synthesis based color reproduction techniques do not consider the noise during image acquisition and assume that the CFA data are noiseless.To tackle the noisy CFA data,a novel approach is proposed by inserting a subband denoising scheme into the conventional subband synthesis framework.Second,conventional subband synthesis based techniques exploit the decimated wavelet transform that is not shift-invariant and could result in ringing artifacts in the result.To alleviate these artifacts,the directional cycle-spinning（DCS） technique is exploited.Furthermore,a new cycle-spinning pattern is proposed according to the sampling pattern of the Bayer CFA data.Extensive experiments are conducted to demonstrate that the proposed approach outperforms several approaches.

COLOR-SCALE MORPHOLOGICAL FILTERS WITH MULTIPLE STRUCTURING ELEMENTS

With the wide use of color in many areas, the interest on the color perception and processing has been growing rapidly. An important topic in color image processing is the development of efficient tools capable of filtering images without blurring them and without changing their original chromatic contents. In this paper, a new technique reducing noise of color image is developed. A class of color-scale morphological operations is introduced, which extend mathematical morphology to color image processing, representing a color image as a vector function. The correlation between color components is utilized to perform noise removal. Color-scale morphological niters with multiple structuring elements (CSMF-MSEs) are proposed. Their properties are discussed and proved. Experimental results show that CSMF-MSEs are suitable and powerful to eliminate noise and preserve edges in color image because of efficient utilization of inherent correlation between color components, and they perform better than vector

Accurate Tools for Analyzing the Behavior of Impulse Noise Reduction Filters in Color Images

Effective cancellation of noise and preservation of color/structural information are features of paramount importance for any filter devoted to impulse noise removal in color images. In this paper novel full-reference tools for analyzing the behavior of this family of filters are presented. The proposed approach is based on the classification of color errors into two main classes that separately take into account the inaccuracy in removing noise pulses and the filtering distortion. The distortion errors are then classified into two subclasses for a deeper analysis of the filtering behavior. Computer simulations show that the proposed method gives more accurate results than using other measures of filtering performance in the literature. Furthermore, the method can easily yield the spatial location of the different filtering features in the image.

Preparation and Optical Patterning of Organic-Inorganic Hybrid Color-Filter Films Using Latent Pigments by Utilizing Photo-Acid-Generator and Microwave Irradiation

Preparation and photo-patterning characteristics of organic-inorganic hybrid thin film containing latent pigment by using photo-acid-generator (PAG) and microwave irradiation have been investigated. The acrylic thin film modified with methoxysilane containing PAG was formed on a glass substrate and irradiated with ultraviolet rays to promote sol-gel reaction by catalytic action of acid which was generated from PAG. And then the film was hardened with microwave irradiation, yielding organic-inorganic hybrid polymer film having hardness, highly transparency and strong adhesion with a glass substrate. Since this reaction only occurred in the optically (UV) irradiated regions, by exploiting the difference between the adhesivenesses of these regions photo-irradiated through photomask with a glass substrate, it was possible to form a patterned film with pitch of 100 to 50 μm by a simple lift-off method. A pigment-containing film using latent pigments (with subtractive three primary colors of coloring materials) and a patterned film were prepared, and it was possible to make these films multi-colored by varying the mixing ratio of the pigments. This multi-colored film-preparation method is effective for simply and efficiently forming a color-filter film by applying optical and microwave irradiation.

Assessing the Effect of Colored Filters on Glare Sensitivity of Post Refractive Surgery Patients

Purpose:The use of colored filters is one recommended way for patients to reduce glare..This study assessed the effect of colored filters for reducing glare symptoms in post refractive surgery patients.Method:.Log MAR visual acuity was determined in 70 participants.(140 eyes).who had undergone PRK refractive surgery using three colored filters(Yellow,Green,and Red)in different light conditions.Results:.Measured visual acuity was significantly reduced with red and green filters in glare and nonglare conditions when compared to its measurement without a filter.An asymmetrical light condition also revealed a significant difference in the visual acuity of the right and left eye when compared to each other.However,no significant differences were observed for the yellow filter in either the measured visual acuity of each eye in both light conditions or of the right and left eyes compared to each other.Conclusion:Red and green filters are poor choices for reducing glare in post refractive surgery patients but a yellow filter could be used to decrease glare and improve acuity.

Edge Pattern Based Demosaicking Algorithm of Color Filter Array

An efficient adaptive approximation demosaicking algorithm based on the sampled edge pattern was presented for mosaic images from Bayer color filter array. The proposed algorithm determined edge patterns by four nearest green values surrounding the green interpolation location. Then according to the edge patterns, different adaptive interpolation steps were applied. Simulations on 12 Kodak photos and 15 IMAX high-quality images showed that the proposed method outperformed the other four demosaicking methods (bilinear, effective color interpolation, Lu's method and Chen's method) for average color peak signal to noise ratios and maintained a relatively low complexity owing to constant color-difference interpolation step and a reasonable terminating condition of iteration.

Angle robust transmitted plasmonic colors with different surroundings utilizing localized surface plasmon resonance

Color filters in different surroundings inherently suffer from angular sensitivity,which hinders their practical applications.Here,we present an angle-insensitive plasmonic filter that can produce different color responses to different surrounding environments.The color filters are based on a two-dimensional periodically and randomly distributed silver nanodisk array on a silica substrate.The proposed plasmonic color filters not only produce bright colors by altering the diameter of the Ag nanodisk,but also achieve continuous color palettes by changing the surrounding environment.Due to the weak coupling between the metallic nanodisks,the plasmonic color filters can enable good incident angle-insensitive properties(up to 30°).The strategy presented here could exhibit robust and promising applicability in anti-counterfeiting and imaging technologies.

基于多尺度梯度域引导滤波的煤矿井下图像增强方法

煤矿井下图像存在较严重的光照不均匀和噪声干扰,现有基于Retinex的方法直接应用于煤矿井下图像增强易出现光晕伪影、边缘模糊、过增强和噪声放大等问题。针对上述问题,提出了一种基于多尺度梯度域引导滤波的煤矿井下图像增强方法。首先,将多尺度思想引入梯度域引导滤波中,实现对非均匀光照的准确估计,有效解决了增强图像时光晕伪影及边缘模糊的问题。然后,利用Retinex模型分离出光照分量和反射分量:对于光照分量,通过自适应伽马校正函数逐像素地修正光照信息,实现对图像暗区域增强的同时,抑制亮区域过增强,并使用限制对比度自适应直方图均衡化方法调整图像对比度;对于反射分量,将梯度域引导滤波与多尺度细节提升相结合,在准确去除噪声后提升纹理细节,避免了增强图像时噪声放大的问题。最后,将处理后的光照分量及反射分量融合,计算图像增益系数,并使用线性色彩恢复方法实现对原始RGB图像的逐像素增强,提升方法处理效率。实验结果表明,从主客观角度与现有方法相比,经所提方法处理后的图像在色彩保持、对比度、噪声抑制、细节保留等方面均取得了较好的增强效果,同时处理效率较高。

中国经济周期波动的典型化事实:一个基于CF滤波的研究

从宏观时间序列经验特征中概括经济周期波动的典型化事实是经济学研究的一项重要课题,也是当前中国经济周期波动研究的欠缺所在。本文采集23个主要宏观经济变量数据,运用新近提出的CF滤波,分解得到它们的周期性成分,并计算这些周期性成分的标准差、自相关系数以及它们之间的时差相关系数。在此基础上,分析了中国经济周期波动的经验特征,总结出中国经济周期波动的典型化事实,并与美国的研究结果加以对比,揭示出中国经济周期波动经验特征和典型化事实的一般性和特殊性。本文的研究进一步验证了Lucas(1977)命题,也有助于为相关理论发展和宏观调控操作提供参照和借鉴。

CFA图像插值算法在DSP实时系统上的应用

彩色滤波阵列(CFA)格式的图像需要进行图像插值,才能获得全彩色图像。但是,由于相机噪声的存在,不仅该点的彩色信息失真,同时还会影响邻近像素利用该点信息进行插值的图像颜色。为了得到高质量的全彩色图像,采用了一种基于梯度的滤噪插值算法,在保留了图像边缘和细节信息的同时,滤除了噪声,使图像的信噪比提高了近1倍;由于这种数字相机没有白平衡处理,使插值恢复的彩色图像颜色与实际景物相比存在较大差异,为了消除这种差异,实现了自适应白平衡校正方法,使图像方差提高了近20%,与人眼观察到实际景物的颜色更接近;整个彩色编码算法应用了DSP的并行流水线技术,保证了其在DSP上运行的实时性,处理频率达到25 Hz。

融合有限差分及梯度的Bayer-CFA插值方法

为了实现对边缘像素点的高精度插值,融合有限差分、图像梯度、图像相关性提出了一种先插值再修正的Bayer彩色滤波阵列(color filter array,CFA)插值方法Bayer-CFA。首先,把CFA图像中的已知像素点作为离散的网格节点,利用像素点间的空间相关性构造插值函数。然后,结合色彩相关性设计插值G像素的水平、垂直方向的插值算子,并用梯度信息建立两个方向的权重因子,实现G平面插值;再根据G像素点左右的已知R像素点的对称性及色彩相关性构建插值函数,应用色差公式完成R平面插值,并用与R平面插值相同的方法完成B平面插值。最后,对每个插值结果,在以其为中心的3×3邻域内进行梯度修正,采用梯度信息构造8个方向的权重因子,用像素点的空间位置决定加权系数,以消除不规则边缘及纹理引起的插值误差。仿真结果表明:相较于EET算法,Bayer-CFA的彩色图像峰值信噪比提高了0.57 dB,S-CIELAB空间的色差降低了0.23;Bayer-CFA在使用梯度修正后能减少伪彩色,沿边缘方向的插值有效削弱了锯齿现象,能保留图像的边缘纹理细节。

用于钢铁回收中的目标检测与尺寸估计算法

为解决钢铁回收过程中由于开放式复杂场景而无法准确地获得目标废钢点云进行尺寸估计,文章提出一种基于Mask R-CNN模型预测掩膜自适应颜色阈值的目标点云提取算法。针对Mask R-CNN模型边缘分割的不完整性,通过预测框对点云进行截取,利用自适应颜色滤波阈值对截取的点云进行HSV颜色空间滤波,将非目标点云离散化,最后通过欧式聚类对目标点云进行分割并进行尺寸估计。通过废旧汽车B柱模拟回收场景,获取汽车B柱点云,验证了该算法的有效性。

基于协方差矩阵的CFA插值盲检测方法

从数字图像中盲检测数码相机采用的CFA插值算法,可以为数字图像取证提供重要的技术手段。该文基于线性插值模型,利用协方差矩阵构建插值系数方程组,并将估计的插值系数构成特征向量空间,采用支持向量机作为分类工具,提出了一种对不同的CFA插值算法进行准确分类的盲检测方法。实验表明,该文方法对于不同的CFA插值算法均能达到较高检测正确率。同时,相比现有的CFA插值检测方法,该文算法对加性高斯白噪声和有损JPEG压缩具有更好的鲁棒性。