模糊数据的风险判别分析

引入建立在模糊样本均值和方差基础上的模糊距离概念，借助文献[2]的思想对文献[1]的模糊判别分析给出了此判别的风险分析方法。     

基于离散小波变换提高MTD检测性能的仿真分析

MTD雷达的多卜勒滤波器组由于加权处理而工作于失配状态,文献[1]介绍了一种利用离散小波变换(DWT)补偿信噪比损失的方法,但这种方法仅在回波多卜勒频率与滤波器中心频率偏移比较大时方显出其优势.作者在文献[2]中提出了一种基于加权FFT(WFFT)与FFT-DWT并行处理的新方法.本文则直接将WFFT与DWT作串行链接,仿真结果表明,该方法在整个频率范围内具有最优的检测性能.     

基于信息熵的图像置乱程度评价方法

在基于数字图像的信息隐藏算法中，如何评价图像置乱程度是一个很重要的问题。本文以图像分块信息熵与整体信息熵的比值作为置乱程度的判决标准，并同时利用各分块中互为相邻的像素差值的平均值作为加权系数进行加权平均提出一种新的图像置乱程度的评价方法，实验结果表明该评价方法可以有效地描述图像的置乱程度。     

一种融合局部像素信息和改进NLFCM的SAR图像分割方法

针对传统局部信息模糊C均值聚类算法权重系数仅由像素间欧式距离决定，无法准确衡量和充分利用像素间的相似性，对SAR图像分割不准确的问题，提出了一种全新的局部信息相似性描述方法，并结合图像的非局部信息，对像素到聚类中心的距离和像素隶属度计算方法进行改进，并提出了一种同时包含图像局部和非局部信息的改进SAR图像分割方法。实验表明，与其他模糊聚类方法相比，该方法在抑制SAR图像相干斑噪声的同时，能较好地保护SAR图像目标的边缘和细节，具有很好的SAR图像分割效果。     

一种基于感兴趣区域的红外目标提取方法

针对复杂背景下的红外图像的小目标提取问题,提出了一种新的红外图像自动分割方法.为了更好地控制计算复杂性及目标提取的准确性,本方法建立在通过自适应Butterworth高通滤波器找到的感兴趣区域之上并充分地利用了该区域中背景信息比较简单、目标易被分割的特性.同时,考虑到像素灰度是红处图像区分目标与背景的重要因素,而像素间的相邻度则能较好的防止虚警的产生,结合像素的灰度和相邻度的综合关系提出了一种新的分割原则.实验证明,新算法取得了很好的效果.     

图像脉冲噪声的模糊检测与消除

论述了基于模糊规则的脉冲噪声滤波器。该滤波器由模糊脉冲噪声检测器、噪声消除器与模糊结合器构成。模糊脉冲噪声检测器用窗口风的中值与邻近像素信息来检测脉冲噪声,而脉冲消除器用最小值算法来计算噪声像素的估计值。与传统的脉冲噪声滤波器相比较,所设计的新滤波器具有良好的脉冲噪声抑制与图像细节边缘保护的性能。     

一种具有细节保护功能的改进型中值滤波器

针对椒盐噪声污染的图像提出了一种改进型中值滤波算法.该算法是一种自适应型中心加权的高效中值滤波算法.通过计算边缘隶属度来自适应地调整中心像素的权值,从而控制新的滤波器对图像不同区域进行不同程度的平滑,即对细节丰富的图像区域进行轻度的平滑,而对细节较少的图像区域进行重度的平滑.实验结果表明,新的滤波算法优于传统的中值滤波器及常规的中心加权中值滤波器.     

一种改进型低功耗判决反馈均衡器的实现方法

以文献[2]中的PIPEADFE2结构为基础提出一种改进型的PIPEADFE2结构，并在算法级进行一种适用于低功耗设计的代数变换，将其应用在复数滤波器中，得到一种改进型的低功耗判决反馈均衡器结构。在复数滤波器的应用中，相比于文献[2]中提出的1、2两种结构，这种结构在收敛速度上有所提高，而且硬件复杂度也相对较低。     

网络、滤波、滤波器

0620077基于自相似和优化滤波器的防御DDoS软件设计与实现=Design and Realization of Software for Guard Against DDoS Based on Self-Similar and Optimization Filter[刊,英]／伍训仪／／中国邮电高校学报(英文版)．- 2006,13(1)．-44-48(E) 0620078迂回相位编码技术制作匹配滤波器的宏像素选取[刊,中]／张勇／／激光与红外．-2006,36(4)．-292-294(G)实验中选择了不同的宏像素取法制作光学相关器的匹配滤波器,可保留更多的复振幅信息,从而大大改善了光学相关器的识别能力,实验结果验证了该方法的正确性。参9     

整流滤波电路傅立叶分析方法的讨论

本文研究了带LC低通滤波的全波整流电路输出电压与负载和滤波器参数之间的关系,讨论了用傅立叶分析法计算电感电流和负载电压的可行性,评述了叠加定理在这种电路中的应用方法。通过以上论述,解释了文献[1]对文献[2]例题6.6的质疑。本文有助于读者对此类问题的深入理解。     

A Fuzzy Switching Median Filter of Impulses in Digital Imagery (FSMF)

This paper proposed a fuzzy-based switching technique that aims at detection and filtering of impulse noises from digital images. Two types of noise models are used to obtain the noisy images. In this two-step process, the noise-free pixels are remained unchanged. The proposed detection algorithm uses 5 \(\times \) 5 window, based on all neighboring pixels on the center of the window of a noisy pixel. Two weighted median filters are devised, and a particular one is applied selectively to the noisy pixel based on the characteristics of the neighboring pixels within the window. Instead of a single threshold, two threshold values are used in the proposed fuzzy membership function to partition the noise level, and accordingly, a filtering method is applied to restore the corrupted pixel. Experimental results show that the proposed technique outperforms the existing impulse denoising methods in terms of peak signal-to-noise ratio and visual effects, with a comparable time complexity with the existing methods.     

Joint-adaptive bilateral depth map upsampling

In this paper, we present a new depth upsampler in which an upsampled depth map is computed at each pixel as the average of neighboring pixels, weighted by color and depth intensity filters. The proposed method features two parameters, an adaptive smoothing parameter and a control parameter. The adaptive smoothing parameter is determined based on the ratio between a depth map and its corresponding color image. The adaptive smoothing parameter is used to control the dynamic range of the color-range filter. The control parameter assigns a larger weighting factor to pixels in the object to which a missing pixel belongs. In a comparison with five existing upsamplers, the proposed method outperforms all five in terms of both objective and subjective quality.     

基于相关度量的高椒盐噪声软阈值直方图滤波算法

利用图像邻域相关和直方图对椒盐噪声的鲁棒性,提出了一种针对高椒盐噪声图像的软阈值直方图加权滤波算法.对邻域灰度相关进行了量化分析,定义了灰度相关函数作为信号邻域相关性的度量,并将该系数作为直方图加权滤波算法的软阈值,根据像素被判定为噪声或有效信号的概率,自行调整滤波强度,减少图像滤波处理中的细节损失.仿真结果表明,对于高椒盐噪声图像,本算法在椒盐噪声滤除方面有良好的表现.     

Accurate object localization in gray level images using the center of gravity measure: accuracy versus precision

A widely used subpixel precision estimate of an object center is the weighted center of gravity (COG). We derive three maximum-likelihood estimators for the variance of the two-dimensional (2-D) COG as a function of the noise in the image. We assume that the noise is additive, Gaussian distributed and independent between neighboring pixels. Repeated experiments using 2500 generated 2-D bell-shaped markers superimposed with an increasing amount of Gaussian noise were performed, to compare the three approximations. The error of the most exact approximative variance estimate with respect to true variance was always less than 5% of the latter. This deviation decreases with increasing signal-to-noise ratio. Our second approximation to the variance estimate performed better than the third approximation, which was originally presented by Oron et al. by up to a factor /spl ap/10. The difference in performance between these two approximations increased with an increasing misplacement of the window in which the COG was calculated with respect to the real COG.     

A Spatial Contrast Retina With On-Chip Calibration for Neuromorphic Spike-Based AER Vision Systems

We present a 32 times 32 pixels contrast retina microchip that provides its output as an address event representation (AER) stream. Spatial contrast is computed as the ratio between pixel photocurrent and a local average between neighboring pixels obtained with a diffuser network. This current-based computation produces an important amount of mismatch between neighboring pixels, because the currents can be as low as a few pico-amperes. Consequently, a compact calibration circuitry has been included to trimm each pixel. Measurements show a reduction in mismatch standard deviation from 57% to 6.6% (indoor light). The paper describes the design of the pixel with its spatial contrast computation and calibration sections. About one third of pixel area is used for a 5-bit calibration circuit. Area of pixel is 58 mum times 56 mum , while its current consumption is about 20 nA at 1-kHz event rate. Extensive experimental results are provided for a prototype fabricated in a standard 0.35-mum CMOS process.     

Propagated guided image filtering for edge-preserving smoothing

This paper proposes an edge-preserving smoothing filtering algorithm based on guided image filter (GF). GF is a well-known edge-preserving smoothing filter, but is ineffective in certain cases. The proposed GF enhancement provides a better solution for various noise levels associated with image degradation. In addition, halo artifacts, the main drawback of GF, are well suppressed using the proposed method. In our proposal, linear GF coefficients are updated sequentially in the spatial domain by using a new cost function, whose solution is a weighted average of the neighboring coefficients. The weights are determined differently depending on whether the pixels belong to the edge region, and become zero when a neighborhood pixel is located within a region separated from the center pixel. This propagation procedure is executed twice (from upper-left to lower-right, and vice versa) to obtain noise-free edges. Finally, the filtering output is computed using the updated coefficient values. The experimental results indicate that the proposed algorithm preserves edges better than the existing algorithms, while reducing halo artifacts even in highly noisy images. In addition, the algorithm is less sensitive to user parameters compared to GF and other modified GF algorithms.     

Improved interview video error concealment on whole frame packet loss

An improved DIBR-based (Depth image based rendering) whole frame error concealment method for multiview video with depth is designed. An optimal reference view selection is first proposed. The paper further includes three modified parts for the DIBRed pixels. First, the missing 1-to-1 pixels are concealed by the pixels from another view. The light differences between views are taken care of by the information of the motion vector of the projected coordination and a reverse DIBR procedure. Second, the generation of the many-to-1 pixels is improved via their depth information. Third, the hole pixels are found using the estimated motion vectors derived efficiently from a weighted function of the neighboring available motion vectors and their distance to the target hole pixel. The experimental results show that, compared to the state-of-the-art method, the combined system of the four proposed methods is superior and improves the performance by 5.53 dB at maximum.     

Reversible data hiding in encrypted images based on absolute mean difference of multiple neighboring pixels

Recently, with the development of cloud computing, more and more secret data are stored in cloud. Reversible data hiding in encrypted images is a technique that makes contribution to cloud data management in privacy preserving and data security. In previous works, Zhang and Hong presented two reversible dada hiding methods in encrypted images, respectively. However, Zhang’s work neglected the pixels in the borders of image blocks, and Hong et al.’s research only considered two adjacent pixels of each pixel. In addition, their works only considered that all image blocks are embedded into additional data. In this paper, we propose a novel method of evaluating the complexity of image blocks, which considers multiple neighboring pixels according to the locations of different pixels. Furthermore, data embedding ratio is considered. Experiments show that this novel method can reduce average extracted-bit error rate when the block size is appropriate.     

基于灰度差值的均值滤波算法及其在AXI中的应用

在AXI系统中,图像会由于射线散射和量子起伏等因素的干扰而产生噪声,影响成像质量.为了不影响对缺陷进行判断,需要对图像进行降噪处理,同时也要尽量保持图像边缘不发生变化.为达到这一目的,本文提出一种基于灰度差值的均值滤波方法,通过设置一个阈值,计算邻域像素与中心像素灰度值之差的绝对值,若此绝对值大于阈值,则设置该邻域像素的权值为0,否则该邻域像素的权值为阈值与以上绝对值之差.通过对比实验证明该方法可以有效的地去除图像中的噪声,且对图像细节几乎没有损失.