Edge Detection in Digital Images Using Guided L0 Smoothen Filter and Fuzzy Logic

Image segmentation is an important process in computer vision. Recently fuzzy logic based edge detection is heavily investigated as by changing the number of rules edge detection can be improved. However, due to large colour variations in the images false edges are detected and even using fuzzy rules they cannot be reduced significantly. These falsely detected edges can be controlled by using smoothen filter while controlling the degree of smoothness. This paper, presents fuzzy logic based edge detection mechanism while using Guided L₀ smoothen filter for the smoothening of image under various degree of smoothens. Simulation results for edge detection is presented for Canny, Sobel, Fuzzy logic based edge detection and finally fuzzy logic edge detection with inclusion of L₀ smoothen filter. The results are compared with classical and modern methods. Simulation is performed on Berkley Segmentation Database (BSD) and USC-SIPI Image Database while considering more than 100 images. The obtained F-measure is as high as 0.848.

     

冲激信号SAR成像的方位分辨率分析

本文在分析冲激信号SAR成像特点的基础上,在发射和接收均为"超宽带信号"、"大方位积累角"的情况下,推导出了冲激信号SAR方位分辨率的解析表达式,并通过仿真实验验证了其正确性.     

基于二进小波变换的边缘保持图像插值算法

利用离散二进小波变换(DDWT)所具有的良好的多尺度边缘提取特性以及子带间的相关性,提出了基于DDWT的边缘保持图像插值算法。算法利用多尺度边缘的指数衰减规律预测损失掉的高频子带中的边缘,并利用三次样条插值算法恢复损失掉的高频子带中的非边缘信息。最后通过离散二进小波合成得到高分辨率图像。实验结果显示,该算法优于传统的双线性和双三次插值算法。对于像Lena这样的纹理较少的图像其峰值信噪比(PSNR)提高了2dB以上,而对其它图像插值的结果也有不同程度的质量改善,插值的结果更符合人的视觉系统特性。     

用B样条小波进行图像的多尺度边缘检测

提出了一种基于B样条小波理论的多尺度图像边缘检测算子,并与传统的边缘检测算子:Carnny算子和Sobel算子,进行了比较.计算机仿真结果显示,该算子性能优于Sobel算子,与Canny算子性能相当,但比Canny算子算法简单,效率高.     

Adaptation of CDMA Soft Handoff Thresholds Using Fuzzy Inference System

This paper proposes a new procedure to adjust soft handoff thresholds dynamically by using fuzzy inference system. This algorithm is compared with IS-95A and IS-95B/cdma2000 soft handoffs. The aims are to increase the thresholds at high traffic loads in order to release the traffic channel for supporting more carried traffic, and to decrease the thresholds at low traffic loads in order to give high quality of traffic channel. The inputs of the proposed algorithm are the number of remaining channels of each base station and the number of active pilots in active set of each mobile station. The output is the new soft handoff thresholds. In the fuzzy inference module, the triangular membership function, the max-min composition, and the weighted average formula defuzzification are selected. By comparison of all performance indicators among three algorithms, soft handoff using fuzzy inference tends to give higher performance than those of IS-95A and IS-95B/cdma2000 soft handoffs at high traffic loads and at lower soft handoff thresholds while the quality of traffic channel is still acceptable. Moreover, the wider soft handoff window size of the proposed algorithm gives high carried traffic and low blocking probability but lower quality of traffic channels. In addition, the adaptive soft handoff window size can give lower blocking probability while still keep acceptable quality of traffic channels.     

Registration of Brain Atlas to MR Images Using Topology Preserving Front Propagation

Registration of brain atlases to MR images is important in both anatomic and functional studies of human brains. Existing intensity-based methods are confronted with the translation of image-similarity functions to desired anatomic correspondences; while feature-based methods are challenged with the automated extraction of required features. In this paper, we propose a non-rigid registration method, in which, a block matching method is first used to calculate boundary displacement of all structures in a brain atlas, and a topology preserving front propagation method is then used to deform the atlas by warping the structures according to their boundary displacements. The novelty of our method is that the registration procedure is automated and anatomically driven while there is no need to extract particular structures. Experiments on the registration of the Talairach–Tournoux brain atlas to phantom brain MR images and real data show that our method is robust to noise and intensity inhomogeneity, more accurate than the commonly used Talairach stereotaxic spatial normalization, and thus promising to open new applications for brain atlases.     

基于顶帽变换的红外图像模糊边缘检测算法

红外成像技术广泛应用航空航天、国家防卫、农业工程及医学工程等各个领域,红外图像边缘信息的获取具有重要意义。提出了改进的图像模糊边缘检测算法,首先改变隶属度函数,简化运算量和缩短处理时间。其次,在选取分割阈值过程中引用基于顶帽变换的自适应方法求取不同图像的阈值,使得分割更加准确。实验结果表明,本算法可以保留红外图像更多的低灰度边缘信息,且较传统的Pal-King算法减少了运算时间,可应用于红外目标探测以及红外目标识别等领域。     

基于边缘特征的异质图像目标配准方法

目标检测作为计算机视觉的重要研究课题,在视频监控和智能导航方面有重要应用.图像配准技术是刚体目标检测方法之一.异质图像间目标的纹理差异极大,为此,对于目标的可见光俯视图像与机载红外摄像机观测异质图像,通过研究基于边缘特征的配准技术,实现对地面平面目标的配准检测.笔者首先通过建立机载运动摄像机空间模型,解决了红外观测图像的视角变换问题,将其换到与参考图像一致的视角,提出一种新颖的基于稳定区域轮廓合成的边缘提取方法,更好地控制异质图像的边缘提取效果,边缘特征匹配是在距离变换的基础上实现的,提出了一种基于稳定区域距离图像互相关的匹配度量准则.实验表明,算法能有效地实现异质图像间的目标配准检测.     

Prolog模糊推理机

本文采用基于模糊集会论的推理策略，为TurboProlog设计了一个模糊推理机外壳，使其能够在保持原有系统功能的基础上处理模糊信息。     

自适应边缘保持图像缩放及VLSI设计

提出的自适应边缘保持图像缩放方法,以自适应的方式对传统的线性插值方法非线性修正,使得不同位置的像素采用相应的插值方法.边缘保持插值算法能消除图像边缘模糊,锯齿效应,棋盘效应等,达到增强插值图像的效果.本算法处理后的放大图像的边缘更加锐利,能够实现图像的无级放大,可应用于实际的数字视频处理芯片中.     

Restoring Spline Interpolation of CT Images

In this paper a new technique is used to interpolate the sampled CT image data in the axial direction for a coronal display. This technique also compensates the high spatial frequency components in that direction to get a narrower point-spread function. Computer simulation results are presented here to show the effect of aperture convolution and the effect of spatial sampling in a practical imaging system. It is illuminating to describe the procedures of interpolation in terms of digital filtering. The advantage of restoring spline interpolation is due to the extra frequency compensation in the matrix inversion step. Both step function and sinusoidal function are used in the simulation. The enhanced transition edge and the smaller absolute error in the restoring spline interpolated results are shown. The absolute error depends to a certain extent on the sampling interval relative to the Nyquist interval which is also discussed. There is a small amount of amplification of existing noise or generation of new noise in this technique. Some initial results on a CT image using this technique are also presented.     

二进小波增强与边缘局部信息FCM的SAR图像变化检测

合成孔径雷达图像中固有的相干斑噪声往往导致变化检测结果中存在大量虚警与漏警。针对这一问题,本文提出一种利用二进小波增强与边缘局部信息模糊C均值的变化检测方法。首先利用二进小波对对数比差异图进行自适应增强,平抑噪声的同时均衡灰度分布;然后,利用指数加权均值比算子对差异图进行边缘信息提取,修正局部信息模糊C均值算法中邻域窗内像素点权值,使邻域窗滑动至变化区域的边缘部分时能够对噪声切向平抑,保留细节信息。最后对差异图进行分割,得到变化检测结果二值图。仿真与实测数据实验结果表明,本文方法能够有效抑制相干斑噪声,同时对变化区域的细节保持效果较好。      

Adaptive Least Squares Interpolation of Infrared Images

This paper presents an adaptive block-by-block least squares (LS) algorithm for the interpolation of infrared (IR) images. The suggested algorithm is based on the segmentation of the low resolution (LR) image into overlapping blocks and the interpolation of each block, separately. The purpose of the overlapping is to avoid edge effects between blocks. An iterative implementation of the proposed algorithm, which considers the image acquisition model, is used for the minimization of the estimation error in each block. A weight matrix of moderate dimensions is estimated in a small number of iterations to interpolate each block. This proposed algorithm avoids the large computational complexity resulting from the matrices of large dimensions required to interpolate the image as a whole. The performance of the proposed algorithm is compared with the standard as well as the warped distance optimal interpolation of maximal order with minimal support (O-MOMS) algorithm from the peak signal-to-noise ratio (PSNR) point of view. Numerical results reveal the superiority of the proposed LS algorithm to the cubic O-MOMS algorithm.     

基于模糊变换的模糊系统和模糊推理建模法

首先针对双输入单输出模糊系统提出了一种模糊变换方法,指出这种模糊变换不仅与单输入和单输出模糊系统有密切的联系,而且利用这种模糊变换构造的模糊系统具有很好的泛逼近性.然后将这种模糊变换应用到模糊推理建模法中,导出了所研究的模糊系统的微分方程模型和状态空间模型,从而给出了一种新的模糊推理建模法.理论分析和仿真实验均表明:利用模糊变换构造的微分方程对所研究的模糊系统具有很好的泛逼近性.     

基于数字激光散斑图像的位移测量的多层平截算法

通过对数字激光散斑图像特性的分析及其位移测量法的研究，给出了一种利用激光散斑图像进行位移测量的多层平截算法。该算法把数字激光散斑图像的灰度看作三维空间的高度，用不同高度的水平面平截散斑图得到截值点，分析物体发生位移前后的散斑图像上截值点，由截值点相互位置的概率分布计算出物体的实际位移。改进后的多层平截算法可较大的节省测量所需的散斑图像面积，且能测量亚pixel级的位移。实验表明，该多层平截算法是一种实用、速度快及精度高的位移和变形测量方法。     

基于视觉感知和边缘保持的光照不变人脸识别

提出一种具有视觉感知特性和边缘保持特性的光照不变人脸识别方法.方法在各向异性扩散算法基础上引入视觉感知机制,提出具有视觉感知特性的图像梯度替代传统的图像空间梯度,使算法更符合人类视觉系统特性;同时,考虑到传统各向异性扩散算法采用的传递系数受参数影响较大,易产生明显的边缘锐化现象,提出一种新的传递系数,该系数不受参数影响,能够始终保持良好的边缘保持特性.新方法所获的光照不变人脸图像保持了良好的边缘,并极大程度上消除了光晕和白斑现象.在EYaleB和CMU PIE人脸图像库上的实验验证了该方法的有效性.     

Edge Preserving Lossy Image Compression with Wavelets and Contourlets

In this paper an edge preserving lossy image coder is presented. An edge image is obtained from the original with a digital image processing module using four different filters: Canny, Sobel, Roberts and Prewitt, then the original image is domain transformed with wavelets or contourlets, and a pixel mapping from original domain to transformed is done. For the compression, the edges points and the approximation image (which determines the compression factor) are selected; finally the image is decompressed in order to observe the reconstruction quality and edge preserving. The stages of the compression system are: a) Image selection, b) Digital image processing, c) Feature vector extraction, d) Domain Transformation, e) Pixel mapping, f) Image compression and g) Image decompression. Additionally, the results obtained from comparisons of error measures between original and decompressed images are shown and finally conclusions about the coder are presented.     

基于角点保护的偏微分方程图像插值方法

图像插值是数字图像处理领域中的一个基本问题,利用插值技术可以实现图像的缩放和图像恢复。传统的插值方法易使边缘产生锯齿效应或使插值结果模糊不清。该文提出一种基于角点保护的偏微分方程插值方法。该方法针对图像中不同的特征进行特定插值,在保持边缘结构清晰的同时,还能保护尖锐的角形结构,有效改善插值后图像的整体视觉效果和峰值信噪比。此外,对方程的主要参数进行分析,提出了相应的参数确定方法,从而提高该方法的适用性。     

A QoS Aware Dynamic Scheduling Scheme Using Fuzzy Inference System for IEEE 802.16 Networks

Providing quality of service (QoS) for diverse multimedia services is an important issue in IEEE 802.16 (WiMAX) networks. A scheduling mechanism that satisfies the QoS requirements has become more important for multimedia networks. In addition, scheduling algorithms for wireless networks are much more complex than that of wired networks because of channel quality variations and radio resource limits. This paper introduces a QoS Aware Scheduling System, based on fuzzy logic, for traffic management in WiMAX point-to-multi-point (PMP) networks. The proposed method attempts to guarantee delay and throughput QoS criteria. It considers QoS criteria and radio quality of each user in decision making processes. A series of simulation experiments have been carried out to evaluate the performance of the proposed scheduling system. The results show that the proposed method performs effectively to achieve QoS criteria and attains significant system performance for different types of traffic.