基于PCNN与LR的低对比度图像增强方法

图像增强是指对图像进行加工,以获得更“好”的视觉效果的一种图像处理技术。由于图像的最终接收者是人,所以评价图像“好坏”的关键在于其是否符合人类视觉系统的特性。针对低对比度图像,结合人眼视觉神经系统的感知特性,提出了一种基于PCNN与LR模型的图像增强方法。分析和仿真结果表明,该法能够较好地突出图像的边缘细节信息,明显地改善图像的视觉效果。     

图像增强方法研究新进展

图像增强是一种重要的图像处理方法,其可以增强图像中的细节信息,抑制噪声,改善图像质量,利于后续图像处理.阐述了图像增强研究的现状,对比分析了常用的图像增强方法的优势和局限性,讨论了近些年新涌现的图像增强方法,分析了图像增强评价指标,指出了图像增强方法值得进行深入研究的方向.     

基于Matlab的云纹干涉图像处理的实现与应用

由于实验现场及周围环境的干扰,采集的图像中往往包含一些不必要的信息,为得到真实反映实验结果的数据,对采集的实验图像需要进行必要的图像处理.应用Matlab语言的图像处理功能,对云纹干涉法得到的干涉条纹图进行了图像增强、噪声处理、二值化和细化等图像处理工作.结果表明,利用基于Matlab语言进行图像处理,方便快捷,能够为后续图像分析、计算提供良好的基础,能够提高实验结果的可靠度.不同图像增强处理方法得到的结果具有不同边界及内部效果,实际应用中要取长补短,根据具体情况合理采用图像增强方法,才能达到预期目的.     

一种避免颜色失真的图像增强算法

针对现有的图像增强算法对噪声比较敏感,容易产生颜色失真的现象,提出了一种避免颜色失真的图像增强算法。在分析对数图像处理模型的基础上,提出了一种正切图像处理模型,从调色板中提取颜色信息,避免颜色失真,该算法简单、易于实现,对噪声具有一定的抑制作用,可以增强和保留图像的细节信息。实验结果表明,所提算法明显优于其他图像增强算法。     

滤波特性比较及分析

本文介绍了图像增强的概念,图像增强处理的分类,依据增强处理方法的不同,分为空域图像处理和频域图像处理。文章从这两方面对图像增强算法进行讨论和研究。简要分析了在图像增强方面的处理,着重对频域图像处理中的高通滤波器(IHPF)通过MATLAB进行仿真分析,仿真实验的结果表明,高通滤波器对频域图像处理效果较好,具有较强的实用性和应用价值。     

一种自适应非线性彩色图像增强技术

在图像处理和模式识别中,经常会遇到图像有过亮或过暗的区域.不仅会使图像的视觉效果不佳.而且会造成图像特征的丢失.提出一种新的自适应非线性彩色图像增强算法.新算法包括五个步骤:将彩色图像转换为灰度图像;利用非线性函数对图像增强;利用高斯核函数与图像进行卷积得到图像的邻域信息;根据邻域信息对图像进行自适应增强;图像色彩还原.最后,利用了基于SNoW的人脸定位器对算法的效果进行了验证.实验表明这种图像增强技术能够提高人脸定位器的准确率.     

基于正切图像处理(TIP)模型的自适应图像增强算法

针对图像增强算法复杂度高、对噪声敏感等问题,在分析对数图像处理模型的基础上,提出了一种基于正切图像处理模型的自适应图像增强算法,该算法具有实现容易、运算速度快等特点,对噪声具有一定的抑制作用,可以增强和保留图像细节信息。既可以增强灰度图像,又可以增强彩色图像,实验和理论分析说明了该算法的优越性。     

本期摘要

基于非线性处理的图像增强算法研究作者：何楚瑶单位：中北大学信息与通信工程学院山西太原030051摘要近年来．基于非线性处理的图像增强技术成为相关领域研究人员关注的一个热点。尽管非线性方法与通常的图像增强算法相比,其计算量非常大．但是灵活多样的数值计算方法使其能够满足高质量图像方面的需要,因而基于非线性图像处理的图像增强方法逐渐在图像处理领域中受到青睐。     

基于Matlab的图像增强算法研究

在获取图像的过程中,由于多种因素的影响,导致图像质量会有所退化.为解决这样的问题,提高图像使用价值,图像增强处理技术应运而生.MATLAB作为国内外流行的数字计算软件,具有强大的图像处理功能,是图像处理系统的理想开发工具.作者在MATLAB软件平台上,分别运用灰度均衡化、平滑滤波器、锐化滤波器、巴特沃斯低通滤波器、同态滤波器等图像处理方法进行程序处理,根据特定的需要,突出图像中的重要信息,同时减弱或去除不需要的信息,达到改善图像特征的目的.再对实验运行结果进行比较分析,发现MATLAB强大的运算和图形展示功能,以及简单、实用、可读性强的特点,使得这些图像增强算法变得更加的简单和直观,提高了图像处理的效率.     

方向场和频率场约束的结构光条纹图像增强算法

条纹图像增强在指纹图像处理与识别、结构光三维重建中有重要应用。针对结构光三维重建的条纹图像处理,提出了一种基于图像方向场与频率场约束的条纹图像增强算法,设计了图像方向场与频率场的计算方法,构造了方向场与频率场的约束的Gabor滤波器。算法首先对条纹图像进行高斯滤波,去除图像亮度不均匀的影响;然后计算条纹图像的方向场与频率场;最后在图像方向场与频率场的约束下对图像进行Gabor滤波。实验结果表明,算法可有效消除图像光照不均匀的影响,较好地增强结构光图像的条纹信息。     

Estimating life-form cover fractions in California sage scrub communities using multispectral remote sensing

The California sage scrub (CSS) community type in California's Mediterranean-type ecosystems is known for its high biodiversity and is home to a large number of rare, threatened, and endangered species. Because of extensive urban development in the past fifty years, this ecologically significant community type is highly degraded and fragmented. To conserve endangered CSS communities, monitoring internal conditions of communities is as crucial as monitoring distributions of the community type in the region. Vegetation type mapping and field sampling of individual plants provide ecologically meaningful information about CSS communities such as spatial distribution and species compositions, respectively. However, both approaches only provide spatially comprehensive information but no information about internal conditions or vice versa. Therefore, there is a need for monitoring variables which fill the information gap between vegetation type maps and field-based data. A number of field-based studies indicate that life-form fractional cover is an effective indicator of CSS community health and habitat quality for CSS-obligated species. This study investigates the effectiveness of remote sensing approaches for estimating fractional cover of true shrub, subshrub, herb, and bare ground in CSS communities of southern California. Combinations of four types of multispectral imagery ranging from 0.15 m resolution scanned color infrared aerial photography to 10 m resolution SPOT 5 multispectral imagery and three image processing models - per-pixel, object-based, and spectral mixture models - were tested.An object-based image analysis (OBIA) routine consistently yielded higher accuracy than other image processing methods for estimating all cover types. Life-form cover was reliably predicted, with error magnitudes as low as 2%. Subshrub and herb cover types required finer spatial resolution imagery for more accurate predictions than true shrub and bare ground types. Positioning of sampling grids had a substantial impact on the reliability of accuracy assessment, particularly for cover estimates predicted using multiple endmember spectral mixture analysis (MESMA) applied to SPOT imagery. Of the approaches tested in this study, OBIA using pansharpened QuickBird imagery is one of the most promising approaches because of its high accuracy and processing efficiency and should be tested for more heterogeneous CSS landscapes. MESMA applied to SPOT imagery should also be examined for effectiveness in estimating factional cover over more extensive habitat areas because of its low data cost and potential for conducting retrospective studies of vegetation community conditions.     

基于邻域灰度值聚类的图像色彩量化

在将图像中的多种颜色或灰度量化成数目较少的颜色或灰度的过程中,存在着计算过于复杂、量化后图像偏差较大等问题,鉴于此,提出基于邻域灰度值聚类的图像色彩量化方法.首先结合邻域像素的灰度和空间信息对像素进行一维灰度化;然后采用基于像素灰度加权系数的改进模糊 均值聚类算法对像素进行聚类.分析和实验表明,该方法可以减少量化计算的复杂度,保持图像的整体层次,量化后图像偏差较小,对图像处理具有一定的实用价值.     

An adaptive fuzzy-genetic algorithm approach for building detection using high-resolution satellite images

We propose a new approach for building detection using high-resolution satellite imagery based on an adaptive fuzzy-genetic algorithm. This novel approach improves object detection accuracy by reducing the premature convergence problem encountered when using genetic algorithms. We integrate the fundamental image processing operators with genetic algorithm concepts such as population, chromosome, gene, crossover and mutation. To initiate the approach, training samples are selected that represent the specified two feature classes, in this case “building” and “non-building”. The image processing operations are carried out on a chromosome-by-chromosome basis to reveal the attribute planes. These planes are then reduced to one hyperplane that is optimal for discriminating between the specified feature classes. For each chromosome, the fitness values are calculated through the analysis of detection and mis-detection rates. This analysis is followed by genetic algorithm operations such as selection, crossover and mutation. At the end of each generation cycle, the adaptive-fuzzy module determines the new (adjusted) probabilities of crossover and mutation. This evolutionary process repeats until a specified number of generations has been reached. To enhance the detected building patches, morphological image processing operations are applied. The approach was tested on ten different test scenes of the Batikent district of the city of Ankara, Turkey using 1 m resolution pan-sharpened IKONOS imagery. The kappa statistics computed for the proposed adaptive fuzzy-genetic algorithm approach were between 0.55 and 0.88. The extraction performance of the algorithm was better for urban and suburban buildings than for buildings in rural test scenes.     

Task-based annotation and retrieval for image information management

Continuing advances in digital image capture and storage are resulting in a proliferation of imagery and associated problems of information overload in image domains. In this work we present a framework that supports image management using an interactive approach that captures and reuses task-based contextual information. Our framework models the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. During image analysis, interactions are captured and a task context is dynamically constructed so that human expertise, proficiency and knowledge can be leveraged to support other users in carrying out similar domain tasks using case-based reasoning techniques. In this article we present our framework for capturing task context and describe how we have implemented the framework as two image retrieval applications in the geo-spatial and medical domains. We present an evaluation that tests the efficiency of our algorithms for retrieving image context information and the effectiveness of the framework for carrying out goal-directed image tasks.     

雷达图像特征信息提取及多源数据复合处理的地质应用研究

以湖南香花岭地区机载侧视雷达图像资料为基础，针对雷达图像特征，综合地球物探、地球化学异常数据，对工作区的成矿地质条件进行综合分析，形成了工作区多源地学数据集。在对该数据集进行多元统计的判别分析以后，建立了湖南香花岭地区锡、钨矿的找矿预测模型，得到综合成矿预测得分图，提出了预测远景区并进行了综合评价。总结出的一整套实用方法和技术将对雷达图像的地质应用研究及雷达地质的发展起着重要作用     

The effect of image compression on synthetic PROBA-V images

We have carried out an in-depth investigation into the effects of image compression on synthetic Probe for On-Board Autonomy – Vegetation (PROBA-V) scenes and Landsat-derived image tiles. The two image compression implementations used were the TER implementation and a bespoke implementation of the Consultative Committee for Space Data Systems (CCSDS) Blue Book standard, which are functionally identical but operate on different image architectures. This work included (1) the development of an approach for producing synthetic scenes that were appropriate in terms of structure and content, and (2) evaluation of the image compression approach on the two kinds of image in terms of their usefulness for land-cover mapping. The synthetic image (SI) generation approach has been rigorously tested and produces images that are statistically similar to real scenes, both compressed and uncompressed. The results of our work show that the effects of image compression vary significantly between bands and with different compression ratios, and that the impact of image compression on image quality does vary with spatial scale. We also found indications of increased error rate at boundaries within the imagery. While the SI generation process and the processing chain of this imagery are not completely consistent with PROBA-V imagery, agreement was found among many of the results produced by the two approaches.     

VR 系统信息可视化模型

针对虚拟环境中用户认知负荷较重和资源分配不协调问题,综合分析了人脑认知 活动中信息的显性化表达,提出一种基于分布式认知的信息可视化资源模型。通过计算机感知 虚拟环境中用户动作、行为、任务等信息,依据资源分配方案确定资源和信息之间映射关系, 并以信息表象的形式贮存;通过对信息表象进一步精致化,实现交互界面视觉元素的优化布局; 本文结合眼动追踪设备对VR 系统原型进行可用性评估实验,实验结果表明该可视化模型能够 降低用户认知负荷,改善用户体验。     

基于面向对象方法的遥感影像桥梁提取

面向对象的分析方法是一种有效的高分辨率遥感影像处理技术,提出一种基于图像对象的水上桥梁识别方法。首先采用区域生长方法对影像进行分割,以分割后产生的图像对象为基本处理单元进行分类,提取出水体类别。然后在分析桥梁目标特征的基础上,利用图像对象的形状特征,以及桥梁和水体的上下文关系特征,提取影像中的桥梁目标。最后以实验验证了所提出方法的有效性。     

Object-based change detection

Characterizations of land-cover dynamics are among the most important applications of Earth observation data, providing insights into management, policy and science. Recent progress in remote sensing and associated digital image processing offers unprecedented opportunities to detect changes in land cover more accurately over increasingly large areas, with diminishing costs and processing time. The advent of high-spatial-resolution remote-sensing imagery further provides opportunities to apply change detection with object-based image analysis (OBIA), that is, object-based change detection (OBCD). When compared with the traditional pixel-based change paradigm, OBCD has the ability to improve the identification of changes for the geographic entities found over a given landscape. In this article, we present an overview of the main issues in change detection, followed by the motivations for using OBCD as compared to pixel-based approaches. We also discuss the challenges caused by the use of objects in change detection and provide a conceptual overview of solutions, which are followed by a detailed review of current OBCD algorithms. In particular, OBCD offers unique approaches and methods for exploiting high-spatial-resolution imagery, to capture meaningful detailed change information in a systematic and repeatable manner, corresponding to a wide range of information needs.     

基于图像结构信息的城市房屋震害特征自动提取技术

由于常规边界检测算法难以完全满足城市房屋震害特征提取的需求，本研究提出了一种基于最优方法的边界跟踪方法，并利用ENVI IDL二次开发语言实现了基于区域结构和纹理统计特性相结合的损坏房屋自动识别算法。最后以1976年我国唐山地震的黑白航空影像为例，进行倒塌房屋的自动识别，得到了较为满意的结果。结果表明，利用本所提出的震害建筑自动识别方法，在提取震害房屋信息方面是有效的，其结果与目视结果大体一致。在完全倒塌的试验区，震害房屋的识别结果与目视解译的结果几乎完全一致，符合程度在99％左右；在其部分倒塌区，自动识别的结果与目视解译的结果符合程度也达到了89％。在这项自动识别理论中，由于采用了基于区域的图像处理与分析技术，所以保持了房屋建筑最基本的特性——区域特征，完全不同于基于光谱特征的震害房星识别技术。故而可以得到较好的自动识别结果。