An integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images.

This paper describes an integrated prototype computer-based system for the characterization of skin digital images. The first stage includes an image acquisition arrangement designed for capturing skin images, under reproducible conditions. The system processes the captured images and performs unsupervised image segmentation and image registration utilizing an efficient algorithm based on the log-polar transform of the images' Fourier spectrum. Border- and color-based features, extracted from the digital images of skin lesions, were used to construct a classification module for the recognition of malignant melanoma versus dysplastic nevus. Different methods, drawn from the fields of artificial intelligence (neural networks) and statistical modeling (discriminant analysis), were used in order to find the best classification rules and to compare the results of different approaches to the problem.     

SAR图像上舰船目标检测的一种新算法

提出了一种改进的KSW算法检测SAR图像上的舰船目标.在该算法中,检测门限被选择以最大化背景与目标灰度熵加权和.由于加权系数的引入,该算法能针对SAR图像上舰船目标检测的实际情况,调整背景与目标灰度熵在准则函数中所占比例.当海杂波较弱时,该算法与传统的KSW算法等价.当海杂波较强时,其较传统的KSW算法有更好的表现.     

一种新的序列图像匹配定位算法

景象匹配是飞行器导航定位中广泛采用的一项技术,如何提高图像的匹配概率,始终是该项技术中一个值得研究的课题。针对传统的利用单幅实时图像进行匹配时,存在的实时景象图过小、匹配特征不足,从而导致匹配效率过低的问题。文中研究了一种基于归一化灰度相关序列图像匹配算法,利用飞行器飞越匹配区时所得到的序列实时图像,在序列中各单幅图像匹配的基础上,利用一定的规则来综合单幅图像的匹配结果,从而得到最终匹配结果。实验证明,文中方法不仅能显著提高匹配性能,而且有较大的实用性。     

A new search algorithm for feature selection in hyperspectralremote sensing images

A new suboptimal search strategy suitable for feature selection in very high-dimensional remote sensing images (e.g., those acquired by hyperspectral sensors) is proposed. Each solution of the feature selection problem is represented as a binary string that indicates which features are selected and which are disregarded. In turn, each binary string corresponds to a point of a multidimensional binary space. Given a criterion function to evaluate the effectiveness of a selected solution, the proposed strategy is based on the search for constrained local extremes of such a function in the above-defined binary space. In particular, two different algorithms are presented that explore the space of solutions in different ways. These algorithms are compared with the classical sequential forward selection and sequential forward floating selection suboptimal techniques, using hyperspectral remote sensing images (acquired by the airborne visible/infrared imaging spectrometer [AVIRIS] sensor) as a data set. Experimental results point out the effectiveness of both algorithms, which can be regarded as valid alternatives to classical methods, as they allow interesting tradeoffs between the qualities of selected feature subsets and computational cost     

A new multiscale Bayesian algorithm for speckle reduction in medical ultrasound images

This paper introduces a new multiscale speckle reduction method based on the extraction of wavelet interscale dependencies to visually enhance the medical ultrasound images and improve clinical diagnosis. The logarithm of the image is first transformed to the oriented dual-tree complex wavelet domain. It is then shown that the adjacent subband coefficients of the log-transformed ultrasound image can be successfully modeled using the general form of bivariate isotropic stable distributions, while the speckle coefficients can be approximated using a zero-mean bivariate Gaussian model. Using these statistical models, we design a new discrete bivariate Bayesian estimator based on minimizing the mean square error (MSE). To assess the performance of the proposed method, four image quality metrics, namely signal-to-noise ratio, MSE, coefficient of correlation, and edge preservation index, were computed on 80 medical ultrasound images. Moreover, a visual evaluation was carried out by two medical experts. The numerical results indicated that the new method outperforms the standard spatial despeckling filters, homomorphic Wiener filter, and new multiscale speckle reduction methods based on generalized Gaussian and symmetric alpha-stable priors.     

A new method for shaded surface display of biological and medical images

Shaded surface display is a useful aid in visualizing and analyzing three-dimensional biological and medical images. However, currently available algorithms have limitations, particularly when applied to clinically important image data requiring fast and flexible interactive analysis. In addition to the problem of computation time is the cost of specialized hardware and the quality of shading. A new algorithm has been designed for use with three-dimensional biological/ medical images which attempts to overcome these limitations. This is accomplished by eliminating less important capabilities and optimizing the essential ones of speed and realistic shading. The algorithm has been successfully employed in planning reconstructive bone surgery, in assessment of both congenital and acquired heart disease, and in studies of normal and pathological lung physiology. Examples which illustrate the versatility and speed of the new algorithm are presented.     

A new clustering algorithm applicable to multispectral andpolarimetric SAR images

The authors applied a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, a 12-dimensional feature vector for each pixel was extracted from the scattering matrix. The clustering algorithm partitioned a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and its insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use     

一种针对JPEG图像的通用隐写分析算法

提出了一种针对JPEG图像的通用隐写分析算法。该算法提取了15个具有良好分类特性的特征参数,输入构建的KS—SVM分类器．以达到检测载密图像的目的。实验结果表明,该算法的检测正确率较高,检测速度快,能够实现针对各类JPEG载密图像的有效检测。     

多传感器图像的二次匹配算法

针对光学图像的多光谱、多传感器图像的自动配准,提出了一种基于边缘重心的多传感器图像二次匹配算法.首先,通过边缘检测和相应的后期链接处理,提取出较为完整的图像边缘;然后,根据图像边缘的链码相关以及区域不变矩策略,寻找匹配边缘,并对已匹配边缘的重心进行一致性检验获得控制点对;最后,采用最小二乘法估计图像粗匹配变换参数.在粗匹配的基础上,根据匹配后图像共有区域内边缘的主要方向和重心,再次对图像进行细匹配,修正匹配参数以提高匹配精度.多种遥感图像数据的配准实验和对比试验证实了该自动算法具有较高的可靠性和配准精度.     

A super-resolution reconstruction algorithm for hyperspectral images

The spatial resolution of a hyperspectral image is often coarse because of the limitations of the imaging hardware. Super-resolution reconstruction (SRR) is a promising signal post-processing technique for hyperspectral image resolution enhancement. This paper proposes a maximum a posteriori (MAP) based multi-frame super-resolution algorithm for hyperspectral images. Principal component analysis (PCA) is utilized in both parts of the proposed algorithm: motion estimation and image reconstruction. A simultaneous motion estimation method with the first few principal components, which contain most of the information of a hyperspectral image, is proposed to reduce computational load and improve motion field accuracy. In the image reconstruction part, different image resolution enhancement techniques are applied to different groups of components, to reduce computational load and simultaneously remove noise. The proposed algorithm is tested on both synthetic images and real image sequences. The experimental results and comparative analyses verify the effectiveness of this algorithm.     

一种新型高偏振度的偏振分光棱镜

本文提出了一种新型结构的偏振分光棱镜，其偏振度可达到５０ｄＢ以上。     

一种鲁棒的彩色图像多功能水印算法

首先转换彩色图像的颜色空间抽取相应的灰度图像,再对灰度图像进行提升小波分解,在分解过程中利用图像压缩操作,引起近半数的小波系数增大,另一半系数减小,基于系数增减特征实现版权水印和消费者数字指纹的同时嵌入,从而获得版权认证和盗版追踪的双重功能。仿真实验表明该算法具有良好的鲁棒性和不可感知性。     

基于TSPL的图像椒盐噪声去除新算法

在提出的三子集划分的灰度图像分层表示（TSPL）算法的基础上,主要研究对常见的椒盐噪声的去除。TSPL算法是一种新型的数字图像变换方法,其核心思想是用一系列具有解析形式的灰度函数逼近不规则的原图像灰度函数。在此分别处理由TSPL算法生成的各层基函数图像,将其划分为A,B,C三个区并将每个像素点赋值为0,1,2;结合图像椒盐噪声的特点,利用投票策略处理每个像素点的8?邻域,从而达到椒盐噪声去除的目的;最终通过TSPL算法对基函数重构来恢复原图像。采用在人类视觉系统的前提下提出的基于结构相似性的方法MSSIM算法作为图像质量评价的标准,实验结果表明,在主客观方面,该方法在去除噪声和保留图像细节方面明显优于传统的中值滤波方法。     

A parametric fitting algorithm for segmentation of cell images

This paper presents a parametric fitting algorithm for segmentation of cervical and breast cell images from cytology smears. A parametric elliptical model for cells is introduced and the parameters adjusted to fit the cell shapes while minimizing a cost function. Segmentation results of noisy human cervical cell and textured breast cell images demonstrate that the proposed parametric fitting algorithm is very successful in segmentation of images of both nonoverlapped and overlapped elliptically shaped cells     

A wavelet-based watermarking algorithm for ownership verificationof digital images

Access to multimedia data has become much easier due to the rapid growth of the Internet. While this is usually considered an improvement of everyday life, it also makes unauthorized copying and distributing of multimedia data much easier, therefore presenting a challenge in the field of copyright protection. Digital watermarking, which is inserting copyright information into the data, has been proposed to solve the problem. In this paper, we first discuss the features that a practical digital watermarking system for ownership verification requires. Besides perceptual invisibility and robustness, we claim that the private control of the watermark is also very important. Second, we present a novel wavelet-based watermarking algorithm. Experimental results and analysis are then given to demonstrate that the proposed algorithm is effective and can be used in a practical system.     

A multiplicative Nakagami speckle reduction algorithm for ultrasound images

Speckle noise of ultrasound images is of multiplicative nature which degrades the image quality in terms of resolution and contrast. While there exist a number of algorithms for reduction of multiplicative Rayleigh distributed random speckle noise, the low signal-to-noise ratio (SNR) issue of the multiplicative Rayleigh noise is still not adequately resolved. In this paper, a simple 2-dimensional (2D) local intensity smoothing method is presented which transforms the Rayleigh noise contaminated in ultrasound images to Nakagami distributed noise so as to improve the SNR of processed images. A 2D total variation regularized Nakagami speckle reduction algorithm is derived based on the maximum a posteriori estimation framework, which performs well in restoring piecewise-smooth reflectivity and preserving fine details of the image. The proposed algorithm is verified by a series of computer-simulated and real ultrasound image data. It is shown that the algorithm considerably improves the quality of ultrasound images and outperforms the Rayleigh noise based speckle reduction methods in terms of speckle SNR and contrast-to-noise ratio.     

一种新的图像水印方案

目标区域是图像中视觉上最重要的部分。针对现有的水印算法很少考虑图像中确定的目标区域这一问题，提出了一种基于目标区域的水印方案(WIOR)。方案首先利用小波变换分析图像的目标特征，并依据图像的小波高频系数特征对其进行聚类，获得水印的嵌入域，在此嵌入域中，选择小波系数并对其进行量化调制来嵌入二值扩谱水印；同时，通过只在图像的局部区域内嵌入较少的水印信息来改善水印的隐蔽性。实验结果表明，该方案对于一类具有突出目标特征的图像具有较好的效果。嵌入的水印主要优势在于真正把水印嵌入图像的视觉重要部分，从而能有效地抵御剪切攻击，而且可以实现盲检测。     

A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms

We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential interferograms produced by data pairs characterized by a small orbital separation (baseline) in order to limit the spatial decorrelation phenomena. The application of the singular value decomposition method allows us to easily "link" independent SAR acquisition datasets, separated by large baselines, thus increasing the observation temporal sampling rate. The availability of both spatial and temporal information in the processed data is used to identify and filter out atmospheric phase artifacts. We present results obtained on the data acquired from 1992 to 2000 by the European Remote Sensing satellites and relative to the Campi Flegrei caldera and to the city of Naples, Italy, that demonstrate the capability of the proposed approach to follow the dynamics of the detected deformations.