An adaptive method based on the improved LPA-ICI algorithm for MRI enhancement

Various diseases are diagnosed using medical imaging used for analysing internal anatomical structures. However, medical images are susceptible to noise introduced in both acquisition and transmission processes. We propose an adaptive data-driven image denoising algorithm based on an improvement of the intersection of confidence intervals (ICI), called relative ICI (RICI) algorithm. The 2D mask of the adaptive size and shape is calculated for each image pixel independently, and utilized in the design of the 2D local polynomial approximation (LPA) filters. Denoising performances, in terms of the PSNR, are compared to the original ICI-based method, as well as to the fixed sized filtering. The proposed adaptive RICI-based denoising outperformed the original ICI-based method by up to 1.32 dB, and the fixed size filtering by up to 6.48 dB. Furthermore, since the denoising of each image pixel is done locally and independently, the method is easy to parallelize.     

Crystallization‐Induced Emission Enhancement of a Deep‐Blue Luminescence Material with Tunable Mechano‐ and Thermochromism

Organic luminescent materials with the ability to reversibly switch the luminescence when subjected to external stimuli have attracted considerable interest in recent years. However, the examples of luminescent materials that exhibit multiresponsive properties are rarely reported. In this work, a new stimuli‐responsive dye P1 is designed and synthesized with two identical chromophores of naphthalimide, one at each side of an amidoamine‐based spacer. This amide‐rich molecule offers many possibilities for forming intra‐ and intermolecular hydrogen bond interactions. Particularly, P1 has an intrinsic property of cocrystallizing with methanol. Compared with the pristine P1 sample, the as‐prepared two‐component cocrystalline material displays an exceptive deep‐blue emission, which is extremely rare among naphthalimide‐based molecules in the solid state. Furthermore, the target material exhibits an obvious mechanochromic fluorescent behavior and a large spectral shift under force stimuli. On the other hand, the cocrystalline material shows an unusual “turn off” thermochromic luminescence accompanied by solvent evaporation. Moreover, using external stimuli to reversibly manipulate fluorescent quantum yields is rarely reported to date. The results demonstrate the feasibility of a new design strategy for solid‐state luminescence switching materials: the incorporation of solvents into organic compounds by cocrystallization to obtain a crystalline state luminescence system.     

Medical image contrast enhancement based on improved sparrow search algorithm

The collection or transmission of medical images is often disturbed by various factors, such as insufficient brightness and noise pollution, which will result in the deterioration of image quality and significantly affect the clinical diagnosis. To improve the quality of medical images, a contrast enhancement method based on improved sparrow search algorithm is proposed in this paper. The method is divided into two steps to enhance the medical images. First, a new transform function is introduced to improve the brightness or contrast of medical images, and two parameters in the transform function are optimized by the improved sparrow search algorithm. Second, adaptive histogram equalization method with contrast limited is used to equalize the result image of the previous step to make the pixel distribution of the image more uniform. Finally, a large number of experiments and qualitative and quantitative analyses were conducted on the common data sets. The analysis results demonstrate that the presented approach outperforms some existing medical image processing approaches.     

Parallel algorithms for image enhancement and segmentation by region growing, with an experimental study

This paper presents efficient and portable implementations of a powerful image enhancement process, the Symmetric Neighborhood Filter (SNF), and an image segmentation technique that makes use of the SNF and a variant of the conventional connected components algorithm which we call -Connected Components. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient connected components algorithm based on a novel approach for parallel merging. The algorithms have been coded in Split-C and run on a variety of platforms, including the Thinking Machines CM-5, IBM SP-1 and SP-2, Cray Research T3D, Meiko Scientific CS-2, Intel Paragon, and workstation clusters. Our experimental results are consistent with the theoretical analysis (and provide the best known execution times for segmentation, even when compared with machine-specific implementations). Our test data include difficult images from the Landsat Thematic Mapper (TM) satellite data.Also affiliated with the Department of Electrical Engineering.Also affiliated with the Department of Computer Science and the Center for Automation Research.     

基于二阶梯度的图像增强算法研究

针对PCB图像的特点对图像进行增强处理,使得图像的边缘更加突出,灰度的对比度增加,同时滤除靠近边缘的噪声,为后续图像分割时更有效的选取阈值打下良好基础。使用二阶梯度算子获得图像的增强效果,实验表明,不仅解决了边缘附近噪声去除问题,而且有效地突出了边缘信息,图像的黑白对比分明,尤其是目标图像靠近边缘部分灰度值明显高于其他的非边缘区域。     

Local contrast enhancement and adaptive feature extraction for illumination-invariant face recognition

Recognizing human faces in various lighting conditions is quite a difficult problem. The problem becomes more difficult when face images are taken in extremely high dynamic range scenes. Most of the automatic face recognition systems assume that images are taken under well-controlled illumination. The face segmentation as well as recognition becomes much simpler under such a constrained condition. However, illumination control is not feasible when a surveillance system is installed in any location at will. Without compensating for uneven illumination, it is impossible to get a satisfactory recognition rate. In this paper, we propose an integrated system that first compensates uneven illumination through local contrast enhancement. Then the enhanced images are fed into a robust face recognition system which adaptively selects the most important features among all candidate features and performs classification by support vector machines (SVMs). The dimension of feature space as well as the selected types of features is customized for each hyperplane. Three face image databases, namely Yale, Yale Group B, and Extended Yale Group B, are used to evaluate performance. The experimental result shows that the proposed recognition system give superior results compared to recently published literatures.     

高质量通信信号时频图处理及应用

针对信号监测工作中信号时频图清晰显示重要性的问题,首先介绍了信号时频特征获取,之后进行信号时频图显示处理,利用基于灰度变换图像对比度增强、图像渐变平滑处理、图像的锐化处理的数字图像处理相关算法对信号时频图进行显示处理,并成功的在实践工程中进行了运用,解决了信号时频特征在时频域直观显示的问题,从而能够在时频域上表示出信号...     

基于空间信息的SAR图像船只交通监测方法

快速准确获得研究区海上船只状态,对海洋交通监测具有重要意义。本文从技术角度提出了基于空间信息的SAR图像海上船只交通监测方法。首先利用已有的空间先验信息对图像进行自动陆地掩膜;建立海面杂波分布模型,对海面船只进行检测;估算船只的长度、面积、中心坐标等参数信息,并对目标进行筛选;最后根据船只信息库结合空间信息平台进行统计与分析,可为海上船只监测以及交通规划等应用提供决策信息。重点介绍了数据处理方法,并以9景ERS2数据进行了实验和详细分析,通过实验,分析了技术的可行性与正确性。     

基于听觉感知模型的多通道语音增强系统

提出以模拟听觉感知模型的非均匀滤波器组为基础的多通道语音增强系统,与基于均匀滤波器组的语音增强系统相比,该方法达到相同频率分辨率所需的通道数较少。采用Itakura-Saito距离对系统进行客观评价,仿真结果表明,该系统增强后的语音比均匀多通道系统增强后的语音具有更好的改善效果。