提升小波变换结合改进的SPIHT算法实现图像压缩

传统小波变换SPIHT算法编码过程重复运算,存储量较大.考虑图像传输的实时性和在保证图像质量下获得高压缩比要求,提出了一种新的基于提升方案的快速的SPlHT算法.提出的算法引入快速的提升小波变换,提高了图像的重构质量和小波变换的速度,同时考虑到人眼的视觉特性,提高了主观上图像的复原质量.     

基于小波-Contourlet变换的图像去噪算法

为解决噪声图像增强中抑制噪声和增强边缘细节的矛盾,提出一种基于小波-轮廓变换的图像去噪方法。小波-轮廓变换具有多分辨率、多方向、各向异性等特点。根据这一特点,先在变换域中设置阈值抑制噪声;再用非线性增强算子对变换的各子带系数做增强处理。实验结果表明,该方法有效去除了图像噪声,增强了边缘细节和纹理特征。     

基于多小波变换的地震资料随机噪音压制技术研究及应用

本文分析了多小波变换的基本理论、变换过程及预处理方法,提出了基于多小波分析的地震资料随机噪音压制技术。通过对理论数据和实际资料进行处理,表明利用多小波变换能够有效压制随机噪声,同时还能较好的保留原信号的有效信息,是一种行之有效的去噪方法。     

面向水下环境的图像对比度增强算法研究

在采集水下图像时,由于水面对光的反射和散射会导致水下图像对比度下降。针对这一情况,提出了一种基于离散平稳小波变换的算法,对图像进行去噪和对比度增强的处理。实验表明：新算法能够有效地增强水下图像的对比度,同时还能够很好地抑制图像中的白噪声。     

基于小波变换的陶瓷机械齿轮传动噪声消除方法

在进行陶瓷机械齿轮传动噪声消除的过程中,由于存在所耗时间过长的问题,而且还会随着主观意识而改变其自身准确度,因此提出基于小波变换的陶瓷机械齿轮传动噪声消除方法。通过降低信号中干扰频率的响应值,改变小波滤波器的频率,并在其中增加连续和离散小波分析算法,基于小波变换消除陶瓷机械齿轮传动产生的噪声。实验表明：使用小波变换在进...     

基于小波变换的图像压缩技术研究

本文首先阐述了基于小波变换的图像压缩的基本原理和主要过程。对于图像压缩过程中,图像的小波分解、小波基的选取、小波变换的层次确定、图像恢复时边界处理技术,以及图像分解后信号的量化及编码等关键技术进行详细的分析与研究。以实例分析了小波变换在MPEG4静止图像的应用。     

基于小波变换的语音增强算法研究

信号在实际的传输过程中会受到许多噪声的干扰，直接对信号的质量产生影响。语音增强技术的目的就是对含有噪声的信号进行去噪处理操作，是一种改善信号有效性和去除噪声的方法。本文是基于小波变换的阈值去噪方法，在小波变换的小波去噪处理中，研究一种新的阈值选取算法，达到较好的降噪效果，从而实现语音增强。在软件Matlab程序中加入事先录好的其他语音信号，对信号进行加入高斯噪声的处理，然后在算法代入语音信号处理程序中进行去噪，观察最后重构出的信号波形图，并与语音信号时域波形、软阈值降噪、硬阈值降噪后的波形进行对比，确认是否改善了信号去噪效果。     

陶瓷粉体粒度分布的测定方法与应用

通过对几种陶瓷粉体粒度分布的测试方法进行比较.探讨了BT-9300S激光粒度分布仪的测试原理,提出了测试过程中应注意的问题.并对其在陶瓷生产中的应用作了介绍.在陶瓷产品生产过程中,快速测量和有效控制粉体的粒度及其分布,对提高产品质量、降低生产成本具有重要意义.     

基于广义S变换的地震信号时频分析

S变换结合了短时傅里叶变换和连续小波变换的思想,具有良好的时频分析特点,但是基本小波不变,使得其在实际信号分析中有一定的缺陷.广义S变换克服了这些缺陷,可以根据实际信号灵活地选取窗函数,具有更好的时频分辨率.本文首先介绍了广义S变换的基本原理,然后通过仿真试验和地震模拟信号的对比,凸显了广义S变换的时频聚焦性.最后对实际地震信号进行了处理,取得了较好的结果.     

一种基于熵的WBCT自适应方向分解优化算法

提出一种基于熵的WBCT自适应方向分解优化算法,在对图像进行小波变换的基础上,对各级高频子带进行完全方向分解,然后分析各子带不同方向分解数目时熵的变化情况,并根据最小熵原则给出各个子带的最优方向分解数目。采用SPECK编码方法验证了方向分解数目的合理性。结果表明:经笔者算法处理后的重构图像PSNR值均有明显提高。     

基于Curvelet变换的地震数据去噪研究

Curvelet变换是一种新的多尺度几何分析方法,在图像处理领域有其自身的优点。通过改进的curvelet变换图像降噪方法,对地震数据进行处理,实验结果表明,用该方法有效的去除了地震数据中的随机干扰,提高了地震数据的信噪比,Curvelet变换作为一种崭新的理论思路在地震数据处理中将会得到越来越广泛的应用。     

固体推进剂SEM图像分形维数研究

以GAP(缩水甘油叠氮聚合物)、NEPE(硝酸酯增塑聚醚)和HTPB(端羟基聚丁二烯)推进剂为研究对象,对3种推进剂的扫描电镜(SEM)图像分形维数进行了研究.利用分形维数对固体推进剂裂纹定量表征以研究推进剂的力学性能,对阈值选取方法进行了分析,结果表明,利用全局阈值分割法选取图像适合的阈值可以对图像进行可靠的分割.固...     

基于角点检测的裂纹瓷图像拼接及裂纹重建

对裂纹瓷表面的纹饰进行图像拼接,可更好地应用于纹理等外部特征的分析与瓷器鉴别.图像处理技术可实现快速、无损的陶瓷器检测与分析,弥补了传统检测方法的不足.本文以具有裂纹釉的龙泉青瓷茶杯为研究对象,提取瓷器的多个侧面图像,采用Harris角点检测方法提取图像中的角点,然后进行图像配准和拼接,将多侧面图像拼接为完整图像;通过...     

基于图像傅里叶变换纹理特征和概率神经网络的气固流化床流型识别

提出一种基于图像傅里叶变换纹理特征和概率神经网络相结合的气固流化床流型识别的新方法。该方法利用高速摄影系统获取流型图像。首先对流型图像进行组合滤波去噪,然后运用长方环傅里叶周向谱能量百分比法来计算图像频率分布特征,从而建立流型图像的纹理特征向量,并结合概率神经网络进行训练,实现流型的识别。实验结果表明,该方法能有效地识别气固流化床中鼓泡床、节涌床、湍动床、快速流化床、稀相输送五种典型流型,整体识别率达到98%,为流型识别开辟一条新途径。     

A novel approach toward microstructure evaluation of sintered ceramic materials through image processing techniques

In this paper, an image processing technique is introduced to measure the grain size and their distributions from the SEM image of copper oxide (CuO) and titanium dioxide (TiO₂) doped sintered alumina ceramics accurately. The noise present in SEM image is removed by applying low pass Gaussian filter followed by suppression of regional minima over a threshold. The clarity of individual grains and grain boundaries have been done by applying Watershed transform to this preprocessed SEM image. Morphological operations like dilation and erosion are used to make the grain-boundary edges clear and continuous. The individual grain size in µm scale is measured from the pixel length of the rectangular bounding box drawn around the segmented grain. The normal Gaussian type distribution of grain size is observed in both CuO- and TiO₂-doped grains in SEM image. The average grain size of CuO-doped alumina grains (2.24 µm) is very close to G₅₀ value (2.17 µm), but G₅₀ value of TiO₂-doped grains (8.59 µm) is slightly higher than its average grain size (7.96 µm). The proposed algorithm is compared with linear intercept method and the grain sizes obtained are very close to each other.     

论现代陶艺中构建意象的纽带--想象

本文认为无论什么形态意象都少不了陶艺家主观心灵的意识想象 ,任何陶艺作品离开创作想象 ,其作品意象都是苍白无力的。陶艺家在创作想象环节中 ,应针对陶艺创作的表达予以全面分析、思考和设计 ,尽可能地把陶艺作品的意象美展示给大众     

基于改进BP神经网络陶瓷梭式窑火焰图像识别方法

在陶瓷产品生产过程中,不同烧制阶段陶瓷梭式窑烧结带温度发生相应的变化,其对应的火焰图像也随着变化。本文针对陶瓷梭式窑烧结带温度检测提出一种基于改进BP神经网络的火焰图像识别方法。首先对获取的火焰图像利用改进的小波阈值算法去除图像中的噪音进行预处理,其次基于改进的BP神经网络对得到的火焰图像三个分量值R、G、B和测得的火焰温度进行数据拟合,最后测试已训练的神经网络识别火焰图像的效果。实验结果表明,改进后的BP神经网络收敛速度更快、训练时间更短、误差更小,能够更好地检测陶瓷梭式窑火焰图像温度。     

Color pattern recognition for yarn‐dyed fabrics

In the process of designing and analyzing the yarn‐dyed fabric, the yarn color pattern has an important effect on the appearance of the fabric. An automatic color pattern recognition method for yarn‐dyed fabric is proposed in this study. The proposed method uses the fabric images obtained from a high‐resolution digital camera image acquisition system. The local statistical texture features are used for yarn texture segmentation. The yarn color classification problem is then formulated in a research framework of multiregion fuzzy segmentation, which can be added auxiliary variables and solved efficiently by the fast dual projection algorithm. The color values of the yarn crossing points are calculated by the yarn color classification results. The locations of the yarn crossing points are detected by a lightness gradient projection method. Different kinds of fabrics are tested in the experiments. Experiments on 14 actual fabrics show that the approach proposed in this study is effective for classifying yarn color and extracting the yarn color pattern in yarn‐dyed fabric.     

A smoke segmentation algorithm based on improved intelligent seeded region growing

Image segmentation method based on region growing has the advantages of simple segmentation method and complete segmentation target. Because the color discrimination and gray gradient of smoke are not obvious, the traditional region growing segmentation method is difficult to separate it from the image, resulting in an unsatisfactory segmentation effect. To solve this problem, this paper partially improved the region growing method and proposed a new smoke segmentation algorithm based on the improved intelligent seeded region growing (IISRG) method. First, smoke images obtained from experimental videos were converted from the RGB color space to the HSV color space, and image binarization was achieved using background subtraction with an adaptive threshold in the V channel. Then, a pixel in the binary image was selected intelligently as the seed point, which was used for the regional growth. The final smoke segmentation images were obtained by the morphological processing of region growing images. Experimental smoke segmentation results show that the proposed algorithm has a higher overlap rate and a lower overflow rate, and performs a better smoke segmentation effect compared with the other two approaches. In addition, this algorithm can also effectively solve the problems of under‐segmentation and over‐segmentation of smoke images.     

Segmentation of map image using opponent color dimensions

This article describes a method for segmentation of color geographic map images based on color opponency. In this method, a color-map image is transformed into a color opponent representation as proposed for human vision. The color contrast is enhanced in a manner analogous to the opponent surround receptive fields. The enhancement process separates adjacent foreground and background regions into pairs of opponent colors. The segmentation process can then be easily completed based on this opponent structure. © 1996 John Wiley & Sons, Inc.