基于Radon和小波变换的图像检索

提出一种基于Radon和小波变换的图像纹理特征检索算法.对原始图像进行坐标系的方向归一化,再对方向归一化后的图像进行Radon变换.根据Radon变换投影数据的几何特性,构造了适合投影数据的具有尺度和平移不变性的小波分解,该小波分解系数具有旋转、平移和尺度不变性.采用图像中各尺度小波系数的能量值作为图像的纹理特征,以此作为纹理特征进行图像检索.基于纹理特征的试验结果表明该特征具有旋转、平移和尺度不变性,与其他算法相比具有较高的检索率.     

基于KL距离和双密度小波变换的纹理图像检索

为了进一步提纹理图像的检索性能，提出了一种基于双密度小波的算法。该算法根据双密度小波分解的特点。从系数角度出发首先进行子带组合，然后提取子带小波系数直方图分布特性作为纹理特征。利用最大似然估计规则将特征提取和相似计算结合起来．采用KL距离进行度量．与单小波和双密度小波方法比较．该算法具有时移不变性、特证数少等特点。理论分析和纹理图像检索的对比实验数据说明了组合双密度小波在纹理特征提取方面的性能优于单小波和双密度小波。检索率分别提高了。     

一种基于纹理特征的小波变换域数字水印算法

本文提出一种基于二进小波变换的水印算法。通过对图像的小波系数进行分析,确定图像的纹理和边缘区域的小波系数,将水印信息嵌入到对应位置的低频系数中。仿真结果表明了该算法的不可见性及抗攻击性都较好。     

一种基于小波域图像纹理特征的数字水印技术

提出一种基于小波域图像纹理特征的彩色图像盲水印算法。该算法根据。图像小波变换后小波系数的特点选择视觉重要系数，量化嵌入二值水印序列。利用人类视觉系统的纹理掩蔽特性和照度掩蔽特性自适应调整量化间距，以保证水印的透明性。算法实现了水印的盲检测。仿真实验的结果表明，算法对各种常用的水印攻击方法具有较好的鲁棒性。     

基于空域相关的多聚焦图像融合

提出了一种基于空域相关滤波的多聚焦图像融合算法.利用小波多孔算法将原图像分解,得到与原图像同样大小的低频近似图像和高频细节图像.选择低频系数时基于绝对值最大原则,高频信息先计算相邻小波面对应点的相关性,取相关性大的小波系数作为融合图像的小波系数.实验表明,该方法能简单有效地将各图像的信息集成在一起,完好的保留各图像的边缘和纹理信息.     

用方向小波域的维纳滤波图像去噪算法

方向小波是在多尺度几何分析(MGA)的思想下产生的一种新的图像处理工具.针对含高斯噪声图像的方向小波系数仍服从高斯分布的特点,提出一种方向小波域的维纳滤波去噪方法.修正了多方向框架,给出了维纳滤波处理方向小波系数的方法及过程.并将其分别应用于不同纹理复杂程度和信噪比的图像,利用信噪比进行了验证.实践证明了方向小波域的维纳滤波算法具有计算简单、去噪效果好、保持纹理等特点.     

基于统计模型和KL距离的纹理图像检索

为了进一步提高纹理图像的检索性能,提出了一种基于统计模型离的纹理特征提取算法。根据小波分解的特点,从小波系数角度出发,以每个子带的小波系数系数直方图分布特性作为纹理特征,采用混合高斯模型和一般高斯模型分别对低频和高频信息进行描述,利用最大似然估计规则将特征提取和相似计算结合起来,采用KL距离进行度量。与一般高斯模型方法比较,该算法具有检索精度高等特点。理论分析和在纹理图像检索的对比实验数据说明该算法在纹理特征提取方面的性能较一般高斯模型方法提高了5%。     

基于视觉特性的灰度级自适应盲水印算法

提出了一种基于小波变换和视觉感知特性的灰度级自适应盲水印算法。该算法利用视觉系统的背景亮度、纹理和边界掩盖特性把载体图像的小波系数分为18类；在对256级灰度水印图像压缩后。依据载体图像小波系数的分类，以不同强度嵌入到载体中。该算法在抽取水印时不需要原始载体图像和原始水印。实验结果表明此算法可有效地隐藏灰度水印图像，并有较好的顽健性，能抵抗裁剪、JPEG压缩、加噪、图像增强、滤波等多种处理。     

基于混沌与自适应小波变换的图像水印算法

目前基于小波变换的数字水印算法,主要根据低频小波系数的幅值大小确定是否嵌入水印,该算法的缺点是嵌入水印后的图像透明性有待提高。基于以上问题,提出一种基于混沌加密和自适应小波变换的图像数字盲水印算法。采用混沌映射和m序列先后对水印置乱,结合人眼视觉特性确定载体图像的纹理区,选用自适应小波变换分解纹理区,将水印信息嵌入其高频子带中。实验结果表明,该算法可有效提高水印的安全性,具有较好的鲁棒性和不可见性。     

一种基于提升方案小波和小波块的图像水印算法

数字水印技术是多媒体信息安全领域的一个重要研究课题。文章提出一种基于提升方案小波和小波块的图象水印算法。首先，利用提升方案小波对宿主图像和水印图像进行分解，同时利用小波系数的树结构，将宿主图像的小波系数块按纹理密度分成两类，并根据嵌入位置所隶属的小波块的纹理强弱，嵌入不同强度的水印信息，这在一定程度上保证了所嵌入水印在不可见性前提下的极大鲁棒性。实验结果验证了所提出算法的有效性。     

小波图像的膨胀-游程编码算法

提出了一种基于形态膨胀运算和游程编码的新型小波编码器膨胀-游程(Dilation-Run)算法。编码器根据图像小波变换后重要系数的带内聚类特性和重要系数分布的带间相似性,利用数学形态学中的膨胀运算搜索并编码各聚类中的重要系数;同时使用一种高效的游程编码技术对各聚类的种子系数,即膨胀运算起始点的位置进行编码,从而避免了小波图像中非重要系数的逐个编码。编码器算法简单,并且基于位平面实现,因此输出码流具有渐进性。实验结果表明,膨胀-游程算法的性能优于零树小波编码器SPIHT,并能与两种形态学小波编码器MRWD 和SLCCA的性能媲美。对于聚类特性显著的图像,算法的性能则优于上述形态学小波编码器。     

Context-based entropy coding of block transform coefficients for image compression

It has been well established that state-of-the-art wavelet image coders outperform block transform image coders in the rate-distortion (R-D) sense by a wide margin. Wavelet-based JPEG2000 is emerging as the new high-performance international standard for still image compression. An often asked question is: how much of the coding improvement is due to the transform and how much is due to the encoding strategy? Current block transform coders such as JPEG suffer from poor context modeling and fail to take full advantage of correlation in both space and frequency sense. This paper presents a simple, fast, and efficient adaptive block transform image coding algorithm based on a combination of prefiltering, postfiltering, and high-order space-frequency context modeling of block transform coefficients. Despite the simplicity constraints, coding results show that the proposed coder achieves competitive R-D performance compared to the best wavelet coders in the literature.     

Spherical Coding Algorithm for Wavelet Image Compression

In recent literature, there exist many high-performance wavelet coders that use different spatially adaptive coding techniques in order to exploit the spatial energy compaction property of the wavelet transform. Two crucial issues in adaptive methods are the level of flexibility and the coding efficiency achieved while modeling different image regions and allocating bitrate within the wavelet subbands. In this paper, we introduce the ldquospherical coder,rdquo which provides a new adaptive framework for handling these issues in a simple and effective manner. The coder uses local energy as a direct measure to differentiate between parts of the wavelet subband and to decide how to allocate the available bitrate. As local energy becomes available at finer resolutions, i.e., in smaller size windows, the coder automatically updates its decisions about how to spend the bitrate. We use a hierarchical set of variables to specify and code the local energy up to the highest resolution, i.e., the energy of individual wavelet coefficients. The overall scheme is nonredundant, meaning that the subband information is conveyed using this equivalent set of variables without the need for any side parameters. Despite its simplicity, the algorithm produces PSNR results that are competitive with the state-of-art coders in literature.     

Curved wavelet transform for image coding.

The conventional two-dimensional wavelet transform used in existing image coders is usually performed through one-dimensional (1-D) filtering in the vertical and horizontal directions, which cannot efficiently represent edges and lines in images. The curved wavelet transform presented in this paper is carried out by applying 1-D filters along curves, rather than being restricted to vertical and horizontal straight lines. The curves are determined based on image content and are usually parallel to edges and lines in the image to be coded. The pixels along these curves can be well represented by a small number of wavelet coefficients. The curved wavelet transform is used to construct a new image coder. The code-stream syntax of the new coder is the same as that of JPEG2000, except that a new marker segment is added to the tile headers. Results of image coding and subjective quality assessment show that the new image coder performs better than, or as well as, JPEG2000. It is particularly efficient for images that contain sharp edges and can provide a PSNR gain of up to 1.67 dB for natural images compared with JPEG2000.     

Image coding based on wavelet transform and uniform scalar dead zone quantizer

In this paper, a new wavelet transform image coding algorithm is presented. The discrete wavelet transform (DWT) is applied to the original image. The DWT coefficients are firstly quantized with a uniform scalar dead zone quantizer. Then the quantized coefficients are decomposed into four symbol streams: a binary significance map symbol stream, a binary sign stream, a position of the most significant bit (PMSB) symbol stream and a residual bit stream. An adaptive arithmetic coder with different context models is employed for the entropy coding of these symbol streams. Experimental results show that the compression performance of the proposed coding algorithm is competitive to other wavelet-based image coding algorithms reported in the literature.     

A lossless compression algorithm of remote sensing image for space applications

A simple and adaptive lossless compression algorithm is proposed for remote sensing image compression, which includes integer wavelet transform and the Rice entropy coder. By analyzing the probability distribution of integer wavelet transform coefficients and the characteristics of Rice entropy coder, the divide and rule method is used for high-frequency sub-bands and low-frequency one. High-frequency sub-bands are coded by the Rice entropy coder, and low-frequency coefficients are predicted before coding. The role of predictor is to map the low-frequency coefficients into symbols suitable for the entropy coding. Experimental results show that the average Comprcssion Ratio （CR） of our approach is about two, which is close to that of JPEG 2000. The algorithm is simple and easy to be implemented in hardware. Moreover, it has the merits of adaptability, and independent data packet. So the algorithm can adapt to space lossless compression applications.     

ATM网中可变比特率小波视频编码和码率控制

本文提出了小波视频编码系统及其码率控制的新方法。对原始图像序列进行时间、水平和垂直三维小波分解,并采用改进的等级树集合分区的算法对小波系数进行量化。在图像组级上对该编码器进行码率控制,使其输出码流遵循漏桶控制器的参数,并对不同大小的漏桶缓冲器进行了讨论。仿真实验证明了该编码系统及其码率控制方法的有效性。     

基于能量树编码的小波图像压缩算法

针对小波变换的空间能量聚集特性,提出了一种基于能量树编码的小波图像压缩算法。该算法在离散小波变换的基础上,分别对图像的各高频子带按其局部能量构建分层能量树,利用总能量和各层的能量角等效表示子带的小波系数;根据给定的压缩比,选择合适的代价函数构建最佳能量树,然后对其进行量化和编码,通过自适应的比特率分配实现小波图像压缩。实验结果表明,该算法实现简单,重构图像质量好,与当前多种主流的小波图像压缩算法相比,压缩性能有了明显提高。     

基于IPCT/3-D Tarp的高光谱图像无损压缩

研究了一种将变换矩阵分解为三角元素可逆矩阵(TERM)实现的主成分变换整数近似算法(IPCT).为限制误差和提高计算效率,改进了TERM分解中选择主元的方法.结合可逆整数PCT和三维Tarp编码技术,提出了一种新的高光谱图像无损压缩算法.该算法在进行空间维小波变换以后,利用改进的IPCT去除谱间相关;在编码阶段,新颖的三维Tarp编码器能利用五个简单的递归滤波器进行概率估计,以驱动一个非自适应算术编码器,对变换系数的显著性映射和细化信息进行熵编码.该算法复杂度较低,能够产生嵌入式码流,并且较已有的算法能获得更高的压缩比.     

Adaptive compression of medical ultrasound images

An adaptive image-coding algorithm for compression of medical ultrasound (US) images in the wavelet domain is presented. First, it is shown that the histograms of wavelet coefficients of the subbands in the US images are heavy-tailed and can be better modelled by using the generalised Student's t-distribution. Then, by exploiting these statistics, an adaptive image coder named JTQVS-WV is designed, which unifies the two approaches to image-adaptive coding: rate-distortion (R-D) optimised quantiser selection and R-D optimal thresholding, and is based on the varying-slope quantisation strategy. The use of varying-slope quantisation strategy (instead of fixed R-D slope) allows coding of the wavelet coefficients across various scales according to their importance for the quality of reconstructed image. The experimental results show that the varying-slope quantisation strategy leads to a significant improvement in the compression performance of the JTQVS-WV over the best state-of-the-art image coder, SPIHT, JPEG2000 and the fixed-slope variant of JTQVS-WV named JTQ-WV. For example, the coding of US images at 0.5 bpp yields a peak signal-to-noise ratio gain of >0.6, 3.86 and 0.3 dB over the benchmark, SPIHT, JPEG2000 and JTQ-WV, respectively.