小波变换在图像压缩中的应用

以小波分析为切入点,阐述了小波变换在图像处理中的应用,小波变换域传统数据压缩模式相结合,取得好的压缩效果。掌握基于Mallat的小波变换对图像处理的作用,通过小波变换可以取得图像压缩及图像重构非常好的效果。     

基于DCT变换的图像压缩技术研究

图像DCT变换是图像压缩的一项重要技术，如何准确、快速的进行图像压缩一直是国内外研究的热点。概要的论述了图像DCT变换的概念和特点，对基于DCT变换的图像压缩技术的算法进行了研究，并用MATLAB进行了算法仿真，取得了较为理想的效果。     

多媒体数据压缩技术研究(连载I)

从两方面对多媒体数据压缩编码进行探讨。首先是压缩算法,当前高效的小波变换用于图像压缩的算法,以及最新的波包、多小波及用Ｌｉｆｔｉｎｇ Ｓｃｈｅｍｅ构造的小波。其次是压缩标准,主要介绍 １９９８年年底出台的ＭＰＥＧ－４,研究其中的视频部分包括的技术内容。探讨了多媒体数据压缩的发展方向。     

雷达图像压缩中2D-DWT的FPGA设计

首先介绍小波变换(WT)理论,分析图像压缩的基本原理。结合雷达图像数据压缩的特点,着眼于系统的实时性最佳性能,提出FPGA硬件实现算法最优解决方案,详细叙述了FPGA设计总体结构,一维滤波器组设计,行列滤波数据缓存等关键算法的实现。     

基于小波变换的指纹图像压缩方法

小波分析是傅里叶分析方法的突破性进展，在非平稳信号处理中，取得了良好的效果。数据压缩是伴随小波分析产生最早的应用领域。指纹自动识别系统因其本身的特殊性对指纹图像压缩提出了特殊的要求。为此，简要的介绍了小波变换的基本原理，提出了一种新的指纹图像压缩评价准则并给出了基于小波变换的指纹图像压缩方法。     

多媒体数据压缩技术研究(连载Ⅰ)

从两方面对多媒体数据压缩编码进行探讨。首先是压缩处法,当前高效的小波变换用于图像压缩的算法,以及最新的波包、多小波及用Ｌｉｆｔｉｎｇ Ｓｃｈｅｍｅ构造的小波。其次是压缩标准,主要介绍１９９８年年底出台的ＭＰＥＧ－４,研究其中的视频部分包括的技术内容。探讨了多媒体数据压缩的发展方向。     

浅析数字图像处理中的小波变换原理

近年来,国内外研究小波变换在图像处理中应用的专家学者越来越多。有的企业直接将小波变换技术通过网络运用到数字图像处理中来,将小波变换原理运用于实践的同时,对网络带宽的要求进一步降低,极大地推进了数字图像信息的处理技术与传播速度。目前,图像文字资料数字化的趋势越来越明显,数字化所带来的直接结果就是产生了不少图像数据,使得图像压缩技术作用得以突显,而小波变换原理可以为图像压缩提供良好的技术支撑,因此,小波变换技术将在数字图像处理技术领域发挥更加重要的作用,推动我国数字图像处理技术的发展。     

图像压缩编码中Walsh变换与DCT变换及其比较

图像变换是图像处理的基础,是图像压缩的第一步。在图像压缩中,DCT变换因其变换效果好而被广泛采用,成为目前最常用的图像压缩变换方法,而Walsh变换还未被广泛采用。通过对这两种变换的算法分析以及Matlab仿真实验和峰值信噪比的对比,结果表明,walsh变换在算法上比DCT简单,实现较为容易,其变换性能并不亚于DCT变换,在某些量化级上甚至还优于DCT变换,Walsh变换有着广泛的应用前景。     

频带压缩、数据压缩、数据平滑

0014632可逆的 DCT 整型变换与无失真图像压缩[刊]/同字松//软件学报.—2000,11(5).—620～627(C)使用提升的方法,利用 FFT 的蝶型构造,完成了FFT 与 DCT 的从整数到整数的变换,变换本身是可逆均,因此非常适合于无失真图像压缩。0014633多媒体数据压缩技术研究[刊]/陈文周//电视技术.—2000,(5).—20～23(L)0014634     

基于JPEG标准的图像压缩DCT变换

图像DCT变换是图像压缩的一项重要技术,如何准确、快速地进行图像压缩一直是国内外研究的热点.现研究了两种二维离散余弦变换(DCT)的方法.在DCT算法结构上利用了变换的可分离性和行列的可分解性,并采用行列分解的方法将二维DCT转换为2个串行的一维DCT实现.     

基于脊波变换的图像压缩算法

自然图像包括大量的具有明显“直线边缘”的图像,而且边缘表示了图像的主要信息。利用脊波对“直线奇异”的良好刻画,针对具有直线特征的图像,设计基于脊波变换的有损压缩算法。首先对图像进行脊波变换,然后对变换系数进行标量量化、扫描、游程编码和熵编码。仿真实验表明,与基于小波变换的JPEG 2000压缩算法相比,该算法能获得更高的压缩率,同时保持较高的信噪比。     

Investigating the relationship between image enhancement and image compression in the context of the multi-scale retinex

Image enhancement and data compression methods arose from the distinct and largely separate disciplines of image processing and communications respectively, yet both are important components of current and future digital imaging systems technology. Here we examine the relationship of these two components with special emphasis on image enhancement and lossy jpeg image compression. When transmission channel capacity is limited, image/data compression is often performed to increase the data throughput. However, this compression has a significant impact on the quality of the final data that is received. In most cases, image enhancement performed after image compression tends to bring out the artifacts injected into the data due to the compression. However, if image enhancement is performed before image compression, there are two issues that arise: (i) image enhancement typically increases the contrast—amount of observable detail—in an image which leads to poorer compression ratios; and (ii) the radiometric information in the original data is typically irretrievably lost. In this paper we address the impact of image enhancement, specifically that of the multi-scale retinex with color restoration (msrcr) on image compression, and vice versa. We also look at the impact of compression on recovering original data from enhanced imagery given certain parameters about the enhancement process. In this context, we also develop an inversion process for the msrcr.     

Tree-structured vector quantization of CT chest scans: image quality and diagnostic accuracy

The authors apply a lossy compression algorithm to medical images, and quantify the quality of the images by the diagnostic performance of radiologists, as well as by traditional signal-to-noise ratios and subjective ratings. The authors' study is unlike previous studies of the effects of lossy compression in that they consider nonbinary detection tasks, simulate actual diagnostic practice instead of using paired tests or confidence rankings, use statistical methods that are more appropriate for nonbinary clinical data than are the popular receiver operating characteristic curves, and use low-complexity predictive tree-structured vector quantization for compression rather than DCT-based transform codes combined with entropy coding. The authors' diagnostic tasks are the identification of nodules (tumors) in the lungs and lymphadenopathy in the mediastinum from computerized tomography (CT) chest scans. Radiologists read both uncompressed and lossy compressed versions of images. For the image modality, compression algorithm, and diagnostic tasks the authors consider, the original 12 bit per pixel (bpp) CT image can be compressed to between 1 bpp and 2 bpp with no significant changes in diagnostic accuracy. The techniques presented here for evaluating image quality do not depend on the specific compression algorithm and are useful new methods for evaluating the benefits of any lossy image processing technique.     

结合置乱与扩频的数字水印算法

提出了一种使用置乱技术置乱水印图像，然后将Gold码用于水印结构设计的扩频数字水印算法。通过置乱技术提高了抽取数字水印的视觉效果，并可以在一定程度上弥补数字水印在嵌入、传输和抽取过程中的损耗。利用Gold码具有较多独立码的特性，以多位二进制信息为单位对置乱后的二值图像水印进行扩频调制，然后将调制信号自适应地加入到载体图像离散余弦变换域的低频分量系数中。应用Gold码使得算法可以采用较长的扩频序列，相应提高了鲁棒性。这种结合置乱和扩频的水印算法对于抵抗各种噪声、滤波和压缩等合法攻击以及其他非法攻击都具有很好的鲁棒性。     

Robust digital signature for multimedia authentication

Image authentication verifies the originality of an image by detecting malicious manipulations. This goal is different from that of image watermarking which embeds into the image a signature surviving most manipulations. Most existing methods for image authentication treat all types of manipulation equally (i.e., as unacceptable). However, some applications demand techniques that can distinguish acceptable manipulations (e.g., compression) from malicious ones. In this paper, we describe an effective technique for image authentication, which can prevent malicious manipulations but allow JPEG lossy compression. The authentication signature is based on the invariance of the relationship between the DCT coefficients at the same position in separate blocks of an image. This relationship will be preserved when these coefficients are quantized in a JPEG compression process. Our proposed method can distinguish malicious manipulations from JPEG lossy compression regardless of how high the compression ratio is. We also show that, in different practical cases, the design of the authenticator depends on the number of recompression times, and whether the image is decoded into integral values in the pixel domain during the recompression process. Theoretical and experimental results indicate that this technique is effective for image authentication.     

图像数据压缩的研究进展

本文介绍了图像数据压缩的常用技术及未来发展趋势。分为两个部分 :无损压缩和有损压缩。重点介绍了一些关键技术 ,如分形、小波变换和MPEG等。对于有关研究人员具有一定的参考价值     

An image multiresolution representation for lossless and lossycompression

We propose a new image multiresolution transform that is suited for both lossless (reversible) and lossy compression. The new transformation is similar to the subband decomposition, but can be computed with only integer addition and bit-shift operations. During its calculation, the number of bits required to represent the transformed image is kept small through careful scaling and truncations. Numerical results show that the entropy obtained with the new transform is smaller than that obtained with predictive coding of similar complexity. In addition, we propose entropy-coding methods that exploit the multiresolution structure, and can efficiently compress the transformed image for progressive transmission (up to exact recovery). The lossless compression ratios are among the best in the literature, and simultaneously the rate versus distortion performance is comparable to those of the most efficient lossy compression methods.     

Edge Preserving Lossy Image Compression with Wavelets and Contourlets

In this paper an edge preserving lossy image coder is presented. An edge image is obtained from the original with a digital image processing module using four different filters: Canny, Sobel, Roberts and Prewitt, then the original image is domain transformed with wavelets or contourlets, and a pixel mapping from original domain to transformed is done. For the compression, the edges points and the approximation image (which determines the compression factor) are selected; finally the image is decompressed in order to observe the reconstruction quality and edge preserving. The stages of the compression system are: a) Image selection, b) Digital image processing, c) Feature vector extraction, d) Domain Transformation, e) Pixel mapping, f) Image compression and g) Image decompression. Additionally, the results obtained from comparisons of error measures between original and decompressed images are shown and finally conclusions about the coder are presented.     

Performance analysis of image compression using wavelets

The aim of this paper is to examine a set of wavelet functions (wavelets) for implementation in a still image compression system and to highlight the benefit of this transform relating to today's methods. The paper discusses important features of wavelet transform in compression of still images, including the extent to which the quality of image is degraded by the process of wavelet compression and decompression. Image quality is measured objectively, using peak signal-to-noise ratio or picture quality scale, and subjectively, using perceived image quality. The effects of different wavelet functions, image contents and compression ratios are assessed. A comparison with a discrete-cosine-transform-based compression system is given. Our results provide a good reference for application developers to choose a good wavelet compression system for their application     

基于QR码的Contourlet域数字水印算法

针对目前数字水印技术无法有效抵抗几何攻击的问题,本文提出了一种基于QR码的Contourlet域数字水印算法。将文字信息进行QR码编码作为水印信息。首先,将载体图像进行Contourlet变换;然后,将得到的低频逼近图像进行分块;最后,将每一位QR码水印信息以量化的方式对应嵌入到每一个子块中。实验结果表明,本算法可以抵抗任意角度旋转和任意等比例缩放攻击,同时对高斯噪声、Speckle噪声、均值滤波、高斯滤波和JPEG压缩攻击具有很强的鲁棒性,并且算法复杂度低;水印提取时不需要借助原始图像,属于盲水印。因此,本文提出的数字水印技术可以广泛应用在数字产品的版权保护中。