整数双正交小波图像压缩及其DSP实现

对于高分辨率相机所成图像,数据量非常巨大,仅用软件压缩远远不能满足实时性要求.本文提出一种适于硬件实现图像压缩算法--整数双正交小波变换的提升算法,并用DSP（Digital Signal Processing）芯片实现该种算法.由于输入的图像的灰度值是整数,为减少误差,我们把滤波器的参数也设计成整数形式,这种小波的计算只需两个浮点运算和16个整数运算,降低运算的复杂度,减少存储空间,进而提高实时性.并结合SPIHT编码方法提高压缩比（可达到31.25）.     

基于双正交小波变换的航空图像压缩研究

提出一种基于提升方案的双正交小波变换结合SPIHT编码的图像压缩方法.小波提升方案是继多分辨分析之后,另一种非常有效的构造小波滤波器的方法,在双正交条件下按所需的小波性能自由构造双正交小波基,并能加快小波变换的执行速度.分析了应用提升方案构造双正交小波的算法,选用性能优良的双正交小波,结合SPIHT编码,进行图像压缩.实验表明,通过该方法进行图像压缩,图像重建质量较高.     

双正交重叠变换的整数实现算法与图像压缩

本文利用提升原理,以二进制整数DCT为基础,提出了双正交重叠变换的整数实现算法,其计算只需要少量的移位和加法运算,因而软件实现和硬件实现都非常简单.实验结果表明,它是一种有效的图像压缩变换,压缩质量大大超过了运算量更多的近似二进制整数小波变换和DCT,与Daubechies 9/7小波也非常接近.     

二元双正交梅花小波结合SPIHT的图像压缩方法

为了研究不可分小波在图像压缩中的应用，利用陪集构造方法构造了一种特殊的二元不可分双正交小波：梅花小波，并将其和SPIHT编码相结合研究了其在图像压缩中的性能。该算法可以实现无浮点的乘法运算，运算速度快，易于硬件设计。     

基于改进小波的图像压缩算法设计与实现

为了减小图像编码中的空间融合,需要进行图像压缩编码。针对当前的LBG图像向量量化压缩算法自适应能力不强的问题,提出一种基于改进小波结合LBG向量量化的图像压缩算法。首先采用双正交小波对原始图像进行正交性分解,采用重构滤波器进行图像的降噪重构,然后运用LBG向量量化方法构造图像的矢量码书,采用三级小波尺度分解进行不同码书尺寸下的图像压缩。最后进行仿真测试,结果表明采用该方法进行图像压缩的信噪比及峰值信噪比较高,说明图像压缩的质量较好,且计算复杂度较低。     

新型9/7小波基构造及快速实现

CDF9/7小波的复杂系数是限制其快速实现的主要因素。该文构造了新的含参双正交提升小波模型,并利用能量集中性法则和迭代搜索算法提出一种压缩性能与此相当适合移位操作的有理数小波基。新小波基在硬件实现时可用一次移位和加法运算代替乘法运算,运算量仅为原来的25%,且无需考虑位长对精度的影响。一维小波4级流水架构已通过FPGA验证,与同类设计相比,减少一半的资源消耗量,并且大幅提高系统的工作频率。     

基于IWT图像压缩技术的LED同步显示系统设计

在全彩LED大屏幕同步显示系统中,存在图像的实时显示与通信带宽之间的矛盾.文章采用整数小波变换(IWT)算法进行图像压缩后传输,大幅减小了通信量.由于IWT算法仅含有整数加减和移位运算,避免了当前大多数图像压缩解压算法需要复杂的浮点型运算的缺陷,从而可以在显示屏控制器中实现图像的快速解压.实验表明,此算法可以得到较好的图像压缩效果,VLSI硬件设计只占用很少的系统逻辑单元,同时可达到很快的图像重构速度,能够满足同步屏图像实时显示的要求.     

基于整数小波变换的准无失真图像压缩技术

 本文首先讨论了一般整数小波的构造方法,然后利用分块DPCM与整数小波变换进行遥感图像的准无失真压缩,该方法可进行实时处理,硬件实现简单,可并行处理,实验结果表明,该方法是一种有效遥感图像压缩方法.     

Q-shift复小波的一种新型构造方法及其在图像去噪中的应用

为了提高复小波变换的效率,本文提出了一种设计Q-shift复小波滤波器的新方法。与目前采用多相位矩阵的晶格分解结构得到正交小波的方法不同的是,这里从更为一般的完全重构滤波器组出发寻求满足特定要求的正交小波。不但可以构造出系数更为简单、运算更加方便的小波,而且可以实现任意精度的复小波变换。该方法的可拓展性好,可以很方便的添加如高阶消失矩等限制并简化设计过程。以普遍采用的Q-shift10/10小波为例,利用本文构造的正交小波可将复小波变换中的乘法运算降低到原来的1/3,而加法基本相当,且小波的频率选择性质更好。将其用于图像去噪的实验表明,采用本文构造的小波可以显著提高处理速度并得到更高的峰值信噪比(PSNR)。     

小波提升格式的研究

小波提升格式以计算快速、能形成整数到整数的可逆变换的优势在数字图像压缩领域得到了广泛应用,而如何把适合于图像压缩的第一代小波映射成整数提升格式也成为一个研究问题。本文应用双正交滤波的多相矩阵的多步三角分解,提出不同多相矩阵表示时寻求提升系数的方法,并利用这种方法给出了多相矩阵的行列式不为1的滤波器组的提升格式。     

一种改进的零树结构编码算法研究

现在大部分图像压缩技术都利用了小波变换后图像不同分辨率反相同方向子带之间的相关性。采用双正交提升小波将图像变换到小波域,通过增加熵编码的符号集,提出了一种基于正交小波变换的增广零树压缩编码算法,在整个编译码过程中仅使用一个系数列表,况且不进行任何排序操作。通过相关实验,证实该方法能有效进行图像压缩,提高了压缩率。     

基于伪中值滤波和小波变换的红外图像增强方法

针对红外图像对比度差、信噪比低的特点,提出一种基于伪中值滤波和小波变换的红外弱小目标增强的算法。图像首先经过伪中值滤波滤除部分噪声,然后进行小波变换得到小波系数,对小于阈值的系数利用基于临近系数保留法进行滤波,防止小目标误判为噪声被滤除,对于大于阈值的系数进行非线性增强,最后重构得到去噪后的增强图像。实验结果表明,本文算法有效地滤除了噪声,提高了图像的对比度,更符合人眼视觉特性。     

Wavelet filter evaluation for image compression

Choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design. Although regularity is sometimes used in filter evaluation, its success at predicting compression performance is only partial. A more reliable evaluation can be obtained by considering an L-level synthesis/analysis system as a single-input, single-output, linear shift-variant system with a response that varies according to the input location module (2(L),2(L)). By characterizing a filter bank according to its impulse response and step response in addition to regularity, we obtain reliable and relevant (for image coding) filter evaluation metrics. Using this approach, we have evaluated all possible reasonably short (less than 36 taps in the synthesis/analysis pair) minimum-order biorthogonal wavelet filter banks. Of this group of over 4300 candidate filter banks, we have selected and present here the filters best suited to image compression. While some of these filters have been published previously, others are new and have properties that make them attractive in system design.     

Design of multiplierless, high-performance, wavelet filter banks with image compression applications

The JPEG2000 image coding standard employs the biorthogonal 9/7 wavelet for lossy compression. The performance of a hardware implementation of the 9/7 filter bank depends on the accuracy and the efficiency with which the quantized filter coefficients are represented. A high-precision representation ensures compression performance close to the unquantized, infinite precision filter bank, but at the cost of increased hardware resources and processing time. If the filter coefficients are quantized such that the filter bank properties are preserved, then, the degradation in compression performance will be minimal. This paper investigates two filter structures and two "compensating" filter coefficient quantization methods for improving the performance of multiplierless, quantized filter banks. Rather than using an optimization technique to guide the design process, the new methods utilizes the perfect reconstruction requirements of the filter bank. The results indicate that the best method (a cascade structure with compensating zeros) realizes image-compression performance very similar to the unquantized filter case while also achieving a fast, efficient hardware implementation.     

17/11双正交小波的优化设计及其对图像压缩性能的分析

许多适合于图像编码的小波,如CDF-9/7,Winger-17/11(W-17/11),Villasenor-6/10和10/18(V-6/10和V-10/18)小波,其滤波器系数是无理数,需要用无限的计算精度实现对应的离散小波变换(DWT)。该文给出了一种参数化构造17/11双正交小波组的简便方法:首先把小波合成滤波器表示为用两个自由参数表达的三角多项式,然后把双正交小波的精确重构条件归结为一个线性方程组,最后求解此方程组得到对应的小波分解滤波器,从而得到了17/11双正交小波滤波器的参数表达式。通过调整表达式中的自由参数,可以随意构造具有所需特征的17/11线性相位小波滤波器。作为构造实例,构造出一种新的有理系数17/11双正交小波滤波器,它具有优化的编码增益。实验表明:其压缩性能与W-17/11和V-10/18小波滤波器相当,优于CDF-9/7和V-6/10小波滤波器。     

Two-channel nonseparable wavelets statistically matched to 2-D images

This paper presents a new approach for the estimation of 2-channel nonseparable wavelets matched to images in the statistical sense. To estimate a matched wavelet system, first, we estimate the analysis wavelet filter of a 2-channel nonseparable filterbank using the minimum mean square error (MMSE) criterion. The MMSE criterion requires statistical characterization of the given image. Because wavelet basis expansion behaves as Karhunen-Loève type expansion for fractional Brownian processes, we assume that the given image belongs to a 1st order or a 2nd order isotropic fractional Brownian field (IFBF). Next, we present a method for the design of a 2-channel two-dimensional finite-impulse response (FIR) biorthogonal perfect reconstruction filterbank (PRFB) leading to the estimation of a compactly supported statistically matched wavelet. The important contribution of the paper lies in the fact that all filters are estimated from the given image itself. Several design examples are presented using the proposed theory. Because matched wavelets will have better energy compaction, performance of estimated wavelets is evaluated by computing the transform coding gain. It is seen that nonseparable matched wavelets give better coding gain as compared to nonseparable non-matched orthogonal and biorthogonal wavelets.     

Simplified biorthogonal discrete wavelet transform for VLSI architecture design

Biorthogonal discrete wavelet transform (BDWT) has gained general acceptance as an image processing tool. For example, the JPEG2000 standard is completely based on the BDWT. In BDWT, the scaling (low-pass) and wavelet (high-pass) filters are symmetric and linear phase. In this work we show that by using a specific sign modulator the BDWT filter bank can be realized by only two biorthogonal filters. The analysis and synthesis parts use the same scaling and wavelet filters, which simplifies especially VLSI designs of the biorthogonal DWT/IDWT transceiver units. Utilizing the symmetry of the scaling and the wavelet filters we introduce a fast convolution algorithm for implementation of the filter modules. In multiplexer–demultiplexer VLSI applications both functions can be constructed via two running BDWT filters and the sign modulator. This work was supported by the National Technology Agency of Finland (TEKES).     

基于Bior小波变换和中值滤波的图像去噪

中值滤波是一种常用的滤波方法,它可以较好地滤除脉冲噪声,但滤除高斯噪声效果不理想,而小波变换可以较好地滤除高斯噪声。本文将Biorthogonal小波变换与中值滤波相结合,同时滤除图像中的高斯噪声和脉冲噪声。实验结果表明,该方法在降低了图像噪声的同时又尽可能地保留图像的细节,其去噪效果优于单纯的小波变换或单纯的中值滤波。