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.     

基于DWT SVD域的彩色图像水印算法

针对数字产品的版权保护问题,提出了一种结合整数小波变换（DWT）和矩阵奇异值分解（SVD）的彩色图像非盲水印算法。该算法首先对待处理图像的蓝色分量进行整数小波分解,再将得到的低频子带的小波系数矩阵进行奇异值分解,然后对水印灰度图像进行奇异值分解,水印图像的奇异值被嵌入到由源图像小波系数分解得到的奇异值中。经过奇异值分解逆变换及整数小波逆变换得到含水印图像。实验结果表明,该算法对加噪、滤波、JPEG压缩、剪切、缩放和旋转攻击均有较强的抵抗力,具有较好的实用价值。     

无损和近似无损图像压缩中的颜色空间变换研究

通过对RGB、YCrCb和可逆JPEG2000三种颜色空间无损压缩方法进行比较,本文给出了在连续的正向和反向变换周期里,对误差进行圆整,误差不会累积的条件,特别是圆整误差在从RGB>YCrCb>RGB的连续周期中不会累积的条件。附加的两位亮度和色度信息可以更好地帮助完成可逆颜色变换,采用YCrCb表示的图像的压缩性能要稍微优于RGB方法表示,但是比采用JPEG2000可逆颜色空间的性能差。本文也研究了近似无损压缩JPEG_LS在连续的压缩与解压周期的累积误差。     

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。     

基于JPEG压缩编码的小波域多图像融合算法研究

为了在一定的区域内融合多幅光学图像的信息,采用了一种基于联合图像专家小组（JPEG）图像压缩编码的小波域多幅图像融合算法。其基本思想是将小波逆变换看作是信息的融合过程,先对多幅图像进行JPEG压缩编码,压缩后得到一组二进制码流,这组二进制码流可以直接作为小波变换的分解系数,经小波逆变换后得到融合信息。结果表明,该算法能够实现多幅灰度图像和彩色图像的融合,提高了单一空间内图像的信息量,有利于多图像的存储和传输。     

JPEG2000标准中无损压缩部分的FPGA实现

小波变换是当代信号处理技术常用的数学方法之一,在图像压缩方面也有很好的应用。新一代的图像压缩标准JPEG2000就是采用这种技术。文中介绍了如何在FPGA(现场可编程门阵列)上实现JPEG2000标准中无损压缩的方法。该算法简单,计算量小,易于硬件实现。硬件实现结果与软件实现结果基本一致。     

整数5/3小波变换的VLSI结构设计

在JPEG 2000中,无损图像压缩是采用整数5/3小波变换实现的.JPEG 2000也给出了5/3小波基于提升方法的算法.对提升方法的整数5/3小波变换算法进行了研究,针对二维的变换提出一种VLSI结构.该结构由4个模块构成,模块之间并行运行,模块内部采用流水线技术.对多级变换,级间的运算还可交叉,体现了提升方法的优势,较大地提高了硬件效率.其主要优点是消耗资源少且运算速度高,同时也适用于其他整数小波变换.     

基于JPEG2000的遥感图像分级量化压缩

介绍了JPEG2000静态图像压缩标准的基本情况;对遥感图像的相关性以及小波变换域统计特性进行了分析,得出遥感图像的特点。针对其特点,设计了基于JPEG2000无损压缩的高频子带分级量化高保真压缩方案。实验结果表明,此方案在对遥感图像进行压缩时取得了较好的效果。     

基于JPEG2000的遥感图像压缩

介绍了JPEG2000静态图像压缩标准的基本情况;对遥感图像的相关性以及小波变换域统计特性进行了分析。得出遥感图像的特点;针对遥感图像的特点,设计了基于JPEG2000无损压缩的高频子带分级量化高保真压缩方案。实验结果表明,此方案在对遥感图像进行压缩时取得了较好的效果。     

基于FPGA的FFT/IFFT处理器的实现

提出一种利用并行算法来实现FFT（快速傅里叶变换）及其逆变换IFFT（快速傅里叶逆变换）的设计方法。该处理器可由用户动态配置成64、256、1024点复数FFT或其逆变换IFFT。     

Matrix Factorizations for Parallel Integer Transformation

Integer mapping is critical for lossless source coding and has been used for multicomponent image compression in the new international image compression standard JPEG 2000. In this paper, starting from block factorizations for any nonsingular transform matrix, we introduce two types of parallel elementary reversible matrix (PERM) factorizations which are helpful for the parallelization of perfectly reversible integer transforms. With improved degree of parallelism and parallel performance, the cost of multiplications and additions can be, respectively, reduced to O(logN) and O(log²N) for an N by N transform matrix. These make PERM factorizations an effective means of developing parallel integer transforms for large matrices. We also present a scheme to block the matrix and allocate the load of processors for efficient transformation     

一种基于三维整型DCT变换的高光谱图像无损压缩方法

本文根据高光谱图像具有空间和谱间相关性的特点,提出一种基于三维整型DCT变换的无损压缩方法.首先采用三维整型DCT变换消除高光谱图像空间和谱间的相关性;然后,对变换系数进行类似小波的树状系数重组,并按子带顺序进行一阶自适应算术编码.实验结果表明,本文提出的方法与JPEG2000中无损压缩算法相比,平均比特率降低0.1～0.4bpp;与JPEG-LS相比,平均比特率降低0.01～0.2bpp.     

Lossy-to-lossless image compression based on multiplier-less reversible integer time domain lapped transform

In this paper, a reversible integer to integer time domain lapped transform (RTDLT) is introduced. TDLT can be taken as a combination of time domain pre- and post-filter modules with discrete cosine transform (DCT). Different from TDLT, the filters and DCT in our proposed RTDLT are realized from integer to integer by multi-lifting implementations after factorizing the filtering and transforming matrixes into triangular elementary reversible matrices (TERMs). Lifting implementations are realized by only shift and addition without any floating-point multiplier to reduce complexity. The proposed method can realize progressive lossy-to-lossless image compression with a single bit-stream. Simulation results show that RTDLT-based compression system obtains comparable or even higher compression-ratio in lossless compression than that of JPEG2000 and JPEG-LS, as well as gratifying rate distortion performance in lossy compression. Besides, RTDLT keeps low-complexity in hardware realization because it can be parallel implemented on the block level.     

JPEG2000中的感兴趣区域编码

图像的感兴趣区域编码技术,即在图像中的感兴趣区域进行无损或近无损压缩,而在其它区域采用有损压缩,从而既可以获得所期望的高质量的图像信息,又保持了较高的压缩比,很好地解决了压缩比和图像质量之间的矛盾。JPEG2000是国际标准组织IEO/IEC正在制定的新的静止图像压缩标准,JPEG2000中一项关键技术就是支持对感兴趣区域的编码。JPEG2000进行感兴趣区域编码采用了MAXSHIFT算法。     

Lossless image compression with projection-based and adaptive reversible integer wavelet transforms

Reversible integer wavelet transforms are increasingly popular in lossless image compression, as evidenced by their use in the recently developed JPEG2000 image coding standard. In this paper, a projection-based technique is presented for decreasing the first-order entropy of transform coefficients and improving the lossless compression performance of reversible integer wavelet transforms. The projection technique is developed and used to predict a wavelet transform coefficient as a linear combination of other wavelet transform coefficients. It yields optimal fixed prediction steps for lifting-based wavelet transforms and unifies many wavelet-based lossless image compression results found in the literature. Additionally, the projection technique is used in an adaptive prediction scheme that varies the final prediction step of the lifting-based transform based on a modeling context. Compared to current fixed and adaptive lifting-based transforms, the projection technique produces improved reversible integer wavelet transforms with superior lossless compression performance. It also provides a generalized framework that explains and unifies many previous results in wavelet-based lossless image compression.     

基于提升小波变换的无损医学图像压缩

随着医学信息网络的发展,医学图像在网络中的传输对于远程医疗、教学以及患者信息的共享非常必要。在传输过程中对传输的速度和图像的质量要求很高,对图像进行压缩传送是目前有限带宽下的必然选择,而传统的压缩算法如基于离散余弦变换(DCT)的JPEG算法、基于字典技术的游程编码RLE难以满足这些要求。本文提出基于提升小波变换的无损医学图像压缩方法,并在JPEG2000标准框架下用PC机对DICOM(Digital Imaging and Communication in Medicine)标准脑部CT图像做了实现,取得满意的效果。     

High‐Quality and Robust Reversible Data Hiding by Coefficient Shifting Algorithm

This study presents two reversible data hiding schemes based on the coefficient shifting (CS) algorithm. The first scheme uses the CS algorithm with a mean predictor in the spatial domain to provide a large payload while minimizing distortion. To guard against manipulations, the second scheme uses a robust version of the CS algorithm with feature embedding implemented in the integer wavelet transform domain. Simulations demonstrate that both the payload and peak signal‐to‐noise ratio generated by the CS algorithm with a mean predictor are better than those generated by existing techniques. In addition, the marked images generated by the variant of the CS algorithm are robust to various manipulations created by JPEG2000 compression, JPEG compression, noise additions, (edge) sharpening, low‐pass filtering, bit truncation, brightness, contrast, (color) quantization, winding, zigzag and poster edge distortion, and inversion.     

基于KL与小波联合变换的多光谱图像压缩

鉴于卫星拍摄的遥感图像的空间分辨率和光谱分辨率越来越高,在一些应用中,常会对多光谱图像进行压缩。为了提高多光谱图像的压缩质量,提出了联合相位相关和仿射变换的图像配准方法,有效提高了图像谱段之间的相关性。针对多光谱图像压缩,提出了结合Karhunen-Love,KL变换去除谱间相关和嵌入式二维小波编码方法。相比JPEG2000谱段图像独立压缩方法,提出方法解压图像的Peak Signal to Noise Ratio,PSNR值平均提高2.1 dB。实验结果表明:所提出的方法能在相同的压缩率下获得比JPEG2000谱段图像独立压缩方法更好的图像质量。     

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.