海量遥感影像数据库实时压缩系统的设计与实现

数据压缩是解决海量数据远程传输的关键技术,编解码速度和重建图像质量是评价压缩系统性能的重要指标。论文介绍了作者自行设计和实现的一个海量遥感影像压缩系统,给出了该系统的工作原理和实现方法。     

An improved lossless image compression algorithm based on Huffman coding

There is an increasing number of image data produced in our life nowadays, which creates a big challenge to store and transmit them. For some fields requiring high fidelity, the lossless image compression becomes significant, because it can reduce the size of image data without quality loss. To solve the difficulty in improving the lossless image compression ratio, we propose an improved lossless image compression algorithm that theoretically provides an approximately quadruple compression combining the linear prediction, integer wavelet transform (IWT) with output coefficients processing and Huffman coding. A new hybrid transform exploiting a new prediction template and a coefficient processing of IWT is the main contribution of this algorithm. The experimental results on three different image sets show that the proposed algorithm outperforms state-of-the-art algorithms. The compression ratios are improved by at least 6.22% up to 72.36%. Our algorithm is more suitable to compress images with complex texture and higher resolution at an acceptable compression speed.

     

星载图像压缩中的无损预测研究

针对星载遥感图像自相关系数较大时MED预测比较理想,反之均值Mean预测更有优势的问题,融合该两种方法的优点提出了改进的MED预测,使之对多种类别的图像特别是遥感图像能够取得较好的预测效果.此外,从预测相关性、运算复杂度、是否带有自动误码纠偏以及采用Rice算法获得的压缩比等角度进行了两种预测残差映射器的研究,确定了选用带自动误码纠偏的差值映射和可调整的预测方式.当信源干扰多大时选取前像素预测,反之采用MED或改进的MED预测,从而兼顾了压缩比和抗误码两方面,且硬件可实现.     

Real-time dynamic tone-mapping operator on GPU

This article presents the parallel implementation on a GPU of a real-time dynamic tone-mapping operator. The operator we describe in this article is generic and may be used by any application. However, the goal of our work is to integrate this operator into the graphic rendering process of a car driving simulator; thus, we studied its real-time implementation. The tone-mapping operator outputs a low dynamic range (LDR) image keeping as much as possible the contrast and luminance of the original input high dynamic range (HDR) image. It performs the mapping between the luminances of the original scene to the output device??s display values. We address the problem of mapping HDR images to standard displays. In this case, the tone mapping compresses the luminances ratio. Several tone-mapping operators can be found in the literature as well as some parallelizations. However, they use either static or adaptations of static operators. We have adapted the dynamic operator of Irawan and parallelized it on GPU. Algorithmic optimizations have been performed, and we have explored the different strategies of repartition of the computation among the CPU and the GPU. We have chosen to implement on the GPU the changes between the color spaces and the interpolation of the histogram which are the most time-consuming steps on the CPU (1?C2?s per image 1,002?×?666). All of these optimizations lead to an increase of the processing rate and the number of HDR-quality images displayed to LDR per second. This operator has been implemented on a RISC processor Pentium 4?at 3.6?GHz and a GPU Nvidia 8800?GTX (728MB, 518GFLOPS). The execution speed has been multiplied by a factor of 15 compared to the naive implementation of the algorithm. The display rate reaches 30 images per second, which fulfills our goal for real-time video rate of 25 images per second.     

基于DSP的JPEG标准编解码系统设计

为了将图像数据高质量地传输,便于图像数据的检索、分析、处理和存储,设计了一个以JPEG标准的静态图像压缩编码系统;将原始图像进行图像压缩编码,同时利用DSP芯片处理速度快的特点,进行核心算法的处理满足系统实时性的要求;经过系统的多次验证,图像压缩编码系统成功地将一个31K大小的BMP格式图像转换为3K大小的JPEG格式图像,完成了10∶1的JPEG标准静态图像压缩;因此将原始图像进行图像压缩编码是解决图像数据量大小与有限存储容量和传输带宽矛盾的最合理方法。     

一种适于移动设备的全景图快速拼接方法

针对传统移动端全景图生成方法存在拼接速度慢、消耗内存以及存在接缝和“鬼影”等问题,提出了一种适用于移动设备的全景图生成算法。算法首先对源序列图像进行色彩校正,从而保证色彩及亮度均匀,以缩短后期图像融合时间;然后在全景图拼接过程中检测“鬼影”,同时运用梯度域目标移除和区域填充方法移除“鬼影”,利用泊松融合进行拼接后的平滑处理;同时在图像拼接过程中优化了内存分配机制,以减少在图像拼接过程中的内存消耗。通过编程实现了该算法,在配置为332MHz处理器和128MB内存的手机上对不同光照下拍摄的分辨率为1280×720的照片进行测试,并与传统的全局全景图拼接算法进行对比,若利用全局全景图拼接算法对2至9张源序列图像进行拼接,内存消耗为12.3~23.6MB,而提出的算法占用更少内存,分别为9.9~14.5MB。实验结果表明该方法消除图像接缝及“鬼影”较彻底,拼接速度快且节省内存,生成的最终全景图质量较好,可用于移动设备上的全景图拼接。     

机载SAR图像的动态金字塔实时显示技术

目的 随着机载SAR（合成孔径雷达）图像分辨率越来越高,幅宽越来越大,传统雷达显控系统将整幅图像放入内存、抽样显示的现有方法存在内存资源紧张、显示图像的等待时间过长等问题,为解决此类问题,提出一种动态金字塔实时显示技术。方法 机载SAR图像实时显示软件包括动态金字塔构建和显示技术。动态金字塔构建技术包括：当接收到一个瓦片的图像数据时,输出第0层级的金字塔瓦片;分6种情况,生成高层级瓦片,随着接收数据不断增多,逐步补全金字塔文件。动态金字塔显示技术是指在瓦片数据不全的情况下,采用递归算法,读取较低层级瓦片,合成、显示当前显示层级图像的技术。这两种技术分属两个独立线程,以硬盘文件（瓦片）为接口,实时交互,协同工作。结果 机载SAR图像实时显示软件仅仅占用30 MB内存,且与图像大小无关;显示第1块SAR图像瓦片的时延小于1 s,与传统显控系统对比,减少约一帧图像的传输时延;显示整帧图像的时延因存储介质读写文件的速率存在差异较大,固态硬盘的时延比较稳定,显示1 GB图像的时延为12.55 s;机械盘的时延受读写速度的影响,当发送时间间隔大于6 ms时,显示1 GB图像的时延仅比传输时延多1.47 s。结论 机载SAR图像实时显示软件能实时向用户呈现接收中的SAR图像,提高了机载SAR图像的显示时效性,降低了机载雷达显控终端的内存需求,改善了机载雷达显控终端的用户体验。     

An effective method for still image compression/decompression for transmission on PSTN lines based on modifications of Huffman coding

This paper presents an effective compression method suitable for transmission the still images on public switching telephone networks (PSTN). Since compression algorithm reduce the number of pixels or the gray levels of a source picture, therefore this will lead to the reduction of the amount of memory needed to store the source information or the time necessary for transmitting by a channel with a limited bandwidth. First, we introduced some current standards and finally the lossy DCT-based JPEG compression method is chosen. According to our studies, this method is one of the suitable methods. However, it is not directly applicable for image transmission on usual telephone lines (PSTN). Therefore, it must be modified considerably to be suitable for our purposes. From Shannon’s Information Theory, we know that for a given information source like an image there is a coding technique which permits a source to be coded with an average code length as close as to the entropy of the source as desired. So, we have modified the Huffman coding technique and obtained a new optimized version of this coding, which has a high speed and is easily implemented. Then, we have applied the DCT¹ and the FDCT² for compression of the data. We have analyzed and written the programs in C++ for image compression/decompression, which give a very high compression ratio (50:1 or more) with an excellent SNR.³In this paper, we present the necessary modifications on Huffman coding algorithms and the results of simulations on typical images.     

基于小波编码的巡航导弹图像压缩方法研究

弹栽图像压缩系统要求压缩算法在保证图像质量的前提下对图像实现大压缩比实时压缩.针对这些要求,提出了采用小波编码算法作为图像压缩系统的实现算法和DSP作为算法的实现平台.小渡压缩算法分为两个部分,即先对图像进行整型提升小波变换,再利用SPIHT(Set Partitioning in Hierarchical Trees)算法对变换结果进行编码.对小渡编码过程中存在重复运算和存储量大的缺点进行了改进,使之适合于DSP并行处理.实验结果表明,改进的算法与原算法相比,重构图像的峰值信噪比相当,大于28dB,满足图像质量要求;图像压缩速度达到20帧/s,完全满足实时性要求.     

基于FPGA的实时无损数据压缩系统设计

针对某些特殊的测试实验,既要求测试系统微体积、低功耗,还要求记录大量数据的问题,提出基于FPGA的数据压缩解决方案.介绍了LZW压缩算法的基本理论及其用FPGA硬件实现的方法.大量的实验表明,系统工作稳定,压缩速度快(8 MB/s以上),对实测数据的压缩效果好(25％左右)、工作时电流小(37 mA),实现了速度、性能...     

FPGA implementation of collaborative representation algorithm for real-time hyperspectral target detection

Hyperspectral image contains various wavelength channels and the corresponding imagery processing requires a computation platform with high performance. Target and anomaly detection on hyperspectral image has been concerned because of its practicality in many real-time detection fields while wider applicability is limited by the computing condition and low processing speed. The field programmable gate arrays (FPGAs) offer the possibility of on-board hyperspectral data processing with high speed, low-power consumption, reconfigurability and radiation tolerance. In this paper, we develop a novel FPGA-based technique for efficient real-time target detection algorithm in hyperspectral images. The collaborative representation is an efficient target detection (CRD) algorithm in hyperspectral imagery, which is directly based on the concept that the target pixels can be approximately represented by its spectral signatures, while the other cannot. To achieve high processing speed on FPGAs platform, the CRD algorithm reduces the dimensionality of hyperspectral image first. The Sherman–Morrison formula is utilized to calculate the matrix inversion to reduce the complexity of overall CRD algorithm. The achieved results demonstrate that the proposed system may obtains shorter processing time of the CRD algorithm than that on 3.40 GHz CPU.     

混沌系统和DNA编码的并行遥感图像加密算法

目的 针对传统基于混沌系统的图像加密算法在加密遥感图像时存在速度差、安全性不足等问题,提出一种混沌系统和脱氧核糖核酸（deoxyribonucleic acid,DNA）编码的并行遥感图像加密算法,提升图像加密的效率和安全性。方法 利用明文图像的安全散列算法256（secure Hash algorithm 256,SHA-256）哈希值修改混沌系统的参数和初始值,提高算法的明文敏感性,并通过2维Hénon-Sine映射置乱图像,打乱像素之间的分布规律;然后利用图形处理器（graphics processing unit,GPU）并行计算密钥序列,缩短加密时间,通过选择多个高维混沌系统和修改混沌系统初始值确保密钥序列的随机性;最后利用密钥序列和GPU对图像进行DNA并行加密,得到最终的密文图像。在DNA并行加密过程中,生成一种DNA-S盒,对DNA编码进行非线性替换。结果 在遥感图像以及普通彩色图像上的仿真实验和安全性分析结果表明,本文算法在加密遥感图像上速度达到80 Mbit/s以上,密钥空间大于10²⁰⁰,信息熵趋近于8,密文图像直方图平坦均匀,且通过了美国国家标准与技术研究院（National Institute of Standards and Technology,NIST）随机测试以及卡方检验;与其他算法相比,本文算法在密钥空间、相邻像素相关性、像素改变率（number of changing pixel rate,NPCR）、统一平均变化强度（unified averaged changed intensity,UACI）和信息熵等评价指标上更接近理想值。结论 本文算法在大幅提升加密速度的同时,保证算法足够安全,能够抵抗各种攻击,适合遥感图像以及大容量图像的保密存储和网络传输。     

VLSI Implementation of Discrete Wavelet Transform for Lossless Compression of Medical Images

This paper presents a VLSI architecture to implement the forward and inverse two dimensional Discrete Wavelet Transform (DWT), to compress medical images for storage and retrieval. Lossless compression is usually required in the medical image field. The word length required for lossless compression makes too expensive the area cost of the architectures that appear in the literature. Thus, there is a clear need for designing a cost-effective architecture to implement the lossless compression of medical images using DWT. The data path word length has been selected to ensure the lossless accuracy criteria leading a high speed implementation with small chip area. The pyramid algorithm is reorganized and the algorithm locality is improved in order to obtain an efficient hardware implementation. The result is a pipelined architecture that supports single chip implementation in VLSI technology. The implementation employs only one multiplier and 352 memory elements to compute all scales what results in a considerable smaller chip area (45 mm²) than former implementations. The hardware design has been captured by means of the VHDL language and simulated on data taken from random images. Implemented in a 0.7 μm technology, it can compute both the forward and inverse DWT at a rate of 3.5 512×512 12 bit images/s corresponding to a clock speed of 33 MHz. This chip is the core of a PCI board that will speedup the DWT computation on desktop computers.     

一种基于GPU的改进光线投射算法

针对传统光线投射算法计算量大、速度慢、在没有硬件加速情况下难以实时重建的问题,提出了一种基于GPU编程的快速计算重采样点值的光线投射算法。首先,设计一个GPU程序确定投射光线的终点与方向;其次,采用加速度步长采样方法确定重采样点的位置并利用快速复合插值方法计算重采样点的颜色值;最后,采用不透明度提前截止法进一步加速重建过程。实验结果表明,该方法计算复杂度低、执行效率高。在保证重建图像质量的同时,与现有基于CPU的光线投射算法相比,重建速度提高6倍,与基于GPU的传统光线投射算法相比,速度提高2倍。     

H.264/AVC中基于决策树的P帧快速模式选择（HHME2013第61号论文）

目的：H.264/AVC帧间预测编码需要对所有可能编码模式计算并比较率失真代价,众多的模式类型导致了P帧编码的计算复杂度非常高。本文提出了一种针对P帧的基于决策树的快速选择候选模式算法。方法：在对宏块进行16×16的帧间运动估计后,首先根据残差宏块中4×4全零系数块个数对部分宏块直接选择出候选模式;然后使用16个4×4块的SATD值,采用决策树分类方法对其余宏块选择候选模式。结果：由于只需对候选模式进行编码,因此有效降低了编码器的计算复杂度。实验结果表明,与原始全搜索编码算法相比,该算法对不同运动程度的视频序列获得了较一致的编码时间节省,同时平均峰值信噪比的损失和平均比特率的增加均较少。结论：本文提出了一种新的P帧帧间预测候选模式选择算法,根据帧间运动估计后的残差宏块信息,采用决策树方法对候选模式集进行分类。实验结果表明,该算法能在保证视频编码质量的前提下,有效地降低编码过程中的计算量,缩短编码时间。     

基于FPGA的并行RICE解码技术研究与实现

RICE算法在无损压缩系统有着广泛的应用。由于RICE算法采用了变长的自适应熵编码,因此在解码时需要对压缩流进行逐位判断和解析,这给高速解压缩的实现带来了困难。现有的RICE解码实现在解码速度和通用性上都不理想。针对RICE算法中自适应熵编码的特点,设计了一种基于有限状态机和查找表的并行RICE解码结构,可在FPGA上完成8比特宽度的并行解码,解码速度最高可达176 MB/s;同时,该解码结构适用于编码参数k变化的情况,具有很强的通用性。     

HEVC-based lossless intra coding for efficient still image compression

Latest advancements in capture and display technologies demand better compression techniques for the storage and transmission of still images and video. High efficiency video coding (HEVC) is the latest video compression standard developed by the joint collaborative team on video coding (JCTVC) with this objective. Although the main design goal of HEVC is the compression of high resolution video, its performance in still image compression is at par with state-of-the-art still image compression standards. This work explores the possibility of incorporating the efficient intra prediction techniques employed in HEVC into the compression of high resolution still images. In the lossless coding mode of HEVC, sample- based angular intra prediction (SAP) methods have shown better prediction accuracy compared to the conventional block-based prediction (BP). In this paper, we propose an improved sample-based angular intra prediction (ISAP), which enhances the accuracy of the highly crucial intra prediction within HEVC. The experimental results show that ISAP in lossless compression of still images outclasses archival tools, state-of-the-art image compression standards and other HEVC-based lossless image compression codecs.     

基于稀疏带状矩阵的二维图像重建

压缩传感（Compressed Sensing,CS）是数据采样同时实现压缩的新理论、新技术。针对大图像重构时采用的测量矩阵维数高,所需存储空间过大的问题,引入稀疏带状概念,提出了稀疏带状测量矩阵,可减少测量矩阵独立随机元,根据图像按列逐步处理的方式,测量矩阵维数大大降低。实验结果表明基于稀疏带状测量矩阵的逐列图像重构算法在保证重建质量的情况下,计算速度也大大提升。     

Performance engineering to achieve real-time high dynamic range imaging

Image-processing applications like high dynamic range imaging can be done efficiently in the gradient space. For it, the image has to be transformed to gradient space and back. While the forward transformation to gradient space is fast by using simple finite differences, the backward transformation requires the solution of a partial differential equation. Although one can use an efficient multigrid solver for the backward transformation, it shows that a straightforward implementation of the standard algorithm does not lead to satisfactory runtime results for real-time high dynamic range compression of larger 2D X-ray images even on GPUs. Therefore, we do a rigorous performance analysis and derive a performance model for our multigrid algorithm that guides us to an improved implementation, where we achieve an overall performance of more than 25 frames per second for 16.8 Megapixel images doing full high dynamic range compression including data transfers between CPU and GPU. Together with a simple OpenGL visualization it becomes possible to perform real-time parameter studies on medical data sets.     

基于HEVC与聚类算法的计算机桌面图像压缩算法

对基于HEVC与聚类算法的计算机桌面图像压缩方案进行研究,将计算机桌面图像进行自适应块分类,利用颜色聚类算法对块进行颜色聚类,简化颜色总类、节省码流、改善编码性能。再利用HEVC帧内预测编码算法对块进行压缩,为高清分辨率计算机桌面图像网络共享,提供高效的图像压缩方法。