基于子带极值阶梯性的SPIHT算法改进方案

多级树集合分裂算法（SPIHT）充分利用了小波分解后相同方向不同尺度子带图像间的相似性,取得了很好的压缩效果,在基于小波的图像编码方案中得到了广泛应用。该文利用子带极值的阶梯性对SPIHT算法进行了改进。理论分析和实验都证明了改进算法在复杂度有所降低的前提下有效地提高了压缩性能。     

Reduced memory listless speck image compression

In this paper a variant of the set partitioned embedded block coder (SPECK) image compression called listless SPECK (LSK) is presented. LSK operates without lists and is suitable for a fast, simple hardware implementation. LSK has a fixed predetermined memory requirement about 50% larger than needed for the independent image. Instead of lists, a state table with two bits per coefficient is used to keep track of the block coding and the information that has been encoded. LSK sparsely marks selected block nodes of insignificant blocks in the state table, in such a way that large groups of predictably insignificant pixels are easily identified and skipped during the coding process. The image data is stored as a one-dimensional recursive zigzag array for computational efficiency and algorithmic simplicity. Performance of the proposed algorithm on standard test images is nearly same as SPECK.     

基于JPEG-LS压缩比控制的图像压缩加密算法

针对传统图像压缩比控制不精细及低维混沌系统保密性不高的问题,提出一种基于连续色调静态图像的无损或近无损压缩标准(JPEG-LS)压缩比控制的图像压缩加密算法.在深入分析JPEG-LS中失真控制参数Near对图像压缩比和重建质量的影响的基础上,首先,对光栅扫描的图像数据进行梯度处理;然后,比较梯度值与Near的大小关系以决定进入游程模式进行游长编码或常规模式进行Golomb编码;再次对三维Lorenz混沌系统生成的序列进行随机性处理,采用该序列作为密钥分别对游程模式、常规模式和全模式(游程和常规两种模式)下的压缩码流进行加密;最后,对Near进行实时动态调整,实现了对图像的压缩比精细控制且提高了保密性.仿真结果表明,所提算法能够实现良好的压缩比控制,且重建图像质量比线性压缩比控制算法提高了大约0.5 dB;同时算法安全性高,能够有效抵抗熵攻击、差分攻击、穷举攻击、统计攻击等多种攻击,且加密对压缩效率基本没有影响.     

基于多小波域SOT结构的SAR图像去噪与压缩算法

合成孔径雷达（SAR）图像固有的相干斑噪声严重影响了SAR图像的判读和进一步压缩处理,提出一种在多小波域将空间方向树（SOT）去噪与压缩相结合的SAR图像压缩算法。首先利用SOT对高频子带的多小波系数进行软阈值去噪,滤除相干斑噪声;然后采用改进的多级树集合分裂（SPIHT）算法编码形成嵌入式码流。利用大量的机载SAR图像对该算法进行了仿真验证,实验结果表明采用该算法进行SAR图像压缩提高了重建图像的PSNR,同时对相干斑噪声进行了有效的抑制。     

基于SPIHT的感兴趣区域编码

感兴趣区域(ROI)编码是一种重要的图像编码思想,可用来解决图像质量与压缩比之间的矛盾,特别适合应用到医学图像压缩中.提出了一种基于层次树集合划分(SPIHT)算法的感兴趣区域编码方法,通过附加ROI掩模信息,无需提升小波系数,使得ROI优先于其它区域编码和传输.     

基于改进SPIHT的医学图像编码

考虑到压缩效率很高的静态图像压缩算法（Set Patitioning in Hierarchical Trees,SPIHT）的压缩效率尚可以进一步提高,提出一种改进的SPIHT算法：在原始算法的基础上,引入一种新的类型树,在初始化时最大限度地保存小波变换后的系数．将改进的SPIHT算法应用到医学图像的压缩中,取得良好的压缩效果．     

基于小波包分解的 SAR图像压缩 *

针对 SAR图像含有丰富的中、高频信息 ,而基于小波变换的图像压缩方法会丢失高频细节信息 ,提出了基于小波包分解的 SAR图像编码算法。小波包变换对 SAR图像进行完全分解 ,再用与后续编码器相关联的代价函数进行最佳基搜索 ,然后根据各子带小波包系数的重要性进行加权 ,采用多级树集合分裂算法 ( SPIHT)编码。实验结果表明 ,该算法更好地保留了 SAR图像的细节信息 ,获得了同压缩比下优于传统 SPIHT算法的编码性能 ,更有利于后续图像处理。     

基于JPEG2000的图像联合压缩加密算法

为实现图像的压缩和加密同步,在深入研究MQ算术编码器的基础上,将Lorenz混沌系统生成的随机序列作为流密钥对JPEG2000压缩算法中比特平面编码形成的上下文和判决进行修正,以改变MQ编码时的概率分布来使得输出的码流发生变化,从而实现图像联合压缩加密.阐述了上下文修正和判决修正加密算法的规则.对算法进行仿真,结果表明,相对于原始压缩算法,所提出的算法对图像的压缩效率几乎没有影响,且安全性好、实时性高.     

Performance study of selective encryption in comparison to full encryption for still visual images

Securing digital images is becoming an important concern in today＇s information security due to the extensive use of secure images that are either transmitted over a network or stored on disks. Image encryption is the most effective way to fulfil confidentiality and protect the privacy of images. Nevertheless, owing to the large size and complex structure of digital images, the computational overhead and processing time needed to carry out full image encryption prove to be limiting factors that inhibit it of being used more heavily in real time. To solve this problem, many recent studies use the selective encryption approach to encrypt significant parts of images with a hope to reduce the eneryption overhead. However, it is necessary to realistically evaluate its performance compared to full encryption. In this paper, we study the performance and efficiency of image segmentation methods used in the selective encryption approach, such as edges and face detection methods, in determining the most important parts of visual images. Experiments were performed to analyse the computational results obtained by selective image encryption compared to full image encryption using symmetric encryption algorithms. Experiment results have proven that the selective encryption approach based on edge and face detection can significantly reduce the time of encrypting still visual images as compared to full encryption. Thus, this approach can be considered a good alternative in the implementation of real-time applications that require adequate security levels.     

An enhanced one-dimensional SPIHT algorithm and its implementation for TV systems

In general, to achieve high compression efficiency, a 2D image or a 2D block is used as the compression unit. However, 2D compression requires a large memory size and long latency when input data are received in a raster scan order that is common in existing TV systems. To address this problem, a 1D compression algorithm that uses a 1D block as the compression unit is proposed. 1D set partitioning in hierarchical trees (SPIHT) is an effective compression algorithm that fits the encoded bit length to the target bit length precisely. However, the 1D SPIHT can have low compression efficiency because 1D discrete wavelet transform (DWT) cannot make use of the redundancy in the vertical direction. This paper proposes two schemes for improving compression efficiency in the 1D SPIHT. First, a hybrid coding scheme that uses different coding algorithms for the low and high frequency bands is proposed. For the low-pass band, a differential pulse code modulation–variable length coding (DPCM–VLC) is adopted, whereas a 1D SPIHT is used for the high-pass band. Second, a scheme that determines the target bit length of each block by using spatial correlation with a minimal increase in complexity is proposed. Experimental results show that the proposed algorithm improves the average peak signal to noise ratio (PSNR) by 2.97 dB compared with the conventional 1D SPIHT algorithm. With the hardware implementation, the throughputs of both encoder and decoder designs are 6.15 Gbps, and gate counts of encoder and decoder designs are 42.8 K and 57.7 K, respectively.     

Compression-unimpaired batch-image encryption combining vector quantization and index compression

As the network bandwidth has grown rapidly, it has become common to share a large number of still images via the Internet by means of batch transmission. Unfortunately, most existing methods encrypt only a single image, so there is room for improvement in our ability to send batches of images at one time. A complete reconstruction of the methods is sometimes necessary, especially when considering performance criteria. This paper presents a novel batch-image encryption algorithm that combines Vector Quantization (VQ) and additional index-compression process to benefit from their computational efficiency and low transmission bandwidth without affecting the original compression rate. The experimental results show the performance of this new scheme in terms of compression rate and computational cost.     

Data compression and encryption using cellular automata transforms

A family of basis functions, generated from the evolving states of Cellular Automata (CA), is used to compress and encrypt data. The operations required in encoding and decoding the data are described under the umbrella Cellular Automata Transforms (CAT). There is a huge number of these transform bases. CAT can be used in the way other mathematical transforms (e.g., Fourier, Discrete Cosine, Laplace, Wavelet, etc.) are utilized. In data-compression applications, the rules and pertinent keys used to generate the CA are selected to favor those that yield basis functions with the best information-packing characteristics. On the other hand, for encryption the selection is biased towards those with the tendency to yield an avalanche effect. In the latter case the transform process must be error-free.     

历史数据压缩算法在DSP上的实现

工业控制中需要记录大量的历史数据,因其数据量庞大,需要的存储空间也及其庞大,同时网络传输过程的实现比较困难,针对这一情况,提出了一种基于整数小波变换和多级树集合分割编码压缩新算法,并在DSP平台上实现,给出仿真结果,结果表明此算法可方便地控制数据压缩比和重构误差,并且具有压缩速度快、熏构误差小和压缩比高的特点。     

一种遥感图像多级感兴趣区域的压缩方法

感兴趣区域(ROI)编码技术具有在不丢失重要信息的同时又有效地压缩了数据量的特点,非常适用于遥感图像的压缩.提出一种遥感图像多级感兴趣区域的压缩方法,以边缘梯度方向为图像分割的准则,利用了遥感图像纹理信息丰富的特点,通过提取图像的边缘区域和纹理区域,得到较好的分割效果;然后采用通用部分位平面偏移方法(GPBShift)进行位平面编码,对所得数据进行SPIHT编码得到最终的压缩结果.仿真结果证明,在相同的压缩比下,可以使感兴趣区域得到更好的恢复质量.从而使全图获得更好的恢复效果,而且,恢复后图像也更符合人眼视觉特性.     

Efficient selective encryption for JPEG 2000 images using private initial table

In this paper, we propose an efficient selective encryption scheme for encrypting JPEG 2000 images. The proposed scheme uses a secret key and a mapping function to generate a private initial table to encrypt the selected DWT codeblocks in the entropy coding stage of JPEG 2000 coding scheme. Theoretical analysis and experimental results show that the proposed scheme can achieve various purposes of selective encryption and is computationally secure. Moreover, the proposed scheme does not decrease the compressibility of the standard JPEG 2000 coding scheme. The proposed selective encryption scheme is practical for applications of JPEG 2000 image protection.     

基于SPIHT的灰度图像部分加密方法

图像数据量大、冗余度高,其实时加密问题亟待解决。图像部分加密方法只加密图像压缩编码的部分重要数据,是一种可行的实时加密方案。该文研究图像压缩编码的多级树集合分裂算法,分析灰度图像SPIHT中不同类型编码数据对图像重建的作用,确定了其中的重要数据,并将其用流密码进行了加密。仿真结果表明,该方法只加密图像编码的很少部分数据,便可达到图像保密的目的。     

一种适合智能手机的JPEG压缩加密方案

智能手机日益贴近人们的生活,给人们生活带来了极大的便利,但开发者们“重体验、轻安全”的观念,使得智能手机所引发的安全问题也越来越突出。在研究图像加密方案的同时,针对智能手机平台的图像安全问题,设计了一种结合JPEG压缩编码的图像加密算法。该算法在保证图像压缩效率的前提下,实现了对图像的加密。通过实验分析发现,JPEG压缩算法在嵌入本加密方案后,压缩比损失和时间增加量均控制在20%以内,因而适合移植到智能手机平台中。     

Formal photograph compression algorithm based on object segmentation

Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize the distinctness of formal photographs. That is, the object is an image of the human head, and the background is in unicolor. Therefore, the compression is of low efficiency and the image after compression is still space-consuming. This paper presents an image compression algorithm based on object segmentation for practical high-efficiency applications. To achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. The areas of the human head and its background are compressed separately to reduce the coding redundancy of the background. Two methods, lossless image contour coding based on differential chain, and modified set partitioning in hierarchical trees （SPIHT） algorithm of arbitrary shape, are discussed in detail. The results of experiments show that when bit per pixel （bpp）is equal to 0.078, peak signal-to-noise ratio （PSNR） of reconstructed photograph will exceed the standard of SPIHT by nearly 4dB.     

一种简单误码检错多分辨率SPIHT算法

由EZW算法演变而来的SPIHT算法是目前为止影响最大的小波压缩算法之一,它通过独特的扫描方式,将小波系数按照能量大小或者重要性程度编码输出。由于引入了小波树,隐藏了扫描路径,SPIHT能获得高压缩比,同时保持较高的图像质量。而后提出的多分辨率SPIHT算法能使解码器根据信道条件,选择图像还原分辨率。然而,SPIHT对路径可靠性要求严苛,任何路径信息的传输错误都会导致剩余所有码元的解码出错。许多学者就路径码元的保护提出了不同改进,却未能从根本上提高算法的抗噪性能。为此,提出了一种改进了的SPIHT算法,该算法在保持较高信噪比和不增加码元数量的基础上,使解码器具有简单误码检错能力。     

Improving the compression and encryption of images using FPGA-based cryptosystems

Compression and encryption technologies are important to the efficient solving of network bandwidth and security issues. A novel scheme, called the Image Compression Encryption Scheme (ICES), is presented. It combines the Haar Discrete Wavelet Transform (DWT), Significance-Linked Connected Component Analysis (SLCCA), and the Advance Encryption Standard (AES). Because of above reason the ICES efficiently reduce the overall processing time. This study develops a novel hardware system to compress and encrypt an image in real-time using an image compression encryption scheme. The proposed system exploits parallel processing to increase the throughout of the cryptosystem for Internet multimedia applications to implement the ICES. Using hardware acceleration for encryption and decryption, the FPGA implementation of DWT, SLCCA and the AES algorithm can be used. Using a pipeline structure, a very high data throughput of 330 Mbit/s at a clock frequency of 40 MHz was obtained. Therefore, the ICES is secure, fast and suited to high speed network protocols such as ATM (Asynchronous Transfer Mode), FDDI (Fiber Distributed Data Interface) or Internet multimedia applications. Shih-Ching Ou is working with the Department of Electrical Engineering, National Central University as a senior professor. His research interests include computer aided design, e-learning system, and virtual reality, etc. In August 2004, he serves as Leader University Professor and Director of Research and Development, now he act as Leader University Professor and Institute of Applied Information (Chairman). He has published a number of international journal and conferences papers related to these areas. Currently, he is the chief of Bioinformatics & CAD Laboratory. Hung-Yuan Chung joined the Department of Electrical Engineering at the National Central University, Chung-li, Taiwan as an associate professor in August 1987. Since August 1992, he was promoted as professor. In addition, he is a registered professional Engineer in R. O. C. He is a life member of the CIEE and the CIE. He received the outstanding Electrical Engineer award of the Chinese Institute of Electrical Engineering in October 2003. His research and teaching interests include System Theory and Control, Adaptive Control, Fuzzy Control, Neural Network Applications, and Microcomputer-Based Control Applications. Wen-Tsai Sung is a PhD candidate at Department of Electrical Engineering, National Central University in Taiwan. His research interests include computer aided design, web-based learning system, bioinformatics and virtual reality. He has published a number of international journal and conferences papers related to these areas. He received a BS degree from the Department of Industrial Education, National Taiwan Normal University, Taiwan in 1993 and received a MS degree from the Department of Electrical Engineering, National Central University, Taiwan in 2000. He has win the dragon thesis award; master degree thesis be recognized the most outstanding academic research. The thesis entitle is: “Integrated computer graphics system in a virtual environment.” Sponsor is Acer Foundation (Acer Universal Computer Co.). Currently, he is studying PhD at the Department of Electrical Engineering, National Central University as a researcher of Bioinformatics & CAD Laboratory.