一种基于混合整型变换和3D-SPIHT的高光谱图像嵌入式无损压缩方法

利用高光谱图像空间、谱间相关性不同的特点,本文提出了一种基于混合整型变换和三维分层树集合划分算法(3D-SPIHT)的高光谱图像无损压缩方法,首先将波段进行分组,针对每一分组,采用不同的整型变换技术去相关,然后对变换系数进行系数重组,采用高效的基于小波系数特点的3D-SPIHT编码方法得到嵌入式码流,具有一定的抗误码性能.实验结果表明,该方法能够有效的去除高光谱图像的空间和谱间相关性,与现有的国际标准JPEG-LS、JPEG2000和基于三维离散余弦变换(3D-DCT)或三维离散小波变换(3D-DWT)的编码方法相比,压缩后的平均比特率均有明显降低.     

多光谱图像的信息分析及数据压缩

首先利用条件熵对成像光谱仪多光谱图像在空间维和光谱维方向的信息冗余度进行了分析，结果表明成像光谱图像在空间维具有很强的相关性，而在光谱维方向，图像信息不平稳，相关性略小。然后对标准的基于JPEG量化表进行改进，提出了一种既能有效保真图像边缘信息，又能提高压缩倍数的改进JPEG压缩算法-I-JPEG。随后又提出了I-JPEG／DPCM压缩算法。这种方法在I-JPEG基础上，利用局部化特性较好的无损DPCM方法去除图像在光谱维的相关性，使压缩性能得到进一步提高。     

基于OpenMP的JPEG2000图像并行编码算法

JPEG2000是新一代图像压缩标准,具有编码效率高、性能好等优点,由于采用小波和比特平面编码技术,其编码复杂度高,编码速度较慢。为了提高JPEG2000的编码速度,提出一种基于OpenMP的JPEG2000图像并行编码算法,通过对离散小波变换和EBCOT算法的并行处理,提高编码速度。结果表明,该算法在保持了JPEG2000良好特性的基础上,大大提高了编码速度,而且图像越大,对编码速度的改善越明显,使JPEG2000更加适用于大数据量的图像的传输。     

Image coding using lapped biorthogonal transform

The wireless sensor network utilizes image compression algorithms like JPEG, JPEG2000, and SPIHT for image transmission with high coding efficiency. During compression, discrete cosine transform (DCT)–based JPEG has blocking artifacts at low bit-rates. But this effect is reduced by discrete wavelet transform (DWT)–based JPEG2000 and SPIHT algorithm but it possess high computational complexity. This paper proposes an efficient lapped biorthogonal transform (LBT)–based low-complexity zerotree codec (LZC), an entropy coder for image coding algorithm to achieve high compression. The LBT-LZC algorithm yields high compression, better visual quality with low computational complexity. The performance of the proposed method is compared with other popular coding schemes based on LBT, DCT and wavelet transforms. The simulation results reveal that the proposed algorithm reduces the blocking artifacts and achieves high compression. Besides, it is analyzed for noise resilience.     

基于分形和小波变换的自适应混合图像编码

待编码图像经过金字塔型离散小波变换后的系数在小波域内可以组成分层树状数据结构一个小波树，这些跨越不同分辨率的小波树之间存在一定的相似性，可以通过分形变换来描述，本文正是构造小波树的基础邮基于分形和小波变换的自适应混合图像压缩算法，实验证明，我们提出的图像压缩方法与ＪＰＥＧ相比，能够在相近的压缩比的情况下（６０：１～７０：１）使得重建图像的ＰＳＮＲ（〉２９．５ｄＢ）增加约５．４ｄＢ并且图像的主观视觉     

Preserving radiometric resolution in remotely sensed data withlossy compression

Recent advances in imaging technology make it possible to obtain remotely sensed imagery data of the Earth at high spatial, spectral, and radiometric resolutions. The rate at which the data is collected from these satellites can far exceed the channel capacity of the data downlink. Reducing the data rate to within the channel capacity can often require painful trade-offs in which certain scientific returns are sacrificed for the sake of others. The authors focus on the case where radiometric resolution is sacrificed by dropping a specified number of lower order bits (LOB) from each data pixel. To limit the number LOBs dropped, they also compress the remaining bits using lossless compression. They call this approach “truncation followed by lossless compression” or TLLC. They then demonstrate the suboptimality of this TLLC approach by comparing it with the direct application of a more effective lossy compression technique based on the JPEG algorithm. This comparison demonstrates that, for a given channel rate, the method based on JPEG lossy compression better preserves radiometric resolution than does TLLC     

基于整数小波变换的有损与无损嵌入式图像压缩

提出了基于整数小波变换的嵌入式图像编码方案，能够进行有损和无损两种模式的图像压缩，在非常低的比特率时能够获得较高质量的重构图像。该方法适合图像的渐进传输，它是使用扩增的零树信号和位面编码的合成技术，最后对产生的符号流进行算术编码。文中给出了该方法与有损和无损压缩标准的性能比较。     

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.     

Compression Quality Prediction Model for JPEG2000

A compression quality prediction model is proposed for grey images coding with JPEG2000. With this model, the compression quality (PSNR) could be estimated according to the given compression ratio (CR) and the image activity measures (IAM) without coding images. The image activity measure is the weighted sum of the IAM values based on the 1-pixel-distance and 2-pixel-distance gradients along horizontal and vertical directions. We have shown that IAM is a function of the image variance and autocorrelation coefficients. Based on Shannon's rate-distortion theorem, a theoretical justification is provided for the correlation of IAM with PSNR. Experimental results show that the prediction error is lower than 1 dB for more than 70% sample images when CR is higher than 15. The prediction error is less than 2 dB for over 90% images. This prediction performance is acceptable for general applications.      

Information loss recovery for block-based image coding techniques-afuzzy logic approach

A new technique to recover the information loss in a block-based image coding system is developed in this paper. The proposed scheme is based on fuzzy logic reasoning and can be divided into three main steps: (1) hierarchical compass interpolation/extrapolation (HCIE) in the spatial domain for initial recovery of lost blocks that mainly contain low-frequency information such as smooth background (2) coarse spectra interpretation by fuzzy logic reasoning for recovery of lost blocks that contain high-frequency information such as complex textures and fine features (3) sliding window iteration (SWI), which is performed in both spatial and spectral domains to efficiently integrate the results obtained in steps (1) and (2) such that the optimal result can be achieved in terms of surface continuity on block boundaries and a set of fuzzy inference rules. The proposed method, which is suitable for recovering both isolated and contiguous block losses, provides a new approach for error concealment of block-based image coding systems such as the JPEG coding standard and vector quantization-based coding algorithms. The principle of the proposed scheme can also be applied to block-based video compression schemes such as the H.261, MPEG, and HDTV standards. Simulation results are presented to illustrate the effectiveness of the proposed method.     

小波域含噪图像的压缩方法研究

针对含噪图像的压缩问题,分析了噪声对图像压缩的影响,介绍了在小波域同时实现去噪与压缩的重要思想。把软阈值函数和带死区的量化技术结合起来,提出了基于Bayes Shrink阈值和EZW算法的压缩方案,与EZW压缩和JPEG压缩方法进行了比较,仿真实验结果表明：在相同的压缩比下文中方法得到了更好的重建图像质量。     

一种基于人眼对比度敏感视觉特性的图像自适应量化方法

为了提高图像的压缩比和压缩质量,结合人眼对比度敏感视觉特性和图像变换域频谱特征,该文提出一种自适应量化表的构建方法。并将该表代替JPEG中的量化表,且按照JPEG的编码算法对3幅不同的彩色图像进行了压缩仿真实验验证,同时与JPEG压缩作对比分析。实验结果表明:与JPEG压缩方法相比,在相同的压缩比下,采用自适应量化压缩后,3幅解压彩色图像的SSIM和PSNR值分别平均提高了1.67%和4.96%。表明该文提出的结合人眼视觉特性的自适应量化是一种较好的、有实用价值的量化方法。     

JPEG2000全通道并行EBCOT-Tier1编码器结构设计

新一代静止图像压缩标准JPEG2000采用了EBCOT算法。该算法Tier1部分在上下文生成过程中需要对位平面进行多次通道扫描,效率很低,难以满足高质量图像实时压缩的要求。目前已有多种改进方案被相继提出,主要基于PS/GOCS和多窗口通道并行扫描。该文设计出一种适用于硬件实现的单窗口全通道并行编码结构,目前已通过FPGA验证。实验表明,该结构下Tier1编码速度明显优于现有几种优化方案。同时,本设计所采用的编码逻辑在解码过程中亦可使用,便于进行编解码复用设计。     

三维图像的任意形状ROI小波零块压缩编码算法

感兴趣区(ROI)编码是在JPEG2000中提出的一种重要的技术,然而JPEG2000算法却无法同时支持任意形状ROI和任意提升因子.本文提出了一种基于任意形状ROI和3D提升小波零块编码的3D体数据图像压缩算法.新的算法支持ROI内外从有损到无损的编码.一种简单的任意形状无损ROI掩码(Mask)生成方法被提出.考虑到3D子带的特点,我们采用改进的3DSPECK零块算法对变换后的系数进行编码.一些其它支持任意形状ROI编码的算法也在本文中被评估,试验显示本文算法具有更好的编码性能.     

A hybrid scheme for low bit-rate coding of stereo images

We propose a hybrid scheme to implement an object driven, block based algorithm to achieve low bit-rate compression of stereo image pairs. The algorithm effectively combines the simplicity and adaptability of the existing block based stereo image compression techniques with an edge/contour based object extraction technique to determine appropriate compression strategy for various areas of the right image. Unlike the existing object-based coding such as MPEG-4 developed in the video compression community, the proposed scheme does not require any additional shape coding. Instead, the arbitrary shape is reconstructed by the matching object inside the left frame, which has been encoded by standard JPEG algorithm and hence made available at the decoding end for those shapes in right frames. Yet the shape reconstruction for right objects incurs no distortion due to the unique correlation between left and right frames inside stereo image pairs and the nature of the proposed hybrid scheme. Extensive experiments carried out support that significant improvements of up to 20% in compression ratios are achieved by the proposed algorithm in comparison with the existing block-based technique, while the reconstructed image quality is maintained at a competitive level in terms of both PSNR values and visual inspections.     

基于全相位IDCT滤波器的内插重采样分层编码技术

该文提出了一种基于全相位逆离散余弦变换(APIDCT)内插滤波器的重采样分层编码技术。全相位数字滤波器(APDF)是一种新型的线性相位滤波器。该文给出了APIDCT的设计方法,并通过比较几种APDF的性能,证明APIDCT在图像内插方面性能优异。在此内插方法基础上,结合重采样和自适应算术编码形成了分层图像编码技术,这种技术算法简单,适用于空间可分级编码。实验结果表明仅用其中3层,重建图像的峰值信噪比和压缩率就可达到略优于JPEG的效果,并且压缩率高时也不会出现块效应。     

用于JPEG2000图像认证的半脆弱性数字水印算法

本文给出一种适用于JPEG2000图像认证的半脆弱性数字水印算法,该算法与JPEG2000编、解码器相结合,它根据JPEG2000图像压缩过程中的不变参量进行水印生成和嵌入调制,利用小波变换特性对图像篡改区域进行定位.实验表明,采用该算法实现的水印不仅具有良好的视觉透明性,而且还有较佳的篡改区域指示功能.     

JPEG2000标准中压缩算法原理分析

随着多媒体技术应用的不断增加,人们对图像压缩技术也提出了更高的要求,JPEG2000正是为适应不断发展的图像压缩应用而出现的新的静止图像压缩编码标准。文章从JPEG2000的目标和基本特征出发,阐述了JPEG2000图像编码采用的基本压缩算法,并对这一新标准的特点及其优缺点进行了简单介绍。     

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。     

Fractal coding of subbands with an oriented partition

We propose a new image compression scheme based on fractal coding of the coefficients of a wavelet transform, in order to take into account the self-similarity observed in each subband. The original image is first decomposed into subbands containing information in different spatial directions and at different scales, using an orthogonal wavelet-generated filter bank. Subbands are encoded using local iterated function systems (LIFS), with range and domain blocks presenting horizontal or vertical directionalities. Their sizes are defined according to the correlation lengths and resolution of each subband. The edge degradation and the blocking effects encountered at low bit-rates using conventional LIFS algorithm are reduced with this approach. The computation complexity is also greatly decreased by a 12:1 factor in comparison to fractal coding of the full resolution image. The proposed method is applied to standard test images. The comparison with other fractal coding approaches and with JPEG shows an important increase in terms of PPSNR/bit-rate. Especially for images presenting a privileged directionality, the use of adaptive partitions results in about 3 dB improvement in PPSNR. We also discuss the distorsion versus rate improvement obtained on high-frequency subbands when fractal coding instead of pyramidal vector quantization is used. Our approach achieves a real gain in PPSNR for low bit-rates between 0.3 and 1.2 bpp.