无链表SPIHT图像提升小波编码的硬件算法

为了解决小波零树编码算法中,SPIHT(分级树的集合分裂)算法占用大量存储空间的问题,给出了一种无链表SPIHT图像压缩算法.在这种算法中,小波系数按照SPIHT的顺序输入到编码器中,编码器按照NLS算法编码,小波变换采用9/7提升分解算法,量化算法为均匀标量量化,图像边界延拓采用了补零延拓方法.实验结果表明,该算法图像压缩比与JPEG2000的EBCOT(基于优化截断的嵌入式块编码)算法几乎相同,编码速度大约是后者的2倍,一幅512×512的图像仅需要17.875KB额外内存.     

基于EZW与ROI混合编码的身份照片压缩算法研究

研究了一种针对感兴趣区域的身份证照片的混合压缩算法，该算法采用小波零树编码(EZW)和感兴趣区域(ROI)编码相结合的方法对身份照片进行压缩．仿真结果表明文中的压缩方法对身份照片进行压缩所获得的压缩质量和视觉效果要优于用普通的EZW编码对身份照片进行压缩效果，特别是面部区域的视觉质量得到了较大的提高．     

基于小波变换与分形相结合的图像压缩

研究小波变换与分形压缩相结合的图像压缩方法,即对小波变换的低频系数编码运用分形图像压缩算法,对高频系数进行零树编码,这样可以解决零树编码没有考虑最低频子带图像能量高特点的问题,同时减少分形压缩在图像恢复时方块效应带来的影响.     

面向并行安全网关流水线模型的无锁队列算法

提出一种适用于并行安全网关流水线模型中共享数据缓冲区操作的无锁队列算法．与其他类似算法比较,该算法采用链表结构组织队列数据,避免了采用循环数组结构引起的缓冲区长度限制和内存浪费的问题;与通用的链表队列无锁算法比较,算法实现更为简洁,执行效率更高．证明了算法具有线性化和非阻塞特性．通过模拟试验,验证了算法在理想环境和各种实际应用环境中都具有较好的性能指标．     

提升高精度图像弱目标视觉质量的高效压缩算法

为了实现对高精度图像进行高效压缩,同时确保重建图像的弱目标区域有较好的保真效果,提出了一种提升弱目标区域质量的基于误差优化编码的高精度图像压缩算法. 首先,使用JPEG-LS （joint photographic experts group lossless）压缩算法对图像数据进行压缩,在游程编码过程中自适应地选择需要二次编码的误差数据,并完成了基于视觉质量的非均匀量化;其次,对量化值进行数据分解,去除量化值之间的相关性,并对分解后的数据进行MQ算术编码的熵编码;图像重建时根据量化间隔重建反量化值,并设计了反量化优化和滤波优化过程;最后,将本文算法与JPEG-LS、JPEG2000 （joint photographic experts group 2000）算法进行了性能比较,结果表明:本算法能够实现高精度图像数据的高效压缩,且复杂度低,易于硬件实现,虽然引入了误差数据二次优化编码等过程,但增加编码的数据量较小,故与JPEG-LS算法的压缩速度相当,然而比JPEG2000算法的压缩速度提升4.47倍;同时有效减少了常规算法造成的信息损失,重建图像的峰值信噪比与JPEG-LS、JPEG2000相当或略低,但弱目标区域的视觉质量及保真效果更好.      

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针对应用卡尔曼滤波器进行车辆GPS导航信号的动态滤波时难以建立精确的数学模型以及传统小波变换在实时性方面存在不足,提出了基于提升小波变换的GPS动态滤波新算法.该算法采用提升小波变换对车辆GPS导航信号进行分解;用3σ准则和多项式插值方法对各层提升小波变换系数进行粗差探测与数据修复;采用模平方软阈值去噪算法对各层提升小波变换系数进行去噪;最后进行提升小波逆变换,从而实现车辆GPS导航信号的动态滤波。仿真实验结果表明,该算法的导航定位精度优于卡尔曼滤波算法;虽然在导航定位精度方面稍比传统小波变换算法的性能高,但比传统小波变换算法速度快一倍;显然该算法对车辆GPS导航系统是有效的.     

基于视觉显著性的视频差错掩盖算法

为了避免在差错掩盖过程中由于不当的替代块选择而引入新的可察觉失真,将视觉显著性与差错掩盖算法相结合,提出了一种基于视觉显著性的视频差错掩盖算法. 首先使用显著图检测算法将原始视频的每帧图像分为感兴趣区域和非感兴趣区域,接下来在解码端利用视频序列的显著性分布信息进行差错掩盖,保证候选替代块的选择范围被限制在与原始单元具有相似视觉显著性分布水平的区域内;其次在非感兴趣区域受损单元的掩盖算法中引入显著性降低操作算子,通过算子循环迭代来降低其替代块的强度和颜色对比度,使得掩盖后的图像区域既能保持较好的匹配性又具有低显著性;最后利用快速非局部均值去噪算法,对完成差错掩盖操作的视频序列进行去噪处理,以提高视频序列的整体视觉质量. 实验结果表明:在3%、5%、10%丢包率下,相对于传统的边界匹配算法,该算法掩盖后的序列的客观质量具有0.79～1.66 dB的提升;相对于解码端运动估计算法,该算法掩盖后的序列的客观质量具有0.39～1.55 dB的提升;在掩盖完成后使用非局部均值去噪算法,视频序列的客观质量有0.05～0.51 dB的提升.      

多层感知器自监督在线修正的道路识别算法

为解决自主移动机器人非结构化道路识别检测准确性、鲁棒性及实时性的问题,提出一种基于感兴趣区域(Region of Interest,ROI)与多层感知器(Multi-Layer Perceptron,MLP)为核心的自监督在线修正算法.首先,通过ROI算法规定被处理图像的有效计算区域;其次,利用多层感知器对样本数据进行训练,将感兴趣区域按相应特征实现分类处理,并对分类区域进行形态学处理及特征提取处理,筛选出有效的行驶区域;最后,通过自监督在线修正算法替换错误处理结果,进一步保障道路分类识别的准确性.实验结果表明,改进算法能准确地识别出环境中的道路区域,具有良好的实时性与可靠性.     

基于离散小波变换和人类视觉系统的数字水印算法

通过对人类视觉系统(HVS)的亮度特性、频域特性、图像类型特性的研究,提出一种基于离散小波变换和人类视觉系统数字水印算法,将秘密信息嵌入到小波变换不同的方位系数中.实现了水印信号在图像信息中的嵌入与提取,达到隐藏秘密信息的目的.实践证明该算法能提高水印的不可见性,同时具有很强的鲁棒性.     

多层感知器自监督在线修正的道路识别算法

为解决自主移动机器人非结构化道路识别检测准确性、鲁棒性及实时性的问题，提出一种基于感兴趣区域(Region of Interest，ROI)与多层感知器(Multi-Layer Perceptron，MLP)为核心的自监督在线修正算法.首先，通过ROI算法规定被处理图像的有效计算区域；其次，利用多层感知器对样本数据进行训练，将感兴趣区域按相应特征实现分类处理，并对分类区域进行形态学处理及特征提取处理，筛选出有效的行驶区域；最后，通过自监督在线修正算法替换错误处理结果，进一步保障道路分类识别的准确性.实验结果表明，改进算法能准确地识别出环境中的道路区域，具有良好的实时性与可靠性.     

A New Region-of-interest Coding Method to Control the Relative Quality of Progressive Decoded Images

Based on the ideas of controlling relative quality and rearranging bitplanes, a new ROI coding method for JPEG2000 was proposed, which shifts and rearranges bitplanes in units of bitplane groups. It can code arbitrary shaped ROI without shape coding, and reserve almost arbitrary percent of background information. It also can control the relative quality of progressive decoded images. In addition, it is easy to be implemented and has low computational cost.     

Region of interest based selective encryption scheme for privacy protection in H.264 video

A selective encryption scheme for region of interest （ROI） of H.264 video is proposed to protect the personal privacy in a video. The most important part of video can be protected with less cost and operation by only encrypting the content of ROIs. Human face regions are selected as ROI and detected by using Gaussian skin color model. Independent ROI encoding is realized with the mechanism of flexible macro-block ordering （FMO）. Frames are divided into grid-like slice-groups which can be combined flexibly to form a required ROI. Both luminance component and chrominance component of the macro-blocks in ROI are modified to achieve good encryption quality and location accuracy. In the process of decryption, the encrypted area is located automatically. There is no need to transmit additional position information of ROIs to the end of decryption. The encrypted video is decrypted correctly with the secret key. JM18.4 software is employed to perform the simulation experiment. Experimental results show the accuracy and effectiveness of our scheme to encrypt and decrypt the ROIs in H.264 video.     

A POCS-Based Algorithm for Blocking Artifacts Reduction

Introduction Block-based discrete cosine transform(BDCT) is considered to be a basic tool in bothstill and moving image compression standards,such as JPEG, H.261/263, and MPEG, owing toits near-optimal energy compaction property andmoderate hardware complexity. However, sinceeach N×N block is coded independently, the re-constructed images would exhibit annoying discon-tinuities along block boundaries at low bit rate,which are often referred to as the“blocking arti-facts”in the transfo…     

A rate-distortion based quantization level adjustment algorithm in block-based video compression

In this paper, a rate-distortion based quantization level adjustment (RDQLA) algorithm is presented. Based on the rate-distortion criterion, the quantization level adjustment algorithm effectively improves coding efficiency by adaptively optimizing quantization levels of the signals near the boundaries of quantization cells and adjusting quantization levels per block. In addition, it has no overhead and is fully compatible with the existing compression standards. The proposed algorithm can be applied in any block based image and video coding method. In particular, the algorithm has been verified on the platform of H.264. Experimental results show that the proposed algorithm improves objective and subjective performances substantially. It is shown that the proposed algorithm has a gain of several dB comparing with the newest H.264 standard for high bit rates. Foundation item: the Special Foundation of Outstanding Young Teacher of Shanghai     

An Iterative Power Allocation Algorithm for Group-wise Space-Time Block Coding Systems

An iterative transmit power allocation (PA) algorithm was proposed for group-wise space-time block coding (G-STBC) systems with group-wise successive interference cancellation (GSIC) receivers. Group-wise interference suppression (GIS) filters are employed to separate each group's transmit signals from other interferences and noise. While the total power on all transmit symbols is constrained, all transmit PA coefficients are updated jointly according to the channel information at each iteration. Through PA, each detection symbol has the same post-detection signal to interference-and-noise ratio (SINR). The simulation results verify that the proposed PA algorithm converges at the equilibrium quickly after few iterations, and it achieves much lower bit error rates than the previous single symbol SIC PA and the fixed ratio PA algorithms for G-STBC systems with GSIC receivers .     

Infrared and visible image fusion based on region of interest detection and nonsubsampled contourlet transform

In order to enhance the contrast of the fused image and reduce the loss of fine details in the process of image fusion,a novel fusion algorithm of infrared and visible images is proposed.First of all,regions of interest(RoIs)are detected in two original images by using saliency map.Then,nonsubsampled contourlet transform(NSCT)on both the infrared image and the visible image is performed to get a low-frequency sub-band and a certain amount of high-frequency sub-bands.Subsequently,the coefcients of all sub-bands are classified into four categories based on the result of RoI detection:the region of interest in the low-frequency sub-band(LSRoI),the region of interest in the high-frequency sub-band(HSRoI),the region of non-interest in the low-frequency sub-band(LSNRoI)and the region of non-interest in the high-frequency sub-band(HSNRoI).Fusion rules are customized for each kind of coefcients and fused image is achieved by performing the inverse NSCT to the fused coefcients.Experimental results show that the fusion scheme proposed in this paper achieves better efect than the other fusion algorithms both in visual efect and quantitative metrics.