一种降低外存访问带宽占有率的无损压缩算法

高清、超高清视频编解码芯片结构设计中,原始图像帧和解码图像参考帧都存在外部存储器,外存访问带宽是系统设计的一大难题.通过图像压缩编码技术来降低图像冗余度,从而减小图像的存储容量和传输带宽.针对这一问题,提出了一种改进型无损图像压缩算法.与已有无损压缩算法相比,改进后算法以宏块为预测编码的基本单元,支持宏块随机访问;首先在预测部分加入块级预测与分层预测的自适应选择;然后在编码部分融入两种预测模式的半定长变长编码.实验结果表明,可降低带宽约50%.     

一种新的面向隔行视频的AVS帧内预测模式

详细介绍了AVS1-P2中的帧内预测和MBAFF技术,提出了一种新的帧内预测模式.通过分析其中的5种亮度帧内预测模式和新帧内预测模式的相关性利用度,证明该模式很好地利用了隔行视频像素的空间分布特点,与原有的预测模式相比,更好地去除了图像块之间的空间相关性.实验表明该模式可以在标清、高清隔行视频的帧内预测上获得平均0.12dB以上的信噪比增益,平均减少1.77%的码流,是一种有效提高编码效率的预测模式.     

结构相似度的立体视频错误隐藏

针对立体视频传输中右视点整帧丢失,提出了一种基于结构相似度(Structural Similarity,SSIM)的立体视频右视点整帧丢失错误隐藏算法。首先,提出了时域SSIM和视间SSIM的概念。然后,根据视频序列的时域相关性,将前一时刻右视点图像宏块的预测方式作为丢失图像宏块的预测方式。接着,将前一时刻右视点图像以宏块为单位进行时域和视间匹配,求取其以像素为单位的时域SSIM映射图和视间SSIM映射图。最后,计算并比较前一时刻右视点图像每个宏块的时域SSIM和视间SSIM值,得到每个宏块的预测方式,将其预测方式作为丢失帧中宏块的预测方式,从而使用运动补偿预测或者视差补偿预测的方法进行恢复。实验结果表明,与传统的算法和Pang的算法相比,PSNR值分别提高了2.76 dB和3.43 dB,且本文算法主观效果较好。     

一种方向延伸的快速运动搜索算法

利用图像块运动的方向特性,减小帧间编码中运动估计的运算量.该算法利用小模板钻石搜索,先确定中心检测点到最小块失真检测点为搜索方向,然后在此方向上不断延伸一个检测点进行块失真匹配,直至下一个检测点的块失真大于当前检测点的块失真.接着以当前检测点作为中心检测点,重复以上操作,直至中心检测点为最优检测点,结束搜索.搜索中利用自适应门限提前退出搜索.搜索速度比钻石搜索算法提高了20%～60%.     

根据帧间运动特性的变尺寸宏块运动估计

提出了一种新的用于视频编码的变尺寸宏块运动估计方法。该方法通过粗尺度 16×16 的当前块和邻域块运动矢量之间的差值 S 判断场景运动的复杂度,再根据差值 S 和当前矢量,决定宏块尺寸。场景运动平稳的部分采用 16×16 的宏块,复杂的部分采用 8×8 或 4×4 的宏块。实验表明,低码率条件下,采用普通运动补偿算法,该变尺寸宏块运动估计方法的预测帧的平均 PSNR 值比常规的固定尺寸块运动估计约提高 1.1-2.7 dB,并显著降低了方块效应。     

基于平滑度测量与互相关制约的图像修复算法

目的为了解决当前较多图像修复算法在对损坏区域实施填充修复时没有考虑图像块之间的相关性,导致修复图像中存在振铃以及连接间断等不足,拟设计平滑度测量因子耦合互相关制约的图像修复算法。方法将图像的Laplace算子引入到优先权的计算过程中,以增加图像的边缘信息,优化数据项的成分,并利用置信度、图像的Laplace算子和数据项构造优先权计算模型,以获取优先修复块。利用等照度线的二阶导数,构造平滑度测量因子获取图像的平滑度,并以图像的平滑度为导向,对最优匹配块的搜索区域进行定位。通过误差平方和函数(SumofSquaredDifferences,SSD)在定位的搜索区域中搜寻最优匹配块,并采用互相关系数函数对最优匹配块的唯一性进行制约,以提高所获最优匹配块的准确性。结果实验结果显示,与当前修复技术相比,所提方法具有更高的连接完整性和清晰度。结论所提方案可对损坏图像完成较好的视觉复原,在图像信息处理领域具有一定的参考价值。     

纹理的HEVC编码块尺寸决策算法

针对高效视频编码(HEVC)帧内编码算法计算复杂度高的问题,提出了一种基于纹理的HEVC编码块尺寸快速决策算法.首先,提出了编码块四个方向的纹理复杂度衡量指标,再通过训练视频序列选取在不同量化参数(QP)下的最佳阈值,最后根据阈值判断当前编码块的纹理复杂度,纹理复杂度高的编码块跳过率失真(RD)代价的计算,纹理复杂度低的编码块将会终止划分.实验结果表明,在全帧内模式配置下,与HM10.0相比较,该算法的编码时间可缩短45.3%,同时BD-Bitrate(Bjontegaard Delta Bitrate)增加了1.27%,BD-PSNR(Bjontegaard Delta Peak Signal-to-noise Rate)减少了0.058dB;与GEC-LEC算法相比,编码时间可节省3%,BD-Bitrate增加了0.5%,BD-PSNR减少了0.023dB.     

基于形态学膨胀和差分缩减的DCT域嵌入式图像压缩算法

提出了一种基于形态学膨胀操作和差分缩减的DCT域图像编码方法,该方法根据块内DCT系数的聚集特性和块间DCT系数的相似性,使用形态学膨胀算子优化DCT重要系数的编码,并对重要性检测和符号编码精心设计了上下文自适应算术模型,有效去除了块内、块间DCT的统计相关性;使用差分缩减方式对各DCT系数聚类簇的起始位置和稀疏系数进行编码,提高对不重要DCT系数的编码效率;算法还结合预处理和后处理滤波器,进一步提高编码效率的同时可有效抑制解码图像的方块效应.编码器基于位平面实现,码流具有渐进性.实验结果表明本文算法的编码性能普遍优于目前主流的图像编码器,例如在0.25 bpp下,Lena和Barbara图像的峰值信噪比分别较JPEG2000提高0.4dB和1.7dB.     

基于优先权和匹配度量的图像修复算法

目的 针对当前图像修复算法主要通过固定单一模板大小实现修复块与匹配块之间的匹配度量来完成图像复原,导致其存在一定的模糊效应以及振铃效应等不足,这里提出基于改进优先权和匹配优化度量的图像修复算法。方法 首先,利用数据项构造平滑因子,建立优先权模型,度量待修复像素点的优先权,选定优先修复块。然后,制定四级模板大小,利用误差平方和函数,结合模板大小特性,构造匹配度量模型,用于实现修复块和匹配块之间的动态匹配,选取最优匹配模板,对待修复块进行填充修复。最后,利用待修复像素点及其邻域像素点的灰度值构造邻域灰度差分模型,用于对修复区域的边缘进行缝合,优化修复效果。利用最优匹配度量结果,构造置信度更新模型,对置信度项进行更新,实现图像修复。结果 仿真实验结果显示,与当前图像修复算法相比,所提算法具有更高的修复质量,其输出图像无模糊效应与振铃效应。结论 所提算法能够较好地对损坏图像进行复原,在图像信息处理领域具有一定的参考价值。     

视频编码中基于时空信息运动估计的研究

提出了一种基于视频图像的时间和空间相关性信息的运动矢量预测方法，由于相领两帧图像中的内容应具有相关性，图像中物体的运动轨迹也具有相似性，因此可以利用前一帧图像中宏块的运动矢量确定运动轨迹，进而估计当前宏块的运动矢量，但是这种运动估计是受限的，因为估计运动矢量时的宏块顺序是逐行的按先后顺充进行，在当前帧中，当前宏块预测时只能利用具有因果关系的相邻宏块，但其与相邻宏块并非都具有因果关系，因此给出了预测矢量的资格检验方法，用以判断和剔除伪预测矢量，在搜索过程中采用菱形搜索（Pyramid)，相邻的两次搜索过程，要去除两个重叠区域，上述算法减少计算量，对Suzie序列测试结果，平均搜索次数是14－17次，并且解码图像的信噪比PSNR与FS搜索相比降级不多。     

Adaptive fractal image coding in subband domain

Abstract

In this paper, we propose and evaluate a method for fractal image coding in the subband domain. The subband decomposition scheme acts as a classifier, which can efficiently reduce encoding time. The proposed fractal image coding scheme is an adaptive one. The adaptability is based on the variance of each subband. At each subband, the scheme adaptively sets the map block size that should be encoded. In addition, the domain blocks are adaptively restricted to the neighborhood of their respective range block. Simulation results show that good picture quality of the coded image is obtained at 0.370 bpp. It also indicates that such an adaptive scheme makes a better trade‐off between the required bit rate and picture quality than a fixed size one. Moreover, the adaptive shceme can save a large amount of time.     

Bit rate reduction techniques for absolute moment block truncation coding

Abstract

Block Truncation Coding uses a two‐level moment preserving quantizer that adapts to local properties of the images. It has the features of low computation load and low memory requirement while its bit rate is only 2.0 bits per pixel. A more efficient algorithm, the absolute moment BTC (AMBTC) has been extensively used in the field of signal compression because of its simple computation and better MSE performance. We propose postprocessing methods to further reduce the entropy of two output data of AMBTC, including the bit map and two quantization data (a, b). A block of a 2×4 bit map is packaged into a byte‐oriented symbol. The entropy can be reduced from 0.965 bpp to 0.917 bpp on average for our test images. The two subimages of quantization data (a, b) are postprocessed by the Peano Scan. This postprocess can further reduce differential entropy about 0.4 bit for a 4×4 block. By applying arithmetic coding, the total bit reduction is about 0.3～0.4 bpp. The bit rate can reach 1.6～1.7 bpp with the same quality as traditional AMBTC.     

Progressive edge detection compression for fingerprint images

In this article, a progressive fingerprint image compression (for storage or transmission) that uses an edge detection scheme is developed. First, the image is decomposed into two components: the primary component, which contains the edges, and the secondary component, which contains the textures and the features. Then, a general grasp for the image is reconstructed in the first stage at bit rates of 0.0223 and 0.0245 bpp for the tested fingerprints images (samples 1 and 2), respectively. The quality of the reconstructed images is competitive with the 0.75‐bpp target bit set by the FBI standard. Also, the compression ratio and the image quality of this algorithm are competitive with other methods reported in the literature. The compression ratio for our algorithm is about 45:1 (0.180 bpp). © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol 12, 211–216, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10025     

卫星图像码率控制方法的改进

JPEG2000存在大量计算冗余和消耗较大内存资源的缺陷.为了适应实时性要求高和资源有限的卫星图像的传输,提出一种新的基于率失真斜率的卫星图像码率控制算法.本方法是根据编码块的有效位平面数大致呈下降趋势和率失真斜率的三个属性提出一个简单的公式,通过此公式求得的率失真斜率作为层1编码的门限值,丢掉小于此门限值的编码通道,然后在该值基础上层2计算最优率失真斜率和截断点以实现码率控制,因而不需要编码所有的编码通道.实验结果表明,在0.125 bpp 时,本算法的存储量约占 PCRD 存储量的33%,而信噪比保持不变.因此,本方法可以有效地提高卫星图像的编码效率.     

Variable‐rate hierarchical vector quantization with variance classification

Because the bit rate can be adjusted depending on the network traffic situation, the variable bit rate is more suitable than a fixed rate for transmitting images on the network. In this paper, a new variable rate hierarchical classified vector quantization (VHCVQ) scheme is proposed. This technique is suitable for progressive transmission. In our two‐stage VHCVQ scheme, we use the differences between the first‐stage input vectors and the first‐stage quantized vectors, called residual vectors, to code the image in the second stage. Usually the values between these differences are small and each is close to one another. Using the difference to code the image may reduce the codebook size and the bit rate as well. In our simulation, using these differences reduced the bit rate by about 0.075 bpp. © 2000 John Wiley & Sons, Inc. Int J Imaging Syst Technol 11, 138–143, 2000     

Lossless and lossy image compression using boolean function minimization

A novel approach for lossless as well as lossy compression of monochrome images using Boolean minimization is proposed. The image is split into bit planes. Each bit plane is divided into windows or blocks of variable size. Each block is transformed into a Boolean switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube based two level function minimizer. The minimized cubes are encoded using a code set which satisfies the prefix property. Our technique of lossless compression involves linear prediction as a preprocessing step and has compression ratio comparable to that of JPEG lossless compression technique. Our lossy compression technique involves reducing the number of bit planes as a preprocessing step which incurs minimal loss in the information of the image. The bit planes that remain after preprocessing are compressed using our lossless compression technique based on Boolean minimization. Qualitatively one cannot visually distinguish between the original image and the lossy image and the value of mean square error is kept low. For mean square error value close to that of JPEG lossy compression technique, our method gives better compression ratio. The compression scheme is relatively slower while the decompression time is comparable to that of JPEG.     

Colour image coding scheme using absolute moment block truncation coding and block prediction technique

Abstract

A predictive colour image compression scheme based on absolute moment block truncation coding is proposed. In this scheme, the high correlations among neighbouring image blocks are exploited by using the similar block prediction technique. In addition, the bit plane omission technique and the coding of quantisation levels are used to cut down the storage cost of smooth blocks and complex blocks respectively. According to the experimental results, the proposed scheme provides better performance than the comparative schemes based on block truncation coding. It provides better image qualities of compressed images at low bit rates. Meanwhile, it consumes very little computational cost. In other words, the proposed scheme is quite suitable for real time multimedia applications.     

基于自相似性与稀疏表示的超分辨率算法

目的为了解决当前稀疏表示的超分辨率算法效果依赖参与训练的数据的问题,结合图像的自相似性,提出一种基于自相似性与稀疏表示相结合的超分辨率算法。方法算法利用图像的多维自相似性,构建多维图像金字塔,采用改进的相似块搜索策略,得到对应的高低分辨率图像块作为训练样本,然后对样本进行字典训练,最后根据稀疏表示得到超分辨率图像。结果实验结果显示,文中算法在峰值信噪比(PSNR)和结构相似度(SSIM)上优于其他算法,对于实验图像而言,PSNR平均提升了0.5 dB。结论提出的超分辨率算法未引入外部数据库,具有较好的效果,能够用于超分辨率重建。     

一种基于小波子带熵的遥感图像压缩算法

提出了一种使用小波子带熵进行比特分配的遥感图像压缩算法.对遥感图像进行小波提升分解后,分析了各高频子带能量百分比及其熵的变化趋势,在此基础上提出了一种新的快速比特分配方法-使用子带熵进行比特分配.然后对各个高频子带进行均匀量化,量化后的数据采用比特平面编码.对最高比特平面只记录该比特平面中非零系数的坐标,其它比特平面采用行程编码和Huffman编码方法进行压缩.实验结果表明,纹理复杂以及相对平坦的遥感图像使用该算法压缩后都可以获得很好的重构图像质量,峰值信噪比均大于34dB,而压缩比则与图像的复杂程度有关.     

基于刚性运动模型的全局运动矢量探测方法

针对帧间旋转图像序列的稳定处理,提出一种新的运动矢量探测方法.首先进行多区域的块匹配,得到不同区域的局部平移运动矢量;然后利用刚性运动模型,获得包含旋转角度的全局运动矢量.与平移运动模型相比,刚性运动模型更加符合帧间运动的真实过程,因而本方法具有更好的稳像效果.航拍图像处理结果表明,帧间峰值信噪比达到29.47 dB,比基于平移运动模型的方法提高2.02 dB.