Comparison of transform coding techniques for two-dimensional arbitrarily shaped images

Envisioned advanced multimedia video services include arbitrarily shaped (AS) image segments as well as regular rectangular images. Image segments of the TV weather report produced by the chromo-key technique [1] and image segments produced by video analysis and image segmentation [2–4] are typical examples of AS image segments. This paper explores efficient intraframe transform coding techniques for general two-dimensional (2D) AS image segments, treating the traditional rectangular images as a special case. In particular, we focus on the transform coding of the partially defined image blocks along the boundary of the AS image segments. We recognize two different approaches — thebrute force transform coding approach and theshape-adaptive transform coding approach. The former fills the uncovered area with the optimal redundant data such that the resulting transform spectrum is compact. A simple but efficient mirror image extension technique is proposed. Once augmented into full image blocks, these boundary blocks can be processed by traditional block-based transform techniques like the popular discrete cosine transform (DCT). In the second approach, we change either the transform basis or the coefficient calculation process adaptively based on the shape of the AS image segment. We propose an efficientshape-projected problem formulation to reduce the dimension of the problem. Existing coding algorithms, such as the orthogonal transform by Gilge [5] and the iterative coding by Kaup and Aach [6], can be interpreted intuitively. We also propose a new adaptive transform based on the same principle as that used in deriving the DCT from the optimal Karhunen-Loeve transform (KLT). We analyze the tradeoff relationship between compression performance, computational complexity, and codec complexity for different coding schemes. Simulation results show that complicated algorithms (e.g., iterative, adaptive) can improve the quality by 5–10 dB at some computational or hardware cost. Alternatively, the simple mirror image extension technique improves the quality by 3–4 dB without any overheads. The contributions of this paper lie in efficient problem formulations, new transform coding techniques, and numerical tradeoff analyses.     

一种通用的基于MVP的图像编解码系统的硬件实现

德州仪器公司推出的ＴＭＳ３２０Ｃ８０,为需要高计算能力的算法（如视频压缩算法）提供了新的思路。本文给出一种基于Ｃ８０的硬件系统设计,也可以作为一种通用系统用于其他场合。     

数字视频编码技术在安全驾驶中的应用

将最新的数字视频编码技术与现在普遍的关注的汽车电子安全问题结合起来,对数字视频编码技术H.264进行分析,应用在汽车安全驾驶中;这种技术可以快速而准确的实时显示图像;本文对视频信号的编码速率和效果进行实时性分析,利用对司机的人眼识别,得到最新的人眼状态,以便进行对司机脸部的图像分析,判断状态,达到安全驾驶的目的。     

A computationally efficient algorithm for enhancing linear features in images

We present a computationally efficient algorithm for highlighting long linear features in images. The algorithm is based on the recursive binary decomposition of the image into subimages that have been line enhanced along different directions. After a number of successive decompositions, the subimages are recombined to yield a line enhanced image. The performance of the algorithm is similar to that of rotating-kernel-type enhancement routines. However, the new algorithm can be executed much faster, making it ideal for use on large noisy images such as those provided by synthetic aperature radar.     

全搜索算法的SSE并行优化

在基于宏块划分的视频编码算法中,运动估计阶段因为其庞大的计算量占用了绝大多数的编码时间.特别是在对高清视频进行编码时,运动估计已经成为提升编码性能的最大瓶颈.本文通过对全搜索运动估计算法进行基于像素的并行化修改和优化,使用SSE指令调用CPU的SIMD单元同时对当前宏块与参考宏块的多个像素进行SAD运算,对运动估计进行了并行化的实现.在相同的硬件环境以及保证编码质量的前提下,相对于传统的全搜索CPU运算获得了2倍以上的编码性能提升.     

基于小波变换的雾霾立体图像增强算法研究

针对立体图像在雾霾环境下的质量问题,运用小波变换的多尺度特征,提出了一种雾霾环境下的立体图像增强算法,主要用于中度污染情况下的雾霾立体图像,以提高图像资源的清晰程度。该算法将原始雾霾立体图像的深度信息与多尺度小波分解相结合,在不同尺度下分解得到的小波高频子图中设置人为操控因子,调控对比度增强的强度;锐化分解后的小波低频子图边缘来突出整体轮廓。实验从PSNR指标、视觉效果和DMOS主观评价值三个方面验证了算法的成效,该方法的增强性能均好于传统的边缘锐化和四层小波变换方法,具备很好的图像边缘增强能力,细节保护能力,且与传统小波变换有相同的算法时间复杂度。     

极低比特率的图象编码技术

介绍了几种极低比特率图象编码的基本概念、现状、存在的问题以及进一步研究的方向,并对两类典型的基于模型的图象编码和三维子波图象编码方法的特点、关键技术的实现方法、需要解决的问题进行了详细的论述,最后还从图象信号表示的角度探讨了各种极低比特率图象编码技术中存在的根本问题。     

Finding out general tendencies in speckle noise reduction in ultrasound images

This article investigates and compiles some of the techniques mostly used in the smoothing or suppression of speckle noise in ultrasound images. With this information, a comparison of all the methods studied is done based on an experiment, using quality metrics to test their performance and show the benefits each one can contribute. To test the methods, a synthetic, noise-free image of a kidney is created and later simulations using Field II program to corrupt it are performed. This way, the smoothing techniques can be compared using numeric metrics, taking the noise-free image as a reference. Since real ultrasound images are already noise corrupted images and real noise-free images do not exist, conventional metrics cannot be used to indicate the quality obtained with filtering. Nevertheless, we propose the use of the tendencies observed in our study in real images.     

Spatial-temporal joint probability images for video segmentation

Effective annotation and content-based search for videos in a digital library require a preprocessing step of detecting, locating and classifying scene transitions, i.e., temporal video segmentation. This paper proposes a novel approach—spatial-temporal joint probability image (ST-JPI) analysis for temporal video segmentation. A joint probability image (JPI) is derived from the joint probabilities of intensity values of corresponding points in two images. The ST-JPT, which is a series of JPIs derived from consecutive video frames, presents the evolution of the intensity joint probabilities in a video. The evolution in a ST-JPI during various transitions falls into one of several well-defined linear patterns. Based on the patterns in a ST-JPI, our algorithm detects and classifies video transitions effectively.Our study shows that temporal video segmentation based on ST-JPIs is distinguished from previous methods in the following way: (1) It is effective and relatively robust not only for video cuts but also for gradual transitions; (2) It classifies transitions on the basis of predefined evolution patterns of ST-JPIs during transitions; (3) It is efficient, scalable and suitable for real-time video segmentation. Theoretical analysis and experimental results of our method are presented to illustrate its efficacy and efficiency.     

Hiding secret data in images via predictive coding

This paper presents a prediction-based image-hiding scheme that embeds secret data into compression codes during image compression. This scheme employs a two-stage structure: a prediction stage and an entropy coding stage. The secret data is embedded into the difference values of a given image after the prediction stage is performed.According to the experimental results, the image quality is better than Jpeg-Jsteg and its improved scheme (Inform. Sci. 141 (1-2) (2002) 123). The average image quality of the stego-images in the proposed scheme is greater than 50 dB when the hiding capacity is 1 bit per pixel, whereas those values in Jpeg-Jsteg and scheme in Chang et al. (Inform. Sci. 141 (1-2) (2002) 123) are 37.04 and 33.73 dB, respectively. The hiding capacity of the proposed scheme is 65,536 bits when the hiding capacity is 1 bit per pixel, whereas it is 53,248 bits in scheme (Inform. Sci. 141 (1-2) (2002) 123) and less than 3000 bits in Jpeg-Jsteg.     

Segment-based coding of color images

Based on the idea of second generation image coding, a novel scheme for coding still images is presented. At first, an image was partitioned with a pulse-coupled neural network; and then an improved chain code and the 2D discrete cosine transform was adopted to encode the shape and the color of its edges respectively. To code its smooth and texture regions, an improved zero-trees strategy based on the 2nd generation wavelet was chosen. After that, the zero-tree chart was selected to rearrange quantified coefficients. And finally some regulations were given according to psychology of various users. Experiments under noiseless channels demonstrate that the proposed method performs better than those of the current one, such as JPEG, CMP, EZW and JPEG2000. Supported by the Senior University Technology Innovation Essential Project Cultivation Fund Project (Grant No. 706028) and the Natural Science Fund of Jiangsu Province (Grant No. BK2007103)     

Near lossless compression of hyperspectral images based on distributed source coding

Effective compression technique of on-board hyperspectral images has been an active topic in the field of hyperspectral remote sensintg.In order to solve the effective compression of on-board hyperspectral images,a new distributed near lossless compression algorithm based on multilevel coset codes is proposed.Due to the diverse importance of each band,a new adaptive rate allocation algorithm is proposed,which allocates rational rate for each band according to the size of weight factor defined for hyperspectral images subject to the target rate constraints.Multiband prediction is introduced for Slepian-Wolf lossless coding and an optimal quantization algorithm is presented under the correct reconstruction of Slepian-Wolf decoder,which minimizes the distortion of reconstructed hyperspectral images under the target rate.Then Slepian-Wolf encoder exploits the correlation of the quantized values to generate the final bit streams.Experimental results show that the proposed algorithm has both higher compression efficiency and lower encoder complexity than several existing classical algorithms.     

彩色图像的分割技术

图像分割是计算机早期视觉不可缺少的一步。彩色图像由于具有比灰度图像更多的视觉信息,受到了越来越多的重视。文章将彩色图像的分割技术分为6类,并分别加以介绍,分析了各种技术的优缺点。最后提及了彩色图像分割技术与彩色空间的关系。     

G-quadtree: A hierarchical representation of gray-scale digital images

We proposeG-quadtree as a hierarchical representation method for gray-scale digital images. G-quadtree is an extended quadtree each leaf of which holds a multi level-value. An algorithm constructing a G-quadtree from the array representation of a gray-scale image is described, implemented and tested. The algorithm is established in such a way that the conventional binary array-to-quadtree conversion algorithm is applied to each bit of array elements repeatedly in descending order of significance. Space efficiency analysis reveals that G-quadtree representation is sufficient in a particular application to a color coding of macroautoradiography of rat brains.     

从视频中检测人脸

视频中人脸检测的应用领域广泛,近来受到了极大关注。文中提出一种在MPEG流中检测人脸的新方法,它可以从复杂背景中有效地检测方向、大小不同的人脸,还可以处理多个人脸交叠的情况,为适应视频检索的需要,该算法依据帧间冗余性,自适应地调整肤色检测器,利用MPEG流中的运动矢量在一个GOP内跟踪人脸,依据场景的变化更新分割码本等措施,有效地提高了计算速度。用算法测试多个视频序列,实验结果令人满意。     

多模式3维视频形状编码

目的 具有立体感和高端真实感的3D视频正越来越受到学术界和产业界的关注和重视,未来在3D影视、机器视觉、远程医疗、军事航天等领域将有着广泛的应用前景。对象基3D视频是未来3D视频技术的重要发展趋势,其中高效形状编码是对象基3D视频应用中的关键问题。但现有形状编码方法主要针对图像和视频对象,面向3D视频的形状编码算法还很少。为此,基于对象基3D视频的应用需求,提出一种基于轮廓和链码表示的高效多模式3D视频形状编码方法。方法 对于给定的3D视频形状序列逐帧进行对象轮廓提取并预处理后,进行对象轮廓活动性分析,将形状图像分成帧内模式编码图像和帧间预测模式编码图像。对于帧内编码图像,基于轮廓内链码方向约束和线性特征进行高效编码。对于帧间编码图像,采用基于链码表示的轮廓基运动补偿预测、视差补偿预测、联合运动与视差补偿预测等多种模式进行编码,以充分利用视点内对象轮廓的帧间时域相关性和视点间对象轮廓的空域相关性,从而达到高效编码的目的。结果 实验仿真结果显示所提算法性能优于经典和现有的最新同类方法,压缩效率平均能提高9.3%到64.8%不等。结论 提出的多模式3D视频形状编码方法可以有效去除对象轮廓的帧间和视点间冗余,能够进行高效编码压缩,性能优于现有同类方法,可广泛应用于对象基编码、对象基检索、对象基内容分析与理解等。     

基于像素纹理分类的图像预测编码方法

JPEG-LS标准实现对静止图像的无损压缩以及近无损高保真压缩,其预测编码仅采用简单的中值边缘检测法。将充分利用邻域像素纹理的连续性与相关性,研究参考像素的选取、基于纹理信息的非线性分类预测器的构建与预测器参数的设计,增强梯度检测能力,提出新的四阶分类预测器。实验证明,该算法在低运算复杂度的前提下,有效提高了预测编码的性能。     

Analysis of textual images using the Hough transform

The analysis of images of printed pages of text is considered. Since printed text can be viewed as textured line, the use of the Hough transform for detecting straight lines is proposed as an analysis tool. Methods for handling several discretization problems that arise in mapping the rectangular image space to the (, ) accumulator array are described. Several applications of analyzing the accumulator array are proposed. They include detecting the text skew angle, determining the signature of a text line so as to accept or reject a block as containing only text, using profile analysis to segment text into lines, and determining whether a textual block is rightside-up or otherwise.