医学影像多尺度压缩传输方法的研究

医学影像数字化后需要的存储量很大且要求的精确度高,为了保证医学影像的使用质量,现在的医学影像在传输时常需采用无损压缩。但是,这样的医学影像传输方法会占用相当大的带宽,也大大降低了传输速度。提出一种对医学影像的感兴趣区域和非感兴趣区域进行多尺度压缩的方法实现有损压缩传输,获得了良好的效果,并且把实验结果与其他方法进行了对比,结果表明该方法可以有效提高压缩率,提高传输速率。     

Context based medical image compression for ultrasound images with contextual set partitioning in hierarchical trees algorithm

The basic goal of medical image compression is to reduce the bit rate and enhance the compression efficiency for the transmission and storage of the medical imagery while maintaining an acceptable diagnostic image quality. Because of the storage, transmission bandwidth, picture archiving and communication constraints and the limitations of the conventional compression methods, the medical imagery need to be compressed selectively to reduce the transmission time and storage cost along with the preservance of the high diagnostic quality. The other important reason of context based medical image compression is the high spatial resolution and contrast sensitivity requirements. In medical images, contextual region is an area which contains the most useful and important information and must be coded carefully without appreciable distortion. A novel scheme for context based coding is proposed here and yields significantly better compression rates than the general methods of JPEG and JPEG2K. In this proposed method the contextual part of the image is encoded selectively on the high priority basis with a very low compression rate (high bpp) and the background of the image is separately encoded with a low priority and a high compression rate (low bpp) and they are re-combined for the reconstruction of the image. As a result, high over all compression rates, better diagnostic image quality and improved performance parameters (CR, MSE, PSNR and CoC) are obtained. The experimental results have been compared to the scaling, Maxshift, implicit and EBCOT methods on ultrasound medical images and it is found that the proposed algorithm gives better and improved results.     

Universal noiseless and noisy data compression techniques — the state of the art

The technique of data compression demonstrates desirable properties that assure performance improvements of advanced network architectures such as ISDN, serial communication channels, data storage and data archiving. A global trend in telecommunications networks is the conversion from analogue to digital transmission. The design goal of these new networks is that voice, data, and images will be transmitted in fundamentally the same way, requiring neither prior knowledge as to the type of data being transmitted nor operator intervention. However, the bandwidth requirements for digital transmission are generally high. Spectrum bandwidth utilization is a design parameter for these systems that will benefit from the transmission of compressed data. The proposed Integrated Services Digital Network (ISDN) combines digital voice, data, and images on the same network. Since this network has limited bandwidth for transmission of information, the available bandwidth must be used as efficiently as possible.     

JPEG2000压缩率控制算法的研究

JPEG2000是一种最新的静止图象压缩标准,此标准采用了很先进的压缩技术使其在压缩性能、渐进传输和灵活性等方面都优于JPEG,并且能够提供优良的压缩率控制功能。通过对压缩率的控制,使码流可在任意位置截断,并可利用截断的码流对图像进行解码,能够很方便地实现图像质量、分辨率的渐进传输。压缩率控制算法对图像压缩质量、编码效率、存贮器占用有直接影响。该文详细阐述了两种压缩率控制算法原理,其中一种是JPEG2000建议的压缩后率失真优化PCRD算法,另一种是优先扫描率分配PSRA算法,并对两种算法在算法复杂度、存贮器消耗和压缩质量进行了比较,最后用实验数据评价了两种算法的有效性。     

多光谱影像星上压缩方法探讨

在星地数据传输信道带宽有限的情况下,为提高星载影像数据的单轨下传量,科研人员已开展卫星影像数据星上压缩方法的研究工作。区别于全色影像的压缩,多光谱或高光谱影像的星上压缩不仅需要考虑诸如JPEG等基于空间相关性的压缩算法,还需要结合如PCA等基于谱间相关性的方法,从而在数据压缩过程中保证空间和光谱两方面的信息保真度。因此,本文将回顾目前基于空间变换和谱间变换,以及基于内容的遥感影像压缩方法。进一步针对常规性监测和灾害应急监测两种需求,在考虑星上数据预处理和智能处理的基础上,提出了一种多光谱或高光谱影像星上压缩的理论框架及其对应的地面数据处理流程。最后,本文指出了多光谱或高光谱影像星上压缩研究工作中需进一步探讨的若干技术问题。     

Investigation into lossless hyperspectral image compression for satellite remote sensing

Hyperspectral sensors acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-infrared (IR), mid-IR and thermal IR portions of the spectrum, thus requiring large data storage on board the satellite and high bandwidth of the downlink transmission channel to ground stations. Image compression techniques are required to compensate for the limitations in terms of on-board storage and communication link bandwidth. In most remote-sensing applications, preservation of the original information is important and urges studies on lossless compression techniques for on-board implementation. This article first reviews hyperspectral spaceborne missions and compression techniques for hyperspectral images used on board satellites. The rest of the article investigates the suitability of the integer Karhunen–Loève transform (KLT) for lossless inter-band compression in spaceborne hyperspectral imaging payloads. Clustering and tiling strategies are employed to reduce the computational complexity of the algorithm. The integer KLT performance is evaluated through a comprehensive numerical experimentation using four airborne and four spaceborne hyperspectral datasets. In addition, an implementation of the integer KLT algorithm is ported to an embedded platform including a digital signal processor (DSP). The DSP performance results are reported and compared with the desktop implementation. The effects of clustering and tiling techniques on the compression ratio and latency are assessed for both desktop and the DSP implementation.     

Adaptive image compression technique for wireless sensor networks

When using wireless sensor networks for real-time image transmission, some critical points should be considered. These points are limited computational power, storage capability, narrow bandwidth and required energy. Therefore, efficient compression and transmission of images in wireless sensor network is considered. To address the above mentioned concerns, an efficient adaptive compression scheme that ensures a significant computational and energy reduction as well as communication with minimal degradation of the image quality is proposed. This scheme is based on wavelet image transform and distributed image compression by sharing the processing of tasks to extend the overall lifetime of the network. Simulation results are presented and they show that the proposed scheme optimizes the network lifetime, reduces significantly the amount of the required memory and minimizes the computation energy by reducing the number of arithmetic operations and memory accesses.     

Internet transmission of DICOM images with effective low bandwidth utilization

Progressive transmission of medical images through Internet has emerged as a promising protocol for teleradiology applications. The major issue that arises in teleradiology is the difficulty of transmitting large volume of medical data with relatively low bandwidth. Recent image compression techniques have increased the viability by reducing the bandwidth requirement and allowing cost-effective delivery of medical images for primary diagnosis. This paper highlights a wavelet based set partitioning in hierarchical trees (SPIHT) coder for progressive transmission of DICOM images. The header of the DICOM image is first transmitted followed by the compressed image data and then at the receiving end, images are reconstructed from low quality to high (or perfect) quality. The performance of the coder is evaluated using two image quality assessment criteria, namely, mean squared error (MSE) and mean structural similarity (MSSIM) index. The results prove that our method provides diagnostically useful information as rapidly as possible utilizing minimum bandwidth than variants of JPEG as reported in literature.     

Best parameters selection for wavelet packet-based compression of magnetic resonance images.

Transmission of compressed medical images is becoming a vital tool in telemedicine. Thus new methods are needed for efficient image compression. This study discovers the best design parameters for a data compression scheme applied to digital magnetic resonance (MR) images. The proposed technique aims at reducing the transmission cost while preserving the diagnostic information. By selecting the wavelet packet's filters, decomposition level, and subbands that are better adapted to the frequency characteristics of the image, one may achieve better image representation in the sense of lower entropy or minimal distortion. Experimental results show that the selection of the best parameters has a dramatic effect on the data compression rate of MR images. In all cases, decomposition at three or four levels with the Coiflet 5 wavelet (Coif 5) results in better compression performance than the other wavelets. Image resolution is found to have a remarkable effect on the compression rate.     

Colour volumetric compression for realistic view synthesis applications

Colour volumetric data, which is constructed from a set of multi-view images, is capable of providing realistic immersive experience. However it is not widely applicable due to its manifold increase in bandwidth. This paper presents a novel framework to achieve scalable volumetric compression. Based on wavelet transformation, data rearrangement algorithm is proposed to compact volumetric data leading to high efficiency of transformation. The colour data is rearranged using the characteristics of human visual system. A pre-processing scheme for adaptive resolution is also proposed in this paper. The low resolution overcomes the limitation of the data transmission at low bitrates, whilst the fine resolution improves the quality of the synthesised images. Results show significant improvement of the compression performance over the traditional 3D coding. Finally, effect of using residual coding is investigated in order to show a trade off between the compression and view synthesis performance.     

无线多媒体传感器网络图像通信性能分析

对无线视频传感器节点的图像通信活动进行研究,分析了其在资源受限的无线多媒体传感器网络中进行图像编码和传输的性能。对基于DCT和DWT的图像编码与传输的能量消耗和率失真进行建模分析。根据所建立的能量消耗与率失真模型,对有限的能量和传输带宽进行优化分配。根据监测场景的统计信息,调整编码中所使用的参数,以使得能量消耗最小化。仿真实验结果表明,所提出的方法在保证应用所需图像质量的情况,有效地降低了无线传感器节点的数据通信量和计算过程的能耗。     

基于分块匹配的文档图像压缩性能分析与仿真

文档图像作为图像的一种,在生活中的应用越来越广泛,然而其又不同于常规的文本文档或图像,它主要由具有特定含义的不同形状的字符串组成,其局部像素变化比较剧烈,高频分量相对丰富,采用常规的压缩方式很难获得较高的压缩率。常用的压缩方式没有考虑文档图像的特殊性,因而压缩性能有限。本文针对文档图像的特点,采用分块匹配的方法对文档图像进行压缩,即按照特定的规则对整幅图像进行分割,然后将分割的块图像进行分类并编码,从而在二维空间上消除了文档图像的相关性,获得了远高于常规无损压缩方式的压缩率。文中对分块匹配算法进行了描述,并对其性能进行了理论分析和仿真。     

易错视频传输中基于带宽-失真代价最小化准则的部分重传算法

针对视频传输系统主要关注的两个因素:传输所用的总体带宽和终端最终的解码失真,提出带宽-失真(B D)代价函数的概念,给出B-D关系定理及其证明.利用视频数据本身存在的时空相关的特点,进一步提出了基于最小化B D代价的部分重传机制.实验结果及分析表明,相对于尽力而为ARQ机制,所提出的算法有如下几个特点:(1)在保持终端接收质量基本不变的前提下,能有效减少带宽(可达20%以上);(2)在低比特率情形下性能比高比特率下的性能要好,所以更适合于低比特应用;(3)对运动平缓和纹理平滑的视频序列更为有效.     

Quadtrees, Transforms and Image Coding

Transforms and quadtrees are both methods of representing information in an image in terms of the presence of information at differing length scales. This paper presents a mathematical relationship between these two approaches to describing images in the particular case when Walsh transforms are used. Furthermore, both methods have been used for the compression of images for transmission. This paper notes that under certain circumstances, quadtree compression produces identical results to Walsh transform coding, but requires less computational effort to do so. Remarks are also made about the differences between these approaches.     

Toward practical guideline for design of image compression algorithms for biomedical applications

Improvements in medicine and healthcare are accelerating. Information generation, sharing, and expert analysis, play a great role in improving medical sciences. Big data produced by medical procedures in hospitals, laboratories, and research centers needs storage and transmission. Data compression is a critical tool that reduces the burden of storage and transmission. Medical images, in particular, require special consideration in terms of storage and transmissions. Unlike many other types of big data, medical images require lossless storage. Special purpose compression algorithms and codecs could compress variety of such images with superior performance compared to the general purpose lossless algorithms. For the medical images, many lossless algorithms have been proposed so far. A compression algorithm comprises of different stages. Before designing a special purpose compression method we need to know how much each stage contributes to the overall compression performance so we could accordingly invest time and effort in designing different stages. In order to compare and evaluate these multi-stage compression techniques and to design more efficient compression methods for big data applications, in this paper the effectiveness of each of these compression stages on the total performance of the algorithm is analyzed.     

基于OMAP的视频监控系统关键技术研究

随着监控技术的不断发展,嵌入式视频监控系统以其占用资源少、构建灵活以及很强的扩展性得到了越来越多的应用。文中以实现实时视频监控为目的,研究了视频传输中的几项关键技术。基于TI的OMAP4430平台,充分利用其多核特性,介绍了一种基于H.264的远程视频监控系统设计方案,采用H.264的视频编解码方法比MPEG系列能够提供更高的压缩率,在很大程度上增大了带宽的利用率。在此基础上,分析了RTP/RTCP协议在视频传输中的关键参数、RTP封装等几项关键技术,并最终实现了视频的实时传输。实验结果表明该方案传输性能良好,有较高的可靠性。     

HEVC快速编码深度选择算法

高效视频编码（High Efficiency Video Coding,HEVC）作为下一代新的视频编码标准,旨在有限网络带宽下传输高质量的网络视频。与现有的视频编码标准相比,高效视频编码具有更高的灵活性和压缩率。编码单元（Coding Unit,CU）是视频编码处理的基本单元,原有的算法通过四叉树递归获取最佳CU深度,在提高视频压缩性能的同时引入了较高的计算复杂度。针对该问题,提出了一种快速编码深度选择算法,该算法利用相邻CU的深度信息计算一个深度预测特征值,通过该特征值进行深度选择,以避免不必要的计算,降低计算复杂度。实验结果表明,该算法在保证视频压缩效果的同时有效降低了计算复杂度。     

基于Web的嵌入式远程监控系统的研究与实现

视频监控应用于社会生活各个领域,而远程视频监控更是研究的热点受到了极大的关注.文章采用ARM9为核心处理器,在移植Linux操作系统的基础上,搭建Web服务器,利用MJPG-streamer视频流服务器的相关功能,完成图像的采集、压缩、传输、显示.通过采用减小图像分辨率、改变像素色深、图像传输帧率和图像压缩率的方法减小数据传输时占用的带宽.解决了可能因为数据量过大而造成网络拥塞、延迟从而产生图像停顿、延时、误码等问题.最后用户可以在本地Web浏览器中实时监控远端的视频图像.     

基于单元尺度的自适应码率控制算法

随着信息技术的快速发展,压缩编码已成为多媒体存储和传输领域的研究热点。针对视频压缩的编码效率问题,ITU-T与ISO/IEC两大标准组织于2003年联手推出了H.264/AVC视频编码标准。为了能够在目标带宽上有效地传输视频,就必须合理地控制码流的波动强度,以使其尽可能地接近目标带宽。其中码率控制虽然不是标准中的一部分,但由于其一直在视频编码标准的发展过程中占有举足轻重的地位,为此,针对H.264/AVC编码的视频序列码率控制问题,在JVT-G012算法的基础上,提出了一种基于STGS图的自适应地选择基本单元大小的码率控制算法。该算法在编码时产生的码率波动总是与G012算法产生的最小码率波动相当。而且具有较小的运算复杂度,易于实时实现。