Colour Reproduction Theory and Separation Filters

Comparison of recent views on colour reproduction theory with its now clossical aspects shows that theoretically deduced filter requirements are not necessarily of absolute validity. Empirical filter determinations are discussed and examples of the effects of filter set variations are given in some practically occuring instances of process reproduction.     

JPEG-LS近无损图像编码器VLSI结构设计

标准JPEG-LS图像压缩算法性能优越、算法复杂度低,因而被广泛应用于空间通信、医疗等领域.但是,该算法工作在近无损压缩模式时,计算当前像素的预测值需要使用前一像素的重建值,而重建值需要复杂运算才能得到,导致编码器存在大延时的反馈电路,这给编码器的高速硬件实现带来困难.在对JPEGLS算法的深入研究的基础上,采用重建值的前向预测方法,提出一种全新的JPEG-LS近无损图像编码器超大规模集成电路结构,能够有效避免编码过程中的反馈延时.与现有方案相比,提出的超大规模集成电路结构具有编码速率高、不需要片外缓存、系统功耗低等优点,适用于资源受限的星载图像压缩.     

基于纹理特征的医学彩色图像无损压缩法

彩色图像的压缩要兼顾效率及质量方面的指标。医学图像具有纹理特征较明显的特点,在此基础上提出了一种新的基于图像纹理特征预测技术的图像压缩方法。该算法与JPEG-LS标准完全兼容,通过纹理特征预测模型,实现图像信息冗余量的最佳去除;同时该算法沿袭了JPEG-LS低复杂度的特点,具有较高的执行效率,适用于实时的医学图像数据采集系统。     

无损压缩DICOM文件解读的实现

文中主要介绍基于DICOM标准的DCM文件的解读，使其在解读后采用其它新提出的压缩标准，例如用JPEG-LS，JPEG2000进行压缩，以提高压缩比，缓解对网络带宽的要求；更有利于不同地区和国家、医院之问交换信息，进一步推动远程医疗的发展。     

星上多通道遥感图像的实时合成压缩

针对星上图像整合电路工作频率过高而造成的成像系统工作不稳定的问题,讨论了相机结构的改进,提出了一种基于现场可编程门阵列（FPGA）平台实现星上时间延迟积分CCD（TDICCD）遥感图像实时合成压缩的方法。介绍了星上多通道遥感图像实时合成压缩的原理。针对TDICCD线阵推扫成像模式的特点,使用改进的JPEG-LS压缩算法;通过自适应量化动态地控制码率,在FPGA硬件平台上实现了图像数据的实时合成压缩。试验验证结果表明,在无损压缩和2倍压缩时,系统主时钟从原来的100 MHz分别降低为80 MHz和64 MHz,整合电路的工作稳定,恢复图像的峰值信噪比（PSNR）满足大于80 dB的要求。提出算法的存储量小,处理每行的平均时间为57.5 μs,小于相机的最小行周期63 μs,满足实时性要求。本文系统可靠性高,算法稳定,实现了星上多通道时间延迟积分CCD相机内部的实时合成压缩。     

基于激光扫描的室内环境三维模型重建

精确的环境三维模型在公共服务、救援、军事侦察等领域有着重要作用,激光扫描传感器在环境三维模型重建中应用广泛。本文提出一种由pioneer3-AT移动机器人（数据采集平台）和SICKL MS200激光扫描仪（测量环境距离信息）组成的三维环境模型重建系统。利用Player／stage开放软件实现对移动机器人和激光扫描仪控制来进行激光扫描数据采集并采用JPEG-LS压缩算法对扫描数据进行压缩以提高数据传输率。在远程主机通过OpenGL技术对扫描数据进行处理以显示室内环境三维模型。实验结果表明,可得到较精确的3维环境模型。     

A vector quantization based approach for CFA data compression in wireless endoscopy capsule

A novel approach for near-lossless compression of Color Filtering Array （CFA） data in wireless endoscopy capsule is proposed in this paper. The compression method is based on pre-processing and vector quantization. First, the CFA raw data are low pass filtered and rearranged during pre-processing. Then, pairs of pixels are vector quantized into macros of 9 bits by applying block partition and index mapping in succession. These macros are entropy compressed by Joint Photographic Experts Group-Lossless Standard （JPEG-LS） finally. The complex step of codeword searching in Vector Quantization （VQ） is avoided by a predefined partition rule, which is suitable for hardware implementation. By control of the pre-processor and VQ scheme, either high quality compression under unfiltered case or high ratio compression under filtered case can be realized, with the average Peak Signal-to-Noise Ratio （PSNR） more than 43dB and 37dB respectively. Compared with the state-of-the-art method and the previously proposed method, our compression approach outperforms in compression performance as well as in flexibility.     

Dictionary-based histogram packing technique for lossless image compression

This paper proposes a dictionary-based histogram packing technique for lossless image compression. It is used to improve the performance of the state-of-the-art lossless image compression standards and methods when compressing sparse and locally sparse histogram images. The proposed method leverages inter-block correlations and similarities not only within the neighborhood but also across the entire image, thereby effectively reducing the block boundary artifacts commonly observed in block-based histogram packing techniques. To achieve this, a dictionary is employed to represent highly correlated blocks using a key that captures the union of their active symbol sets. Experimental results have demonstrated that the proposed method, when applied to sparse and locally sparse histogram images, enhances the performance of various state-of-the-art lossless image compression techniques. Notably, improvements were observed in standards and methods such as JPEG-2000, JPEG-LS, JPEG-XL, PNG, and CALIC.     

基于FPGA的近无损图像压缩实现

介绍了JPEG-LS标准的基本框架,叙述了JPEG-LS近无损图像压缩的实现过程。重点分析了JPEG-LS近无损图像压缩的硬件实现结构,成功进行了RTL逻辑描述,并进行了仿真验证。     

基于JPEG-LS帧间扩展的图像无损压缩算法

介绍了JPEG—LS帧间三维扩展的无损压缩算法，分析算法原理和性能在帧间扩展上的改进，给出了帧间编码的基本预测模板。在考虑邻域像素的相关性的基础上，采用自适应选择帧间／帧内预测与运动补偿技术实现了压缩比的提高。通过实验，对帧内压缩与帧间压缩在压缩比与运算复杂度作出了定性和定量的分析比较。