Automatic phasing of MR images. Part I: linearly varying phase

In spin-echo and well shimmed gradient-echo images, the phase of the complex image often varies linearly in both the readout and phase-encode directions. Thus, in principle, it is possible to display an image in absorption mode. However, manually determining the two first-order and one zero-order phase parameters needed to display an absorption-mode image is a formidable task. In this paper, the Bayesian calculations needed to automatically determine these parameters are presented, and the calculations are illustrated using spin-echo images.     

Image sharing scheme based on combination theory

We present a simple algorithm for sharing and hiding secret image based on combination theory. The secret image is firstly encrypted by matrix multiplications and then shared into many shadow images by multiplying binary random sampling matrices. The sampling matrices randomly assign the pixel values to the shadow images which satisfy a specific combination rule as a constrain, so that the (t, n) threshold secret sharing scheme can be implemented. Numerical experiments have demonstrated the effectiveness of this image sharing algorithm.     

多光谱成像技术诊断植物病虫害的人工神经网络模型

为了实现可靠的植物病虫害诊断,提出把人工神经网络和多光谱成像技术结合的方法,并将该方法用于常见的三种黄瓜病害的识别研究。在此基础上,实验采用窄带多光谱成像技术获取患病黄瓜叶面的14个可见光通道和近红外通道、全色通道的多光谱图像。利用BP网络对病斑样本的光谱信息进行学习分类。和14通道训练结果比较,增加850nm的近红外通道和全色通道,使网络的训练时间缩短、预测能力提高。实验结果表明,这种方法对植物进行快速、准确和非破坏性诊断提供可靠的技术支持。     

卫星干涉多光谱图像压缩新算法

根据卫星干涉多光谱图像的成像特性,提出一种基于分类权值率失真优化截取和自适应编码深度控制的部分SPIHT光谱图像压缩算法.首先根据干涉区域类型和编码平面的重要性,对各棵零树各个编码过程赋予不同的重要性权值,然后采用部分SPIHT算法对每棵零树独立编码,编码时根据比特平面层中重要系数的统计概率自适应地进行3种编码模式的选择,同时依据重要性权值和深度控制因子自适应地控制每棵零树的编码深度,最后在编码深度内,根据不同干涉区域的零树对恢复光谱的失真贡献,采用分类权值率失真方法对码流进行优化截取,使码流分配与失真达成最优.实验结果表明,本算法比传统算法更好地保护了光谱信息.