基于多尺度区间插值小波法的牛肉图像中大理石花纹分割

牛肉大理石花纹的丰富程度代表着脂肪含量的多少,是牛肉等级划分的重要指标。基于计算机图像的自动分级技术中图像的降噪和分割处理是大理石花纹提取的基础。该文利用多尺度区间插值小波解偏微分方程的方法对牛眼肌切面图像进行处理,基于中心相似变换的延拓方法有效解决边界效应。处理中自适应选取配置点,提高计算效率。试验证明,该算法不仅达到降噪目的,同时还实现了对不同对象区域的保边平滑,使图像纹理和边缘更加清晰。降噪结果与传统滤波法进行对比,峰值信噪比值平均比均值滤波高9.0 d B,比中值滤波高8.2 d B,比维纳滤波高6.6 d B,结构相似性数值平均比均值滤波高0.42,比中值滤波高0.40,比维纳滤波高0.34。与大津法相比,去噪后采用灰度进行图像分割的效果更好,既能分割出大脂肪,又能分割出小脂肪,提高了牛肉等级判定的准确度。

基于暗通道先验和区间插值小波变换的图像去雾霾方法

针对在雾霾天气条件下采集到的图像质量退化,影响现代化农业精准作业的问题,该文提出一种基于暗通道先验理论和区间插值小波变换的图像去雾新方法。该文将暗通道先验模型和区间插值小波变换相结合,期望能有效滤除雾霾信息,恢复景物颜色特征,使图像更加清晰。结果表明:经过该方法处理后,图像整体较明亮,图像的对比度和清晰度都得到提高,达到滤除图像中雾霾的效果。主观上符合人眼的观察感受,图像的层次感突出,景物细节纹理也保持较好,彩色图像的色彩饱和度被很好地保持住,图像的失真度较低,逼近景物的真实颜色。去雾效果与暗通道先验算法对比,该文算法标准差数值在R通道平均提高25.44%;G通道平均提高27.90%;B通道平均提高26.24%。因此,采用该方法可以实现图像去雾,为进一步准确获取图像信息奠定基础,适应于现代精准农业的应用。

线性插值的误差计算方法研究

文中提出了对某些函数可以准确地计算出线性插值误差的方法。在一定精度要求下,以两种常用函数(飞机磁航向和气压高度)为例算出插值区间。

三次样条在北斗卫星轨道插值中的应用

本文选用三次样条函数对北斗高轨卫星的轨道数据进行插值计算,结果表明,三次样条函数基本没有龙格现象,但插值模型中含有明显的随机性系统差,因此本文采用附加系统差的最小二乘配置,对三次样条的插值结果进行处理,使精度提高了10倍左右。

多片遥感图像的快速无缝拼接方法

针对多片遥感图像拼接过程的计算量大、结果易存在拼接缝等问题,提出了一种多片遥感图像的快速无缝拼接方法。首先,根据多片CCD器件的搭接结构确定初步重叠区域;然后,为了减少计算量,对初步重叠区域进行一维金字塔分解,利用互相关匹配方法完成多片图像的拼接,得到精确重叠区域;最后,利用区间插值映射方法对重叠区域进行直方图匹配,建立直方图查找表,对原始图像进行重新赋值,消除了多片图像之间因色调差异造成的拼接缝现象。实验结果表明:该方法切实可行,图像拼接质量较好。

水面舰船破损稳性的概率评估方法

水面舰船生命力的主要影响因素之一是舰船遭遇不同武器破坏下的薄弱性,而薄弱性主要由破损稳性决定。目前,舰船破损稳性评估主要运用确定性方法,但该方法不能全面评估舰船破损稳性。为了更加客观、全面地评估舰船破损稳性,探讨水面舰船破损稳性评估的概率方法,提出变区间线性插值计算残存概率Si的新方法并开发计算程序。以某水面舰船为例,计算各种破损情况的进水概率Pi以及残存概率Si,并累加所有破损情况Pi和Si的乘积,得到分舱指数A。研究表明:通过将分舱指数A作为评估指标并考虑不同武器和碰撞的综合破坏效应,概率方法可以实现水面舰船破损稳性定量且整体的评估,能为舰船初步设计阶段主船体的分舱优化以致提高舰船生命力提供一种解决途径。

Spatial interpolation method based on integrated RBF neural networks for estimating heavy metals in soil of a mountain region

A novel spatial interpolation method based on integrated radial basis function artificial neural networks （IRBFANNs） is proposed to provide accurate and stable predictions of heavy metals concentrations in soil at un- sampled sites in a mountain region. The IRBFANNs hybridize the advantages of the artificial neural networks and the neural networks integration approach. Three experimental projects under different sampling densities are carried out to study the performance of the proposed IRBFANNs-based interpolation method. This novel method is compared with six peer spatial interpolation methods based on the root mean square error and visual evaluation of the distribution maps of Mn elements. The experimental results show that the proposed method performs better in accuracy and stability. Moreover, the proposed method can provide more details in the spatial distribution maps than the compared interpolation methods in the cases of sparse sampling density.

Using a 3D Interval Type-2 Fuzzy Interpolation System to Improve Modeless Robots Measurement and Calibration Accuracy

This paper is an extended research for a novel technique used in the pose error compensations of the robot and manipulator calibration process based on an IT2FEI （interval type-2 fuzzy error interpolation） method. Robot calibrations can be classified into model-based and modeless methods. A model-based calibration method normally requires that the practitioners understand the kinematics of the robot therefore may pose a challenger for field engineers. An alternative yet effective means for robot calibration is to use a modeless method; however with such a method there is a conflict between the calibration accuracy of the robot and the number of grid points used in the calibration task. In this paper, an interval type-2 fuzzy interpolation system is applied to improve the compensation accuracy of the robot in its 3D workspace. An on-line type-2 fuzzy inference system is implemented to meet the needs of on-line robot trajectory planning and control. The simulated results given in this paper show that not only robot compensation accuracy can be greatly improved, but also the calibration process can be significantly simplified, and it is more suitable for practical applications.