目的:通过分析宝石光谱成像(GSI)模式下获取的虚拟单色图像的特性,初步评估将其应用于放射治疗计划剂量计算的可行性。方法:采用GE公司的Revolution ES CT扫描系统对CIRS 062M电子密度模体进行扫描;对比不同能量下不同物质的CT测量值与...目的:通过分析宝石光谱成像(GSI)模式下获取的虚拟单色图像的特性,初步评估将其应用于放射治疗计划剂量计算的可行性。方法:采用GE公司的Revolution ES CT扫描系统对CIRS 062M电子密度模体进行扫描;对比不同能量下不同物质的CT测量值与理论值之间的差异;比较间隔26 d的两次扫描CT值;建立单色图像的CT到电子密度(ED)转换曲线。结果:在两次扫描中,不同单色能量下,高密度材料的CT值变化显著,密度小于或等于水的材料的CT值变化较小;较高密度材料(如Dense Bone 800)的CT理论计算值和实测值之间的差异在较低能量时较大;较高能量虚拟单色CT图像的CT-ED转换曲线与普通模式下获得的多色图像一样具有一致的线性关系;但较低能量虚拟单色CT图像的CT-ED转换曲线是双线性。结论:双线性的CT-ED转换曲线可能会带来剂量计算误差,所以将其应用于临床剂量计算时必须选择正确的能量相关CT-ED转换关系。展开更多
遥感图像在成像过程中,容易受到云层和雾霾天气的影响,形成带雾图像;同时在下传时,会受到多种因素影响(如发送接收误码、电离层和对流层的随机变化对信号形成扰动等),使图像信息丢失或掺杂噪声。本文针对信息丢失的带雾单色遥感图像,提...遥感图像在成像过程中,容易受到云层和雾霾天气的影响,形成带雾图像;同时在下传时,会受到多种因素影响(如发送接收误码、电离层和对流层的随机变化对信号形成扰动等),使图像信息丢失或掺杂噪声。本文针对信息丢失的带雾单色遥感图像,提出了基于矩阵复原和暗通道理论的单色遥感图像去雾算法,通过基于交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)的矩阵复原算法与传统暗通道理论相结合,有效实现了信息丢失下的遥感雾图复原。通过主观评价和客观评价相结合的方式,将本文算法与经典算法对比。结果表明,本文算法得到的结果在直观视觉上效果更好,且相对于信息丢失30%的雾图,6个场景的平均信息熵提升1.6652,平均峰值信噪比提升11.7029,平均结构相似性提升0.8146,客观评价指标结果优异。进一步在不同比例信息丢失情况下进行实验,结果表明,即使在信息大量丢失的情况下,依然能够得到清晰的复原去雾图像。展开更多
Machine vision has been recently utilized for quality control of food and agricultural products, which was traditionally done by manual inspection. The present study was an attempt for automatic defect detection and s...Machine vision has been recently utilized for quality control of food and agricultural products, which was traditionally done by manual inspection. The present study was an attempt for automatic defect detection and sorting of some single-color fruits such as banana and plum. Fruit images were captured using a color digital camera with capturing direction of zero degree and under illuminant D65. It was observed that growing decay and time-aging made surface color changes in bruised parts of the object. 3D RGB and HSV color vectors as well as a single channel like H （hue）, S （saturation）, V （value） and grey scale images were applied for color quantization of the object. Results showed that there was a distinct threshold in the histogram of the S channel of images which can be applied to separate the object from its background. Moreover, the color change via the defect and time-aging is correctly distinguishable in the hue channel image. The effect of illumination, gloss and shadow of 3D image processing is less noticeable for hue data in comparison to saturation and value. The value of H channel was quantized to five groups based on the difference between each pixel value and the H value of a healthy object. The percentage of different degree of defects can be computed and used for grading the fruits.展开更多
文摘目的:通过分析宝石光谱成像(GSI)模式下获取的虚拟单色图像的特性,初步评估将其应用于放射治疗计划剂量计算的可行性。方法:采用GE公司的Revolution ES CT扫描系统对CIRS 062M电子密度模体进行扫描;对比不同能量下不同物质的CT测量值与理论值之间的差异;比较间隔26 d的两次扫描CT值;建立单色图像的CT到电子密度(ED)转换曲线。结果:在两次扫描中,不同单色能量下,高密度材料的CT值变化显著,密度小于或等于水的材料的CT值变化较小;较高密度材料(如Dense Bone 800)的CT理论计算值和实测值之间的差异在较低能量时较大;较高能量虚拟单色CT图像的CT-ED转换曲线与普通模式下获得的多色图像一样具有一致的线性关系;但较低能量虚拟单色CT图像的CT-ED转换曲线是双线性。结论:双线性的CT-ED转换曲线可能会带来剂量计算误差,所以将其应用于临床剂量计算时必须选择正确的能量相关CT-ED转换关系。
文摘遥感图像在成像过程中,容易受到云层和雾霾天气的影响,形成带雾图像;同时在下传时,会受到多种因素影响(如发送接收误码、电离层和对流层的随机变化对信号形成扰动等),使图像信息丢失或掺杂噪声。本文针对信息丢失的带雾单色遥感图像,提出了基于矩阵复原和暗通道理论的单色遥感图像去雾算法,通过基于交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)的矩阵复原算法与传统暗通道理论相结合,有效实现了信息丢失下的遥感雾图复原。通过主观评价和客观评价相结合的方式,将本文算法与经典算法对比。结果表明,本文算法得到的结果在直观视觉上效果更好,且相对于信息丢失30%的雾图,6个场景的平均信息熵提升1.6652,平均峰值信噪比提升11.7029,平均结构相似性提升0.8146,客观评价指标结果优异。进一步在不同比例信息丢失情况下进行实验,结果表明,即使在信息大量丢失的情况下,依然能够得到清晰的复原去雾图像。
文摘Machine vision has been recently utilized for quality control of food and agricultural products, which was traditionally done by manual inspection. The present study was an attempt for automatic defect detection and sorting of some single-color fruits such as banana and plum. Fruit images were captured using a color digital camera with capturing direction of zero degree and under illuminant D65. It was observed that growing decay and time-aging made surface color changes in bruised parts of the object. 3D RGB and HSV color vectors as well as a single channel like H （hue）, S （saturation）, V （value） and grey scale images were applied for color quantization of the object. Results showed that there was a distinct threshold in the histogram of the S channel of images which can be applied to separate the object from its background. Moreover, the color change via the defect and time-aging is correctly distinguishable in the hue channel image. The effect of illumination, gloss and shadow of 3D image processing is less noticeable for hue data in comparison to saturation and value. The value of H channel was quantized to five groups based on the difference between each pixel value and the H value of a healthy object. The percentage of different degree of defects can be computed and used for grading the fruits.
