本研究以VS.Net2005为开发平台,在Windows XP SP3运行环境下,运用单位面积标定物和数字图像处理技术,实现了植物叶片病斑数量和面积的自动化测量。首先利用高分辨率数码相机对含病斑的活体待测叶片和单位面积标定物进行拍照,根据预先设...本研究以VS.Net2005为开发平台,在Windows XP SP3运行环境下,运用单位面积标定物和数字图像处理技术,实现了植物叶片病斑数量和面积的自动化测量。首先利用高分辨率数码相机对含病斑的活体待测叶片和单位面积标定物进行拍照,根据预先设定获取标定物位置,并统计其像素点数量,然后利用HSV颜色分量过滤及中值滤波除噪获得叶片病斑区域块,统计病斑数量和总像素数量,通过叶病斑区域总像素数量和标定物面积换算,最终自动计算出叶片病斑总面积,效果较好。展开更多
A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV col...A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization(CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods.展开更多
文摘本研究以VS.Net2005为开发平台,在Windows XP SP3运行环境下,运用单位面积标定物和数字图像处理技术,实现了植物叶片病斑数量和面积的自动化测量。首先利用高分辨率数码相机对含病斑的活体待测叶片和单位面积标定物进行拍照,根据预先设定获取标定物位置,并统计其像素点数量,然后利用HSV颜色分量过滤及中值滤波除噪获得叶片病斑区域块,统计病斑数量和总像素数量,通过叶病斑区域总像素数量和标定物面积换算,最终自动计算出叶片病斑总面积,效果较好。
基金supported by the China Scholarship CouncilPostgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX17_0776)the Natural Science Foundation of NUPT(No.NY214039)
文摘A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization(CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods.
