The application discloses a garden
plant health state monitoring method based on
image analysis and belongs to the technical field of
image analysis and
plant health monitoring, and comprises the following steps: collecting reflection images and polarized light images of the same
plant area under multiple wave bands; calculating the
penetration depth of each
wave band in the plant medium based on a
radiation transmission model and a plant optical parameter
library; enhancing the reflection images by adopting a multi-scale
Retinex algorithm, removing the
specular reflection interference by utilizing the polarized light images, and obtaining corrected images; extracting abnormal texture areas of the corrected images, combining the
penetration depth information, and constructing a multispectral
feature fusion matrix; based on the fusion matrix, shallow normal and deep abnormal areas and areas with abnormal
layers are compared and analyzed, internal abnormal classification discrimination rules are executed, the tomographic distribution of the plant internal health state is determined, and a tomographic imaging diagram distinguishing areas by different colors is generated, so that nondestructive, non-contact and accurate detection of the internal hollow rot of the
tree trunk is realized, and the detection result is intuitive and visual.