Research on Method of Engine Fault Diagnosis Based on Improved Minimum Entropy Deconvolution
In the process of 3D reconstruction of digital images,problems such as noise and distortion in the original data lead to low efficiency and accuracy of feature matching.To address this issue,a 3D digital image reconstruction method based on SIFT(Scale-Invariant Feature Transform)feature point extraction algorithm is proposed.The Bilateral filter algorithm is used to eliminate the environmental noise in the digital image,retain the edge information of the digital image,and improve the accuracy of feature point extraction.The SIFT algorithm is used to obtain feature point pairs.Using this feature point pair as the initial patch,a dense matching method for spatial object multi view images is used to achieve 3D reconstruction of digital images.The experimental results show that the proposed method has high feature matching efficiency and accuracy and strong noise reduction ability.The average time required for generating 3D reconstructed images is 26.74 ms.
万方数据
维普
