Extraction of depth dimension information from spectral image

Abstract

Conventional spectral imaging contains two-dimensional and spectral-dimensional information, but lacks spatial depthdimensional information. The light field imaging technique can acquire both intensity and direction information of the light simultaneously, so that the depth information of the target can be extracted and processed. This paper applies light field imaging technology to spectral imaging, builds a spectral light field imaging system with spectral range in the visible band and resolution of 10 nm, and proposes the theory of recovering true color images from spectral dimensional images of the same viewpoint and then performing depth estimation, and realizes an adaptive depth estimation algorithm for multiinformation fusion. The algorithm uses the correspondences information of the angular entropy representation, the scattered focus information of the color similarity constraint to obtain the initial depth and confidence level, and then fuses with the edge information to achieve the depth estimation of the scene. The experimental results show that the algorithm can solve the occlusion problem well and the edge information of the depth map is preserved intact. The theory and algorithm provide new ideas for the three-dimensional modeling of spectral images and lay an experimental foundation for the extension of spectral imaging technology to three-dimensional space and its wide application in object recognition and classification, three-dimensional display, biomedicine and other fields.