The existing 3D imaging methods can hardly acquire both visual image and depth information of a scene using a single device and a single frame. They cannot have the merits of high efficiency, compact size, and low energy consumption at the same time. Therefore, this study proposes an innovative multispectral 3D imaging method. The method obtains depth from the defocused images, which are captured by an image capture system consisting of an optical imaging lens with longitudinal dispersion and a snapshot multispectral image sensor. Its basic principle is illustrated as follows. First, the inherent longitudinal chromatic aberration of an optical imaging system (especially the longitudinal dispersionenhanced one) makes the defocusing blurs vary with different spectral bands. Secondly, a snapshot narrowband multispectral image (SNBMSI) sensor is used to obtain multiple spectral images at each single imaging frame. Finally, the depth from defocusing algorithm is utilized to recover the 3D information from the edge gradients of multiple spectral images. Evaluation experiments are conducted using a chromatic dispersionenhanced optical imaging system and a SNBMSI camera to capture 450±10, 525±10 and 620±10 nm three spectral images to recover depth of objects that are within 5 m away from the camera. Experimental results suggest that error of depth recovery is no higher than 5 cm. The proposed multispectral 3D imaging method can realize depth estimation using a monocular and with a single frame image. The proposed method has capability of obtaining both visual and depth information without neither spatial registration nor precalibration of depth. The time of single frame 3D imaging time is about 0186 s. The size of the image capture system is 120 mm×77 mm×65 mm and the working power of the image capture system is about 10W. The advantages of the proposed method include high time efficiency, compact volume, and low energy consumption. Therefore, the proposed multispectral 3D imaging method can be widely used in unmanned driving and intelligent robots.