US 9,851,252 B2Granted

Compressive sensing-based multispectral video imager with double channels and imaging method

AssigneeXidian University

InventorsGuangming Shi, Lizhi Wang, Danhua Liu, Dahua Gao, Guo Li, Yang Liu

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Abstract

A compressive sensing-based multispectral video imager comprises a beamsplitter, a first light channel, a second light channel, and an image reconstruction processor; the beamsplitter is configured to divide the beam of an underlying image into a first light beam and a second light beam; the first light beam enters the first light channel, processed and sampled in the first light channel, to obtain a first mixing spectral image which is transferred to the image reconstruction processor; the second light beam enters the second light channel, processed and sampled in the second light channel, to obtain a second mixing spectral image which is transferred to the image reconstruction processor; the image reconstruction processor is configured to reconstruct the underlying spectral image based on the first mixing spectral image and the second mixing spectral image by using non-linear optimization method.

Claims5

Dependent claims

A compressive sensing-based multispectral video imager with double channels, comprising:

a beamsplitter, a first light channel, a second light channel, and an image reconstruction processor, wherein:
the beamsplitter is configured to divide the light beam of an underlying image into a first light beam and a second light beam;
wherein the first light beam enters the first light channel, and the second light beam enters the second light channel;
the first light channel is configured to process and sample the first light beam to obtain a first mixing spectral image, and transfer it to the image reconstruction processor;
the second light channel is configured to process and sample the second light beam to obtain a second mixing spectral image, and transfer it to the image reconstruction processor;
and
the image reconstruction processor is configured to reconstruct the underlying spectral image based on the first mixing spectral image and the second mixing spectral image by making use of non-linear optimization method, wherein:
the first light channel comprises a first objective lens, a first coded aperture, a first bandpass filter, a first relay lens set, a first prism set, and a first sensor array which are sequentially arranged;
the second light channel comprises a second objective lens, a second coded aperture, a second bandpass filter, a second relay lens set, a second prism set, and a second sensor array which are sequentially arranged;
the first light beam entering the first light channel is focused and imaged on the first objective lens, the first coded aperture performs random coding for beams on positions of a spectral image;
beams of the coded spectral image are filtered by the first bandpass filter, then are relayed by the first relay lens set to the first prism set to produce dispersion;
and beams of the dispersed spectral image are sensed by the first sensor array to obtain the first mixing spectral image;
and
the second light beam is focused and imaged on the second objective lens, the second coded aperture performs random coding for beams on positions of a spectral image;
beams of the coded spectral image are filtered by the second bandpass filter, then are relayed by the second relay lens set to the second prism set to produce dispersion;
and beams of the dispersed spectral image are sensed by the second sensor array to obtain the second mixing spectral image.

13 more elements

A compressive sensing-based multispectral video imaging method using double channels, comprising the following steps:

(S1) dividing a light beam of a underlying spectral image into a first light beam and a second light beam;
wherein the first light beam and the second light beam enter a first light channel and a second light channel respectively;
(S2) obtaining a first mixing spectral image (X1) by the following steps:
(S2a) focusing and imaging the first light beam in the first light channel to obtain a spectral image;
(S2b) randomly coding the spectral image, comprising random blocking the light beam at each position of the spectral image;
wherein the blocked position presents code 0, and the non-blocked position presents code 1;
(S2c) filtering the coded spectral image, to filter out a light beam of the spectral image outside the bandwidth to be reconstructed;
(S2d) shifting images of spectral dimensions of the spectral image in the direction of spatial dimension, to disperse the light beam of the spectral image and to change relative positions between all images of spectral dimension;
(S2e) obtaining, by a sensor array, the light quantity of light beam at each position of the shifted spectral image, to obtain the first mixing spectral image (X1);
(S3) obtaining a second mixing spectral image (X2) by the following steps:
(S3a) focusing and imaging the second light beam in the second light channel to obtain a spectral image;
(S3b) complementarily to the spectral image in the first light channel, coding the spectral image in the second light channel, comprising correspondingly blocking the light beam at each position of the spectral image in the second light channel, so that the blocking state of each position is complementary to that of the same position of the spectral image in the first light channel;
(S3c) filtering the light beam of the coded spectral image, to filter out a light beam outside the bandwidth to be reconstructed;
(S3d) shifting images of spectral dimensions of the spectral image in the direction of spatial dimension, to disperse the light beam of the spectral image and to change relative positions between all images of spectral dimension;
(S3e) obtaining, by a sensor array, the light quantity of light beam at each position of the shifted spectral image, to obtain the second mixing spectral image (X2);
(S4) based on the first mixing spectral image (X1) and the second mixing spectral image (X2), reconstructing the underlying spectral image (X) by using non-linear optimization method;
and
(S5) repeatedly imaging the same one scene by repeating the steps (S1) to (S4), to obtain multiple spectral images of the scene at different times, and to form the multispectral video.

15 more elements

Dependencies are inferred from the claim text.

Facts

Application: 14/407,782Filed 9 Jun 2013
Priority: CN 2012 1 019324413 Jun 2012
Published: US 2015/0153227 A14 Jun 2015
Granted: 26 Dec 2017
Term ends: Not estimatedThe source records don’t support an estimate.

Classification7 codes

G01J 3/2823
Investigating the spectrum: imaging spectrometer
G01J 3/027
Details: control of working procedures of a spectrometer; Failure detection; Bandwidth calculation
H04N 23/60
Cameras or camera modules comprising electronic image sensors; Control thereof: control of cameras or camera modules
H04N 23/95
Cameras or camera modules comprising electronic image sensors; Control thereof: computational photography systems, e.g. light-field imaging systems