CN116164841B - Spectrum reconstruction method based on calculation enhanced pixel spectroscopic imaging chip - Google Patents
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Abstract
The invention discloses a spectrum reconstruction method based on a calculation enhanced pixel spectral imaging chip, which relates to the field of spectrum imaging detectors. The spectrum reconstruction method based on the calculation enhanced pixel spectroscopic spectrum imaging chip comprises a calculation enhanced spectrum reconstruction mode and a calculation direct spectrum reconstruction mode, has high signal-to-noise ratio, wide spectrum range and high spectrum precision, and has the accuracy and precision of scientific metering level.
Description
Technical Field
The invention relates to the technical field of spectrum imaging detectors, in particular to a spectrum reconstruction method based on a calculation enhanced pixel spectral imaging chip.
Background
The optical filter for the spectrum imaging chip mainly comprises a pixel narrow-band optical filter and a pixel random optical filter, and the spectrum imaging chip based on the two optical filters has the characteristics of simple structure, small volume and small spectrum image distortion. When the spectrum imaging chip based on the two filters is used, separately, the spectrum imaging chip based on the pixel narrowband filter has the problems of low signal-to-noise ratio and narrow coverage spectrum range when the spectrum imaging chip based on the pixel narrowband filter is used because the light energy utilization rate of the pixel narrowband filter is low; in addition, when the spectrum imaging chip based on the pixel random filter is used, the broadband pixel random filter is firstly used for encoding an incident spectrum, and then an algorithm is used for multi-spectrum reconstruction, and although the spectrum imaging chip based on the pixel random filter has the advantages of high signal-to-noise ratio and wide single-chip coverage spectrum range when in use, a large amount of training data is required to achieve multi-spectrum reconstruction precision when the algorithm is used for multi-spectrum reconstruction, the data stability is insufficient, and the method reliability is reduced.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a spectrum reconstruction method based on a calculation enhanced pixel spectral imaging chip.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention relates to a calculation enhancement type pixel spectroscopic spectrum imaging chip which comprises a plurality of spectrum detection units, wherein each spectrum detection unit consists of a plurality of narrow-band optical filters and a plurality of random optical filters, and the plurality of narrow-band optical filters and the plurality of random optical filters are etched on the surface of a detector by using a photoetching process to form the spectrum detection units.
Further, each spectrum detection unit consists of 4 narrow-band filters and 12 random filters, wherein the 4 random filters are arranged in the center, and a circle of 12 narrow-band filters are arranged at the periphery of the random filters.
The invention relates to a spectrum reconstruction method based on a calculation enhanced pixel spectroscopic imaging chip, which is realized by adopting the calculation enhanced pixel spectroscopic imaging chip, and comprises the following steps of:
the original spectrum is subjected to narrow-band filter and random filter on the calculation enhanced pixel spectroscopic imaging chip
The coding acquisition is carried out, the coded light intensity is sensed by a light intensity detector, the light intensity is subjected to analog-digital conversion to obtain corresponding light intensity digital quantity, all the light intensity digital quantity is input into a spectrum reconstruction network for network training and optimization, and the spectrum reconstruction network is adjusted through optimizationNetwork parameters of the network are such that the spectrum is reconstructed +.>
Continuously approximates the original spectrum +.>
High-precision, wide-spectrum and high-signal-to-noise ratio spectrum information reconstruction is realized.
Further, the specific operation steps of the network training and optimizing are as follows:
first forward propagating to obtain a reconstructed spectrum
Calculating a loss term value and its relation to the network parameter +.>
According to which the network parameters are updated by a back propagation algorithm +.>
Repeating this process causes the loss term drop to converge and approach zero, thereby achieving optimization of the spectral reconstruction network.
Further, the network parameter optimization expression of the spectrum reconstruction network is as follows:
in the method, in the process of the invention,
for regularization factor, ++>
For network parameters +.>
Reconstructing spectrum +.>
Is a regular term; spectral reconstruction network->
The network parameter optimization expression of (2) is divided into two items,/->
Reconstruction error term, representing reconstruction spectrum +.>
Is +.>
Fitting degree of (3); />
The regular term is a network parameter constraint term for preventing spectral reconstruction network->
Overfitting with +.>
Regularizing the constraint such that ∈ ->
The two terms are added to form a penalty term, which is optimized such that the penalty term value approaches zero.
The invention relates to a spectrum reconstruction method based on a calculation enhanced pixel spectroscopic imaging chip, which is realized by adopting the calculation enhanced pixel spectroscopic imaging chip, and comprises the following steps of calculating a straight-through spectrum reconstruction mode:
the original spectrum is subjected to narrow-band filter and random filter on the calculation enhanced pixel spectroscopic imaging chip
Performing coding acquisition, namely sensing coded light intensity by a light intensity detector, and performing analog-digital conversion on the light intensity to obtain a corresponding light intensity digital quantity; inputting the light intensity digital quantity coded by the narrow-band filter into a spectrum restoration function to obtain a restored spectrum; encoding the random filterThe light intensity digital quantity of the spectrum is input into a spectrum reconstruction network to carry out network training and optimization, and the network parameters of the spectrum reconstruction network are optimally adjusted to enable the reconstructed spectrum +.>
Continuously approximates the original spectrum +.>
Finally, a high-precision recovery spectrum and a high-signal-to-noise specific gravity spectrum are obtained.
Further, the spectral restoration function is s1=g ([ I ] 1 ,I 12 ]) G is a Gaussian function.
Further, the specific operation steps of the network training and optimizing are as follows:
first forward propagating to obtain a reconstructed spectrum
Calculating a loss term value and its relation to the network parameter +.>
According to which the network parameters are updated by a back propagation algorithm +.>
Repeating this process causes the loss term drop to converge and approach zero, thereby achieving optimization of the spectral reconstruction network.
Further, the network parameter optimization expression of the spectrum reconstruction network is as follows:
in the method, in the process of the invention,
for regularization factor, ++>
For network parameters +.>
Reconstructing spectrum +.>
Is a regular term; spectral reconstruction network->
The network parameter optimization expression of (2) is divided into two items,/->
Reconstruction error term, representing reconstruction spectrum +.>
Is +.>
Fitting degree of (3); />
The regular term is a network parameter constraint term for preventing spectral reconstruction network->
Overfitting with +.>
Regularizing the constraint such that ∈ ->
The two terms are added to form a penalty term, which is optimized such that the penalty term value approaches zero.
The beneficial effects of the invention are as follows:
according to the spectrum reconstruction method based on the calculation enhanced pixel spectral imaging chip, the spectrum reconstruction is realized through designing the calculation enhanced pixel spectral imaging chip and the spectrum reconstruction mode, and the spectrum reconstruction method has high signal-to-noise ratio, wide spectrum range and high spectrum precision, and has the accuracy and precision of scientific metering level.
The spectrum reconstruction method based on the calculation enhanced pixel spectral imaging chip has two spectrum reconstruction modes, namely a calculation enhanced spectrum reconstruction mode and a calculation through spectrum reconstruction mode, and can solve the problems of low light energy utilization rate, low signal to noise ratio and narrow coverage spectrum range of the existing pixel narrowband filter-based spectrum imaging chip in use; the problems that a large amount of training data is needed to achieve the reconstruction accuracy of the multispectral spectrum, the data stability is insufficient and the reliability of the method is reduced when the spectrum imaging chip based on the pixel random filter is used can be solved.
Drawings
Fig. 1 is a schematic structural diagram of a spectrum detecting unit.
FIG. 2 is a schematic diagram of a spectral detection unit area array on a computational enhancement pixel spectral imaging chip.
Fig. 3 is a schematic diagram of a spectrum acquisition and reconstruction process in a computationally enhanced spectrum reconstruction mode.
Fig. 4 is a schematic diagram of a spectrum acquisition and reconstruction process in a calculation-through spectrum reconstruction mode.
In the figure: 1. a narrow-band filter and a random filter.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention relates to a calculation enhanced pixel spectroscopic imaging chip which mainly comprises a plurality of spectroscopic detection units, wherein the spectroscopic detection units are mainly used for imaging and spectrum acquisition, and each spectroscopic detection unit is equivalent to one pixel of an imaging spectrometer.
The structure of each spectrum detection unit is shown in fig. 1, the spectrum detection unit mainly comprises a plurality of narrowband optical filters 1 and a plurality of random optical filters 2, the narrowband optical filters 1 and the random optical filters 2 are arranged according to a certain rule, in the embodiment, a preferable arrangement mode is shown in fig. 1, but the arrangement mode is not limited to the embodiment, specifically, 4 random optical filters 2 are arranged in the center, a circle of 12 narrowband optical filters 1 are arranged at the periphery of the random optical filters, and the spectrum detection unit can be formed by etching the narrowband optical filters 1 and the random optical filters 2 on the surface of a detector by using a photoetching process during manufacturing.
After the spectrum detection units are manufactured, the spectrum detection units are scanned or repeatedly arranged or periodically copied to form a calculation enhancement type pixel spectral imaging chip with different scales, as shown in fig. 2. The manufacturing method can enable the computational enhancement type pixel spectral imaging chip to traverse the whole view field, and realize spectral image acquisition of the whole view field.
In the calculation enhanced pixel spectral imaging chip, the spectral detection unit consists of the narrow-band optical filter and the random optical filter, and the combination of the spectral structures is not limited to the mode in fig. 1, so that the calculation enhanced pixel spectral imaging chip can acquire high-precision narrow-band spectral information and high-signal-to-noise ratio broadband spectral information at the same time.
The invention discloses a spectrum reconstruction method based on a calculation enhanced pixel spectroscopic spectrum imaging chip, which mainly comprises two spectrum reconstruction modes, namely a calculation enhanced spectrum reconstruction mode and a calculation straight-through spectrum reconstruction mode, wherein the two spectrum reconstruction modes are respectively described below.
1. Computing an enhanced spectral reconstruction pattern
The process of spectrum acquisition and reconstruction in the calculation enhanced spectrum reconstruction mode is shown in fig. 3. The original spectrum S is encoded and collected by utilizing narrow-band filters (FP 1 to FP 12) and random filters (RF 1 to RF 4) on a computational enhancement type pixel spectroscopic imaging chip, and the light intensity i after being encoded is sensed by a light intensity detector 1 To i 16 Then for the light intensity i 1 To i 16 Respectively performing analog-digital conversion (ADC) to obtain corresponding light intensity digital quantity I 1 To I 16 The method comprises the steps of carrying out a first treatment on the surface of the Digital quantity I of light intensity encoded by narrowband filters (FP 1 to FP 12) and random filters (RF 1 to RF 4) 1 To I 16 Together with the input to the spectrum reconstruction network
(the spectrum reconstruction network->
The system consists of 5 layers of full-connection layers, namely an input layer, a first hidden layer, a second hidden layer, a third hidden layer, a fourth hidden layer, a fifth hidden layer and an output layer; the input size of the input layer is 16; the input size of the first hidden layer is 300, and the output size of the first hidden layer is 500; the input size of the second hidden layer is 500, and the output size of the second hidden layer is 800; the input size of the third hidden layer is 800, and the output size of the third hidden layer is 500; the input size of the output layer is 500, and the output size of the output layer is 100) is subjected to network training and optimization to obtain a reconstructed spectrum +.>
Thereby realizing high-precision, wide-spectrum and high signal-to-noise ratio spectrum information reconstruction.
The specific operation steps of the spectrum reconstruction network training and optimizing are as follows:
digital quantity of light intensity I 1 To I 16 Together with the input to the spectrum reconstruction network
The reconstructed spectrum +.>
By optimizing the tuning of the spectral reconstruction network +.>
Network parameters of (a) such that the spectrum is reconstructed +.>
Continuously approximates the original spectrum +.>
. Spectrum reconstruction network
The network parameter optimization expression of (a) is as follows:
in the method, in the process of the invention,
for regularization factor, ++>
For network parameters +.>
Reconstructing spectrum +.>
Is a regular term.
Spectrum reconstruction network
The network parameter optimization expression of (2) can be divided into two items, the former item +.>
Reconstruction error term, representing reconstruction spectrum +.>
Is +.>
Fitting degree of (3); the latter item->
The regular term is a network parameter constraint term for preventing spectral reconstruction network->
Overfitting is generally carried out using +.>
Regularizing the constraint such that ∈ ->
The two terms are added to form a penalty term, which is optimized such that the penalty term value approaches zero.
The specific optimization process comprises the following steps: first, forward propagation results in a reconstructed spectrum
Then calculates the loss term value and its corresponding network parameter +.>
According to which the network parameters are updated by a back propagation algorithm +.>
Repeating this process so that the loss term value drop converges and approaches zero, thereby realizing a spectrum reconstruction network +.>
Is described.
2. Computing through spectral reconstruction patterns
The process of spectrum acquisition and reconstruction in the calculation through spectrum reconstruction mode is shown in fig. 4, the original spectrum S is acquired by using narrowband filters (FP 1 to FP 12) and random filters (RF 1 to RF 4) on the calculation enhanced pixel spectral imaging chip, and the light intensity i after the encoding is sensed by the light intensity detector 1 To i 16 Then for the light intensity i 1 To i 16 Respectively performing analog-digital conversion (ADC) to obtain corresponding light intensity digital quantity I 1 To I 16 The method comprises the steps of carrying out a first treatment on the surface of the Light intensity digital quantity I after encoding narrow-band filters (FP 1 to FP 12) 1 To I 12 Input to spectral restoration function s1=g ([ I ] 1 ,I 12 ]) Wherein G is a Gaussian function to obtain a restored spectrum S 1 The method comprises the steps of carrying out a first treatment on the surface of the Light intensity digital quantity I after coding random filters (RF 1 to RF 4) 13 To I 16 Input to a spectral reconstruction network
Is subjected to network training and optimization to obtain a reconstructed spectrum +.>
Finally, a high-precision recovery spectrum and a high-signal-to-noise specific gravity spectrum are obtained.
The specific operation steps of the spectrum reconstruction network training and optimizing are as follows:
digital quantity of light intensity I 13 To I 16 Together with the input to the spectrum reconstruction network
The reconstructed spectrum +.>
By optimizing the tuning of the spectral reconstruction network +.>
Network parameters of (a) such that the spectrum is reconstructed +.>
Continuously approximates the original spectrum +.>
. Spectrum reconstruction network
The network parameter optimization expression of (a) is as follows:
in the method, in the process of the invention,
for regularization factor, ++>
For network parameters +.>
Reconstructing spectrum +.>
Is a regular term.
Spectrum reconstruction network
The network parameter optimization expression of (2) can be divided into two items, the former item +.>
Reconstruction error term, representing reconstruction spectrum +.>
Is +.>
Fitting degree of (3); the latter item->
The regular term is a network parameter constraint term for preventing spectral reconstruction network->
Overfitting is generally carried out using +.>
Regularizing the constraint such that ∈ ->
The two terms are added to form a penalty term, which is optimized such that the penalty term value approaches zero.
The specific optimization process comprises the following steps: first, forward propagation results in a reconstructed spectrum
Then calculates the loss term value and its corresponding network parameter +.>
According to which the network parameters are updated by a back propagation algorithm +.>
Repeating this process so that the loss term value drop converges and approaches zero, thereby realizing a spectrum reconstruction network +.>
Is described.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (9)
1. The spectrum reconstruction method based on the calculation enhancement type pixel spectroscopic imaging chip is characterized by being realized by adopting the calculation enhancement type pixel spectroscopic imaging chip, wherein the calculation enhancement type pixel spectroscopic imaging chip comprises a plurality of spectrum detection units, each spectrum detection unit consists of a plurality of narrow-band optical filters and a plurality of random optical filters, and the narrow-band optical filters and the random optical filters are etched on the surface of a detector by utilizing a photoetching process to form the spectrum detection units; the spectrum reconstruction method comprises the steps of calculating an enhanced spectrum reconstruction mode, and specifically comprises the following steps:
the method comprises the steps of utilizing a narrow-band filter and a random filter on a calculation enhancement type pixel spectroscopic spectrum imaging chip to encode and collect an original spectrum S, sensing the encoded light intensity by a light intensity detector, carrying out analog-digital conversion on the light intensity to obtain corresponding light intensity digital quantity, inputting all the light intensity digital quantity into a spectrum reconstruction network to carry out network training and optimization, and enabling the spectrum reconstruction network to carry out network parameter optimization adjustment by optimizing the spectrum reconstruction network
The method is continuously approximate to the original spectrum S, and realizes high-precision, wide-spectrum and high-signal-to-noise ratio spectrum information reconstruction.
2. The spectrum reconstruction method based on the computational enhancement pixel spectroscopic imaging chip as claimed in claim 1, wherein the specific operation steps of the network training and optimization are as follows:
first forward propagating to obtain a reconstructed spectrum
Calculating a loss term and its gradient to the network parameter omega, updating the network parameter by a back propagation algorithm based on the gradientBy ω, repeating this process causes the loss term drop to converge and approach zero, thereby achieving optimization of the spectral reconstruction network.
3. The spectrum reconstruction method based on the computational enhancement pixel spectroscopic imaging chip as claimed in claim 1, wherein the network parameter optimization expression of the spectrum reconstruction network is as follows:
in the formula, gamma is a regularization factor, omega is a network parameter,
reconstructing the spectrum, wherein R (omega) is a regularization term; spectral reconstruction network REC ω The network parameter optimization expression of (2) is divided into two items, namely S-REC ω (I)|| 2 Reconstruction error term, representing reconstruction spectrum +.>
Fitting degree with the original spectrum S; the R (omega) regularization term is a network parameter constraint term used for preventing the spectrum reconstruction network REC ω Overfitting with l 2 Regularizing constraints such that ω 2 C is more than or equal to 0 and less than or equal to C < ++), the two items are added to form a loss item, and the loss item value is optimized to be close to zero.
4. The spectrum reconstruction method based on the computational enhancement pixel spectroscopic imaging chip according to claim 1, wherein each spectrum detection unit consists of 4 narrowband filters and 12 random filters, the 4 random filters are arranged in the center, and a circle of 12 narrowband filters are arranged at the periphery of the random filters.
5. The spectrum reconstruction method based on the calculation enhancement type pixel spectroscopic imaging chip is characterized by being realized by adopting the calculation enhancement type pixel spectroscopic imaging chip, wherein the calculation enhancement type pixel spectroscopic imaging chip comprises a plurality of spectrum detection units, each spectrum detection unit consists of a plurality of narrow-band optical filters and a plurality of random optical filters, and the narrow-band optical filters and the random optical filters are etched on the surface of a detector by utilizing a photoetching process to form the spectrum detection units; the spectrum reconstruction method comprises the steps of calculating a straight-through spectrum reconstruction mode, and specifically comprises the following steps:
the original spectrum S is coded and acquired by utilizing a narrow-band filter and a random filter on a calculation enhanced pixel spectral imaging chip, the coded light intensity is sensed by a light intensity detector, and the light intensity is subjected to analog-digital conversion to obtain a corresponding light intensity digital quantity; inputting the light intensity digital quantity coded by the narrow-band filter into a spectrum restoration function to obtain a restored spectrum; inputting the light intensity digital quantity encoded by the random optical filter into a spectrum reconstruction network for network training and optimization, and optimizing and adjusting network parameters of the spectrum reconstruction network to reconstruct a spectrum
The original spectrum S is continuously approximated, and finally, a high-precision recovery spectrum and a high-signal-to-noise specific gravity spectrum are obtained.
6. The method for reconstructing a spectrum based on a computational enhancement pixel spectral imaging chip of claim 5, wherein the spectral recovery function is s1=g ([ I ] 1 ,I 12 ]) G is a Gaussian function.
7. The spectrum reconstruction method based on the computational enhancement pixel spectroscopic imaging chip as claimed in claim 5, wherein the specific operation steps of the network training and optimization are as follows:
first forward propagating to obtain a reconstructed spectrum
Calculating a loss term and its gradient to the network parameter omega, based on which the inverse is calculatedThe network parameters omega are updated to the propagation algorithm, and the process is repeated so that the loss term value is reduced and converged to be close to zero, thereby realizing the optimization of the spectrum reconstruction network.
8. The spectrum reconstruction method based on the computational enhancement pixel spectroscopic imaging chip as set forth in claim 5, wherein the network parameter optimization expression of the spectrum reconstruction network is as follows:
in the formula, gamma is a regularization factor, omega is a network parameter,
reconstructing the spectrum, wherein R (omega) is a regularization term; spectral reconstruction network REC ω The network parameter optimization expression of (2) is divided into two items, namely S-REC ω (I)|| 2 Reconstruction error term, representing reconstruction spectrum +.>
Fitting degree with the original spectrum S; the R (omega) regularization term is a network parameter constraint term used for preventing the spectrum reconstruction network REC ω Overfitting with l 2 Regularizing constraints such that ω 2 C is more than or equal to 0 and less than or equal to C < ++), the two items are added to form a loss item, and the loss item value is optimized to be close to zero.
9. The spectrum reconstruction method based on the computational enhancement pixel spectroscopic imaging chip according to claim 5, wherein each spectrum detection unit consists of 4 narrowband filters and 12 random filters, the 4 random filters are arranged in the center, and a circle of 12 narrowband filters are arranged at the periphery of the random filters.
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