CN111356649B - Image sensor and imaging method - Google Patents
Image sensor and imaging method Download PDFInfo
- Publication number
- CN111356649B CN111356649B CN201880068674.1A CN201880068674A CN111356649B CN 111356649 B CN111356649 B CN 111356649B CN 201880068674 A CN201880068674 A CN 201880068674A CN 111356649 B CN111356649 B CN 111356649B
- Authority
- CN
- China
- Prior art keywords
- cavity
- image sensor
- pixel
- sensor array
- reflector
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000003384 imaging method Methods 0.000 title claims abstract description 13
- 238000001914 filtration Methods 0.000 claims abstract description 26
- 230000003287 optical effect Effects 0.000 claims abstract description 15
- 238000000034 method Methods 0.000 claims abstract description 8
- 238000012545 processing Methods 0.000 claims description 12
- 239000000463 material Substances 0.000 claims description 7
- 229910052782 aluminium Inorganic materials 0.000 claims description 4
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims description 4
- 230000008021 deposition Effects 0.000 claims description 4
- 229910052709 silver Inorganic materials 0.000 claims description 4
- 239000004332 silver Substances 0.000 claims description 4
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 238000005316 response function Methods 0.000 claims description 3
- 238000003786 synthesis reaction Methods 0.000 claims description 3
- 239000000523 sample Substances 0.000 claims 1
- 229910052751 metal Inorganic materials 0.000 description 10
- 239000002184 metal Substances 0.000 description 10
- 238000002834 transmittance Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 5
- 239000007769 metal material Substances 0.000 description 4
- BQCADISMDOOEFD-UHFFFAOYSA-N Silver Chemical compound [Ag] BQCADISMDOOEFD-UHFFFAOYSA-N 0.000 description 3
- 238000002310 reflectometry Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000005315 distribution function Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 239000010409 thin film Substances 0.000 description 2
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 239000010408 film Substances 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 229910044991 metal oxide Inorganic materials 0.000 description 1
- 150000004706 metal oxides Chemical class 0.000 description 1
- 150000002739 metals Chemical class 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000001579 optical reflectometry Methods 0.000 description 1
- 230000005693 optoelectronics Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
- 239000010703 silicon Substances 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B81—MICROSTRUCTURAL TECHNOLOGY
- B81B—MICROSTRUCTURAL DEVICES OR SYSTEMS, e.g. MICROMECHANICAL DEVICES
- B81B7/00—Microstructural systems; Auxiliary parts of microstructural devices or systems
- B81B7/02—Microstructural systems; Auxiliary parts of microstructural devices or systems containing distinct electrical or optical devices of particular relevance for their function, e.g. microelectro-mechanical systems [MEMS]
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L27/00—Devices consisting of a plurality of semiconductor or other solid-state components formed in or on a common substrate
- H01L27/14—Devices consisting of a plurality of semiconductor or other solid-state components formed in or on a common substrate including semiconductor components sensitive to infrared radiation, light, electromagnetic radiation of shorter wavelength or corpuscular radiation and specially adapted either for the conversion of the energy of such radiation into electrical energy or for the control of electrical energy by such radiation
- H01L27/144—Devices controlled by radiation
- H01L27/146—Imager structures
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/04—Scanning arrangements, i.e. arrangements for the displacement of active reading or reproducing elements relative to the original or reproducing medium, or vice versa
- H04N1/203—Simultaneous scanning of two or more separate pictures, e.g. two sides of the same sheet
Abstract
The embodiment of the invention discloses an image sensor, which comprises: the pixel sensor array and the F-P cavity reflection type filtering structure are positioned at the front end of the pixel sensor array; the F-P cavity reflection type optical filtering structure comprises a bottom layer reflecting mirror, an F-P cavity and a top layer reflecting mirror; the structure of the image sensor sequentially comprises a pixel sensor array, a bottom reflector, an F-P cavity and a top reflector from bottom to top; the structural properties and parameters of the F-P cavity reflective optical filtering structure can be adjusted. In addition, the embodiment of the invention also discloses a high dynamic range image imaging method. By adopting the image sensor and the imaging method, the problem of underexposure or overexposure of each wave band in the imaging process is solved, and the pixel utilization rate and the dynamic range of the photographed image are improved.
Description
Technical Field
The present invention relates to the field of image sensing technologies, and in particular, to an image sensor and an imaging method.
Background
In the prior art, based on the abundant research results of optoelectronic devices, engineers have manufactured various image sensors and corresponding signal processing systems suitable for the fields of industry, agriculture, mining and monitoring. Unlike conventional black and white or RGB sensors, multispectral sensors can use different bands of light to detect objects for more information. By adding different filtering structures in front of a conventional sensor, a plurality of narrow-band optical signals with different wave bands can be obtained, such as a filtering wheel based on a dye color filter, a liquid crystal adjustable filter (Liquid Crystal Tunable Filter, LCTF) based on a Lyot filter group and an Acousto-optic adjustable filter (Acoust-optical Tunable Filter, AOTF) based on an elasto-optic effect. However, the inventors have found that the multispectral sensor in the prior art has the problems of large volume, long overall capturing time and wide filtering bandwidth.
At present, based on the traditional Bayer RGB sensor, the trichromatic dye filter in front of the original pixel array is replaced by a reflection type filter structure formed by Fabry-Perot (F-P) cavities, and the narrow-band filtering effect of different wave bands can be obtained by changing the length of the reflection cavity. However, the inventors have found that in the prior art, since the quantum efficiency of a silicon-based Complementary Metal Oxide Semiconductor (CMOS) image sensor has significant fluctuations under different wavelength conditions, in order to ensure that the image sensor has close response to all the wavelength bands to avoid the pixel from being saturated over a large area or being lower than the noise level, it is necessary to optimize the transmittance of the filtering structure in the prior art so that the energy of each wavelength band is balanced.
Disclosure of Invention
Based on this, in order to solve the technical problem in the prior art, a special image sensor is proposed, including:
the pixel sensor array and the F-P cavity reflection type filtering structure are positioned at the front end of the pixel sensor array; the F-P cavity reflection type optical filtering structure comprises a bottom layer reflecting mirror, an F-P cavity and a top layer reflecting mirror; the structure of the image sensor is sequentially provided with a pixel sensor array, a bottom reflector, an F-P cavity and a top reflector from bottom to top; the structural properties and parameters of the F-P cavity reflective optical filtering structure can be adjusted.
In one embodiment, the adjustable structural properties and parameters include the cavity length of the F-P cavity, the cavity medium of the F-P cavity, the thicknesses of the bottom layer mirror and the top layer mirror, and the materials of the bottom layer mirror and the top layer mirror.
In one embodiment, the pixel sensor array and the F-P cavity reflective filter structure corresponding to the front end thereof are arranged according to a mosaic, wherein each pixel has a unique combination of wave band and exposure intensity.
In one embodiment, the band and the exposure intensity of each pixel point are segmented by using a balanced binary tree model.
In one embodiment, the bottom reflector and the top reflector are made of aluminum or silver.
In one embodiment, the pixel sensor array is a CMOS sensor array.
In addition, in order to solve the technical problems in the prior art, a method for imaging a high dynamic range image is specifically provided:
the method comprises the steps that firstly, a single frame image obtained by an image sensor is utilized to obtain a plurality of low-spatial resolution images under a plurality of wave bands and a plurality of exposure intensities;
secondly, carrying out high dynamic range synthesis processing on a plurality of exposure images of each wave band, and carrying out normalization processing on pixel values under different exposure intensities by using a camera response function; repeating the same operation on each wave band to obtain a high dynamic range pixel value of each wave band;
third, for pixels lost due to saturation of the pixels or due to a noise level being lower, interpolation processing is performed with pixels in the neighborhood to restore, and a high dynamic range image after resolution restoration is generated.
In one embodiment, the neighborhood of the pixel points to be interpolated is enlarged and the weight of the different pixel points in the neighborhood in the fitting process is determined by calculating the gradient change of the pixel values.
The implementation of the embodiment of the invention has the following beneficial effects:
the F-P cavity reflective filter can cover a large range of wave bands in real time, densely and continuously, has the characteristic of narrow-band high transmittance, and F-P cavities with different media and thicknesses are matched with reflectors with different materials and thicknesses, so that the problem of underexposure or overexposure in each wave band can be solved, and the utilization rate of pixels and the dynamic range of a shot image are improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Wherein:
FIG. 1 is a schematic diagram of an image sensor according to the present invention;
FIG. 2 is a schematic diagram of an energy balance filter in the visible light band according to the present invention;
FIG. 3 is a schematic diagram of the present invention utilizing a balanced binary tree model to segment the wavelength bands and the exposure intensities, respectively;
FIG. 4 is a schematic layout diagram of a pixel sensor array and an F-P cavity reflective filter structure corresponding to the front end of the pixel sensor array;
fig. 5 is a flowchart of a high dynamic range image imaging method according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention discloses an image sensor, in particular to a chip-integrated real-time hyperspectral high-dynamic-range image sensor. In an embodiment of the invention, an F-P cavity thin film array is directly deposited on a pixel sensor array of an image sensor by using a semiconductor thin film technology to replace the traditional RGB dye filter. As shown in fig. 1, a schematic diagram of an image sensor structure in the present invention is shown, in the image sensor, a bottom reflector 2 is disposed above a pixel sensor array 3, a top reflector 1 is disposed above an F-P cavity 4,F-P cavity 4 above the bottom reflector 2, that is, the structure of the image sensor sequentially includes the pixel sensor array 3, the bottom reflector 2, the F-P cavity 4, and the top reflector 1 from bottom to top; wherein, the bottom reflector 2, the F-P cavity 4 and the top reflector 1 form an F-P cavity reflection type filtering structure; when the bottom reflector 2 and the top reflector 1 are made of metal materials, the bottom reflector 2 and the top reflector 1 form a metal reflecting layer of an F-P cavity reflection type filtering structure.
In one embodiment, the image sensor is a CMOS image sensor.
As shown in fig. 1, the wavelength and intensity of the transmitted light can be controlled by changing the structural properties and parameters of the F-P cavity reflective filter structure at the front end of the pixel sensor array 3, so that the image sensor obtains uniform response in each band.
The structural parameters and properties that can be changed include, but are not limited to, the cavity length of the F-P cavity 4, the cavity medium of the F-P cavity 4 (different cavity mediums have different refractive indexes), the thicknesses of the bottom reflector 2 and the top reflector 1, the materials of the bottom reflector 2 and the top reflector 1, and the like.
The cavity medium deposition thickness of the F-P cavity 4 is changed by changing the cavity medium deposition time of the F-P cavity 4 at the front end of each pixel point in the pixel point sensor array 3, so that the cavity length of the F-P cavity 4 can meet the constructive interference condition of the target wavelength, and the light with the specific wavelength is selected.
Wherein, changing the optical length of the F-P cavity 4 includes, but is not limited to, changing the cavity length of the F-P cavity 4, changing cavity media with different transmittance, modulating the cavity media with variable refractive index, etc., thereby realizing the selection of the transmission wavelength. The filter wavelength of the F-P cavity can be expanded to a near infrared region by increasing the cavity length of the F-P cavity 4 or utilizing a cavity medium with a higher refractive index, so that the hyperspectral acquisition capability of the image sensor is further enhanced.
Wherein reducing the thickness of the bottom mirror 2 or the top mirror 1 can reduce the reflectivity of the mirror. When the bottom reflector 2 and the top reflector 1 are manufactured by using metal materials, the bottom reflector 2 and the top reflector 1 form a metal reflecting layer of an F-P cavity reflection type filtering structure; reducing the thickness of the metal reflective layer can reduce the reflectivity of the metal reflective layer and increase the transmissivity of the F-P cavity 4 and the half-wave width of the transmission band. By utilizing the principle, the quantum efficiency of the CMOS image sensor in the selected wave band can be improved, and the normalized response of each wave band of the CMOS image sensor is on the same level.
Wherein, the transmissivity of the F-P cavity reflection type filtering structure to the light rays of different wave bands can be changed by using different metal materials to manufacture the bottom reflector 2 and the top reflector 1; when the bottom reflector 2 and the top reflector 1 are made of metal materials, the bottom reflector 2 and the top reflector 1 form a metal reflecting layer of an F-P cavity reflection type filtering structure. For different wave bands, different metals can be used for preparing the metal reflecting layer of the F-P cavity reflecting type optical filtering structure.
In one embodiment, aluminum (Al) may be used as the material of the metal reflective layer of the F-P cavity reflective filter structure, and since aluminum (Al) has a lower reflectivity in the near infrared band, the lower quantum efficiency of the CMOS image sensor in the near infrared band may be compensated for to achieve energy balance.
In one embodiment, silver (Ag) can be used as the material of the metal reflecting layer of the F-P cavity reflecting filter structure, and the light reflectivity of the silver (Ag) in the range below 450nm is low, so that the F-P cavity can obtain higher transmissivity in a short wave band, the energy balance is further improved, and the normalized response M of the image sensor in each wave band is realized n Approximately equal.
The normalized response M n The calculation formula of (2) is as follows:
where λ is the wavelength, nI (lambda) is the energy distribution under different illumination occasions, R (lambda) is the response of the bare sensor under each wave band, T n As a function of the transmittance of the channel filters for each band. Further, for the transmittance function T n The distribution function of the F-P cavity is utilized to replace the Gaussian distribution function commonly used by the dye filter for optimal design. Fig. 2 is a schematic diagram of the filter design of energy balance in the visible light band according to the present invention.
By adjusting the structural parameters and the attributes of the F-P cavity reflection type optical filtering structure, a plurality of F-P cavity film arrays with different transmission wavelengths and different transmission intensities can be obtained on the image sensor. After single-frame shooting is carried out by utilizing the image sensor, multidimensional image information comprising spatial position, wavelength, brightness and the like can be acquired.
When the image sensor is applied to a remote sensing shooting scene, besides the hyperspectral information of the scene can be obtained in real time, the image information of the shot object under different exposure intensities can be obtained by utilizing the additionally added pixel information generated by the F-P cavity reflection type optical filtering structure with multi-stage transmittance in the same wave band. The low dynamic range (Low Dynamic Range, LDR for short) images of the shot object under single brightness are synthesized to obtain the images with high dynamic range (High Dynamic Range, HDR for short), so that the capability of capturing bright and dark details of the sensor under a scene with larger brightness span, in particular the resolution capability of areas such as reflective water bodies, roads, forest shadows and the like, can be enhanced. Since the pixel sensor array is divided by a plurality of different wave bands and exposure intensities, in order to achieve ideal image quality, the sub-images must be fused, so that the spatial resolution of the image is restored.
FIG. 3 is a schematic diagram of the present invention in which the balanced binary tree model is used to divide the wavelength band and the exposure intensity, so as to ensure that each wavelength band or exposure intensity is not discriminated; wherein A/B/… in FIG. 3 represents exposure differences caused by different transmittances, and 1/2/3/4/… represents different wavelength bands.
As shown in fig. 4, the pixel sensor array of the image sensor in the present invention is designed according to a mosaic arrangement, and the F-P cavity reflection type filtering structure at the front end of the pixel sensor array is also arranged according to the mosaic corresponding to the pixel sensor array, where a/B/… represents exposure differences caused by different transmittances, 1/2/3/4/… represents different wavebands, and in order to ensure spatial distribution uniformity of each pixel, each pixel is uniformly distributed in the whole image sensor area as much as possible, so as to avoid degradation of a certain imaging area due to sparse sampling; wherein each pixel has a unique combination of wavelength band and exposure intensity.
In one embodiment, the length of the balanced binary tree for the sub-bands and sub-exposures, respectively, may be scaled to change the number of band channels for different applications. For example, when the image sensor is applied to a scene having a large luminance range, the number of exposure condition channels is appropriately increased. Alternatively, when the image sensor is applied to the detection industry, in order to improve the frequency domain resolution, or in order to expand the detection range to a wider band range, the number of exposure channels may be reduced and allocated to new band channels.
The embodiment of the invention discloses an imaging method, in particular to an imaging method of a high dynamic range image. Fig. 5 is a flowchart of a method for implementing high dynamic range image imaging by using the image sensor according to the present invention:
the method comprises the steps that firstly, a single frame image obtained by an image sensor is utilized to obtain a plurality of low-spatial resolution images under a plurality of wave bands and a plurality of exposure intensities;
secondly, performing High Dynamic Range (HDR) synthesis processing on a plurality of exposure images of each wave band, and performing normalization processing on pixel values under different exposure intensities by using a camera response function so as to improve the dynamic range of the images; repeating the same operation for each band to obtain a High Dynamic Range (HDR) pixel value for each band;
third, for pixels that are lost due to saturation of the pixels or due to below noise level, pixel interpolation in the neighborhood is used to recover resolution, resulting in a resolution recovered high dynamic range image.
For the pixel point to be interpolated, pixels in the neighborhood of the pixel point contain different exposure intensity and wave band information; since the pixel points of each band are sparsely distributed on the image sensor, in order to effectively perform resolution recovery processing, it is necessary to expand the neighborhood of the pixel point to be interpolated, and to determine the weights of different pixel points in the neighborhood in fitting processing by calculating the gradient changes of the pixel values.
The implementation of the embodiment of the invention has the following beneficial effects:
the F-P cavity reflection type filtering structure is adopted to replace a trichromatic RGB dye filter in a traditional image sensor to select the wavelength of light, and the selection of the transmission wavelength is realized by changing the optical length of the F-P cavity; the transmissivity of the F-P cavity is adjusted to achieve energy balance by changing the materials and thicknesses of a bottom layer reflector and a top layer reflector (metal reflecting layer) in the F-P cavity reflection type optical filtering structure, a plurality of transmissivity gears are arranged on each wave band to obtain a plurality of LDR images with low dynamic range, and the shooting of the HDR images with high spectrum and high dynamic range can be realized only by single-frame shooting.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. An image sensor, comprising:
the pixel sensor array and the F-P cavity reflection type optical filtering structure are positioned at the front end of the pixel sensor array; the F-P cavity reflection type optical filtering structure comprises a bottom layer reflecting mirror, an F-P cavity and a top layer reflecting mirror; the structure of the image sensor is sequentially provided with a pixel sensor array, a bottom reflector, an F-P cavity and a top reflector from bottom to top; the structural properties and parameters of the F-P cavity reflective optical filtering structure can be adjusted;
wherein the adjustable structural attributes and parameters comprise the cavity length of the F-P cavity and the cavity medium of the F-P cavity; the deposition thickness of the cavity medium is changed by changing the deposition time of the cavity medium, so that the cavity growth of the F-P cavity meets the constructive interference condition of the target wavelength, and the light with the specific wavelength is selected.
2. The image sensor of claim 1, wherein the image sensor comprises a sensor array,
the adjustable structural attributes and parameters also comprise thicknesses of the bottom reflector and the top reflector, and materials of the bottom reflector and the top reflector.
3. The image sensor of claim 2, wherein the image sensor further comprises a sensor element,
the pixel sensor array and the F-P cavity reflection type optical filtering structure corresponding to the front end of the pixel sensor array are distributed according to mosaics, wherein each pixel has a unique wave band and exposure intensity combination.
4. The image sensor of claim 3, wherein the image sensor comprises a sensor array,
and dividing the wave band and the exposure intensity of each pixel point by using a balanced binary tree model.
5. The image sensor of claim 2, 3 or 4, wherein,
the bottom reflector and the top reflector are made of aluminum or silver.
6. The image sensor of claim 2, 3 or 4, wherein,
the pixel sensor array is a CMOS sensor array.
7. An imaging method applied to the image sensor of any one of claims 1-6, comprising:
the method comprises the steps that firstly, a single frame image obtained by an image sensor is utilized to obtain a plurality of low-spatial resolution images under a plurality of wave bands and a plurality of exposure intensities;
secondly, carrying out high dynamic range synthesis processing on a plurality of exposure images of each wave band, and carrying out normalization processing on pixel values under different exposure intensities by using a camera response function; repeating the same operation on each wave band to obtain a high dynamic range pixel value of each wave band;
third, for pixels lost due to saturation of the pixels or due to a noise level being lower, interpolation processing is performed with pixels in the neighborhood to restore, and a high dynamic range image after resolution restoration is generated.
8. The method of claim 7, wherein the step of determining the position of the probe is performed,
and expanding the neighborhood of the pixel points to be interpolated, and determining the weights of different pixel points in the neighborhood in fitting processing by calculating the gradient change of the pixel values.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2018/112266 WO2020082392A1 (en) | 2018-10-27 | 2018-10-27 | Image sensor and imaging method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111356649A CN111356649A (en) | 2020-06-30 |
| CN111356649B true CN111356649B (en) | 2023-10-13 |
Family
ID=70332102
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201880068674.1A Active CN111356649B (en) | 2018-10-27 | 2018-10-27 | Image sensor and imaging method |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN111356649B (en) |
| WO (1) | WO2020082392A1 (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113093322B (en) * | 2021-03-30 | 2023-03-28 | 联合微电子中心有限责任公司 | CMOS image sensor, interference type optical filter and preparation method thereof |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008128372A1 (en) * | 2007-04-20 | 2008-10-30 | Eth Zurich | Transmission interferometric adsorption sensor |
| CN102741671A (en) * | 2009-11-30 | 2012-10-17 | Imec公司 | Integrated circuit for spectral imaging system |
| CN106672893A (en) * | 2016-12-29 | 2017-05-17 | 深圳先进技术研究院 | Tunable filter and tunable filter array |
| CN106768324A (en) * | 2016-11-17 | 2017-05-31 | 天津津航技术物理研究所 | A kind of light spectrum image-forming microsensor |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6783900B2 (en) * | 2002-05-13 | 2004-08-31 | Micron Technology, Inc. | Color filter imaging array and method of formation |
| US8902321B2 (en) * | 2008-05-20 | 2014-12-02 | Pelican Imaging Corporation | Capturing and processing of images using monolithic camera array with heterogeneous imagers |
| CN102437166B (en) * | 2011-10-09 | 2013-05-01 | 中国科学院苏州纳米技术与纳米仿生研究所 | Manufacturing method of non-refrigeration infrared detection system pixel array |
| CN105450937B (en) * | 2014-08-29 | 2019-03-05 | 展讯通信（上海）有限公司 | Image processing method and image processor |
| CN104535007A (en) * | 2014-12-15 | 2015-04-22 | 哈尔滨工程大学 | Distributed type optical fiber strain measurement system based on cavity-length-adjustable F-P white light interference demodulating device |
-
2018
- 2018-10-27 CN CN201880068674.1A patent/CN111356649B/en active Active
- 2018-10-27 WO PCT/CN2018/112266 patent/WO2020082392A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008128372A1 (en) * | 2007-04-20 | 2008-10-30 | Eth Zurich | Transmission interferometric adsorption sensor |
| CN102741671A (en) * | 2009-11-30 | 2012-10-17 | Imec公司 | Integrated circuit for spectral imaging system |
| CN106768324A (en) * | 2016-11-17 | 2017-05-31 | 天津津航技术物理研究所 | A kind of light spectrum image-forming microsensor |
| CN106672893A (en) * | 2016-12-29 | 2017-05-17 | 深圳先进技术研究院 | Tunable filter and tunable filter array |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2020082392A1 (en) | 2020-04-30 |
| CN111356649A (en) | 2020-06-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CA2864763C (en) | Method and device for measuring the colour of an object | |
| CN113884184B (en) | Spectral sensor system using an optical filter sub-array | |
| JP2001099710A5 (en) | ||
| JP4328424B2 (en) | Image conversion method | |
| EP2160904B1 (en) | Digital image sensor, image capture and reconstruction method and system for implementing same | |
| CN105891928B (en) | A kind of camera shooting wave filter of day and night dual-purpose | |
| CN111999788B (en) | Wide spectrum coding full color filter array | |
| CN113676628B (en) | Image forming apparatus and image processing method | |
| CN113447118B (en) | Multispectral imaging chip capable of realizing color imaging and color imaging method | |
| CN111024229B (en) | Single-chip integrated spectral imaging micro-system spectral data correction method | |
| CN109716758A (en) | There is the monitoring camera of the compound filter method of robustness using the change to visibility state and using its video monitoring system | |
| KR20190036442A (en) | Hyperspectral Imaging Reconstruction Method Using Artificial Intelligence and Apparatus Therefor | |
| CN111356649B (en) | Image sensor and imaging method | |
| Sun et al. | Sparse spectral signal reconstruction for one proposed nine-band multispectral imaging system | |
| US20230170363A1 (en) | Optical filter array, mobile terminal, and device | |
| CN107734231B (en) | Optical filtering-based imaging system dynamic range expansion method | |
| KR20190036459A (en) | Hyperspectral Imaging Reconstruction Method Using Artificial Intelligence and Apparatus Therefor | |
| FR2899696A1 (en) | METHOD FOR PROCESSING A RELATIVE LIGHT PHENOMENON ON A DIGITAL IMAGE AND ASSOCIATED TREATMENT SYSTEM | |
| US11696043B2 (en) | White balance compensation using a spectral sensor system | |
| Monno et al. | N-to-sRGB mapping for single-sensor multispectral imaging | |
| Liu et al. | Single-image night haze removal based on color channel transfer and estimation of spatial variation in atmospheric light | |
| CN115000107A (en) | Multispectral imaging chip, multispectral imaging component, preparation method and mobile terminal | |
| Péguillet et al. | Energy balance in single exposure multispectral sensors | |
| Li et al. | Polarized color image denoising | |
| Li et al. | Universal Demosaicking for Interpolation-Friendly RGBW Color Filter Arrays |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |