CN109345481B - Quantum optimization method for aerospace optical remote sensing image - Google Patents
Quantum optimization method for aerospace optical remote sensing image Download PDFInfo
- Publication number
- CN109345481B CN109345481B CN201811140484.4A CN201811140484A CN109345481B CN 109345481 B CN109345481 B CN 109345481B CN 201811140484 A CN201811140484 A CN 201811140484A CN 109345481 B CN109345481 B CN 109345481B
- Authority
- CN
- China
- Prior art keywords
- remote sensing
- quantum
- optical remote
- sensing image
- bit plane
- 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
- 230000003287 optical effect Effects 0.000 title claims abstract description 120
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000005457 optimization Methods 0.000 title claims abstract description 24
- 239000013598 vector Substances 0.000 claims abstract description 128
- 239000002096 quantum dot Substances 0.000 claims abstract description 93
- 238000003384 imaging method Methods 0.000 claims abstract description 30
- 238000001914 filtration Methods 0.000 claims abstract description 23
- 238000010606 normalization Methods 0.000 claims abstract description 4
- 238000013139 quantization Methods 0.000 claims description 14
- 230000005283 ground state Effects 0.000 claims description 5
- 239000011159 matrix material Substances 0.000 claims description 4
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 claims description 3
- 241001394244 Planea Species 0.000 claims description 3
- 230000002146 bilateral effect Effects 0.000 claims description 3
- 150000001875 compounds Chemical class 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 abstract 1
- 238000003672 processing method Methods 0.000 description 7
- 230000000694 effects Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 238000000354 decomposition reaction Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000015556 catabolic process Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration using local operators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
- Light Receiving Elements (AREA)
Abstract
The invention provides a quantum optimization method for an aerospace optical remote sensing image, which comprises the following steps: (1) imaging the satellite through the border to the ground to obtain an optical remote sensing image of an observation target, and performing normalization processing; (2) converting the normalized optical remote sensing image into a quantum space, and decomposing the normalized optical remote sensing image into n quantum bit planes to obtain quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane; (3) based on the optical remote sensing imaging system model, filtering the quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane by adopting a norm optimization method; (4) carrying out enhancement processing on the quantum state vectors of the quantized information of the filtered optical remote sensing image on each quantum bit plane to obtain enhanced quantum state vectors on each quantum bit plane; (5) and reconstructing the enhanced quantum state vector on each quantum bit plane and converting the reconstructed quantum state vector into a high-definition optical remote sensing image. The invention can effectively improve the evaluation index.
Description
Technical Field
The invention provides a quantization filtering method for an optical remote sensing image, and belongs to the technical field of optical remote sensing information processing.
Background
At the stage of on-orbit imaging of the existing optical remote sensor, the ground resolution is very low due to the limited size of a detector, and a large amount of random noise, such as photon noise, thermal noise and the like, appears on a focal plane due to the performance degradation of detection components and parts caused by various complex factors such as space environment change and the like, so that speckle noise and system blurring appear in an acquired image; in addition, the inherent characteristics of the detection device perform down-sampling on the natural ground object signals with continuous signals, so that the whole energy of the image is insufficient, and the imaging quality is seriously degraded.
At present, in the in-orbit stage of a satellite, due to the limited processing capacity, the imaging quality is difficult to effectively improve, a large amount of effective information is lost while the traditional mean filtering denoising is adopted, an ideal effect is difficult to obtain, and the noise estimation is not accurate enough. Therefore, new means are needed to further improve the imaging quality of the optical sensor.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method overcomes the defects of the prior art, provides the optical remote sensing image quantization filtering method, and improves the imaging quality of the optical sensor.
The technical solution of the invention is as follows: a quantum optimization method for an aerospace optical remote sensing image comprises the following steps:
(1) the satellite transit imaging is carried out, an optical remote sensing imaging system is adopted to obtain an optical remote sensing image of an observation target, and normalization processing is carried out;
(2) converting the normalized optical remote sensing image into a quantum space, and decomposing the normalized optical remote sensing image into n quantum bit planes to obtain quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane;
(3) based on the optical remote sensing imaging system model, filtering the quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane by adopting a norm optimization method;
(4) carrying out enhancement processing on the quantum state vectors of the quantized information of the filtered optical remote sensing image on each quantum bit plane to obtain enhanced quantum state vectors on each quantum bit plane;
(5) and reconstructing the enhanced quantum state vector on each quantum bit plane and converting the reconstructed quantum state vector into a high-definition optical remote sensing image.
The quantum state vector of the quantization information of the optical remote sensing image on each quantum bit plane is represented as follows:
pk(u,v)|ψk(u,v)><ψk(u,v)|,k∈[1,n]
in the formula, pkRepresenting the probability amplitude, | ψ, of quantized information corresponding to the optical remote sensing image on the kth quantum bit planek(μ,ν)>A right vector of quantum state vectors in a k-th quantum bit plane for corresponding quantized information of the optical remote sensing image,<ψk(mu, v) | is the left vector of the quantum state vector of the quantized information corresponding to the optical remote sensing image in the kth quantum bit plane, and is | ψk(μ,ν)>The (μ, ν) represents the position coordinates of the quantum state vector on the quantum bit plane.
Right vector | ψ of quantum state vector in kth quantum bit plane of quantization information corresponding to the imagek(μ,ν)>The expression is as follows:
in the formula, |0> and |1> are respectively expressed as two ground states in the image qubits, f is the normalized optical remote sensing image, and f (m, n) belongs to [0,1 ].
When the image pixel values are distributed according to exponential distribution probability, the right vector | ψ of quantum state vector in k-th quantum bit plane of the corresponding quantization information of the imagek(μ,ν)>The expression is as follows:
in the formula, theta and phi respectively represent included angles between corresponding vectors on a quantum bit space and a Z axis of a Cartesian product coordinate system; the corresponding vector is projected on an included angle between an XOY surface and an X axis of a Cartesian product coordinate system.
And (2) filtering the quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane by adopting a 2+ p norm optimization method.
The 2+ p norm optimization method comprises the following steps: seeking right vector of quantum state vector of ideal optical remote sensing image I in kth quantum bit plane
So that it satisfies the following formula:
so as to lead the ideal optical remote sensing image I to be right vector of the quantum state vector of the kth quantum bit plane
As a right vector of the k-th quantum bit plane quantum state vector of the filtered optical remote sensing image I, and then calculating
The left side of the quantum state vector of the k quantum bit plane of the filtered optical remote sensing image I is obtainedVector;
in the formula (I), the compound is shown in the specification,
a matrix H corresponding to the point spread function of the optical remote sensing imaging system is a right vector of a quantum state vector of a kth quantum bit plane;
λktaking the adjustment coefficient of each bit plane to be between 0 and 1;
expressing the minimization of 2 norm, | ·| non-woven phosphorpDenotes the p norm, 0<p<1,ρkTo adjust the factor, 0<ρk<1，DkIs a gradient value and the formula is as follows:
wherein, | Fk(μ,ν)>And (3) corresponding quantum bit values of pixel points at the optical remote sensing image (mu, v) on the kth bit plane.
And (4) enhancing the image by adopting a bilateral filtering method.
The information reconstruction method comprises the following steps:
wherein the content of the first and second substances,
for the right vector of the quantum state vector in the k-th quantum bit plane of the corresponding quantized information of the enhanced optical remote sensing image,
the left vector of the quantum state vector in the k quantum bit plane for the corresponding quantized information of the enhanced optical remote sensing image is
The conjugate transpose of (1); f' (m, n) is the converted optical remote sensing image.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention considers the information of the superposition state from the information quantization angle and carries out the norm optimization in the quantum bit plane, thereby being capable of more effectively removing noise and improving the effective information quantity of the image.
(2) The image information is converted into the quantum space, the noise and the signal are separated in the quantum space by using the optimization characteristic of 2+ p norm, and then the information is converted back to the image information from the quantum space to obtain the image with enhanced quality, so that the method is suitable for images which cannot be processed on the satellite or are difficult to denoise on the ground.
(3) Compared with the traditional processing method, the method has better detail fidelity, can obtain clearer images and improves the image quality.
(4) The method can effectively improve the on-orbit imaging quality of the space camera and enhance the perception capability of the target through quantum space filtering enhancement.
(5) The method can be used for optical remote sensing images, and is particularly suitable for removing weak targets and strong background noise in infrared and terahertz spectral bands.
Drawings
FIG. 1 is a flow chart of the optical remote sensing image quantization filtering method of the present invention;
FIG. 2 is a projection of an image on each side of the Qbit according to an embodiment of the present invention; wherein:
FIGS. 2(a) to 2(h) are exploded views of layers 1 to 8, respectively;
FIG. 3 is a comparison of the results of the process of the present invention with those of the conventional method; wherein:
FIG. 3(a) is an image taken by an optical remote sensor according to the present invention;
FIG. 3(b) is an optical remote sensing image obtained by a mean filtering method;
fig. 3(c) shows an optical remote sensing image obtained by the processing method (quantum filtering) of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific examples.
The invention provides a quantization-based image filtering method, which is based on the information quantum state, takes the superposition state information into consideration, realizes denoising through quantum space filtering, and finally improves the information quantity acquired by a system by adopting enhanced filtering. Because the information is expressed in the form of quantum bit, the superposition state between information ground states can be expressed, the noise existing in the superposition state can not be processed by the traditional image processing method, and meanwhile, the better denoising effect is realized by adopting the optimization of '2 + P norm' in the quantum space. Because the method realizes information optimization in the quantum space, the noise separation effect is better.
The method of the invention has the following general flow:
(1) the satellite transit imaging is carried out, an optical remote sensing imaging system is adopted to obtain an optical remote sensing image of an observation target, and normalization processing is carried out;
the concrete implementation is as follows: imaging the satellite through the border to the ground, and starting a camera to acquire target observation information corresponding to the optical remote sensing satellite; and modeling the imaging system by combining the information of the optical remote sensing imaging system to obtain an optical remote sensing image.
(2) Converting the normalized optical remote sensing image into a quantum space, and decomposing the normalized optical remote sensing image into n quantum bit planes to obtain quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane;
after the image values of the optical remote sensing image are normalized, the gray value of each pixel is in the interval of [0,1 ]. The optical remote sensing imaging system can be regarded as a linear system and is represented as follows:
in the formula, (m, l) represents the position coordinates of the pixel points in the optical remote sensing image. 0<m<M,0<l<L, s is the size of the acquired image data, s is the size of the PSF in one direction, I (m, L) is ideal scene information, Noise is a Noise item, H represents the Point Spread Function (PSF) of the optical remote sensing imaging system and can be obtained by measurement
Converting the optical remote sensing image into a quantum space, decomposing the optical remote sensing image into each quantum bit plane to obtain quantum state vectors in the quantum bit plane corresponding to the optical remote sensing image, wherein the quantum state vectors can be expressed as follows:
therefore, the quantum state vector of the quantized information of the optical remote sensing image on each quantum bit plane is represented as follows:
pk(u,v)|ψk(u,v)><ψk(u,v)|,k∈[1,n](3)
in the formula, pkRepresenting the probability amplitude, | ψ, of quantized information corresponding to the optical remote sensing image on the kth quantum bit planek(μ,ν)>A right vector of quantum state vectors in a k-th quantum bit plane for corresponding quantized information of the optical remote sensing image,<ψk(mu, v) | is the left vector of the quantum state vector of the quantized information corresponding to the optical remote sensing image in the kth quantum bit plane, and is | ψk(μ,ν)>The (μ, ν) represents the position coordinates of the quantum state vector on the quantum bit plane.
Right vector | ψ of quantum state vector in kth quantum bit plane of quantization information corresponding to the imagek(μ,ν)>The expression is as follows:
ψk(μ,ν)>＝α|0>+β|1>
wherein, |0>And |1>Represented as two ground states in an image qubit, α, β representing ψ, respectivelyk(μ,ν)>At |0>And |1>The probabilities in the two ground states, α and β, can be understood as the different polarization states formed upon incidence of light and satisfy α2+β2＝1。
f is normalized optical remote sensing image, f (m, n) ∈ [0,1]. The right vector | ψ of the quantum state vector in the k-th quantum bit plane can be used to quantize information corresponding to an imagek(μ,ν)>The expression is as follows:
in the case of an image pixel value with an exponentially distributed probability distribution, it can be further deduced that: right vector | ψ of quantum state vector in kth quantum bit plane of quantization information corresponding to the imagek(μ,ν)>The expression is as follows:
in the formula, theta and phi respectively represent included angles between corresponding vectors on a quantum bit space and a Z axis of a Cartesian product coordinate system; the corresponding vector projects the angle between the xy-plane and the x-axis. In the embodiment of the invention, the remote sensing information can be decomposed into 8 bit planes.
(3) Based on the optical remote sensing imaging system model, filtering the quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane by adopting a norm optimization method;
the embodiment of the invention adopts a 2+ p norm optimization method to filter the quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane and filter noise.
The specific filtering process is as follows: seeking right vector of quantum state vector of ideal optical remote sensing image I in kth quantum bit plane
So that it satisfies the following formula:
so as to lead the ideal optical remote sensing image I to be right vector of the quantum state vector of the kth quantum bit plane
As a right vector of the k-th quantum bit plane quantum state vector of the filtered optical remote sensing image I, and then calculating
The left vector of the quantum state vector of the k-th quantum bit plane of the filtered optical remote sensing image I is obtained;
in the formula (I), the compound is shown in the specification,
a matrix H corresponding to the point spread function of the optical remote sensing imaging system is a right vector of a quantum state vector of a kth quantum bit plane;
λkfor each bit plane, take0 to 1;
expressing the minimization of 2 norm, | ·| non-woven phosphorpDenotes the p norm, 0<p<1,ρkTo adjust the factor, 0<ρk<1，DkIs a gradient value and the formula is as follows:
wherein, | Fk(μ,ν)>And (3) corresponding quantum bit values of pixel points at the optical remote sensing image (mu, v) on the kth bit plane.
The norm space of the quantum domain is similar to the norm space of the image domain, namely the norm expression obtained in different bit planes, the expansion operation of the norm expression obeys the quantum operation rule, and the optimization ensures that
Approaching the ideal value.
|ψk(μ0,ν0)>quantum state vectors on a kth quantum bit plane for the acquired optical remote sensing image;
The norm space of the quantum domain is similar to the norm space of the image domain, namely, the norm expression obtained in different bit planes, and the quantum vector operation complies with the quantum operation rule:
theorem: if it is
And is
Then there is
And
and is provided with
the above equation represents the operational relationship between any two quantum state vectors, wherein the quantum state vector | ψj>Is represented as
And | ψp>Is represented as
Therefore, | ψj>And | ψp>All the operational relations between the two satisfy the expansion formula
And
and (4) performing an operation. Thus, the operation relationship between the quantum state vectors can be realized by the operation between the matrixes.
(4) Carrying out enhancement processing on the quantum state vectors of the quantized information of the filtered optical remote sensing image on each quantum bit plane to obtain enhanced quantum state vectors on each quantum bit plane;
the embodiment of the invention adopts a bilateral filtering method to enhance the image, realizes the enhancement of image texture information and the improvement of image quality while keeping edge information, and the quantum information after filtering is
(5) And reconstructing the enhanced quantum state vector on each quantum bit plane and converting the reconstructed quantum state vector into a high-definition optical remote sensing image. The specific information reconstruction method comprises the following steps:
wherein the content of the first and second substances,
for the right vector of the quantum state vector in the k-th quantum bit plane of the corresponding quantized information of the enhanced optical remote sensing image,
the left vector of the quantum state vector in the k quantum bit plane for the corresponding quantized information of the enhanced optical remote sensing image is
The conjugate transpose of (1); f' is the converted optical remote sensing image.
Example (b):
fig. 2 is an image of an image after the image is subjected to qubit plane decomposition, and it can be seen from fig. 2 that the qubit plane decomposition of the present invention can decompose information in the image more finely and effectively separate noise from signals. FIG. 3 is a comparison of the processing results of the method of the present invention and the conventional method. Table 1 shows a comparison between the conventional processing method and the quantization filtering processing method of the present invention.
TABLE 1 post-conventional processing method vs. the present invention quantization filtering processing method
As can be seen from the quantitative indexes in Table 1, compared with the traditional method, the method disclosed by the patent has higher indexes such as image signal-to-noise ratio, contrast, information entropy and the like. As can be seen from FIG. 3, after being processed, the noise and the blur can be effectively removed, which is beneficial to subsequent image judgment and target identification.
In summary, compared with the traditional method, the method has higher indexes such as image signal-to-noise ratio, contrast, information entropy and the like. After the processing, the noise and the fuzziness can be effectively removed, and the subsequent image judgment and target identification are facilitated.
Parts of the specification which are not described in detail are within the common general knowledge of a person skilled in the art.
Claims (6)
1. A quantum optimization method for an aerospace optical remote sensing image is characterized by comprising the following steps:
(1) the satellite transit imaging is carried out, an optical remote sensing imaging system is adopted to obtain an optical remote sensing image of an observation target, and normalization processing is carried out;
(2) converting the normalized optical remote sensing image into a quantum space, and decomposing the normalized optical remote sensing image into n quantum bit planes to obtain quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane;
(3) based on the optical remote sensing imaging system model, filtering the quantum state vectors of the quantized information of the optical remote sensing image on each quantum bit plane by adopting a norm optimization method;
the method comprises the following steps of filtering quantum state vectors of optical remote sensing image quantization information on each quantum bit plane by adopting a 2+ p norm optimization method;
the 2+ p norm optimization method comprises the following steps: seeking right vector of quantum state vector of ideal optical remote sensing image I in kth quantum bit plane
So that it satisfies the following formula:
so as to lead the ideal optical remote sensing image I to be right vector of the quantum state vector of the kth quantum bit plane
As a right vector of the k-th quantum bit plane quantum state vector of the filtered optical remote sensing image I, and then calculating
The left vector of the quantum state vector of the k-th quantum bit plane of the filtered optical remote sensing image I is obtained;
in the formula (I), the compound is shown in the specification,
a matrix H corresponding to the point spread function of the optical remote sensing imaging system is a right vector of a quantum state vector of a kth quantum bit plane;
λktaking the adjustment coefficient of each bit plane to be between 0 and 1;
expressing the minimization of 2 norm, | ·| non-woven phosphorpDenotes the p norm, 0<p<1,ρkTo adjust the factor, 0<ρk<1，DkIs a gradient value and the formula is as follows:
wherein, | Fk(μ,ν)>Corresponding quantum bit values of pixel points at the optical remote sensing image (mu, v) on a k bit plane;
(4) carrying out enhancement processing on the quantum state vectors of the quantized information of the filtered optical remote sensing image on each quantum bit plane to obtain enhanced quantum state vectors on each quantum bit plane;
(5) and reconstructing the enhanced quantum state vector on each quantum bit plane and converting the reconstructed quantum state vector into a high-definition optical remote sensing image.
2. The quantum optimization method for the aerospace optical remote sensing image according to claim 1, wherein quantum state vectors of quantized information of the optical remote sensing image on each quantum bit plane are represented as follows:
pk(u,v)|ψk(u,v)><ψk(u,v)|,k∈[1,n]
in the formula, pkRepresenting the probability amplitude, | ψ, of quantized information corresponding to the optical remote sensing image on the kth quantum bit planek(μ,ν)>A right vector of quantum state vectors in a k-th quantum bit plane for corresponding quantized information of the optical remote sensing image,<ψk(mu, v) | is the left vector of the quantum state vector of the quantized information corresponding to the optical remote sensing image in the kth quantum bit plane, and is | ψk(μ,ν)>The (μ, ν) represents the position coordinates of the quantum state vector on the quantum bit plane.
3. A quantum optimization method for an aerospace optical remote sensing image according to claim 2, wherein the quantization information corresponding to the image is in kth quantum bit planeRight vector | ψ of vector of intermediate quantum statek(μ,ν)>The expression is as follows:
in the formula, |0> and |1> are respectively expressed as two ground states in the image qubits, f is the normalized optical remote sensing image, and f (m, n) belongs to [0,1 ].
4. The quantum optimization method for the space optics remote sensing image as claimed in claim 1, wherein the right vector | ψ of the quantum state vector of the quantized information corresponding to the image in the k-th quantum bit plane is in the case of the image pixel value according to the exponential distribution probability distributionk(μ,ν)>The expression is as follows:
in the formula, theta and phi respectively represent included angles between corresponding vectors on a quantum bit space and a Z axis of a Cartesian product coordinate system; the corresponding vector is projected on an included angle between an XOY surface and an X axis of a Cartesian product coordinate system.
5. A quantum optimization method for aerospace optical remote sensing images according to claim 1, wherein the step (4) adopts a bilateral filtering method to enhance the images.
6. The quantum optimization method for the aerospace optical remote sensing image according to claim 1, wherein the information reconstruction method comprises:
wherein the content of the first and second substances,
for enhanced optical remote sensing imagesThe corresponding quantized information is the right vector of the quantum state vectors in the kth qubit plane,
the left vector of the quantum state vector in the k quantum bit plane for the corresponding quantized information of the enhanced optical remote sensing image is
The conjugate transpose of (1); f' (m, n) is the converted optical remote sensing image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811140484.4A CN109345481B (en) | 2018-09-28 | 2018-09-28 | Quantum optimization method for aerospace optical remote sensing image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811140484.4A CN109345481B (en) | 2018-09-28 | 2018-09-28 | Quantum optimization method for aerospace optical remote sensing image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109345481A CN109345481A (en) | 2019-02-15 |
| CN109345481B true CN109345481B (en) | 2020-09-18 |
Family
ID=65307257
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811140484.4A Active CN109345481B (en) | 2018-09-28 | 2018-09-28 | Quantum optimization method for aerospace optical remote sensing image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109345481B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110097014B (en) * | 2019-05-08 | 2021-05-07 | 合肥本源量子计算科技有限责任公司 | Quantum bit reading signal processing method based on measurement track |
| CN112529812B (en) * | 2020-12-18 | 2022-12-02 | 西安微电子技术研究所 | Remote sensing image denoising method based on quantum Fourier transform |
| CN115761384B (en) * | 2023-01-09 | 2023-04-28 | 苏州浪潮智能科技有限公司 | Image classification method, device, electronic equipment and storage medium |
| CN116503620B (en) * | 2023-05-11 | 2023-12-08 | 中国科学院空天信息创新研究院 | High-resolution remote sensing image change detection method and device, electronic equipment and medium |
| CN117649613B (en) * | 2024-01-30 | 2024-04-26 | 之江实验室 | Optical remote sensing image optimization method and device, storage medium and electronic equipment |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106600542A (en) * | 2016-10-31 | 2017-04-26 | 北京空间机电研究所 | Spaceflight optical remote sensing high-density quantization information processing method |
| JP6373292B2 (en) * | 2016-03-07 | 2018-08-15 | 日本電信電話株式会社 | Feature generation apparatus, method, and program |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160172397A1 (en) * | 2014-12-15 | 2016-06-16 | Dartmouth College | Solid State Image Sensor with Low Capacitance Floating Diffusion |
-
2018
- 2018-09-28 CN CN201811140484.4A patent/CN109345481B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6373292B2 (en) * | 2016-03-07 | 2018-08-15 | 日本電信電話株式会社 | Feature generation apparatus, method, and program |
| CN106600542A (en) * | 2016-10-31 | 2017-04-26 | 北京空间机电研究所 | Spaceflight optical remote sensing high-density quantization information processing method |
Non-Patent Citations (1)
| Title |
|---|
| 一种基于量子力学的遥感图像滤波方法研究;张智;《红外与激光工程》;20161231;第45卷(第S2期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109345481A (en) | 2019-02-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109345481B (en) | Quantum optimization method for aerospace optical remote sensing image | |
| Hsu et al. | Single image dehazing using wavelet-based haze-lines and denoising | |
| CN106600542B (en) | Aerospace optical remote sensing high-density quantization information processing method | |
| Dharejo et al. | A deep hybrid neural network for single image dehazing via wavelet transform | |
| Cerra et al. | Unmixing-based denoising for destriping and inpainting of hyperspectral images | |
| Bansal et al. | A review of image restoration based image defogging algorithms | |
| Wei et al. | Bayesian fusion of multispectral and hyperspectral images with unknown sensor spectral response | |
| CN108765350B (en) | Aerospace-oriented optical remote sensing image quantization filtering method | |
| CN116823694B (en) | Infrared and visible light image fusion method and system based on multi-focus information integration | |
| Priyadharsini et al. | Underwater acoustic image enhancement using wavelet and KL transform | |
| Hong et al. | Data fusion of multiple polarimetric SAR images using discrete wavelet transform (DWT) | |
| CN109658340A (en) | The SAR image rapid denoising method saved based on RSVD and histogram | |
| US10181181B2 (en) | Denoising with three dimensional fourier transform for three dimensional images, including image sequences | |
| Ye et al. | On linear and nonlinear processing of underwater, ground, aerial and satellite images | |
| Gaber et al. | Performance evaluation of infrared image enhancement techniques | |
| Sheela et al. | Comparative analysis of various filtering techniques for Speckle noise suppression in Ultrasound images | |
| Gao et al. | Sensitivity of multiview 3D point cloud reconstruction to compression quality and image feature detectability | |
| Bharath et al. | Swarm intelligence based image fusion for thermal and visible images | |
| Ye et al. | Quantitative effects of discrete wavelet transforms and wavelet packets on aerial digital image denoising | |
| Nandini et al. | Wavelet-based method for enhancing the visibility of hazy images using Color Attenuation Prior | |
| Mamatha et al. | A non local approach to de-noise SAR images using compressive sensing method | |
| CN112508829B (en) | Pan-sharpening method based on shear wave transformation | |
| Abd Wahab et al. | Image contrast enhancement for outdoor machine vision applications | |
| Reddy et al. | A review of image denoising using machine learning | |
| Aslan et al. | A comparison study for image denoising |
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 |