CN112381728A - Hyperspectral imaging signal processing system and method - Google Patents

Hyperspectral imaging signal processing system and method Download PDF

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Publication number
CN112381728A
CN112381728A CN202011215852.4A CN202011215852A CN112381728A CN 112381728 A CN112381728 A CN 112381728A CN 202011215852 A CN202011215852 A CN 202011215852A CN 112381728 A CN112381728 A CN 112381728A
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image
unit
imaging signal
hyperspectral
filtering
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张利军
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Tianshui Normal University
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Tianshui Normal University
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/70Denoising; Smoothing
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/20Image enhancement or restoration using local operators
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/40Image enhancement or restoration using histogram techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/90Dynamic range modification of images or parts thereof
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/60Noise processing, e.g. detecting, correcting, reducing or removing noise
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20024Filtering details
    • G06T2207/20032Median filtering

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  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Image Processing (AREA)

Abstract

The invention discloses a hyperspectral imaging signal processing system and a hyperspectral imaging signal processing method, wherein the processing system comprises an imaging signal acquisition unit, a filtering unit, a central processing unit and an imaging signal enhancement unit, wherein the imaging signal acquisition unit acquires hyperspectral imaging signals, the imaging signal acquisition unit is connected with the central processing unit through the filtering unit, the central processing unit is connected with the imaging signal enhancement unit, the processing system also comprises a noise removal unit and an imaging signal transmission unit, the noise removal unit is connected with the central processing unit, and the central processing unit is also connected with a background terminal through the imaging signal transmission unit.

Description

Hyperspectral imaging signal processing system and method
Technical Field
The invention relates to the technical field of hyperspectral imaging signal processing, in particular to a hyperspectral imaging signal processing system and a hyperspectral imaging signal processing method.
Background
The hyperspectral image is finely divided in the spectral dimension, and not only is the difference of the traditional black, white or R, G, B, but also N channels are arranged in the spectral dimension, for example, 400nm-1000nm can be divided into 300 channels. Therefore, the hyperspectral equipment acquires a data cube, the data cube has image information and is expanded in spectral dimension, and as a result, not only can the spectral data of each point on the image be acquired, but also the image information of any spectral band can be acquired.
At present, only filtering processing is generally performed on hyperspectral imaging processing, processing efficiency is low, and high-definition image output cannot be realized, so improvement is needed.
Disclosure of Invention
The present invention is directed to a hyperspectral imaging signal processing system and method, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a hyperspectral imaging signal processing system comprises an imaging signal acquisition unit, a filtering unit, a central processing unit and an imaging signal enhancement unit, wherein the imaging signal acquisition unit acquires hyperspectral imaging signals, the imaging signal acquisition unit is connected with the central processing unit through the filtering unit, and the central processing unit is connected with the imaging signal enhancement unit;
the system comprises a background terminal, a noise removing unit and an imaging signal transmission unit, wherein the noise removing unit is connected with a central processing unit, and the central processing unit is also connected with the background terminal through the imaging signal transmission unit.
Preferably, the treatment method comprises the following steps:
A. the imaging signal acquisition unit acquires a hyperspectral image;
B. the collected images are transmitted to a filtering unit for filtering processing, and the filtered images are transmitted to a central processing unit;
C. the central processing unit transmits the filtered image to a noise removing unit to remove noise interference signals;
D. then, the image is transmitted to an imaging signal enhancement unit to carry out enhancement processing on the processed image, and a high-definition hyperspectral image is obtained;
E. and finally, outputting the high-definition hyperspectral image to a background terminal.
Preferably, the filtering unit processing method is as follows:
a. acquiring a scaling configuration parameter and a chroma resampling configuration parameter of an image;
b. generating a brightness signal filter according to the zooming configuration parameters of the image;
c. generating a chrominance signal filter according to the chrominance resampling configuration parameters of the image;
d. and filtering a luminance signal of the input image by using a luminance signal filter, and filtering a chrominance signal of the input image by using a chrominance signal filter to obtain a filtered hyperspectral image.
Preferably, the noise removing unit in step C performs processing by using an image interpolation function, where the function formula is: c '═ a × T + D × (1-T), where C' denotes the output denoised image pixel, a denotes the current image pixel to be processed, T denotes the logical balance variable, and D denotes the noise smooth value of the current pixel to be processed.
Preferably, the imaging signal enhancement unit enhancement method is as follows:
a. dividing pixels of the collected hyperspectral image into a plurality of layers according to brightness values, dividing the layer brightness into 4 layers which are respectively 0-30%, 30-60%, 60-80% and 80-100%, wherein the brightness of each layer is different, and arranging each layer from high to low according to the brightness values;
b. for the image layer with the lowest brightness and the image layer with the largest brightness, namely the image layers of the two areas of 0-30% and 80% -100%, histogram equalization processing is carried out independently, namely, the brightness can be distributed on the histogram better through the histogram equalization; removing background noise and noise points by using a wavelet denoising method, and finally filtering the image by using a median filter;
c. removing noise points of the image layers between the lowest brightness and the highest brightness, then carrying out filtering processing, removing background noise, and finally carrying out histogram equalization processing;
d. and finally merging all the processed image layers into an image after image enhancement.
Compared with the prior art, the invention has the beneficial effects that: the processing system adopted by the invention has a simple working principle, can realize filtering denoising and image enhancement processing on the hyperspectral imaging signal, improves the hyperspectral imaging quality and is convenient for real-time analysis of a background; the adopted filtering unit processing method samples the chrominance component, and the quality of an output image is improved under the condition of not increasing the complexity of a system; the adopted method for enhancing the imaging signal enhancement unit reduces the global brightness difference of the image, enhances the image contrast, effectively inhibits noise and further improves the definition of the image.
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FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "disposed," "connected," and the like are to be construed broadly, such as "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Referring to fig. 1-2, the present invention provides a technical solution: a hyperspectral imaging signal processing system comprises an imaging signal acquisition unit 1, a filtering unit 2, a central processing unit 3 and an imaging signal enhancement unit 4, wherein the imaging signal acquisition unit 1 acquires hyperspectral imaging signals, the imaging signal acquisition unit 1 is connected with the central processing unit 3 through the filtering unit 2, and the central processing unit 3 is connected with the imaging signal enhancement unit 4;
the imaging noise reduction device is characterized by further comprising a noise removal unit 5 and an imaging signal transmission unit 6, wherein the noise removal unit 5 is connected with the central processing unit 3, and the central processing unit 3 is further connected with a background terminal 7 through the imaging signal transmission unit 6.
The processing method comprises the following steps:
A. the imaging signal acquisition unit acquires a hyperspectral image;
B. the collected images are transmitted to a filtering unit for filtering processing, and the filtered images are transmitted to a central processing unit;
C. the central processing unit transmits the filtered image to a noise removing unit to remove noise interference signals;
D. then, the image is transmitted to an imaging signal enhancement unit to carry out enhancement processing on the processed image, and a high-definition hyperspectral image is obtained;
E. and finally, outputting the high-definition hyperspectral image to a background terminal.
The filtering unit processing method comprises the following steps:
a. acquiring a scaling configuration parameter and a chroma resampling configuration parameter of an image;
b. generating a brightness signal filter according to the zooming configuration parameters of the image;
c. generating a chrominance signal filter according to the chrominance resampling configuration parameters of the image;
d. and filtering a luminance signal of the input image by using a luminance signal filter, and filtering a chrominance signal of the input image by using a chrominance signal filter to obtain a filtered hyperspectral image.
In the invention, the noise removing unit in the step C adopts image interpolation function operation to process, wherein the function formula is as follows: c '═ a × T + D × (1-T), where C' denotes the output denoised image pixel, a denotes the current image pixel to be processed, T denotes the logical balance variable, and D denotes the noise smooth value of the current pixel to be processed.
In the invention, the enhancement method of the imaging signal enhancement unit is as follows:
a. dividing pixels of the collected hyperspectral image into a plurality of layers according to brightness values, dividing the layer brightness into 4 layers which are respectively 0-30%, 30-60%, 60-80% and 80-100%, wherein the brightness of each layer is different, and arranging each layer from high to low according to the brightness values;
b. for the image layer with the lowest brightness and the image layer with the largest brightness, namely the image layers of the two areas of 0-30% and 80% -100%, histogram equalization processing is carried out independently, namely, the brightness can be distributed on the histogram better through the histogram equalization; removing background noise and noise points by using a wavelet denoising method, and finally filtering the image by using a median filter;
c. removing noise points of the image layers between the lowest brightness and the highest brightness, then carrying out filtering processing, removing background noise, and finally carrying out histogram equalization processing;
d. and finally merging all the processed image layers into an image after image enhancement.
In conclusion, the processing system adopted by the invention has a simple working principle, can realize filtering and denoising and image enhancement processing on the hyperspectral imaging signals, improves the hyperspectral imaging quality and is convenient for real-time analysis of a background; the adopted filtering unit processing method samples the chrominance component, and the quality of an output image is improved under the condition of not increasing the complexity of a system; the adopted method for enhancing the imaging signal enhancement unit reduces the global brightness difference of the image, enhances the image contrast, effectively inhibits noise and further improves the definition of the image.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.

Claims (5)

1. A hyperspectral imaging signal processing system is characterized in that: the processing system comprises an imaging signal acquisition unit (1), a filtering unit (2), a central processing unit (3) and an imaging signal enhancement unit (4), wherein the imaging signal acquisition unit (1) acquires hyperspectral imaging signals, the imaging signal acquisition unit (1) is connected with the central processing unit (3) through the filtering unit (2), and the central processing unit (3) is connected with the imaging signal enhancement unit (4);
the device is characterized by further comprising a noise removing unit (5) and an imaging signal transmission unit (6), wherein the noise removing unit (5) is connected with the central processing unit (3), and the central processing unit (3) is further connected with a background terminal (7) through the imaging signal transmission unit (6).
2. The processing method for realizing the hyperspectral imaging signal processing system according to claim 1 is characterized in that: the processing method comprises the following steps:
A. the imaging signal acquisition unit acquires a hyperspectral image;
B. the collected images are transmitted to a filtering unit for filtering processing, and the filtered images are transmitted to a central processing unit;
C. the central processing unit transmits the filtered image to a noise removing unit to remove noise interference signals;
D. then, the image is transmitted to an imaging signal enhancement unit to carry out enhancement processing on the processed image, and a high-definition hyperspectral image is obtained;
E. and finally, outputting the high-definition hyperspectral image to a background terminal.
3. The processing method of the hyperspectral imaging signal processing system according to claim 2, characterized by: the filtering unit processing method comprises the following steps:
a. acquiring a scaling configuration parameter and a chroma resampling configuration parameter of an image;
b. generating a brightness signal filter according to the zooming configuration parameters of the image;
c. generating a chrominance signal filter according to the chrominance resampling configuration parameters of the image;
d. and filtering a luminance signal of the input image by using a luminance signal filter, and filtering a chrominance signal of the input image by using a chrominance signal filter to obtain a filtered hyperspectral image.
4. The processing method of the hyperspectral imaging signal processing system according to claim 2, characterized by: and C, processing by the noise removing unit by adopting image interpolation function operation, wherein the function formula is as follows: c '═ a × T + D × (1-T), where C' denotes the output denoised image pixel, a denotes the current image pixel to be processed, T denotes the logical balance variable, and D denotes the noise smooth value of the current pixel to be processed.
5. The processing method of the hyperspectral imaging signal processing system according to claim 2, characterized by: the imaging signal enhancement unit enhancement method is as follows:
a. dividing pixels of the collected hyperspectral image into a plurality of layers according to brightness values, dividing the layer brightness into 4 layers which are respectively 0-30%, 30-60%, 60-80% and 80-100%, wherein the brightness of each layer is different, and arranging each layer from high to low according to the brightness values;
b. for the image layer with the lowest brightness and the image layer with the largest brightness, namely the image layers of the two areas of 0-30% and 80% -100%, histogram equalization processing is carried out independently, namely, the brightness can be distributed on the histogram better through the histogram equalization; removing background noise and noise points by using a wavelet denoising method, and finally filtering the image by using a median filter;
c. removing noise points of the image layers between the lowest brightness and the highest brightness, then carrying out filtering processing, removing background noise, and finally carrying out histogram equalization processing;
d. and finally merging all the processed image layers into an image after image enhancement.
CN202011215852.4A 2020-11-04 2020-11-04 Hyperspectral imaging signal processing system and method Pending CN112381728A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113724312A (en) * 2021-08-13 2021-11-30 辽宁四季环境治理工程有限公司 Real-time monitoring and early warning method and device for geological disasters

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103916649A (en) * 2012-12-31 2014-07-09 展讯通信(上海)有限公司 Image processing method, apparatus and system
JP2014233415A (en) * 2013-05-31 2014-12-15 セイコーエプソン株式会社 Ultrasonic measurement apparatus, ultrasonic image apparatus, and ultrasonic image processing method
CN104732500A (en) * 2015-04-10 2015-06-24 天水师范学院 Traditional Chinese medicinal material microscopic image noise filtering system and method adopting pulse coupling neural network
CN106952246A (en) * 2017-03-14 2017-07-14 北京理工大学 The visible ray infrared image enhancement Color Fusion of view-based access control model attention characteristic
CN109886975A (en) * 2019-02-19 2019-06-14 武汉大学 It is a kind of that raindrop method and system is gone based on the image optimization processing for generating confrontation network
CN109975258A (en) * 2019-03-25 2019-07-05 武汉理工大学 A kind of micro-fluidic detection system of signal enhancing

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103916649A (en) * 2012-12-31 2014-07-09 展讯通信(上海)有限公司 Image processing method, apparatus and system
JP2014233415A (en) * 2013-05-31 2014-12-15 セイコーエプソン株式会社 Ultrasonic measurement apparatus, ultrasonic image apparatus, and ultrasonic image processing method
CN104732500A (en) * 2015-04-10 2015-06-24 天水师范学院 Traditional Chinese medicinal material microscopic image noise filtering system and method adopting pulse coupling neural network
CN106952246A (en) * 2017-03-14 2017-07-14 北京理工大学 The visible ray infrared image enhancement Color Fusion of view-based access control model attention characteristic
CN109886975A (en) * 2019-02-19 2019-06-14 武汉大学 It is a kind of that raindrop method and system is gone based on the image optimization processing for generating confrontation network
CN109975258A (en) * 2019-03-25 2019-07-05 武汉理工大学 A kind of micro-fluidic detection system of signal enhancing

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
苏俊英;舒宁;: "一种基于非线性增益小波滤波的高光谱影像去噪技术研究", 遥感技术与应用 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113724312A (en) * 2021-08-13 2021-11-30 辽宁四季环境治理工程有限公司 Real-time monitoring and early warning method and device for geological disasters

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Application publication date: 20210219