CN107481205B - Terahertz image stripe noise processing method and system - Google Patents
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Abstract
The invention relates to the field of imaging of terahertz detection arrays or infrared detection arrays, and discloses a terahertz image stripe noise processing method and system, which comprise the following contents: carrying out Fourier transform on the obtained terahertz image data to obtain a frequency domain graph representing the frequency domain characteristics of the terahertz image data; performing first band elimination filtering on the frequency domain graph to eliminate periodic noise in a frequency range where stripe noise exists; carrying out high-pass filtering on the frequency domain graph subjected to the first band elimination filtering, and using the frequency domain graph to attenuate or inhibit low-frequency components and highlight the residual stripe noise; performing second band elimination filtering on the frequency domain graph subjected to the high-pass filtering, wherein the second band elimination filtering is used for performing second band elimination filtering on the stripe noise which is not completely filtered by the first band elimination filtering; and the frequency domain graph subjected to the secondary band elimination filtering is subjected to inverse Fourier transform and converted into a time domain graph, so that the terahertz stripe noise can be effectively eliminated.
Description
Technical Field
The invention relates to the field of imaging of terahertz detection arrays or infrared detection arrays, in particular to a terahertz image stripe noise processing method and system.
Background
Terahertz radiation refers to electromagnetic waves with the frequency of 0.1 THz-10 THz, the wave band of the terahertz radiation is between microwave and infrared, and the terahertz radiation belongs to the category of far infrared electromagnetic radiation. The terahertz spectrum of a substance contains abundant physical and chemical information. Meanwhile, due to the characteristics of terahertz radiation, the terahertz radiation can be a complementary technology of a Fourier transform infrared light latent technology and an X-ray technology in many aspects, and the terahertz radiation has a wide development space in many basic research fields, industrial applications and military application fields. It also has great application potential in the fields of biology, medicine, microelectronics, agriculture and safety inspection. In addition, compared with low-frequency electromagnetic waves, the terahertz frequency is higher, and the terahertz frequency can be used as a communication carrier and can bear more information in unit time. The terahertz radiation has good directivity and can be used for short-distance directional secret communication in a battlefield. The terahertz imaging can also be used for obtaining higher spatial resolution, longer depth of field and the like.
However, due to the characteristics of terahertz radiation and long wavelength, interference fringe noise often appears when a terahertz detector is used for image acquisition, so that researchers have conducted a lot of researches on the interference fringe noise, but most of the interference fringe noise still is direct high-frequency filtering and cannot be used for filtering the interference noise in a targeted manner, and therefore the terahertz detector still has many defects. And because the density degree and direction of the fringes are uncertain during collection, the interference fringes are still difficult to remove.
Therefore, the stripe noise of the terahertz image cannot be effectively eliminated in the prior art.
Disclosure of Invention
The invention provides a terahertz image stripe noise processing method and system in order to solve the technical problem that the terahertz image stripe noise cannot be effectively eliminated in the prior art.
In order to solve the technical problems, the invention adopts a technical scheme that: a terahertz image stripe noise processing method comprises the following steps:
carrying out Fourier transform on the obtained terahertz image data to obtain a frequency domain graph representing the frequency domain characteristics of the terahertz image data;
performing first band elimination filtering on the frequency domain graph to eliminate periodic noise in a frequency range where stripe noise exists;
carrying out high-pass filtering on the frequency domain graph subjected to the first band elimination filtering, and using the frequency domain graph to attenuate or inhibit low-frequency components and highlight the residual stripe noise;
performing second band elimination filtering on the frequency domain graph subjected to the high-pass filtering, wherein the second band elimination filtering is used for performing second band elimination filtering on the stripe noise which is not completely filtered by the first band elimination filtering;
and (4) converting the frequency domain graph subjected to the second band elimination filtering into a time domain graph by adopting inverse Fourier transform.
In another aspect, a terahertz image stripe noise processing system is further provided, including:
the terahertz image data processing device comprises a Fourier transform module, a frequency domain analysis module and a processing module, wherein the Fourier transform module is used for carrying out Fourier transform on the terahertz image data to obtain a frequency domain image representing frequency domain characteristics of the terahertz image data;
the first band-stop filter is used for carrying out first band-stop filtering on the frequency domain graph and eliminating periodic noise in a frequency range where the stripe noise is located;
the frequency domain high-pass filter is used for carrying out high-pass filtering on the frequency domain image subjected to the first band elimination filtering, and is used for attenuating or inhibiting low-frequency components and highlighting residual stripe noise;
the second band elimination filter is used for carrying out second band elimination filtering on the frequency domain graph subjected to the high-pass filtering and carrying out second band elimination filtering on the stripe noise which is not completely filtered by the first band elimination filtering;
and the inverse Fourier transform module is used for converting the frequency domain graph subjected to the second band-stop filtering into a time domain graph by adopting inverse Fourier transform.
The invention has the beneficial effects that: unlike the prior art case:
according to the processing method of the terahertz image stripe noise, the acquired terahertz image data is subjected to Fourier transform, then a part of stripe noise is removed through first band elimination filtering, then high-pass filtering is carried out, the remaining stripe noise is filtered through second band elimination filtering, finally inverse Fourier transform is carried out, the terahertz image data is converted into a time domain image, and an image with finally filtered noise is obtained.
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FIG. 1 is a schematic flow chart illustrating steps of a terahertz image fringe noise processing method according to an embodiment of the present invention;
FIGS. 2a to 2f are diagrams illustrating the effect of the terahertz image fringe noise processing process in the embodiment of the present invention;
fig. 3 is a schematic block diagram of a terahertz image fringe noise processing system in an embodiment of the present invention.
Detailed Description
The invention provides a terahertz image stripe noise processing method and system, aiming at solving the technical problem that the stripe noise of a terahertz image cannot be effectively eliminated in the prior art, and further effectively eliminating the terahertz stripe noise.
In order to better understand the technical scheme of the invention, the technical scheme of the invention is described in detail in the following with the accompanying drawings and specific embodiments.
The terahertz image stripe noise processing method provided by the embodiment of the invention, as shown in fig. 1, includes: s101, carrying out Fourier transform on the acquired terahertz image data to obtain a frequency domain graph representing frequency domain characteristics of the terahertz image data; s102, performing first band elimination filtering on the frequency domain graph, and eliminating periodic noise in a frequency range where stripe noise exists; s103, performing high-pass filtering on the frequency domain graph subjected to the first band elimination filtering, and using the high-pass filtering to attenuate or inhibit low-frequency components and highlight the residual stripe noise; s104, performing second band elimination filtering on the frequency domain graph subjected to the high-pass filtering, and performing second band elimination filtering on the stripe noise which is not completely filtered by the first band elimination filtering; and S105, converting the frequency domain graph subjected to the second band elimination filtering into a time domain graph by adopting inverse Fourier transform.
In a specific embodiment, the acquired terahertz image data can be image data that has been acquired by the terahertz imaging system and stored in a memory, and is read out from the memory, or image data that is acquired by the terahertz external imaging system currently implemented, and a specific original image is shown in fig. 2 a.
Specifically, performing fourier transform on the acquired terahertz image data to obtain a frequency domain diagram representing frequency domain characteristics of the terahertz image data, specifically including: shifting the frequency spectrum of the acquired terahertz image data to an original point by adopting Fourier transform, so that the frequency distribution of the terahertz image is symmetrically distributed by taking the original point as a circle center; then, frequency distribution is obtained from the terahertz image after the Fourier transform, and besides the circle center bright point, a symmetrically distributed bright point set exists, wherein the bright point set is generated by interference noise and interference signals with a periodic rule.
The frequency spectrum is shifted to the circle center, the image frequency distribution can be clearly seen, the interference signals with the periodic rule can be separated, the spectrogram shifted to the original point can see that bright spot sets which are symmetrically distributed by taking a certain point as the center exist besides the circle center, the bright spot sets are generated by interference noise, and at the moment, the interference can be visually eliminated by placing the band elimination filter at the position. A specific frequency domain diagram obtained after fourier transform is shown in fig. 2 b.
Since the frequency domain range of the interference fringe noise can be seen in the frequency domain graph obtained in S101, in S102, a suitable first band-stop filter can be constructed, and a formula corresponding to the constructed first band-stop filter is multiplied by a formula corresponding to the terahertz image data after fourier transform, so as to filter most fringe noise components in the frequency domain.
The first band-stop filter is used for suppressing the frequency of a circular ring area with a certain distance from the center of a frequency domain, can be used for eliminating periodic noise in a certain frequency range, and selects the first band-stop filter for carrying out first band-stop filtering, and comprises the following specific steps:
the formula from this band stop filter is:
wherein D is0W is the bandwidth of the band-stop filter for the distance of the frequency point to be blocked from the frequency center, and D is the distance between the frequency point (u, v) and the center of the frequency domain for an image of size M N0(u, v) of the formula
H0(u, v) is the required band stop filter formula, when its value is 1, the band in this frequency domain is completely passed, and when its value is 0, the band in this frequency domain is completely filtered. According to the frequency domain range, the distance D between the frequency point to be blocked and the center of the frequency domain is obtained0And the wide band W of the band-stop filter. Thereby obtaining parameters of the first band pass filter.
Next, in S103, the frequency domain map subjected to the first band elimination filtering is subjected to high-pass filtering for attenuating or suppressing the low-frequency component and emphasizing the remaining streak noise. Specifically, the frequency domain map subjected to the first band-stop filtering is subjected to second-order high-pass filtering processing by using a Butterworth filter for attenuating or suppressing low-frequency components and highlighting remaining streak noise, specifically, the Butterworth filter is a filter type in a Fourier frequency domain, the gradient of a truncated part of a transfer function of the Butterworth filter can be controlled by an index n, the truncated part of the Butterworth filter of a lower order is not steep, and ringing effects can be reduced or avoided. The Butterworth filter is characterized in that a frequency response curve in a same frequency band is flat to the maximum extent and has no fluctuation, and the frequency response curve gradually drops to zero in a stop frequency band. On the bode diagram of logarithm of amplitude versus diagonal frequency, starting from a certain boundary angular frequency, the amplitude gradually decreases with the increase of angular frequency, and tends to be minus infinity, and the attenuation rate of the second-order butterworth filter is 12 decibels per frequency multiplication.
In particular, the transfer function of the Butterworth high-pass filter is
Wherein,D1for an image of size M N, the frequency point (u, v) is at a distance D from the center of the frequency domain1(u, v) of the formula
The frequency domain diagram after passing through the butterworth filter is shown in fig. 2c, it can be seen that some of the interference fringes are not filtered out, and the frequency domain range where the interference fringes are located can be found through the frequency domain diagram at this time, so as to facilitate filtering again.
Therefore, in S104, performing the second band-stop filtering on the frequency domain graph after the high-pass filtering, to perform the second band-stop filtering on the stripe noise that is not completely filtered by the first band-stop filtering, so as to obtain the structure shown in fig. 2D, where the second band-stop filter adopted by the second band-stop filtering also needs to be constructed, because the interference fringes are arranged closely in the first band-stop filtering process, and the photoelectric position on the frequency domain graph is closer to the center origin and has a larger diameter, the distance D between the selected frequency point to be blocked and the frequency center in the first band-stop filter is small, and the bandwidth W is large; in the second band elimination filtering process, the interference fringes are loosely arranged, the photoelectric position on the frequency domain graph is far away from the origin of the center, and the diameter is small, so that the distance D between the frequency point needing to be blocked and selected by the second band elimination filter and the frequency center is large, the bandwidth W value is small, specifically, the distance between the frequency point needing to be blocked and selected by the second band elimination filter and the frequency center is larger than the distance between the frequency point needing to be blocked and selected by the first band elimination filter and the frequency center, and the bandwidth of the second band elimination filter is smaller than that of the first band elimination filter.
Finally, S105 is executed, and the frequency domain map subjected to the second band-stop filtering is converted into a time domain map by using inverse fourier transform. As shown in particular in fig. 2 e.
It can be seen from fig. 2e that the contrast ratio of the image is relatively low, in order to emphasize the overall or local characteristics of the image, the original unclear image is made clear or some interesting features are emphasized, the difference between different object features in the image is enlarged, the uninteresting features are suppressed, the image quality and the information content are improved, the image interpretation and recognition effects are enhanced, and the requirements of some special analyses are met, so that after the time domain image is subjected to inverse fourier transform, the gray scale range is adjusted to obtain the image shown in fig. 2 f.
Specifically, the time domain graph is subjected to linear gray scale stretching in the gray scale range of 0-255. Specifically, when operating the pixel points in the image, the following is described by a formula:
g (x, y) ═ f (x, y) × h (x, y), where f (x, y) is the original image; h (x, y) is a spatial transfer function; g (x, y) represents the processed image. Thereby obtaining a final result graph.
The processed image not only eliminates the stripe noise, but also plays a role in image enhancement.
Based on the same inventive concept, an embodiment of the present invention further provides a terahertz image fringe noise processing system, as shown in fig. 3, including: the terahertz detection device comprises a Fourier transform module 301, a first band-stop filter 302, a frequency domain high-pass filter 303, a second band-stop filter 304 and an inverse Fourier transform module 305, wherein the Fourier transform module 301 is used for performing Fourier transform on the acquired terahertz image data to obtain a frequency domain graph representing frequency domain characteristics of the terahertz image data; the band-stop filtering device comprises a first band-stop filter 302, a frequency domain high-pass filter 303, a second band-stop filter 304 and an inverse Fourier transform module 305, wherein the first band-stop filter 302 is used for carrying out first band-stop filtering on a frequency domain image and eliminating periodic noise in a frequency range where the stripe noise is located, the frequency domain high-pass filter 303 is used for carrying out high-pass filtering on the frequency domain image subjected to the first band-stop filtering and is used for attenuating or inhibiting low-frequency components and highlighting the residual stripe noise, the second band-stop filter 304 is used for carrying out second band-stop filtering on the frequency domain image subjected to the high-pass filtering and carrying out second band-stop filtering on the stripe noise which is not completely filtered.
In this specific embodiment, the terahertz image fringe noise processing system further includes an image enhancement module 306, configured to adjust a gray scale range of the time domain image obtained by the inverse fourier transform module, so as to obtain an image enhanced image.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. A terahertz image stripe noise processing method is characterized by comprising the following steps:
carrying out Fourier transform on the obtained terahertz image data to obtain a frequency domain graph representing the frequency domain characteristics of the terahertz image data;
performing first band elimination filtering on the frequency domain graph to eliminate periodic noise in a frequency range where stripe noise exists;
carrying out high-pass filtering on the frequency domain graph subjected to the first band elimination filtering, and using the frequency domain graph to attenuate or inhibit low-frequency components and highlight the residual stripe noise;
performing second band elimination filtering on the frequency domain graph subjected to the high-pass filtering, wherein the second band elimination filtering is used for performing second band elimination filtering on the stripe noise which is not completely filtered by the first band elimination filtering;
and (4) converting the frequency domain graph subjected to the second band elimination filtering into a time domain graph by adopting inverse Fourier transform.
2. The terahertz image fringe noise processing method as claimed in claim 1, further comprising, after converting the frequency domain map subjected to the second band-stop filtering into a time domain map by using an inverse fourier transform, the method further comprising:
and adjusting the gray scale range of the time domain graph.
3. The method for processing the terahertz image fringe noise according to claim 1, wherein the performing fourier transform on the acquired terahertz image data to obtain a frequency domain map representing frequency domain characteristics of the terahertz image data specifically comprises:
shifting the frequency spectrum of the acquired terahertz image data to an original point by adopting Fourier transform, so that the frequency distribution of the terahertz image is symmetrically distributed by taking the original point as a circle center;
frequency distribution is obtained from the terahertz image after Fourier transformation, and besides the circle center bright spots, symmetrically distributed bright spot sets exist, wherein the bright spot sets are generated by interference noise and interference signals with a periodic rule.
4. The method for processing the terahertz image fringe noise according to claim 1, wherein the first band rejection filtering is performed on the frequency domain map, so as to eliminate periodic noise in a frequency range where the fringe noise exists, and specifically includes:
finding out bright spots symmetrical about the center of a frequency domain for the frequency domain graph, and determining a first band-stop filter which is required to be used and corresponds to first band-stop filtering;
the first band-stop filter is used for suppressing the frequency of a circular ring area with a preset distance from the center of a frequency domain, wherein the formula of the band-stop filter is as follows:
wherein D is0W is the bandwidth of the band-stop filter for the distance of the frequency point to be blocked from the frequency center, and D is the distance between the frequency point (u, v) and the center of the frequency domain for an image of size M N0(u, v) of the formula
And multiplying a formula corresponding to the first band-stop filter with a formula corresponding to the terahertz image data after Fourier transform, and filtering out periodic noise in a frequency domain range where the stripe noise is located.
5. The terahertz image fringe noise processing method as claimed in claim 1, wherein the high-pass filtering is performed on the frequency domain graph subjected to the first band elimination filtering, and is used for attenuating or suppressing the low-frequency component and highlighting the remaining fringe noise, specifically:
performing second-order high-pass filtering processing on the frequency domain graph subjected to the first band rejection filtering by using a Butterworth filter, wherein the second-order high-pass filtering processing is used for attenuating or inhibiting low-frequency components and highlighting residual stripe noise, and the transfer function formula of the Butterworth filter is specifically as follows:
wherein D is1For an image of size M N, the frequency point (u, v) is at a distance D from the centre of the frequency domain1(u, v) of the formula
6. The method for processing the terahertz image stripe noise according to claim 4, wherein a distance between a frequency point to be blocked and a frequency center of a second band elimination filter is greater than a distance between a frequency point to be blocked and a frequency center of a first band elimination filter, a bandwidth of the second band elimination filter is smaller than a bandwidth of the first band elimination filter, the second band elimination filter is adopted for the second band elimination filter, and the first band elimination filter is adopted for the first band elimination filter.
7. The method for processing the terahertz image fringe noise according to claim 2, wherein the time domain map is adjusted in a gray scale range, specifically:
and performing linear gray scale stretching on the time domain graph in a gray scale range of 0-255.
8. A terahertz image stripe noise processing system is characterized by comprising:
the terahertz image processing device comprises a Fourier transform module, a frequency domain analysis module and a processing module, wherein the Fourier transform module is used for carrying out Fourier transform on the acquired terahertz image data to obtain a frequency domain image representing frequency domain characteristics of the terahertz image data;
the first band-stop filter is used for carrying out first band-stop filtering on the frequency domain graph and eliminating periodic noise in a frequency range where the stripe noise is located;
the frequency domain high-pass filter is used for carrying out high-pass filtering on the frequency domain image subjected to the first band elimination filtering, and is used for attenuating or inhibiting low-frequency components and highlighting residual stripe noise;
the second band elimination filter is used for carrying out second band elimination filtering on the frequency domain graph subjected to the high-pass filtering and carrying out second band elimination filtering on the stripe noise which is not completely filtered by the first band elimination filtering;
and the inverse Fourier transform module is used for converting the frequency domain graph subjected to the second band-stop filtering into a time domain graph by adopting inverse Fourier transform.
9. The terahertz image fringe noise processing system of claim 8, further comprising:
and the image enhancement module is used for adjusting the gray scale range of the time domain image.
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| 基于频域滤波的THz图像条纹噪声处理;邹园园 等;《s计算机工程与应用》;20090611;第45卷(第17期);241-243 * |
| 连续太赫兹波图像去噪与对比度增强研究;陈霖;《中国优秀硕士学位论文全文数据库 信息科技辑》;20160115(第01期);I138-613 * |
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