Image edge extraction method, image edge extraction device and storage medium

Abstract

The present disclosure relates to an image edge extraction method, an image edge extraction device and a storage medium. The image edge extraction method comprises: obtaining an image to be processed, and performing Fourier transform on the image to be processed to obtain the spectrum information of the image to be processed; modulating the spectrum information of the image to be processed based on a vortex filter to obtain the modulated spectrum information of the image to be processed, wherein the transmittance function of the vortex filter is obtained by modulating a composite vortex function based on a Bessel function; performing an inverse Fourier transform on the modulated spectrum information to obtain an edge image of the image to be processed. Through the embodiments of the present disclosure, high-contrast isotropic and anisotropic edge enhancement can be achieved for the image to be processed, thereby improving the processing effect of edge extraction.

Description

Technical Field

[0001] The present disclosure relates to the field of image processing technology, and in particular to an image edge extraction method, an image edge extraction device and a storage medium. Background Art

[0002] With the rapid development of science and technology, optical information and image processing technology have been deeply developed. Edge is the most basic feature of the image. Edge detection is an important part of image analysis and recognition, and is the key to dealing with many problems. Other features of the image are derived from the basic features such as edge and region. All information in the image can be restored through edge information. The effect of edge detection will directly affect the segmentation and recognition performance of the image. Image edge detection technology plays an important role in applications such as computer vision and image analysis.

[0003] There are many types of edge detection algorithms, such as differential operator method, template matching method, wavelet detection method, neural network method, etc. Although there are many edge detection and edge extraction methods in current technology, images processed by these methods have problems such as reduced contrast, low edge sharpness, and high background noise, which affect the effect of image edge detection. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides an image edge extraction method, an image edge extraction device and a storage medium.

[0005] According to one aspect of an embodiment of the present disclosure, there is provided an image edge extraction method, comprising: acquiring an image to be processed, and performing Fourier transform on the image to be processed to obtain frequency spectrum information of the image to be processed; modulating the frequency spectrum information of the image to be processed based on an eddy filter to obtain the modulated frequency spectrum information of the image to be processed, wherein a transmittance function of the eddy filter is obtained based on modulating a composite vortex function based on a Bessel function; and performing an inverse Fourier transform on the modulated frequency spectrum information to obtain an edge image of the image to be processed.

[0006] In one embodiment, the transmittance function of the vortex filter is obtained by modulating a superimposed vortex function based on a Bessel function in the following manner: determining a Bessel function based on a circular aperture function and a first-order second-order Bessel function; obtaining a composite vortex function based on the superposition of a positive vortex function and a negative vortex function; and obtaining the transmittance function of the vortex filter by modulating the composite vortex function based on the Bessel function.

[0007] In one embodiment, a Bessel function is determined based on a circular aperture function and a first type of second-order Bessel function, including: determining a first type of second-order Bessel function based on a vortex filter radius and an edge enhancement amplitude value modulation parameter, and determining a circular aperture function based on the vortex filter radius and a specified circular aperture; and determining the product between the first type of second-order Bessel function and the circular aperture function as a Bessel function.

[0008] In one embodiment, a composite vortex function is obtained based on the superposition of a positive vortex function and a negative vortex function, including: while keeping the topological charge parameter as a preset integer, constructing a positive vortex function and a negative vortex function respectively based on the filter polar angle and the set initial phase angle; multiplying one of the positive vortex function and the negative vortex function by a weighting factor, and performing weighted summation to obtain a composite vortex function.

[0009] In one embodiment, the frequency spectrum information of the image to be processed is modulated based on a vortex filter to obtain the modulated frequency spectrum information of the image to be processed, including: acquiring the image size of the image to be processed, and adjusting the radius of the vortex filter and / or the edge enhancement amplitude value based on the image size to obtain a frequency domain vortex filter that modulates the frequency spectrum information of the image to be processed, wherein the frequency domain vortex filter makes the extracted edge image meet the evaluation value of a preset point spread function; based on the frequency domain vortex filter, the frequency spectrum information of the image to be processed is modulated to obtain the modulated frequency spectrum information of the image to be processed.

[0010] According to another aspect of the embodiments of the present disclosure, there is provided an image edge extraction device, comprising: an acquisition module for acquiring an image to be processed; a transformation module for performing Fourier transform on the image to be processed to obtain frequency spectrum information of the image to be processed, and performing inverse Fourier transform on the modulated frequency spectrum information to obtain an edge image of the image to be processed; and a modulation module for modulating the frequency spectrum information of the image to be processed based on a vortex filter to obtain the modulated frequency spectrum information of the image to be processed, wherein the transmittance function of the vortex filter is obtained based on modulating a composite vortex function by a Bessel function.

[0011] In one embodiment, the transmittance function of the vortex filter is obtained by modulating a composite vortex function based on a Bessel function in the following manner: determining a Bessel function based on a circular aperture function and a first-order second-order Bessel function; obtaining a composite vortex function based on the superposition of a positive vortex function and a negative vortex function; and obtaining the transmittance function of the vortex filter by modulating the composite vortex function based on the Bessel function.

[0012] In one embodiment, a composite vortex function is obtained based on the superposition of a positive vortex function and a negative vortex function, including: while keeping the topological charge parameter as a preset integer, constructing a positive vortex function and a negative vortex function respectively based on the filter polar angle and the set initial phase angle; multiplying one of the positive vortex function and the negative vortex function by a weighting factor, and performing weighted summation to obtain a composite vortex function.

[0013] In one embodiment, a composite vortex function is obtained based on the superposition of a positive vortex function and a negative vortex function, including: while keeping the topological charge parameter as a preset integer, constructing a positive vortex function and a negative vortex function respectively based on the filter polar angle and the set initial phase angle; multiplying one of the positive vortex function and the negative vortex function by a weighting factor, and performing weighted summation to obtain a composite vortex function.

[0014] In one embodiment, the frequency spectrum information of the image to be processed is modulated based on a vortex filter to obtain the modulated frequency spectrum information of the image to be processed, including: acquiring the image size of the image to be processed, and adjusting the radius of the vortex filter and / or the polar angle edge enhancement amplitude value of the vortex filter based on the image size to obtain a frequency domain vortex filter that modulates the frequency spectrum information of the image to be processed, wherein the frequency domain vortex filter makes the extracted edge image meet the evaluation value of a preset point spread function; based on the frequency domain vortex filter, the frequency spectrum information of the image to be processed is modulated to obtain the modulated frequency spectrum information of the image to be processed.

[0015] According to another aspect of an embodiment of the present disclosure, there is provided an image edge extraction device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to: execute any one of the aforementioned image edge extraction methods.

[0016] According to another aspect of an embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal can execute any one of the aforementioned image edge extraction methods.

[0017] The technical solution provided by the embodiments of the present disclosure may include the following beneficial effects: obtaining spectral information of the image to be processed by performing Fourier transform on the image to be processed, modulating the spectral information of the image to be processed based on a vortex filter to obtain the modulated spectral information of the image to be processed, the transmittance function of the vortex filter is obtained by modulating the composite vortex function based on the Bessel function, and performing inverse Fourier transform on the modulated spectral information to obtain the edge image of the image to be processed, which can achieve high-contrast isotropic edge enhancement for the image to be processed, and can also enhance the anisotropic edge, thereby improving the processing effect of edge extraction.

[0018] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0020] Figure 1 A comparison chart showing the effects of image processing using the traditional method and the Laguerre-Gaussian modulated vortex filtering method.

[0021] Figure 2 A comparison chart showing the effects of image processing using the Laguerre-Gaussian modulated vortex filtering method and the Airy function modulated vortex method.

[0022] Figure 3a and Figure 3b A comparison of anisotropic edge enhancement effects based on Hilbert transform with different fractional values ​​and different radial displacements in different directions is shown.

[0023] Figure 4 The figure is a flow chart of a method for extracting image edges according to an exemplary embodiment of the present disclosure.

[0024] Figure 5 is a schematic diagram of a 4f imaging system according to an exemplary embodiment of the present disclosure.

[0025] Figure 6 It is a flow chart of a method for determining a transmittance function of a vortex filter according to an exemplary embodiment of the present disclosure.

[0026] Figure 7 It is a flow chart of a method for determining a Bessel vortex filter function in an image edge extraction method according to another exemplary embodiment of the present disclosure.

[0027] Figure 8 It is a flow chart of a method for determining a composite vortex function in an image edge extraction method according to another exemplary embodiment of the present disclosure.

[0028] Fig. 9 The figure is a flowchart of an image edge extraction method according to another exemplary embodiment of the present disclosure.

[0029] Fig.10 The figure is a schematic diagram of an application scenario of an image edge extraction method according to another exemplary embodiment of the present disclosure.

[0030] Fig.11 It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure.

[0031] Fig.12 It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure.

[0032] Fig.13 It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure.

[0033] Fig.14 It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure.

[0034] Fig.15 It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure.

[0035] Fig.16 It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure.

[0036] Fig.17 It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure.

[0037] Fig.18 The figure is a block diagram of an image edge extraction device according to an exemplary embodiment of the present disclosure.

[0038] Fig.19 It is a block diagram of a device according to an exemplary embodiment. DETAILED DESCRIPTION

[0039] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0040] Optical information and image processing technology have been deeply developed. Edge is the most basic feature of the image. Edge detection is an important part of image analysis and recognition, and is the key to dealing with many problems. Other features of the image are derived from the basic features such as edge and region. All information in the image can be restored through edge information. The effect of edge detection will directly affect the segmentation and recognition performance of the image. Image edge detection technology plays an important role in applications such as computer vision and image analysis.

[0041] There are many types of edge detection algorithms, such as differential operator method, template matching method, wavelet detection method, neural network method, and so on. Although there are many edge detection and edge extraction methods in the current technology, the images processed by these methods have problems such as reduced contrast, low edge sharpness, and high background noise.

[0042] In the current technology, the image edge detection method is based on the high-pass filtering method. The high-pass filtering method filters out the low-frequency information in the image while causing most of the energy to be lost, and is mainly used for isotropic edge extraction or detection. The Hilbert transform is sensitive to the complex refractive index gradient of object information, and enhances the image contrast when applied to image edge detection. The radial Hilbert transform is often applied to isotropic image edge enhancement technology. Anisotropy means having directionality. For example, for an image edge, taking a certain point as the center, the characteristics in each direction are different. On the contrary, it has no directionality, that is, isotropy.

[0043] In the isotropic edge extraction technology based on the Hilbert transform, there are the Laguerre-Gaussian modulated vortex filtering method and the Airy function modulated vortex filtering method. Among them, the Laguerre-Gaussian modulated vortex filter uses the Laguerre-Gaussian function for amplitude modulation to reduce the diffraction of the incident light by the central singularity. In this method, it is difficult for the Laguerre amplitude to eliminate the straight-edge diffraction phenomenon of the incident light by the sharp edge of the filter, and the sidelobe distribution in the point spread function is obvious.

[0044] Figure 1 A comparison diagram of the image processing effects of the traditional method and the Laguerre-Gaussian modulated vortex filtering method is shown. Among them, Figure 1 (a) shows the original image containing the Chinese character "mountain", Figure 1 (b) shows the image processed by the traditional vortex filtering method, Figure 1 (c) shows the image processed by the Laguerre-Gaussian modulated vortex filtering method,

[0045] In order to eliminate the sidelobes and improve the image contrast, the Airy function modulated vortex filter is proposed. The Airy function modulated vortex filter eliminates the sidelobes in the point spread function by changing the attenuation factor, so that the sharpness and contrast of the image edge are improved.

[0046] Figure 2 A comparison diagram of the image processing effects of the Laguerre-Gaussian modulated vortex filtering method and the Airy function modulated vortex method is shown. Among them, Figure 2 (a) shows the original image of the resolution class, Figure 2 (b) shows the image processed by the Laguerre-Gaussian modulated vortex filtering method, Figure 2 (c) shows the image processed by the Airy function modulated vortex filtering method, Figure 2 (d), Figure 2(e) and Figure 2 (f) are respectively along Figure 2 (a) Figure 2 (b) and Figure 2 (c) The dashed line is the intensity distribution curve.

[0047] In the anisotropic edge extraction technology based on Hilbert transform, the radial symmetry of the filtering process is broken, including the fractional vortex filtering method and the off-axis vortex filtering method. The fractional vortex filtering method breaks the radial symmetry of the filtering process, thereby producing a controllable edge dislocation, and changes the degree and direction of edge enhancement by controlling the size of the fractional order and the initial phase. As the fractional order decreases, the anisotropy in the image edge extraction is obvious, but the shadow effect will be increased.

[0048] The off-axis vortex filtering method obtains anisotropic edge enhancement effects in all directions by setting different angles and displacement parameters. In the above anisotropic edge extraction technology based on Hilbert transform, there is still an obvious shadow effect on the edge of the image after edge extraction, and a high-contrast edge detection effect cannot be obtained.

[0049] Figure 3a and Figure 3b A comparison of anisotropic edge enhancement effects based on Hilbert transform with different fractional values ​​and different radial displacements in different directions is shown.

[0050] In practical applications, different edge features need to be emphasized according to the scene, and anisotropic edge enhancement technology is needed to emphasize these edges. At the same time, achieving high-contrast isotropic and anisotropic edge detection is an urgent problem to be solved.

[0051] Therefore, the present disclosure provides an image edge extraction method for realizing high-contrast isotropic and anisotropic image edge extraction.

[0052] Figure 4 is a flowchart of an image edge extraction method according to an exemplary embodiment of the present disclosure. Figure 4 As shown, the image edge extraction method includes the following steps.

[0053] In step S101, an image to be processed is acquired, and Fourier transform is performed on the image to be processed to obtain frequency spectrum information of the image to be processed.

[0054] In step S102, the frequency spectrum information of the image to be processed is modulated based on a vortex filter to obtain the modulated frequency spectrum information of the image to be processed, wherein the transmittance function of the vortex filter is obtained by modulating the composite vortex function based on the Bessel function.

[0055] In step S103, an inverse Fourier transform is performed on the modulated frequency spectrum information to obtain an edge image of the image to be processed.

[0056] In the embodiment of the present disclosure, an image to be processed is obtained. The image to be processed may be acquired by an image acquisition device or may be downloaded, received and saved through a network.

[0057] The image edge extraction method in the embodiment of the present disclosure can be implemented based on a 4f imaging system. Figure 5 is a schematic diagram of a 4f imaging system according to an exemplary embodiment of the present disclosure.

[0058] like Figure 5 As shown, o(r0, θ0) represents the object plane, O(ρ, φ) represents the Fourier plane, and o′(r0, θ0) represents the image plane. The object plane and the Fourier plane are located at the front focal plane and the back focal plane of the lens L1, respectively, and the image plane is located at the back focal plane of the lens L2. The vortex filter is set at the Fourier plane, and the spectrum information on the Fourier plane is modulated by the vortex filter. Figure 5 In the system shown, the vortex filter is set in the Fourier plane to realize the Hilbert transform.

[0059] The object information of the image to be processed is Fourier transformed through lens L1, and the object spectrum information F[o(r0, θ0)] is obtained on the Fourier plane, where the symbol F[] represents Fourier transform. After the Fourier plane is modulated by the designed filter, the modulated spectrum information is inversely Fourier transformed to obtain the edge image of the image to be processed.

[0060] The modulated object spectrum information is expressed by multiplying the object spectrum by the filter transmittance function T(ρ, φ), as shown in the following formula.

[0061] O(ρ,φ)=F[o(r0,θ0)]×T(ρ,φ)

[0062] The transmittance function T(ρ, φ) of the vortex filter is obtained by modulating the composite vortex function based on the Bessel function.

[0063] According to the embodiments of the present disclosure, the spectrum information of the image to be processed is obtained by performing Fourier transform on the image to be processed, the spectrum information of the image to be processed is modulated based on the vortex filter to obtain the modulated spectrum information of the image to be processed, the transmittance function of the vortex filter is obtained by modulating the composite vortex function based on the Bessel function, the modulated spectrum information is inversely Fourier transformed to obtain the edge image of the image to be processed, high-contrast anisotropic edge enhancement can be achieved for the image to be processed, and the processing effect of edge extraction can be improved.

[0064] Figure 6FIG. 1 is a flow chart showing a method for determining a transmittance function of a vortex filter according to an exemplary embodiment of the present disclosure. Figure 6 As shown, the transmittance function determination method includes the following steps.

[0065] In step S201 , a Bessel function is determined based on a circular aperture function and a first-kind second-order Bessel function.

[0066] In step S202, a composite vortex function is obtained based on the superposition of the positive vortex function and the negative vortex function.

[0067] In step S203, the composite vortex function is modulated based on the Bessel function to obtain a transmittance function of the vortex filter.

[0068] In the embodiment of the present disclosure, the transmittance function of the vortex filter is obtained based on modulating the composite vortex function by the Bessel function, and the transmittance function T(ρ, φ) can be expressed by the following formula.

[0069]

[0070] where J2 is the second-order Bessel function of the first kind, circl() is the circular aperture function, represents a circular aperture with a radius of R0. When |ρ| is greater than R0, the circular aperture function value is 0. That is, the Bessel function is determined based on the circular aperture function and the first-order second-order Bessel function, realizing the gradual change of the transmittance function T(ρ, φ), thereby reducing noise and improving contrast.

[0071] In the disclosed embodiment, the composite vortex function is obtained based on the superposition of the positive vortex function and the negative vortex function. As shown in the above formula, the composite vortex function is exp[il(φ+φ0)]+exp[-il(φ+φ0)], wherein exp[il(φ+φ0)] represents the positive vortex function and exp[-il(φ+φ0)] represents the negative vortex function. The composite vortex function of the positive vortex function and the negative vortex function realizes the isotropic edge extraction or anisotropic edge extraction of the processed image. Based on the Bessel function modulation of the composite vortex function, the transmittance function of the vortex filter is obtained.

[0072] According to the embodiments of the present disclosure, by modulating the composite vortex function with the Bessel function to obtain the transmittance function of the vortex filter, high contrast and isotropic or anisotropic edge enhancement can be achieved for the processed image, thereby improving the sharpness and contrast of the image edge and improving the image processing effect of edge extraction.

[0073] Figure 7 FIG. 1 is a flow chart of a method for determining a Bessel vortex filter function in an image edge extraction method according to another exemplary embodiment of the present disclosure. Figure 7As shown, the method for determining the Bessel vortex filter function includes the following steps.

[0074] In step S301 , a first-order second-order Bessel function is determined based on the vortex filter radius and the edge enhancement amplitude value modulation parameter, and a circular aperture function is determined based on the vortex filter radius and the specified circular aperture.

[0075] In step S302, the product of the first kind of second-order Bessel function and the circular aperture function is determined as the Bessel function.

[0076] In the disclosed embodiment, the circular aperture function In , ρ is the vortex filter radius, R0 is the specified circular aperture, and the circular aperture function is determined based on the vortex filter radius ρ and the specified circular aperture R0. α is the edge enhancement amplitude modulation parameter, and the first-order second-order Bessel function J2 is determined based on the vortex filter radius R0 and the edge enhancement amplitude modulation parameter. The product between the first-order second-order Bessel function J2 and the circular aperture function ciccl() is determined as the Bessel function, realizing the gradual change of the transmittance function T(ρ, φ), thereby reducing noise, improving contrast, and realizing higher contrast edge detection and extraction.

[0077] According to an embodiment of the present disclosure, by modulating a composite vortex function with a composite Bessel function to obtain a transmittance function of a vortex filter, high contrast and isotropic or anisotropic edge enhancement can be achieved for the processed image, thereby further improving the sharpness and contrast of the image edge.

[0078] Figure 8 FIG. 1 is a flow chart of a method for determining a composite vortex function in an image edge extraction method according to another exemplary embodiment of the present disclosure. Figure 8 As shown, the method for determining the composite vortex function includes the following steps.

[0079] In step S401, while keeping the topological charge parameter as a preset integer, a positive vortex function and a negative vortex function are constructed based on the filter polar angle and the set initial phase angle.

[0080] In step S402, one of the positive vortex function and the negative vortex function is multiplied by a weighting factor and then weighted summed to obtain a composite vortex function.

[0081] In the disclosed embodiment, the composite vortex function is obtained based on the superposition of the positive vortex function and the negative vortex function, and the positive vortex function and the negative vortex function are constructed respectively based on the filter polar angle and the set initial phase angle. The composite vortex function, namely cexp[il(φ+φ0)]+exp[-il(φ+φ0)], wherein l represents the topological charge number parameter, and l is an integer. Exemplarily, the topological charge number parameter l can take the value of 1, the filter polar angle φ, 0≤φ<2π. The set initial phase angle φ0 is used to control the direction of edge enhancement. The initial phase φ0 is set to different angle values ​​to control the edge enhancement in different directions. For example, the initial phase angle φ0 can be 0, π / 4, π / 2 and 3π / 4. The weighting factor c is used to represent the weight ratio of the positive vortex and the negative vortex, and the amplitude of the edge enhancement varies with the numerical value of the weighting factor c. For example, when c=0, isotropic edge enhancement is obtained by the filter.

[0082] According to the embodiments of the present disclosure, a positive vortex function and a negative vortex function are respectively constructed based on the filter polar angle and the set initial phase angle. After multiplying one of the positive vortex function and the negative vortex function by a weighting factor, weighted summation is performed to obtain a composite vortex function, thereby achieving isotropic or anisotropic edge enhancement in different directions and with different enhancement amplitudes, and achieving better edge image extraction effect on the processed image.

[0083] Fig. 9 FIG. 1 is a flowchart of an image edge extraction method according to another exemplary embodiment of the present disclosure. Fig. 9 As shown, the image edge extraction method includes the following steps.

[0084] In step S501, the image size of the image to be processed is obtained, and the radius of the vortex filter and / or the edge enhancement amplitude value are adjusted based on the image size to obtain a frequency domain vortex filter that modulates the frequency spectrum information of the image to be processed, wherein the frequency domain vortex filter makes the extracted edge image meet the evaluation value of a preset point spread function.

[0085] In step S502, the frequency spectrum information of the image to be processed is modulated based on the frequency domain vortex filter to obtain the modulated frequency spectrum information of the image to be processed.

[0086] In the embodiment of the present disclosure, the image size of the image to be processed is obtained, including the size of the image to be processed, that is, the number of pixels, and the pixel size of the image to be processed. The vortex filter radius and / or the edge enhancement amplitude value are adjusted based on the image size, that is, the formula In the method, based on the image size of the image to be processed, α and / or ρ are adjusted to obtain a frequency domain vortex filter that modulates the spectrum information of the image to be processed, so as to achieve a gradual change of the transmittance function T(ρ, φ), reduce noise, and improve contrast.

[0087] Through Fourier transform, the point spread function of the 4f system in polar coordinates can be expressed as:

[0088]

[0089] Among them, (r1, θ1) represents the polar coordinates on the image plane, f2 is the focal length of lens L2, and J1 is the first-order Bessel function of the first kind. The extracted edge image meets the evaluation value of the preset point spread function, that is, the spectrum information of the image to be processed is modulated based on the frequency domain vortex filter to obtain the modulated spectrum information of the image to be processed, the energy is more concentrated on the main lobe located in the center, and the sidelobe noise is better suppressed.

[0090] According to an embodiment of the present disclosure, by adjusting the vortex filter radius and / or the edge enhancement amplitude value based on the acquired image size of the image to be processed, a frequency domain vortex filter that modulates the frequency spectrum information of the image to be processed is obtained, and the frequency spectrum information of the image to be processed is modulated based on the frequency domain vortex filter to obtain the modulated frequency spectrum information of the image to be processed. The frequency domain vortex filter makes the extracted edge image meet the evaluation value of a preset point spread function, thereby realizing edge extraction of images to be processed of different image sizes based on an adaptive vortex filter.

[0091] Fig.10 The figure is a schematic diagram of an application scenario of an image edge extraction method according to another exemplary embodiment of the present disclosure.

[0092] For example, a 532nm single-mode solid-state laser with a power of 300mw is used as the light source, which is expanded and collimated, and the information of the object is amplified through the objective lens and lens L1. An aperture is set between lens L1 and lens L2 to block the remaining diffracted light. Lenses L2 and L3 constitute a 4f imaging system, which performs Fourier transform and inverse Fourier transform respectively. The spatial light modulator is placed on the rear focal plane of lens L2, loads the hologram, and modulates the spectrum information of the object. The complex amplitude of the vortex filter is encoded into a hologram by the method of blazed grating, and the modulated complex amplitude can be obtained in the positive first-order diffraction of the fork grating. Under the reflection of the spatial light modulator and the beam splitter, the first-order diffraction beam is Fourier transformed through lens L3, and the output image is recorded on the camera on the focal plane. The loaded hologram and the recorded image results are controlled by a computer.

[0093] In one embodiment of the present invention, simulations are performed using fractional vortex filtering, off-axis vortex filtering, conventional superposition vortex filtering, Laguerre-Gaussian modulated superposition vortex filtering, and the point spread function of the vortex filter obtained by modulating the composite vortex function based on the Bessel function of the present invention.

[0094] Fig.11It is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure. Fig.11 a1-e1 are the point spread functions of fractional vortex filtering, off-axis vortex filtering, conventional superposition vortex filtering, Laguerre-Gaussian modulation superposition vortex filtering and Bessel modulation superposition vortex filtering, respectively. Fig.11 a2-e2 are the radial cross-sectional intensity distributions of the point spread functions drawn in a1-e1, respectively. The maximum values ​​are normalized to obtain the amplitude curves of the radial cross-sections.

[0095] Reference Fig.11 , the intensity distribution of the point spread function of the fractional vortex filter and the off-axis vortex filter is asymmetric, and there are strong redundant side lobes in the above filters. The point spread function of the conventional superposition vortex filter maintains radial symmetry, but the redundant side lobes are still obvious. In the Laguerre-Gaussian modulated superposition vortex filter, the side lobes of the point spread function are partially suppressed. The filter disclosed in the present invention can effectively suppress the side lobes and maintain the radial symmetry of the filtering process. The energy is more concentrated on the main lobe, and the side lobe noise is better suppressed.

[0096] In one embodiment of the present disclosure, fractional vortex filtering, off-axis vortex filtering, conventional superposition vortex filtering, Laguerre-Gaussian modulation superposition vortex filtering and the Bessel function-based superposition vortex function of the present disclosure are used to compare the effects of edge detection or extraction.

[0097] Fig.12 is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure. Fig.12 a1-e1 are the simulation results of fractional vortex filtering, off-axis vortex filtering, conventional superposition vortex filtering, Laguerre-Gaussian modulation superposition vortex filtering and Bessel modulation superposition vortex filtering respectively. Fig.12 a2-e2 are respectively along Fig.12 The intensity cross section of the dashed lines in a1-e1 is step-by-step.

[0098] Reference Fig.12 , the application of fractional vortex filter and off-axis vortex filter, because the symmetry of the filtering process is destroyed, the shadow effect becomes serious. There are side lobes in the processing results of fractional vortex filter, off-axis vortex filter and conventional superposition vortex filter, and the background noise is significant. Laguerre Gaussian modulated superposition vortex filter can change the amplitude of the singular point, block the diffracted light from the singular point, and detect or extract edges with higher contrast than traditional superposition vortex filters. The contrast of the conventional superposition vortex filter is only 0.62, and the contrast of the image edge extraction method of the embodiment of the present disclosure is 0.98, which has good performance in reducing background noise and improving imaging resolution and contrast.

[0099] In the first embodiment of the present invention, the initial phase angle φ0 is set to different angle values ​​to control edge enhancement in different directions. When the weighting factor c is equal to 1, edge enhancement in different directions can be obtained by setting the initial phase angle φ0 to 0, π / 4, π / 2, and 3π / 4. By changing the value of the weighting factor c to adapt to the situation in the actual application process, anisotropic edges can be detected or extracted with varying power. For example, φ0 is set to π / 2, and the value of the weighting factor c is changed from 0 to 1 to achieve a change in the amplitude of edge enhancement in the horizontal direction.

[0100] Fig.13 is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure. Fig.13 (a)-(d) are the simulation results when the initial phase angle φ0 is set to 0, π / 4, π / 2 and 3π / 4 respectively.

[0101] Fig.14 is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure. Fig.14 (a)-(e) show the simulation results when φ0 is set to π / 2 and different values ​​of the weighting factor c. In (a)-(e), the values ​​of the weighting factor c are 0, 0.3, 0.5, 0.7 and 1 respectively. Fig.14 (f) Yes Fig.10 (a)-(e) Intensity distribution along the dashed line.

[0102] Fig.15 is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure. Fig.15 (a) and (b) are the experimental results of using conventional superposition vortex filtering and applying the vortex filter function of the embodiment of the present disclosure, respectively. (c) and (d) are the intensity cross-sectional distributions along the dotted lines of (a) and (b), respectively. Fig.15 The object in the middle is the letters "AF".

[0103] Fig.16 is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure. Fig.16 (a)-(d) are the anisotropic edge enhancement effects of the letter "1X", and (e)-(h) are the anisotropic edge enhancement effects of four ancient coins.

[0104] Fig.17 is a rendering of an image edge extraction method according to an exemplary embodiment of the present disclosure. Fig.17 (a)-(e) show the experimental results when the vortex filter function of the embodiment of the present disclosure is applied, φ0 is set to π / 2 and the weighting factor c has different values, Fig.17 (f) is the intensity distribution along the dotted line from (a) to (e), and the object is the letters “AF”.

[0105] Based on the same concept, an embodiment of the present disclosure also provides an image edge extraction device.

[0106] It is understandable that in order to realize the above functions, the image edge extraction device provided by the embodiment of the present disclosure includes hardware structures and / or software modules corresponding to the execution of each function. In combination with the units and algorithm steps of each example disclosed in the embodiment of the present disclosure, the embodiment of the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the technical solution of the embodiment of the present disclosure.

[0107] Fig.18 FIG. 1 is a block diagram of an image edge extraction device according to an exemplary embodiment. Fig.18 The image edge extraction device 100 includes an acquisition module 101, a transformation module 102 and a modulation module 103.

[0108] The acquisition module 101 is used to acquire the image to be processed.

[0109] The transform module 102 is used to perform Fourier transform on the image to be processed to obtain the frequency spectrum information of the image to be processed, and to perform inverse Fourier transform on the modulated frequency spectrum information to obtain the edge image of the image to be processed.

[0110] The modulation module 103 is used to modulate the frequency spectrum information of the image to be processed based on the vortex filter to obtain the modulated frequency spectrum information of the image to be processed, wherein the transmittance function of the vortex filter is obtained by modulating the composite vortex function based on the Bessel function.

[0111] In one embodiment, the transmittance function of the vortex filter is obtained by modulating a composite vortex function based on a Bessel function in the following manner: determining a Bessel function based on a circular aperture function and a first-order second-order Bessel function; obtaining a composite vortex function based on the superposition of a positive vortex function and a negative vortex function; and obtaining a transmittance function of the vortex filter by modulating the composite vortex function based on the Bessel function.

[0112] In one embodiment, a composite vortex function is obtained based on the superposition of a positive vortex function and a negative vortex function, including: while keeping the topological charge parameter as a preset integer, constructing a positive vortex function and a negative vortex function respectively based on the filter polar angle and the set initial phase angle; multiplying one of the positive vortex function and the negative vortex function by a weighting factor, and performing weighted summation to obtain a composite vortex function.

[0113] In one embodiment, a composite vortex function is obtained based on the superposition of a positive vortex function and a negative vortex function, including: while keeping the topological charge parameter as a preset integer, constructing a positive vortex function and a negative vortex function respectively based on the filter polar angle and the set initial phase angle; multiplying one of the positive vortex function and the negative vortex function by a weighting factor, and performing weighted summation to obtain a composite vortex function.

[0114] In one embodiment, the frequency spectrum information of the image to be processed is modulated based on a vortex filter to obtain the modulated frequency spectrum information of the image to be processed, including: obtaining the image size of the image to be processed, and adjusting the vortex filter radius and / or the vortex filter polar angle edge enhancement amplitude value based on the image size to obtain a frequency domain vortex filter that modulates the frequency spectrum information of the image to be processed, wherein the frequency domain vortex filter makes the extracted edge image meet the evaluation value of a preset point spread function; based on the frequency domain vortex filter, the frequency spectrum information of the image to be processed is modulated to obtain the modulated frequency spectrum information of the image to be processed.

[0115] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0116] Fig.19 8 is a block diagram of an image edge extraction device 800 according to an exemplary embodiment. For example, the device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0117] Reference Fig.19 , the device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0118] The processing component 802 generally controls the overall operation of the device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0119] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0120] The power component 806 provides power to the various components of the device 800. The power component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 800.

[0121] The multimedia component 808 includes a screen that provides an output interface between the device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0122] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the device 800 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0123] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0124] The sensor assembly 814 includes one or more sensors for providing various aspects of the status assessment of the device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the device 800, and the sensor assembly 814 can also detect the position change of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration / deceleration of the device 800, and the temperature change of the device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0125] The communication component 816 is configured to facilitate wired or wireless communication between the device 800 and other devices. The device 800 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0126] In an exemplary embodiment, the apparatus 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0127] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by the processor 820 of the device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0128] It is to be understood that in the present disclosure, "plurality" refers to two or more than two, and other quantifiers are similar. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. The singular forms "a", "the" and "the" are also intended to include plural forms, unless the context clearly indicates other meanings.

[0129] It is further understood that the terms "first", "second", etc. are used to describe various information, but such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other, and do not indicate a specific order or degree of importance. In fact, the expressions "first", "second", etc. can be used interchangeably. For example, without departing from the scope of the present disclosure, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information.

[0130] It can be further understood that, unless otherwise specified, “connection” includes a direct connection without other components between the two, and also includes an indirect connection with other components between the two.

[0131] It is further understood that, although the operations are described in a specific order in the drawings in the embodiments of the present disclosure, it should not be understood as requiring the operations to be performed in the specific order shown or in a serial order, or requiring the execution of all the operations shown to obtain the desired results. In certain environments, multitasking and parallel processing may be advantageous.

[0132] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0133] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for extracting image edges, characterized in that: include: Acquire an image to be processed, and perform Fourier transform on the image to be processed to obtain frequency spectrum information of the image to be processed; Modulating the frequency spectrum information of the image to be processed based on a vortex filter to obtain the modulated frequency spectrum information of the image to be processed, wherein the transmittance function of the vortex filter is obtained by modulating a composite vortex function based on a Bessel function; Performing inverse Fourier transform on the modulated frequency spectrum information to obtain an edge image of the image to be processed.

2. The image edge extraction method according to claim 1, characterized in that: The transmittance function of the vortex filter is obtained by modulating the composite vortex function based on the Bessel function in the following manner: Determine a Bessel function based on a circular aperture function and a second-order Bessel function of the first kind; Based on the superposition of positive vortex function and negative vortex function, a composite vortex function is obtained; The composite vortex function is modulated based on the Bessel function to obtain a transmittance function of the vortex filter.

3. The image edge extraction method according to claim 2, characterized in that: Based on the circular aperture function and the second-order Bessel function of the first kind, the Bessel function is determined, including: Determine a first kind second order Bessel function based on the vortex filter radius and the edge enhancement amplitude value modulation parameter, and determine a circular aperture function based on the vortex filter radius and the specified circular aperture; The product of the first-type second-order Bessel function and the circular aperture function is determined as a Bessel function.

4. The image edge extraction method according to claim 2 or 3, characterized in that: Based on the superposition of positive vortex function and negative vortex function, a composite vortex function is obtained, including: While keeping the topological charge parameter as a preset integer, a positive vortex function and a negative vortex function are constructed based on the filter polar angle and the set initial phase angle. After multiplying one of the positive vortex function and the negative vortex function by a weighting factor, a weighted sum is performed to obtain a composite vortex function.

5. The image edge extraction method according to claim 4, characterized in that: Modulating the frequency spectrum information of the image to be processed based on the vortex filter to obtain the modulated frequency spectrum information of the image to be processed, including: Acquiring the image size of the image to be processed, and adjusting the radius of the vortex filter and / or the edge enhancement amplitude value based on the image size, to obtain a frequency domain vortex filter that modulates the frequency spectrum information of the image to be processed, wherein the frequency domain vortex filter enables the extracted edge image to meet the evaluation value of a preset point spread function; The frequency spectrum information of the image to be processed is modulated based on the frequency domain vortex filter to obtain the modulated frequency spectrum information of the image to be processed.

6. An image edge extraction device, characterized in that: include: An acquisition module, used for acquiring an image to be processed; A transformation module, used for performing Fourier transformation on the image to be processed to obtain the frequency spectrum information of the image to be processed, and performing inverse Fourier transformation on the modulated frequency spectrum information to obtain the edge image of the image to be processed; The modulation module is used to modulate the frequency spectrum information of the image to be processed based on a vortex filter to obtain the modulated frequency spectrum information of the image to be processed, wherein the transmittance function of the vortex filter is obtained based on modulating a composite vortex function by a Bessel function.

7. The image edge extraction device according to claim 6, characterized in that: The transmittance function of the vortex filter is obtained by modulating the composite vortex function based on the Bessel function in the following manner: Determine a Bessel function based on a circular aperture function and a second-order Bessel function of the first kind; Based on the superposition of positive vortex function and negative vortex function, a composite vortex function is obtained; The composite vortex function is modulated based on the Bessel function to obtain a transmittance function of the vortex filter.

8. The image edge extraction device according to claim 7, characterized in that: The modulation module determines the Bessel function based on the circular aperture function and the second-order Bessel function of the first kind in the following manner: Determine a first kind second order Bessel function based on the vortex filter radius and the edge enhancement amplitude value modulation parameter, and determine a circular aperture function based on the vortex filter radius and the specified circular aperture; The product of the first-type second-order Bessel function and the circular aperture function is determined as a Bessel function.

9. The image edge extraction device according to claim 7 or 8, characterized in that: The modulation module obtains a composite vortex function based on the superposition of a positive vortex function and a negative vortex function in the following manner: While keeping the topological charge parameter as a preset integer, a positive vortex function and a negative vortex function are constructed based on the filter polar angle and the set initial phase angle. After multiplying one of the positive vortex function and the negative vortex function by a weighting factor, a weighted sum is performed to obtain a composite vortex function.

10. The image edge extraction device according to claim 9, characterized in that: The modulation module modulates the frequency spectrum information of the image to be processed based on the vortex filter in the following manner to obtain the modulated frequency spectrum information of the image to be processed: Acquiring the image size of the image to be processed, and adjusting the radius of the vortex filter and / or the edge enhancement amplitude value based on the image size, to obtain a frequency domain vortex filter that modulates the frequency spectrum information of the image to be processed, wherein the frequency domain vortex filter enables the extracted edge image to meet the evaluation value of a preset point spread function; The frequency spectrum information of the image to be processed is modulated based on the frequency domain vortex filter to obtain the modulated frequency spectrum information of the image to be processed.

11. An image edge extraction device, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: execute the image edge extraction method described in any one of claims 1 to 5.

12. A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to execute the image edge extraction method according to any one of claims 1 to 5.

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