A digital image wavelet base extraction method, system and storage medium

Abstract

This invention provides a method, system, and storage medium for wavelet basis extraction of digital images, belonging to the field of digital image data processing technology. The method includes: acquiring the PSF field, image tilt field, and amplitude sampling sequence covering a target image region, and establishing the spatial correspondence among the three; for each desired location within the target image region, extracting the PSF signal from the PSF field, extracting the image slope value, and constructing a sampling path along the slope direction in the PSF signal based on the slope value; performing amplitude superposition processing on the PSF signal along the slope direction to generate the wavelet basis function corresponding to the desired location; performing a one-dimensional convolution operation on the wavelet basis function and the amplitude sampling sequence along the vertical direction to generate a single-channel composite image corresponding to the desired location, and arranging all single-channel composite images according to their spatial positions to form the final image composite profile. This invention achieves an accurate method for wavelet basis extraction and digital image synthesis in digital images.

Description

Technical Field

[0001] This invention relates to the field of digital image processing technology, and more specifically to a method, system, and storage medium for wavelet basis extraction of digital images. Background Technology

[0002] Existing wavelet basis extraction and image synthesis techniques for digital images are primarily built upon the framework of traditional digital image processing. They typically assume that digital images satisfy a linear time-invariant convolution model, meaning the image signal is obtained by convolving a steady-state wavelet basis with an amplitude sampling sequence. Under this model assumption, commonly used wavelet basis extraction schemes include methods for estimating wavelet basis based on statistical properties and the minimum phase assumption method. These methods estimate globally or locally stable wavelets by analyzing the autocorrelation function or spectral characteristics of digital images and are widely used in digital image processing.

[0003] With the development of modern digital image processing technology, some existing techniques attempt to directly apply non-stationary digital image wavelet basis extraction methods to image processing, or assume that the wavelet basis is approximately invariant within a local spatial window, thereby achieving an approximate estimation of the wavelet basis function. However, since the image wavelet basis is significantly affected by changes in image morphology, its waveform is stretched or compressed with changes in spatial location. The above methods are difficult to accurately characterize the actual changes in the wavelet basis under complex conditions. To address the problem of wavelet basis non-stationarity in digital images, some existing techniques have proposed wavelet basis extraction methods based on time-frequency analysis, such as short-time Fourier transform, wavelet transform, and S-transform. These methods map the digital image to the joint time-frequency domain and analyze local spectral features to estimate the wavelet basis parameters at different locations. Some technical solutions also combine spectral decomposition or adaptive window function design to model the frequency variation characteristics of the image wavelet basis.

[0004] Although the above methods have expanded the applicability of traditional digital image wavelet basis extraction techniques to some extent, their wavelet basis estimation results usually depend on the time-frequency decomposition parameter settings, making it difficult to stably and accurately reflect the spatial variation characteristics of the image wavelet basis function in complex digital image processing. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, and storage medium for extracting wavelet basis of digital images, so as to at least solve the problem that existing technologies are unable to accurately characterize the spatial variation features of wavelet basis of digital images under complex conditions.

[0006] To achieve the above objectives, the first aspect of the present invention provides a digital image wavelet basis extraction method, the method comprising: acquiring a PSF field covering a target image region, an image tilt field, and an amplitude sampling sequence, and establishing a spatial correspondence among the three; for each desired location within the target image region, extracting a PSF signal from the PSF field, extracting a slope value from the image tilt field, and constructing a sampling path along the slope direction in the PSF signal based on the slope value; performing superposition processing on the PSF signal according to the sampling path to generate an image wavelet basis corresponding to the desired location; extracting the amplitude sampling sequence corresponding to the desired location, performing a one-dimensional convolution operation on the image wavelet basis and the amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the desired location, and arranging all single-channel composite images according to their spatial positions to form the final composite image result.

[0007] Optionally, the PSF field, image tilt field, and amplitude sampling sequence covering the target image region are acquired, and a spatial correspondence among the three is established. This includes: dividing the target image region into a preset grid sampling position set; spatially sampling the PSF field according to the grid sampling position set to generate a PSF signal set corresponding to each grid sampling position; spatially sampling the image tilt field according to the grid sampling position set to generate a slope value set corresponding to each grid sampling position; extracting the amplitude sampling sequence according to the grid sampling position set to generate an amplitude sampling sequence set corresponding to each grid sampling position; and establishing an index mapping relationship between the PSF signal set, the slope value set, and the amplitude sampling sequence set according to the same grid sampling position to form a spatial correspondence among the PSF field, the image tilt field, and the amplitude sampling sequence.

[0008] Optionally, the rule for extracting slope values ​​from the image tilt field is as follows: For each desired location within the target image region, read the tilt data corresponding to the desired location in the image tilt field, and determine an initial slope value based on the tilt data; extract tilt data from multiple neighboring sampling nodes within the neighborhood of the desired location, and calculate a local tilt consistency parameter based on the tilt data of the neighboring sampling nodes; when the local tilt consistency parameter meets a preset consistency condition, use the initial slope value as the slope value of the desired location; when the local tilt consistency parameter does not meet the preset consistency condition, perform a weighted average calculation based on the tilt data of the neighboring sampling nodes to generate a corrected tilt angle, and determine the slope value of the desired location based on the corrected tilt angle; when the desired location is not located at a tilt field sampling node, perform interpolation calculation based on the tilt data of the neighboring sampling nodes to generate corresponding tilt data, and determine the slope value based on the tilt data.

[0009] Optionally, constructing a sampling path along the slope direction in the PSF signal based on the slope value includes: using the spatial coordinates of the location to be determined in the PSF signal as the starting point of the path; determining the straight line direction passing through the starting point of the path based on the slope value, wherein the straight line direction is determined by the proportional relationship between the slope value and the depth direction; selecting sampling positions point by point in the PSF signal along the straight line direction according to a preset sampling interval to generate a discrete sampling point sequence; when the discrete sampling point sequence exceeds the effective range of the PSF signal, using the effective boundary of the PSF signal as the path termination position to obtain the sampling path along the slope direction.

[0010] Optionally, performing superposition processing on the PSF signal according to the sampling path to generate an image wavelet basis corresponding to the location to be determined includes: sequentially reading the amplitude value of each sampling point from the PSF signal according to the discrete sampling point sequence corresponding to the sampling path, and calculating the path distance of each sampling point relative to the location to be determined; constructing path weight coefficients based on the path distance and the direction parameter of the sampling path, and multiplying the amplitude value of each sampling point with the corresponding path weight coefficient to generate a weighted amplitude value; mapping the weighted amplitude value to a depth-oriented sample index position centered on the location to be determined according to the relative position of each sampling point in the sampling path; performing an accumulation operation on the weighted amplitude values ​​mapped to the same depth-oriented sample index position to generate a depth-oriented amplitude accumulation sequence; and using the depth-oriented amplitude accumulation sequence as the image wavelet basis corresponding to the location to be determined.

[0011] Optionally, the depth-direction amplitude sampling sequence of the location to be determined is extracted, and a one-dimensional convolution operation is performed between the image wavelet basis and the amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the location to be determined. This includes: extracting the amplitude sampling sequence corresponding to the location to be determined according to the spatial coordinates of the location to be determined; determining the corresponding depth sample interval at each depth sampling position of the amplitude sampling sequence according to the length of the image wavelet basis; at each depth sampling position, multiplying the amplitude values ​​of each depth sample of the image wavelet basis with the amplitude sampling values ​​of the corresponding depth positions within the depth sample interval and performing a summation operation; arranging the summation results corresponding to each depth sampling position in depth order to generate a single-channel composite image corresponding to the location to be determined.

[0012] Optionally, all single-channel composite images are arranged according to their spatial positions to form the final image composite result, including: establishing a set of spatial sampling positions corresponding to the target image region; writing the single-channel composite image corresponding to each position to be determined into the spatial sampling position set at the position corresponding to its spatial coordinates; spatially sorting all single-channel composite images according to the spatial coordinate arrangement order in the spatial sampling position set; and outputting all spatially sorted single-channel composite images as the final image composite result.

[0013] A second aspect of the present invention provides a digital image wavelet basis extraction system, the system comprising: a data acquisition unit, configured to acquire a PSF field, an image tilt field, and an amplitude sampling sequence covering a target image region, and establish a spatial correspondence among the three; a processing unit, configured to extract a PSF signal from the PSF field and a slope value from the image tilt field for each desired location within the target image region, and construct a sampling path along the slope direction in the PSF signal based on the slope value; a superposition unit, configured to perform superposition processing on the PSF signal according to the sampling path to generate an image wavelet basis corresponding to the desired location; and a combination unit, configured to extract the amplitude sampling sequence corresponding to the desired location, perform a one-dimensional convolution operation on the image wavelet basis and the amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the desired location, and arrange all single-channel composite images according to their spatial positions to form a final image synthesis result.

[0014] On the other hand, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described digital image wavelet basis extraction method.

[0015] Through the above technical solution, this invention establishes a spatial correspondence between the PSF field, the image tilt field, and the amplitude sampling sequence. It uses tilt information to determine the wavelet construction direction, superimposes the wavelet function along the slope direction in the PSF signal to generate an image wavelet basis consistent with the local construction direction, and further performs a one-dimensional convolution with the amplitude sampling sequence at the corresponding position to form a single-channel synthesized image, which is then aggregated into the final image synthesis result. This method introduces a construction direction constraint during the image wavelet basis construction process, causing the wavelet basis function to adaptively change with spatial position. It characterizes the spatial non-stationary features of the image wavelet basis from the image mechanism level, thereby improving the ability to express the spatial variation law of the image wavelet basis.

[0016] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of the steps of a digital image wavelet basis extraction method provided in one embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of the principle of digital image wavelet basis extraction provided by one embodiment of the present invention;

[0020] Figure 3 This is a flowchart of digital image wavelet basis extraction and final image synthesis provided by one embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of an image model provided in one embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram of a digital image result provided by one embodiment of the present invention;

[0023] Figure 6 This is a schematic diagram of a PSF field provided in one embodiment of the present invention;

[0024] Figure 7 This is a schematic diagram of the image tilt field provided by one embodiment of the present invention;

[0025] Figure 8 This is a schematic diagram of an image wavelet basis obtained by applying the digital image wavelet basis extraction method provided by this invention in one embodiment of the present invention;

[0026] Figure 9 This is a schematic diagram of an amplitude sampling sequence provided in one embodiment of the present invention;

[0027] Figure 10 This is a schematic diagram illustrating the application of the digital image wavelet basis extraction method provided by this invention to obtain the final image synthesis result according to one embodiment of the present invention;

[0028] Figure 11 This is a system structure diagram of a digital image wavelet basis extraction system provided in one embodiment of the present invention;

[0029] Figure 12 This is an internal structural diagram of a computer device provided in one embodiment of the present invention. Detailed Implementation

[0030] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0031] like Figure 1 As shown, embodiments of the present invention provide a method for wavelet basis extraction of digital images, the method comprising:

[0032] Step A1: Obtain the PSF (Point-Spread-Function) field, image tilt field, and amplitude sampling sequence covering the target image region, and establish the spatial correspondence among the three.

[0033] In this embodiment, the acquisition of the PSF field, image tilt field, and amplitude sampling sequence covering the target image region, and the establishment of a spatial correspondence among the three, includes: dividing the target image region into a preset grid sampling position set; spatially sampling the PSF field according to the grid sampling position set to generate a PSF signal set corresponding to each grid sampling position; spatially sampling the image tilt field according to the grid sampling position set to generate a slope value set corresponding to each grid sampling position; extracting the amplitude sampling sequence according to the grid sampling position set to generate an amplitude sampling sequence set corresponding to each grid sampling position; and establishing an index mapping relationship between the PSF signal set, the slope value set, and the amplitude sampling sequence set according to the same grid sampling position to form a spatial correspondence between the PSF field, the image tilt field, and the amplitude sampling sequence.

[0034] The target image region is defined by the spatial extent of the digital image, and this region has a clear sampling interval in both the horizontal and depth directions. Based on this sampling interval, the target image region is divided into a preset set of grid sampling positions. Each grid sampling position includes corresponding planar coordinates and depth coordinates, thus forming a regularly arranged spatial sampling framework.

[0035] The PSF field is spatially sampled according to the grid sampling location set. For PSF data located at the sampling node location, the corresponding PSF signal can be directly read. For locations that do not completely coincide with the PSF sampling node, neighboring PSF sampling points are selected, and the corresponding PSF signal is calculated through interpolation. This embodiment uses a four-point interpolation method to ensure the continuity and stability of the PSF signal in spatial distribution. After the above processing, a PSF signal set corresponding one-to-one with each grid sampling location is formed.

[0036] The image tilt field is also spatially sampled according to the same set of grid sampling locations. For each grid sampling location, the tilt data corresponding to that location is read, and the corresponding slope value is obtained by converting the tilt data, generating a set of slope values ​​that correspond one-to-one with each grid sampling location. The amplitude sampling sequence is also extracted according to the corresponding grid sampling locations, that is, the corresponding amplitude sampling sequence is read along the depth direction at each grid sampling location to form a set of amplitude sampling sequences.

[0037] The PSF signal set, slope value set, and amplitude sampling sequence set are all indexed and mapped based on the same grid sampling positions. Specifically, each grid sampling position corresponds to a unique PSF signal, a unique slope value, and a unique amplitude sampling sequence, and they are associated through the same spatial index. This forms a spatial correspondence between the PSF field, the tilt field, and the amplitude sampling sequence. This spatial correspondence allows for direct location of the corresponding PSF signal, slope value, and amplitude sampling sequence when performing image wavelet basis construction and one-dimensional convolution operations on any desired position, using the spatial index.

[0038] Step A2: For each location to be determined within the target image region, extract the PSF signal from the PSF field, extract the slope value from the tilt field, and construct a sampling path along the slope direction in the PSF signal based on the slope value.

[0039] In this embodiment, when extracting the PSF signal from the PSF field, the corresponding PSF data is read from the PSF field according to the spatial coordinates of the location to be determined. When the location to be determined is not located at a PSF sampling node, the PSF signal corresponding to that location can be obtained by interpolation based on adjacent PSF samples. The calculation of the PSF field can be performed using point spread function methods under existing image processing frameworks, such as based on image operator responses or numerical simulations. The specific calculation rules are existing technologies and will not be elaborated here.

[0040] Optionally, the rule for extracting slope values ​​from the image tilt field is as follows: For each desired location within the target image region, read the tilt data corresponding to the desired location in the image tilt field, and determine an initial slope value based on the tilt data; extract tilt data from multiple neighboring sampling nodes within the neighborhood of the desired location, and calculate a local tilt consistency parameter based on the tilt data of the neighboring sampling nodes; when the local tilt consistency parameter meets a preset consistency condition, use the initial slope value as the slope value of the desired location; when the local tilt consistency parameter does not meet the preset consistency condition, perform a weighted average calculation based on the tilt data of the neighboring sampling nodes to generate a corrected tilt angle, and determine the slope value of the desired location based on the corrected tilt angle; when the desired location is not located at a tilt field sampling node, perform interpolation calculation based on the tilt data of the neighboring sampling nodes to generate corresponding tilt data, and determine the slope value based on the tilt data.

[0041] In this embodiment of the invention, for each desired location within the target image region, corresponding dip angle data is read based on the spatial coordinates of that location in the dip field. The dip angle data characterizes the local tilt direction and degree of the formation reflection interface at that location. After obtaining the dip angle data, it is converted into an initial slope value using a preset dip angle conversion rule. In this embodiment, the initial slope value can be obtained by performing a tangent function operation on the dip angle data to establish a correspondence between the dip angle parameter and the spatial slope, allowing the obtained slope value to be directly used to describe the proportional relationship between the lateral and depth directions of the structural extension direction.

[0042] Furthermore, to avoid directional deviations caused by local noise or discontinuities in the reflection axis in single-point tilt angle data, tilt angle data from multiple neighboring sampling nodes are extracted within the neighborhood of the location to be determined. The neighborhood range can be set based on the spatial sampling interval of the image data; for example, a predetermined number of sampling nodes can be selected around the location to be determined, and the tilt angle data corresponding to these sampling nodes are read to form a neighborhood tilt angle set. After obtaining the neighborhood tilt angle set, a consistency analysis is performed on the neighborhood tilt angle set to calculate the local tilt angle consistency parameter corresponding to the location to be determined. The local tilt angle consistency parameter characterizes the degree of directional concentration among the tilt angle data within the neighborhood, thereby reflecting the stability of the structural orientation in that region.

[0043] When the local dip angle consistency parameter meets the preset consistency condition, it indicates that the structural direction within the neighborhood of the location to be determined has high stability. In this case, the single-point dip angle data can be considered to represent the structural trend of the region well. Therefore, the initial slope value is directly used as the final slope value of the location to be determined. This method can maintain the original information of the slope direction within the continuous structural region, so that the subsequently constructed PSF sampling path can accurately reflect the actual structural direction.

[0044] When the local dip angle consistency parameter does not meet the preset consistency condition, it indicates that the dip angle data within the neighborhood of the location to be determined exhibits significant dispersion or abrupt changes. In this case, to avoid single-point dip angle data misleading the sampling path direction, further processing of the neighborhood dip angle data is required. In this embodiment, a corrected dip angle is generated by performing a weighted average calculation on the neighborhood dip angle set. The weight of each neighboring sampling node can be determined based on its spatial distance from the location to be determined, so that dip angle data closer to the location to be determined has a higher weight in the correction calculation. The corrected dip angle obtained through the above weighted average calculation can weaken the influence of abnormal dip angle data to a certain extent, thereby obtaining more stable structural orientation parameters. Subsequently, the corresponding slope value is calculated based on the corrected dip angle, and this slope value is used as the final slope value of the location to be determined.

[0045] In practical digital image processing, the desired location may not perfectly coincide with the sampling nodes of the tilt field. In this case, it is necessary to estimate the tilt information of the desired location based on the tilt data of neighboring sampling nodes. Specifically, interpolation calculations can be performed based on the tilt data of the neighboring sampling nodes to generate tilt data corresponding to the desired location, and the corresponding slope value can be determined based on the tilt data. The interpolation method can be linear interpolation, bilinear interpolation, or other continuous interpolation methods to ensure the continuous spatial variation of the tilt data.

[0046] By incorporating neighborhood tilt angle consistency analysis and a weighted correction mechanism into the slope value determination process, the slope value not only originates from single-point tilt angle data but also comprehensively reflects the image change trend within the neighborhood, thereby improving the stability and reliability of the slope direction. This approach effectively reduces the impact of local abnormal tilt angles or noise on the sampling path direction, making the subsequent construction of the sampling path along the slope direction in the PSF signal more consistent with the actual image morphology, thus enhancing the consistency between the constructed image wavelet basis and the real image response.

[0047] In another possible implementation, when extracting slope values ​​from the dip field, for each desired location within the target image region, dip angle data corresponding to the spatial coordinates of that location is read from the dip field. This dip angle data characterizes the local dip direction and degree of the stratigraphic interface at that location. In this embodiment, the dip angle data is converted into slope values. Specifically, the slope values ​​can be obtained by calculating the tangent function value of the dip angle data to establish a correspondence between dip angle and spatial slope, allowing the obtained slope values ​​to be directly used to determine the sampling path direction in the PSF signal.

[0048] When the tilt field is discrete grid data, if the location to be determined does not coincide with the sampling nodes of the tilt field, then the tilt data of a predetermined number of sampling nodes adjacent to the location to be determined are selected, and the tilt data corresponding to the location to be determined is generated through interpolation. The slope value is then determined based on this. The interpolation method can be linear interpolation or other continuous interpolation methods to ensure the continuous spatial variation of the slope value.

[0049] It should be noted that the conversion relationship between slope value and dip angle is not limited to the tangent function form. Without changing the technical idea of ​​using dip angle data to characterize the direction of local structure, other equivalent mathematical transformation methods can also be applied and should all fall within the protection scope of this invention.

[0050] Optionally, constructing a sampling path along the slope direction in the PSF signal based on the slope value includes: using the spatial coordinates of the location to be determined in the PSF signal as the starting point of the path; determining the straight line direction passing through the starting point of the path based on the slope value, wherein the straight line direction is determined by the proportional relationship between the slope value and the depth direction; selecting sampling positions point by point in the PSF signal along the straight line direction according to a preset sampling interval to generate a discrete sampling point sequence; when the discrete sampling point sequence exceeds the effective range of the PSF signal, using the effective boundary of the PSF signal as the path termination position to obtain the sampling path along the slope direction.

[0051] When constructing a sampling path along the slope direction in a PSF signal based on the slope value, the spatial coordinates of the location to be determined in the PSF signal are used as the starting point of the path. These spatial coordinates correspond to the position index in the image plane where the PSF signal is located, and are used to determine the starting position of the sampling path. The direction of the straight line passing through the starting point of the path is determined based on the slope value. This direction is determined by the proportional relationship between the slope value and the depth direction, ensuring that the sampling path aligns with the local stratigraphic structure direction.

[0052] Along a straight line, sampling positions are selected point by point in the PSF signal according to a preset sampling interval to form a discrete sampling point sequence. The preset sampling interval can be consistent with the spatial sampling interval of the PSF signal, or it can be set to an integer multiple or fractional multiple of it according to the actual calculation accuracy requirements to ensure the stability and continuity of the path sampling. When the discrete sampling point sequence exceeds the effective range of the PSF signal, the effective boundary of the PSF signal is used as the path termination position, thereby limiting the spatial range of the sampling path.

[0053] It should be noted that the sampling path is not limited to a strict straight line. Under the premise of not deviating from the directional constraint determined by the slope value, an equivalent discrete path construction method can also be used to achieve sampling along the slope direction, and all of these fall within the protection scope of this invention.

[0054] Step A3: Perform superposition processing on the PSF signal according to the sampling path to generate the image wavelet basis corresponding to the position to be determined.

[0055] In this embodiment, the amplitude values ​​of each sampling point are sequentially read from the PSF signal according to the discrete sampling point sequence corresponding to the sampling path, and the path distance of each sampling point relative to the position to be determined is calculated; a path weight coefficient is constructed based on the path distance and the direction parameter of the sampling path, and the amplitude value of each sampling point is multiplied by the corresponding path weight coefficient to generate a weighted amplitude value; based on the relative position of each sampling point in the sampling path, the weighted amplitude value is mapped to a depth-oriented sample index position centered on the position to be determined; an accumulation operation is performed on the weighted amplitude values ​​mapped to the same depth-oriented sample index position to generate a depth-oriented amplitude accumulation sequence; the depth-oriented amplitude accumulation sequence is used as the image wavelet basis corresponding to the position to be determined.

[0056] Furthermore, an accumulation operation is performed on the amplitude values ​​mapped to the same depth direction sample index position to generate a depth direction amplitude accumulation sequence, including: establishing a depth sample index set for the depth direction of the position to be determined according to a preset depth sampling interval; adding the amplitude values ​​mapped to the same depth sample index item by item according to their corresponding discrete sampling points to obtain the accumulated amplitude value corresponding to the depth sample index; performing item-by-item addition processing on all depth sample indices to generate a depth direction amplitude accumulation sequence composed of the accumulated amplitude values ​​corresponding to each depth sample index.

[0057] In embodiments of the present invention, such as Figure 2 As shown, when establishing a local coordinate system with the center of the PSF signal corresponding to the location to be determined, the horizontal direction is denoted as x, and the depth direction is denoted as z. Point (0,z) represents the depth reference point corresponding to the location to be determined, point (x,t) represents the sampling point selected along the slope direction in the PSF signal, and k represents the slope value obtained from the image tilt field conversion. Based on the slope value k, the sampling direction passing through the location to be determined is determined, and the PSF amplitude value is read sequentially along this sampling direction for subsequent mapping and superposition to generate the image wavelet basis.

[0058] Based on the sampling path determined in the preceding steps, a corresponding discrete sampling point sequence is generated in the PSF signal. The discrete sampling point sequence is arranged point-by-point along the sampling path at a preset sampling interval, and each sampling point has clearly defined spatial coordinates. Based on this, the amplitude values ​​corresponding to each sampling point are sequentially read from the PSF signal according to the order of the discrete sampling point sequence, and the path distance of each sampling point relative to the desired location is calculated based on the spatial relationship between the sampling point and the desired location. The path distance characterizes the relative position of the sampling point on the sampling path, and its value can be determined by the spatial distance relationship between the sampling point coordinates and the desired location coordinates.

[0059] After obtaining the path distance, path weighting coefficients are further constructed based on the path distance and the direction parameters of the sampling path. The direction parameters are determined by the slope value based on the tilt field in the preceding steps and are used to describe the spatial extension relationship of the sampling path relative to the depth direction. By combining the path distance and direction parameters, a weighting function reflecting the attenuation characteristics of PSF energy along the sampling path can be established, giving higher weight to sampling points closer to the desired location during the superposition process, while the influence of sampling points farther away gradually weakens on the final result. Based on this, the amplitude value corresponding to each sampling point is multiplied by its corresponding path weighting coefficient to generate the corresponding weighted amplitude value.

[0060] Furthermore, based on the relative positions of each sampling point in the sampling path, the weighted amplitude value is mapped to a depth-oriented sample index position established with the desired position as the center. Specifically, the projection position of the sampling point in the depth direction can be determined based on its spatial coordinates in the sampling path, and the corresponding weighted amplitude value is written into the depth sample index corresponding to that depth position. Through the above mapping process, the amplitude information originally distributed in the two-dimensional PSF space can be reorganized into a one-dimensional amplitude data structure arranged along the depth direction.

[0061] When multiple sampling points are mapped to the same depth sample index position, these weighted amplitude values ​​are accumulated to generate the amplitude value at the corresponding depth sample index position. This accumulation process is performed sequentially on all depth sample index positions to obtain a depth-oriented amplitude accumulation sequence composed of the amplitude values ​​corresponding to each depth sample index. Finally, this depth-oriented amplitude accumulation sequence is used as the image wavelet basis for the position to be determined.

[0062] By introducing a path weighting mechanism jointly constructed from path distance and direction parameters during PSF amplitude superposition, the PSF amplitude can better conform to the energy distribution law of the actual image response during superposition, thereby avoiding excessive influence of PSF energy far from the image center on the result. This processing method enables the generated image wavelet basis to more closely match the morphological characteristics of the real image response, improving the wavelet basis's ability to express the geometric relationships of the image.

[0063] In one specific implementation, when performing superposition processing on the PSF signal according to the sampling path, a two-dimensional coordinate system is established with the image coordinates of the location to be determined as the analysis center. The horizontal coordinates are marked as follows: The depth coordinates are as follows Let the spatial coordinates of the location to be determined be... The coordinates of any point within the PSF signal range are represented as follows: According to the slope value The determined sampling path direction satisfies the following geometric relationship:

[0064]

[0065] In the formula, Represents the depth coordinates of the location to be determined. This represents the depth coordinates of the corresponding sampling point in the PSF signal. Represents the horizontal coordinate. This represents the slope value obtained from the tilt angle conversion. This relationship is used to determine the positional mapping of sampling points along the slope direction in the PSF signal.

[0066] Based on the PSF superposition expression, a digital image can be represented as the convolution integral of the PSF signal and the amplitude sampling sequence:

[0067]

[0068] in, Indicates the PSF signal. Indicates the amplitude sampling sequence. This represents the image synthesis result. For the location to be determined... Given the image results, and considering the slope constraint, the above expression can be transformed along the slope direction to obtain:

[0069]

[0070] This expression shows that the wavelet basis of the image at the desired location can be obtained by superimposing the PSF signal along the slope direction.

[0071] In the specific implementation, the amplitude value of each sampling point is sequentially read from the PSF signal according to the discrete sampling point sequence corresponding to the sampling path. Each sampling point corresponds to one... Coordinates, whose amplitude values ​​are denoted as Based on the aforementioned geometric relationships, the amplitude values ​​of each sampling point are mapped to a depth-oriented sample index position centered on the location to be determined. Specifically, a depth sample index set is established based on the depth coordinates of the location to be determined. The depth sample index is constructed according to a preset depth sampling interval.

[0072] Perform an accumulation operation on the amplitude values ​​mapped to the sample index positions at the same depth. For a given depth sample index... The PSF amplitude values ​​that satisfy the mapping relationship are summed item by item in the order of discrete sampling points to obtain the accumulated amplitude value corresponding to the depth sample index. This accumulation process is performed on all depth sample indices to generate a depth-to-depth amplitude accumulation sequence.

[0073]

[0074] in, Represents depth sample index The cumulative amplitude value at the location, Represents the coordinates of discrete sampling points that satisfy the mapping relationship. (From all...) The resulting sequence is the image wavelet basis corresponding to the position to be determined.

[0075] It should be noted that the above superposition process is strictly based on the sampling path direction determined by the slope value and does not involve any change to the structure of the PSF signal itself. The construction method of the depth sample index set and the setting of the sampling interval can be adjusted according to the sampling accuracy of the actual image data. Without changing the core technical idea of ​​superimposing PSF signals along the slope direction, equivalent implementations of the sampling path discretization method and accumulation order are all within the protection scope of this invention.

[0076] Step A4: Extract the depth amplitude sampling sequence corresponding to the position to be determined, perform a one-dimensional convolution operation on the image wavelet basis and the depth amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the position to be determined, and arrange all single-channel composite images according to their spatial positions to form the final image synthesis result.

[0077] In this embodiment, the depth amplitude sampling sequence of the location to be determined is extracted, and a one-dimensional convolution operation is performed between the image wavelet basis and the amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the location to be determined. This includes: extracting the depth amplitude sampling sequence corresponding to the location to be determined according to the spatial coordinates of the location to be determined; determining the corresponding depth sample interval at each depth sampling position of the depth amplitude sampling sequence according to the length of the image wavelet basis; at each depth sampling position, multiplying the amplitude value of each depth sample of the image wavelet basis with the amplitude sampling value of the corresponding depth position within the depth sample interval and performing a summation operation; arranging the summation results corresponding to each depth sampling position in depth order to generate a single-channel composite image corresponding to the location to be determined.

[0078] Based on the spatial coordinates of the location to be determined, the corresponding amplitude sampling sequence is read along the depth direction in the amplitude sampling sequence to form a depth-direction amplitude sampling sequence. .in, Indicates the sampling coordinates in the depth direction. This indicates that the location to be determined is at a depth of The amplitude sampling value at that location.

[0079] Let the wavelet basis of the image be denoted as Its length is Corresponding depth sample index set At each depth sampling position in the depth-axis amplitude sampling sequence, the corresponding depth sample interval is determined based on the length of the image wavelet basis. Specifically, for a given depth sampling position... Selecting an interval The corresponding amplitude sampling value is matched with the amplitude values ​​of each depth sample of the image wavelet basis.

[0080] At each depth sampling location, the amplitude values ​​of each depth sample of the image wavelet basis are... Amplitude sampling value at the corresponding depth position within the depth sample interval Multiply each value separately and then sum them to obtain the composite amplitude value corresponding to that depth sampling position. The above operation can be expressed as:

[0081]

[0082] in, This indicates that the location to be determined is at a depth of The synthesized amplitude value at the location. The above operation is performed sequentially on all depth sampling positions of the depth-direction amplitude sampling sequence, and the summation results corresponding to each depth sampling position are arranged in depth order to form a single-channel synthesized image corresponding to the position to be determined.

[0083] The aforementioned one-dimensional convolution operation is strictly expanded along the depth direction and does not involve lateral coupling calculations. The image wavelet basis remains unchanged throughout the entire depth-direction sliding process. Any one-dimensional convolution operation that performs equivalent operations on the image wavelet basis and the depth-direction amplitude sampling sequence based on the above mathematical relationship falls within the protection scope of this invention.

[0084] Optionally, all single-channel composite images are arranged according to their spatial positions to form the final image composite result, including: establishing a set of spatial sampling positions corresponding to the target image region; writing the single-channel composite image corresponding to each position to be determined into the spatial sampling position set at the position corresponding to its spatial coordinates; spatially sorting all single-channel composite images according to the spatial coordinate arrangement order in the spatial sampling position set; and outputting all spatially sorted single-channel composite images as the final image composite result.

[0085] A set of spatial sampling positions consistent with the target image region is established. This set of spatial sampling positions is composed of horizontal coordinates and depth direction sampling coordinates, and is used to define the spatial arrangement structure within the target image region. The set of spatial sampling positions is consistent with the spatial grid used in the aforementioned PSF field, tilt field, and amplitude sampling sequence, thereby ensuring the uniformity of spatial indexing.

[0086] Furthermore, the single-channel composite image corresponding to each desired location is written into the spatial sampling position set at its corresponding spatial coordinate. Each single-channel composite image corresponds to a specific lateral coordinate, and its internal data is arranged along the depth direction. Therefore, the writing process is essentially the location and storage of single-channel data according to spatial coordinates. After all writing operations are completed, all single-channel composite images are spatially sorted according to the spatial coordinate arrangement order in the spatial sampling position set, forming a single-channel data set arranged sequentially by lateral coordinates.

[0087] All spatially sorted single-channel composite images are output as the final image synthesis result. This profile reflects the image results at different spatial locations in the horizontal direction and maintains the amplitude sequence structure of the single-channel data in the depth direction. Any implementation method that performs equivalent spatial arrangement of single-channel composite images based on the same spatial index relationship falls within the protection scope of this invention.

[0088] In one specific implementation, such as Figure 3 The method involves selecting a spatial location within the target image region as the desired location and extracting the corresponding PSF signal in the PSF field based on the spatial coordinates of that location. If the location is not located at a PSF sampling node, the corresponding PSF signal is obtained through interpolation.

[0089] Furthermore, tilt angle data corresponding to the desired position is read in the tilt field and converted into a slope value. Based on the slope value, a sampling path along the slope direction is constructed in the PSF signal, and the PSF amplitude values ​​on the path are mapped and accumulated to form the image wavelet basis corresponding to the desired position.

[0090] Furthermore, the amplitude sampling sequence corresponding to the desired location is extracted along the depth direction from the amplitude sampling sequence. A one-dimensional convolution operation is performed between the image wavelet basis and the amplitude sampling sequence to generate a single-channel composite image corresponding to the desired location. The above process is repeated for all desired locations within the target image region, and all single-channel composite images are arranged according to their spatial positions to form the final image synthesis result.

[0091] In another implementation, in addition to the tilt field, a local structural curvature field within the target image region is further calculated to characterize the degree of curvature of the in-phase axis. When constructing the sampling path, the sampling path is modified a second time based on the slope value and the corresponding curvature parameters, so that the sampling path spatially exhibits a curvature consistent with the local structural trend. Subsequently, amplitude reading and accumulation processing are performed on the PSF signal along the modified sampling path to generate an image wavelet basis that matches the strongly curved structure. This implementation is suitable for regions with dense faults or severe folds, making the wavelet basis formation direction more closely match the actual image geometry while maintaining the original wavelet basis construction logic.

[0092] In another possible implementation, after establishing the spatial correspondence between the PSF field, tilt field, and amplitude sampling sequence, for each desired location within the target image region, local PSF window data for that location is extracted from the PSF field. The PSF window, centered on the desired location, extracts the local PSF amplitude distribution in the horizontal and depth directions according to a preset window size. Subsequently, energy distribution statistical analysis is performed on the amplitude distribution within the PSF window to calculate the corresponding PSF energy gradient distribution, and the PSF energy principal axis direction is determined based on the energy gradient distribution. The PSF energy principal axis direction characterizes the main spatial diffusion direction of the PSF amplitude, and its direction parameter reflects the response morphology characteristics of the image operator at that location.

[0093] After obtaining the principal axis direction of the PSF energy, it is jointly analyzed with the structural direction determined by the tilt angle. When the difference between the two directions is less than a preset angle threshold, it indicates that the PSF energy diffusion direction is basically consistent with the structural tilt angle direction. In this case, the sampling path is determined according to the tilt angle as per the original steps, and amplitude sampling and superposition processing are performed along this direction in the PSF signal. When the difference between the two directions is greater than the preset angle threshold, it indicates that the PSF morphology at this location has been significantly deflected due to changes in the velocity field or complex structures. In this case, the sampling path is corrected according to the principal axis direction of the PSF energy, so that the sampling path is constructed along the principal axis direction of the PSF energy. Subsequently, the amplitude value is read from the PSF signal along the corrected sampling path, and amplitude mapping and accumulation processing are performed to generate the image wavelet basis corresponding to the location to be determined.

[0094] Furthermore, after obtaining the image wavelet basis, the depth-direction amplitude sampling sequence corresponding to the position is extracted from the amplitude sampling sequence using the original method. A one-dimensional convolution operation is then performed between the image wavelet basis and the amplitude sampling sequence along the depth direction to generate a single-channel composite image for the corresponding position. This process is repeated for all positions within the target image region, and all single-channel composite images are arranged according to their spatial positions to form the final image synthesis result.

[0095] By introducing a PSF energy principal axis analysis mechanism during wavelet construction, the determination of the sampling path not only depends on the construction tilt angle information but also reflects the spatial energy distribution characteristics of the PSF response shape itself. This makes the constructed image wavelet basis more closely match the response direction of the actual image operator. In complex velocity fields or regions with drastic structural changes, this method can effectively avoid the directional deviation problem caused by relying solely on tilt angle information, making the wavelet extraction results more stable and further improving the consistency between the depth domain convolution synthesis results and the actual migrated image results.

[0096] In another possible implementation, after acquiring the PSF field, tilt field, and amplitude sampling sequence and establishing the spatial correspondence among them, a local constructed curvature field within the target image region is calculated based on the tilt field. This constructed curvature field characterizes the degree of curvature of the reflection phase axis in space, and its calculation can be obtained by analyzing the spatial gradient of the tilt data within the neighborhood, thereby obtaining the curvature parameter corresponding to each desired location.

[0097] After obtaining the curvature parameters, for each desired location within the target image region, the sampling path is further modified based on the curvature parameters, after determining the initial slope direction according to the tilt angle data. When the curvature parameter is less than a preset threshold, it indicates that the structure of the region is relatively gentle, and a straight sampling path along the slope direction is constructed in the original manner. When the curvature parameter is greater than the preset threshold, it indicates that the structure of the region has a significant bending trend, and the sampling path is modified point-by-point according to the curvature parameters so that the sampling path presents a curved shape in space consistent with the bending trend of the reflective interface.

[0098] Furthermore, the amplitude values ​​are read point by point in the PSF signal along the corrected sampling path, and amplitude mapping and superposition processing are performed according to preset rules to generate the image wavelet basis corresponding to the position to be determined.

[0099] Example:

[0100] A complex digital image was selected to verify the method of the present invention. Figure 4 A schematic diagram of the image model is given, which shows that the model has significant image variation features in both the horizontal and depth directions. Figure 5 The resulting digital image from this model is used as a comparison reference. Figure 6 The corresponding PSF field is shown. Due to the complex spatial variation of the image model, the PSF field exhibits obvious morphological differences and amplitude variations at different locations. Figure 7 This is the image tilt field corresponding to the model, used to extract the slope value at each position to be determined.

[0101] Based on the aforementioned PSF field and tilt field, the image wavelet basis constructed according to the method of this invention is as follows: Figure 8 As shown. Further, will Figure 8 Image wavelet basis and Figure 9 The amplitude sampling sequence shown is subjected to a one-dimensional convolution operation along the depth direction to form a single-channel composite image. All single-channel composite images are arranged according to their spatial positions to form the final composite image profile, as shown below. Figure 10 As shown. Comparison Figure 5 and Figure 10 It is evident that the two exhibit a high degree of consistency in image morphology and amplitude energy distribution characteristics.

[0102] like Figure 11 As shown, this invention provides a digital image wavelet basis extraction system. The system includes: a data acquisition unit, used to acquire the PSF field, tilt field, and amplitude sampling sequence covering a target image region, and establish the spatial correspondence among the three; a processing unit, used to extract the PSF signal from the PSF field and the slope value from the tilt field for each desired location within the target image region, and construct a sampling path along the slope direction in the PSF signal based on the slope value; a superposition unit, used to perform superposition processing on the PSF signal according to the sampling path to generate an image wavelet basis corresponding to the desired location; and a combination unit, used to extract the depth-direction amplitude sampling sequence corresponding to the desired location, perform a one-dimensional convolution operation on the image wavelet basis and the depth-direction amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the desired location, and arrange all single-channel composite images according to their spatial positions to form the final image synthesis result.

[0103] The present invention also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described digital image wavelet basis extraction method.

[0104] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 12 As shown, the computer device includes a processor A01, a network interface A02, memory (not shown), and a database (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02, and a database (not shown). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A04. The network interface A02 is used for communication with external terminals via a network connection. When the computer program B02 is executed by the processor A01, it implements a digital image wavelet basis extraction method.

[0105] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0106] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0107] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for wavelet basis extraction of digital images, characterized in that, The method includes: The PSF field, image tilt field, and amplitude sampling sequence covering the target image region are obtained, and the spatial correspondence among the three is established; wherein, the PSF field is a point spread function field; For each desired location within the target image region, a PSF signal is extracted from the PSF field, a slope value is extracted from the image tilt field, and a sampling path along the slope direction is constructed in the PSF signal based on the slope value. The PSF signal is subjected to amplitude superposition processing according to the sampling path to generate the image wavelet basis corresponding to the position to be determined; Extract the depth-direction amplitude sampling sequence of the location to be determined, perform a one-dimensional convolution operation between the image wavelet basis and the amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the location to be determined, and arrange all single-channel composite images according to their spatial positions to form the final image synthesis result.

2. The digital image wavelet basis extraction method according to claim 1, characterized in that, Acquire the PSF field, image tilt field, and amplitude sampling sequence covering the target image region, and establish the spatial correspondence among the three, including: The target image region is divided into a preset grid sampling location set; The PSF field is spatially sampled according to the set of grid sampling positions to generate a set of PSF signals that corresponds one-to-one with each grid sampling position. The image tilt field is spatially sampled according to the set of grid sampling positions to generate a set of slope values ​​that correspond one-to-one with each grid sampling position. The amplitude sampling sequence of the image is extracted according to the set of grid sampling positions, and a set of amplitude sampling sequences corresponding one-to-one with each grid sampling position is generated; The PSF signal set, the slope value set, and the amplitude sampling sequence set are indexed and mapped according to the same grid sampling position to form a spatial correspondence between the PSF field, the image tilt field, and the amplitude sampling sequence.

3. The digital image wavelet basis extraction method according to claim 1, characterized in that, The rule for extracting slope values ​​from the image tilt field is as follows: For each desired location within the target image region, read the tilt angle data corresponding to the desired location in the image tilt field, and determine the initial slope value based on the tilt angle data; Extract tilt angle data from multiple neighboring sampling nodes within the neighborhood of the location to be determined, and calculate a local tilt angle consistency parameter based on the tilt angle data of the neighboring sampling nodes; When the local tilt angle consistency parameter meets the preset consistency condition, the initial slope value is used as the slope value of the position to be determined. When the local tilt angle consistency parameter does not meet the preset consistency condition, a weighted average calculation is performed based on the tilt angle data of the neighboring sampling nodes to generate a corrected tilt angle, and the slope value of the position to be determined is determined based on the corrected tilt angle. When the location to be determined is not located at a slope field sampling node, interpolation calculation is performed based on the slope data of the neighboring sampling nodes to generate corresponding slope data, and the slope value is determined based on the slope data.

4. The digital image wavelet basis extraction method according to claim 3, characterized in that, Constructing a sampling path along the slope direction in the PSF signal based on the slope value includes: The spatial coordinates of the location to be determined in the PSF signal are used as the starting point of the path; The direction of the straight line passing through the starting point of the path is determined based on the slope value, wherein the direction of the straight line is determined by the ratio of the slope value to the depth direction; Along the straight line, sampling positions are selected point by point in the PSF signal according to a preset sampling interval to generate a discrete sampling point sequence; When the discrete sampling point sequence exceeds the effective range of the PSF signal, the effective boundary of the PSF signal is used as the path termination position to obtain a sampling path along the slope direction.

5. The digital image wavelet basis extraction method according to claim 1, characterized in that, The PSF signal is superimposed according to the sampling path to generate an image wavelet basis corresponding to the position to be determined, including: According to the discrete sampling point sequence corresponding to the sampling path, the amplitude value of each sampling point is read sequentially from the PSF signal, and the path distance of each sampling point relative to the position to be determined is calculated. A path weight coefficient is constructed based on the path distance and the direction parameter of the sampling path, and the amplitude value of each sampling point is multiplied by the corresponding path weight coefficient to generate a weighted amplitude value; Based on the relative positions of each sampling point in the sampling path, the weighted amplitude value is mapped to the depth-oriented sample index position centered on the position to be determined; Perform an accumulation operation on the weighted amplitude values ​​mapped to the same depth index position to generate a depth-oriented amplitude accumulation sequence; The depth-axis amplitude accumulation sequence is used as the image wavelet basis for the position to be determined.

6. The digital image wavelet basis extraction method according to claim 1, characterized in that, Extracting the depth-direction amplitude sampling sequence of the location to be determined, and performing a one-dimensional convolution operation along the depth direction on the image wavelet basis and the amplitude sampling sequence to generate a single-channel synthetic image corresponding to the location to be determined, including: Extract the amplitude sampling sequence corresponding to the location to be determined from the image according to the spatial coordinates of the location to be determined; At each depth sampling position in the amplitude sampling sequence, the corresponding depth sample interval is determined according to the length of the image wavelet basis; At each depth sampling position, the amplitude values ​​of each depth sample of the image wavelet basis are multiplied by the amplitude sampling sequence of the corresponding depth position in the depth sample interval and then summed. The summation results corresponding to each depth sampling position are arranged in depth order to generate a single-channel composite image corresponding to the position to be determined.

7. The digital image wavelet basis extraction method according to claim 6, characterized in that, All single-channel composite images are arranged according to their spatial positions to form the final image composite result, including: Establish a set of spatial sampling locations corresponding to the target image region; Write the single-channel composite image corresponding to each position to be determined into the spatial sampling position set at the position corresponding to its spatial coordinates; All single-channel composite images are spatially sorted according to the spatial coordinate arrangement order in the spatial sampling location set; All single-channel composite images after spatial sorting are used as the final image composite result.

8. An image wavelet basis extraction system, characterized in that, The system includes: The data acquisition unit is used to acquire the PSF field, image tilt field, and amplitude sampling sequence covering the target image area, and to establish the spatial correspondence among the three; wherein, the PSF field is a point spread function field; The processing unit is configured to extract a PSF signal from the PSF field, extract a slope value from the image tilt field, and construct a sampling path along the slope direction in the PSF signal based on the slope value for each position to be determined within the target image region. The superposition unit is used to perform superposition processing on the PSF signal according to the sampling path to generate an image wavelet basis corresponding to the position to be determined. The combination unit is used to extract the depth-direction amplitude sampling sequence corresponding to the position to be determined, perform a one-dimensional convolution operation on the image wavelet basis and the amplitude sampling sequence along the depth direction to generate a single-channel composite image corresponding to the position to be determined, and arrange all the single-channel composite images according to their spatial positions to form the final image synthesis result.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the digital image wavelet basis extraction method according to any one of claims 1-7.

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