Light field image anti-aliasing method and system

Abstract

The invention relates to a light field image anti-aliasing method and system, and the method comprises the steps: responding to a received instruction, determining a plurality of objects pointed by the instruction, and enabling the distances between at least two objects and an image collection point to be different; establishing an acquisition domain based on the object and establishing a plurality of acquisition surfaces in the acquisition domain, wherein any two acquisition surfaces are arranged in parallel; fusing the images on all the acquisition surfaces to one acquisition surface and carrying out fusion processing to obtain a standard image; establishing a transition area between the two standard images; determining the middle position of the transition area and establishing a transition line at the middle position; a transition image is established on the transition line and a display image is generated using the standard image and the transition image. According to the light field image anti-aliasing method and system disclosed by the invention, interference factors in a mixing and superposing process are removed in a mode of respectively reconstructing objects at different distance positions and reconstructing the surrounding environment of the objects, so that the obtained display image meets monitoring requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of image data processing, and in particular to a light field image anti-aliasing method and system. Background Art

[0002] When using light field monitoring equipment for monitoring, the final image is generated by superimposing data generated by multiple cameras. For example, in the process of simultaneously displaying monitoring objects at different distances, it is necessary to separate the corresponding data from the collected data and then superimpose them together. The superposition at this time will produce confusion, which is caused by the shooting parameters and sampling methods.

[0003] Specifically, different shooting parameters (such as focal length changes) will result in different amounts of data contained in the monitored object, and the data loss and restoration degrees in the collected data obtained using the subsampling method are also different. This makes it impossible to simply superimpose the images, because it will cause multiple defects such as blurred edges, disappearance of feature areas, and unclear feature areas.

[0004] For example, when displaying objects at different distances simultaneously, traditional monitoring equipment can only use focal length adjustment to select one to display, while light field monitoring equipment can display them simultaneously. However, when the data generated by multiple cameras at multiple focal lengths are superimposed, a lot of interference factors will appear in the picture.

[0005] However, another advantage of light field data is that the image can be reconstructed during the display process. How to achieve anti-aliasing of light field images during the reconstruction process so that the display of objects on the image can meet the display requirements requires further research. Summary of the invention

[0006] The present invention provides a light field image anti-aliasing method and system, which removes interference factors in the mixed superposition process by separately reconstructing objects at different distances and reconstructing the surrounding environment of the objects, so that the obtained display image meets the monitoring requirements.

[0007] The above object of the present invention is achieved through the following technical solutions: In a first aspect, the present invention provides a light field image anti-aliasing method, comprising: In response to the received instruction, determining that at least two of the multiple objects pointed to by the instruction are at different distances from the image acquisition point; Establish a collection domain based on the object and establish multiple collection surfaces in the collection domain, and any two collection surfaces are set in parallel; The images on all acquisition surfaces are fused onto one acquisition surface and fused to obtain a standard image; Establishing a transition region between two standard images; Determine the middle position of the transition area and establish a transition line at the middle position; Establish transition images on transition lines; The display image is generated using the standard image and the transition image.

[0008] In a possible implementation manner of the first aspect, fusing the images on all acquisition planes onto one acquisition plane and performing fusion processing includes: Decomposing the image on the acquisition surface into monochrome images, the monochrome images including red images, green images and blue images; Establish analysis curves on monochrome images; The analysis curve is transferred into the time domain and the frequency domain for decomposition to obtain an analysis curve group, wherein the curves in the analysis curve group have a starting position and a cutoff position; The corresponding analysis curve groups are merged, and the corresponding analysis curve groups come from corresponding monochrome images on different acquisition surfaces.

[0009] In a possible implementation manner of the first aspect, before transferring the analysis curve into the time domain and the frequency domain for decomposition, the analysis curve is further filtered to filter out the intermediate frequency part and the low frequency part of the analysis curve.

[0010] In a possible implementation manner of the first aspect, merging the corresponding analysis curve groups includes: Pick up a similar curve from the analysis curve group, and the starting position, end position, frequency and amplitude of the similar curve are all within the allowable range; Merge similar curves picked up at one time, including mean merging and selective merging; Each time a similar curve is picked up, only one similar curve is picked up from one analysis curve group.

[0011] In a possible implementation manner of the first aspect, merging similar curves picked up once includes: Transfer similar curves picked up at one time into the same coordinate system; Calculate the uniformity of the difference between the starting positions of two adjacent similar curves and the uniformity of the difference between the ending positions of two adjacent similar curves to obtain a calculation result; Choose to use mean merging or select one merging according to the calculation results; Among them, when using selective merging, the similar curve close to the acquisition surface where the standard image is located is retained among the two similar curves with the smallest difference uniformity.

[0012] In a possible implementation manner of the first aspect, establishing a transition image on the transition line includes: determining a collection surface associated with the transition line and adjusting the associated area on the collection surface according to the number of the collection surfaces; The image of the associated area on the acquisition surface is transferred to the transition line to obtain a transition image.

[0013] In a possible implementation manner of the first aspect, after the image of the associated area on the acquisition surface is transferred to the acquisition surface, the method further includes: Determine the dividing line on the transition line; Establish a first fusion area and a second fusion area on both sides of the dividing line; Establishing a fusion reference curve, wherein two ends of the fusion reference curve are respectively located in a first fusion region and a second fusion region; generating a first analysis curve using pixel points of a portion of the fused reference curve located in the first fused region; generating a second analysis curve using pixel points of the fused reference curve located on a portion of the second fused region; Analyzing the distribution of high frequency parts in the first analysis curve and the second analysis curve; Adjust the distribution of high-frequency parts in the first analysis curve and the second analysis curve to be consistent.

[0014] In a second aspect, the present invention provides a light field image anti-aliasing device, comprising: an object determination unit, configured to determine, in response to the received instruction, that the multiple objects pointed to by the instruction have at least two objects at different distances from the image acquisition point; A collection domain establishing unit, used to establish a collection domain based on an object and to establish multiple collection surfaces in the collection domain, wherein any two collection surfaces are arranged in parallel; A fusion processing unit, used for fusing the images on all acquisition planes into one acquisition plane and performing fusion processing to obtain a standard image; A transition region establishing unit, used for establishing a transition region between two standard images; A transition line processing unit, used for determining a middle position of a transition area and establishing a transition line at the middle position; A transition image establishing unit, used for establishing a transition image on a transition line; The result output unit is used to generate a display image using the standard image and the transition image.

[0015] In a third aspect, the present invention provides a light field image anti-aliasing system, the system comprising: one or more memories for storing instructions; and One or more processors, used to call and run the instructions from the memory to execute the method as described in the first aspect and any possible implementation of the first aspect.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium, the computer-readable storage medium comprising: Program, when the program is executed by a processor, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0017] In a fifth aspect, the present invention provides a computer program product, comprising program instructions, and when the program instructions are executed by a computing device, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0018] In a sixth aspect, the present invention provides a chip system comprising a processor for implementing the functions involved in the above aspects, for example, generating, receiving, sending, or processing the data and / or information involved in the above methods.

[0019] The chip system may be composed of chips, or may include chips and other discrete devices.

[0020] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wired or wireless means, or the processor and the memory can also be coupled on the same device. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The present invention provides a light field image anti-aliasing method.

[0022] Figure 2 It is a schematic diagram of establishing a collection domain and a collection surface provided by the present invention.

[0023] Figure 3 It is a schematic diagram provided by the present invention for decomposing an image on a collection surface into monochrome images.

[0024] Figure 4 It is a schematic diagram of mean merging provided by the present invention.

[0025] Figure 5 It is a schematic diagram of selective merging provided by the present invention.

[0026] Figure 6 It is a schematic diagram of the positions of a transition line and a collection surface associated with the transition line provided by the present invention.

[0027] Figure 7 It is a schematic diagram of associated areas on a collection surface provided by the present invention.

[0028] Figure 8It is a schematic diagram of a first analysis curve and a second analysis curve generated provided by the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings.

[0030] The present invention discloses a light field image anti-aliasing method, please refer to Figure 1 In some examples, the light field image anti-aliasing method disclosed in the present invention includes the following steps: S101, in response to a received instruction, determining that at least two of the multiple objects pointed to by the instruction are at different distances from the image acquisition point; S102, establishing a collection domain based on the object and establishing multiple collection surfaces in the collection domain, and any two collection surfaces are set in parallel; S103, fusing the images on all acquisition surfaces onto one acquisition surface and performing fusion processing to obtain a standard image; S104, establishing a transition area between two standard images; S105, determining the middle position of the transition area and establishing a transition line at the middle position; S106, establishing a transition image on the transition line; S107, generating a display image using the standard image and the transition image.

[0031] In general, the light field image anti-aliasing method provided by the present invention is mainly used for the simultaneous display of multiple monitoring objects at different distances. In traditional monitoring scenarios, there are two ways to simultaneously display multiple monitoring objects at different distances, namely, single camera focusing and multiple cameras monitoring separately. Single camera focusing will cause the content of the picture to change, and multiple cameras monitoring separately will result in multiple pictures. The above methods are not conducive to monitoring.

[0032] The technical solution of the present invention is implemented based on a light field monitoring device. The light field monitoring device is composed of an array of cameras. The imaging range and focal length of each camera can be adjusted, so that close-range image acquisition and long-range image acquisition can be achieved simultaneously during the image acquisition process, and the acquired images can also be used to construct three-dimensional images.

[0033] However, the amount of data generated by light field images is large. In the data collection process inside the light field monitoring equipment, sub-sampling data sampling method is generally used for sampling to obtain a larger data compression ratio, and then the image is reconstructed at the display image. During reconstruction, the required data can be directly picked up from the generated data to display the near-field image and the distant image in one image at the same time.

[0034] The technical solution disclosed in the present invention is executed by an image processor at the display image, and the image processor can be a computer, a server, a remote server, a cloud, etc.

[0035] In step S101, firstly, according to the received instruction, multiple objects pointed to by the instruction are determined, among which at least two objects are at different distances from the image acquisition point, that is, a near-view image and a far-view image need to be presented simultaneously.

[0036] When the instruction points to only one object, the object is displayed directly.

[0037] In step S102, refer to Figure 2 , a collection domain will be established based on the object and multiple collection surfaces will be established in the collection domain. Any two collection surfaces are set in parallel. The object and multiple collection surfaces are all located inside the collection domain. The collection surfaces are equivalent to dividing the collection domain.

[0038] Figure 2 The solid line in the figure represents the acquisition domain, and the dotted line represents the acquisition surface. The acquisition surface is located inside the acquisition domain. In order to show it clearly, the acquisition surface is reduced in size in the figure.

[0039] The acquisition plane corresponds to images at different focal lengths, and these images at different focal lengths are finally superimposed together to obtain a standard image. The specific method is to fuse the images on all acquisition planes into one acquisition plane and perform fusion processing, which is the content of step S103.

[0040] In step S104, a transition area is established between the two standard images, and then in step S105, the middle position of the transition area is determined and a transition line is established at the middle position. Then, a transition image is established on the transition line, which is the content of step S106. Finally, in step S107, the standard image and the transition image are used to generate a display image.

[0041] In summary, the light field image anti-aliasing method provided by the present invention obtains a display image by processing the standard image and the transition area separately and then synthesizing them, in order to resist the aliasing problem caused by simple superposition synthesis. This method fundamentally solves the interference problem on the real image caused by simple superposition, and can obtain a display image that meets the monitoring requirements.

[0042] Meeting the monitoring requirements specifically means that the displayed image can present both the near-view image and the distant-view image at the same time and the transition between the various parts of the image is smooth. At the same time, when the distant-view image is enlarged, the details of the distant-view image can be clearly displayed.

[0043] In some examples, the specific method of fusing the images on all acquisition planes into one acquisition plane and performing the fusing process is: S201, decomposing the image on the acquisition surface into monochrome images, where the monochrome images include a red image, a green image, and a blue image; S202, establishing an analysis curve on the monochrome image; S203, transferring the analysis curve into the time domain and the frequency domain for decomposition to obtain an analysis curve group, wherein the curves in the analysis curve group have a starting position and a cutoff position; S204, merging the corresponding analysis curve groups, where the corresponding analysis curve groups come from corresponding monochrome images on different acquisition planes.

[0044] In step S201 to step S204, the image on the acquisition surface is first decomposed into monochrome images, which include red images, green images and blue images. Figure 3 This is because the rich colors contained in the image are mixed in proportion by red, green and blue. The separation processing method can avoid the imbalance of the color (red, green and blue) caused by the subsequent processing process.

[0045] Then the analysis curve is transferred to the time domain and frequency domain for decomposition to obtain an analysis curve group. The curves in the analysis curve group have both time domain characteristics and frequency domain characteristics. The time domain feature refers to that the curves in the analysis curve group have a start time and an end time. Combined with the position here, the curves in the analysis curve group can have a start position and an end position; the frequency domain feature refers to that the curves in the analysis curve group have frequency and amplitude characteristics.

[0046] Finally, the corresponding analysis curve groups are merged, and the corresponding analysis curve groups come from the corresponding monochrome images on different acquisition surfaces.

[0047] It should be understood that different acquisition planes correspond to different focal lengths. When they are merged, the images need to be enlarged or reduced, which may easily cause overlap. It should also be considered that the subsampling process results in a limited number of sampling points, which may lead to a certain amount of data loss, and the location of the loss is uncertain.

[0048] The present invention adopts a method of synthesizing multiple acquisition surfaces, which can retain as much original image information as possible, and uses a merging processing method to perform selective retention to obtain a clear display image.

[0049] In some possible implementations, before transferring the analysis curve into the time domain and frequency domain for decomposition, the analysis curve is also filtered to remove the intermediate frequency and low frequency parts in the analysis curve. This is because the interference problems in the image are mostly caused by the high frequency part. Therefore, in the present invention, only the high frequency part of the analysis curve is merged.

[0050] The specific method of merging the corresponding analysis curve group is: S301, picking up a similar curve from the analysis curve group, where the starting position, the ending position, the frequency and the amplitude of the similar curve are all within the allowable range; S302, merging similar curves picked up once, including mean merging ( Figure 4 shown) and select one and merge ( Figure 5 shown); Each time a similar curve is picked up, only one similar curve is picked up from one analysis curve group.

[0051] In the above steps, similar curves are picked up by starting position, ending position, frequency and amplitude. The specific principle is to set a range, which is generally controlled within 1%-1.5%, that is, the difference between two, three or four of the starting position, ending position, frequency and amplitude is within 1%-1.5%.

[0052] Each time a similar curve is picked, only one similar curve is picked from an analysis curve group. For example, if there are four analysis curve groups at this time, only one similar curve is picked from an analysis curve group in each picking process. In one picking process, the number of similar curves picked is less than or equal to four.

[0053] After the picking is completed, the similar curves picked up once are merged. There are two merging methods, namely mean merging and selective merging. The specific methods are as follows: S401, transferring the similar curves picked up once into the same coordinate system; S402, calculating the uniformity of the difference between the starting positions of two adjacent similar curves and the uniformity of the difference between the ending positions of two adjacent similar curves to obtain a calculation result; S403, selecting to use mean merging or alternative merging according to the calculation result; Among them, when using selective merging, the similar curve close to the acquisition surface where the standard image is located is retained among the two similar curves with the smallest difference uniformity.

[0054] See also Figure 4 and Figure 5 In step S401 to step S403, the uniformity of the difference between the starting positions of two adjacent similar curves and the uniformity of the difference between the ending positions of two adjacent similar curves are calculated. The uniformity of the difference between the starting positions of the similar curves obtained in a picking process refers to the uniformity of the difference between the starting positions of the similar curves obtained in a picking process. The uniformity of the difference between the ending positions is the same and will not be repeated here.

[0055] Choosing to use mean merging or selective merging according to the calculation results means that when the calculation results (the uniformity of the difference between the starting positions of two adjacent similar curves and the uniformity of the difference between the ending positions of two adjacent similar curves) are relatively stable, the merging processing method is used for processing, otherwise only one method is retained for processing.

[0056] This is because when the calculation result is relatively stable, it means that the middle method can be used to obtain an optimal result, which is equivalent to using the mean processing method to obtain the most appropriate result. However, when the calculation result is relatively unstable, it means that the middle method is no longer appropriate. At this time, the similarity curve close to the acquisition surface where the standard image is located among the two similarity curves with the smallest difference uniformity is retained, that is, the similarity curve at the most stable position of the change is used as the final retained similarity curve.

[0057] In some examples, the steps of creating a transition image on a transition line are: S501, determining a collection surface associated with the transition line and adjusting the associated area on the collection surface according to the number of collection surfaces; S502, transferring the image of the associated area on the acquisition surface to the transition line to obtain a transition image.

[0058] See also Figure 6 and Figure 7 In step S501 and step S502, the images of the associated areas on the multiple acquisition surfaces are transferred to the transition line, and then the transition image is obtained. For the associated areas on the acquisition surfaces, the number of acquisition surfaces is first determined and then the associated areas on the acquisition surfaces are adjusted according to the number of acquisition surfaces.

[0059] The purpose of doing this is to make the associated area on the acquisition surface as close to the transition line as possible. Combined with the content mentioned in the previous article, there must be an angle between the transition line and the acquisition surface associated with the transition line. This is why it is impossible to generate a transition image on the transition line using only the content on an acquisition surface associated with the transition line.

[0060] Therefore, in the present invention, multiple acquisition surfaces are used, and a part of the area, that is, the so-called associated area, is selected on each acquisition surface. The distance between these associated areas and the transition line is small, which can make the transition image clearer.

[0061] After transferring the image of the associated area on the acquisition surface to the acquisition surface, it is necessary to use the following steps for processing: S601, determining a dividing line on the transition line; S602, establishing a first fusion region and a second fusion region on both sides of the dividing line respectively; S603, establishing a fusion reference curve, where two ends of the fusion reference curve are located in a first fusion region and a second fusion region respectively; S604, generating a first analysis curve using pixel points of a portion of the fusion reference curve located in the first fusion area; S605, generating a second analysis curve using pixel points of a portion of the fusion reference curve located in the second fusion area; S606, analyzing the distribution of high frequency parts in the first analysis curve and the second analysis curve; S607, adjusting the distribution of high frequency parts in the first analysis curve and the second analysis curve to be consistent.

[0062] The contents in step S601 to step S607 are to merge the contents of two related areas in order to make the image transition smoother. Of course, before this, basic enlargement and reduction are required to align the edges. This part of the content is existing technology and will not be repeated here.

[0063] A specific method is to first establish a first fusion region and a second fusion region on both sides of the dividing line, and then establish a fusion reference curve, wherein both ends of the fusion reference curve are located at the first fusion region and the second fusion region, respectively.

[0064] See also Figure 8 , then generate the first analysis curve and the second analysis curve, then determine the distribution of the high frequency parts in the first analysis curve and the second analysis curve, and finally adjust the distribution of the high frequency parts in the first analysis curve and the second analysis curve to make the two distributions consistent.

[0065] A specific method is to generate a distribution curve of the high-frequency part, and then move one of the distribution curves or move both distribution curves at the same time so that the two distribution curves can overlap as much as possible.

[0066] The present invention also provides a light field image anti-aliasing device, comprising: an object determination unit, configured to determine, in response to the received instruction, that the multiple objects pointed to by the instruction have at least two objects at different distances from the image acquisition point; A collection domain establishing unit, used to establish a collection domain based on an object and to establish multiple collection surfaces in the collection domain, wherein any two collection surfaces are arranged in parallel; A fusion processing unit, used for fusing the images on all acquisition planes into one acquisition plane and performing fusion processing to obtain a standard image; A transition region establishing unit, used for establishing a transition region between two standard images; A transition line processing unit, used for determining a middle position of a transition area and establishing a transition line at the middle position; A transition image establishing unit, used for establishing a transition image on a transition line; The result output unit is used to generate a display image using the standard image and the transition image.

[0067] Furthermore, it also includes: An image decomposition unit is used to decompose the image on the acquisition surface into monochrome images, where the monochrome images include a red image, a green image and a blue image; An analysis curve establishing unit, used for establishing an analysis curve on a monochrome image; An analysis curve decomposition unit is used to transfer the analysis curve into the time domain and the frequency domain for decomposition to obtain an analysis curve group, wherein the curves in the analysis curve group have a starting position and a cutoff position; The first merging processing unit is used to merge the corresponding analysis curve groups, where the corresponding analysis curve groups come from corresponding monochrome images on different acquisition planes.

[0068] Furthermore, before transferring the analysis curve into the time domain and the frequency domain for decomposition, the analysis curve is filtered to remove the intermediate frequency part and the low frequency part of the analysis curve.

[0069] Furthermore, it also includes: A picking unit is used to pick a similar curve from the analysis curve group, and the starting position, the end position, the frequency and the amplitude of the similar curve are all within the allowable range; A second merging processing unit is used to merge similar curves picked up once, and the merging includes mean merging and alternative merging; Each time a similar curve is picked up, only one similar curve is picked up from one analysis curve group.

[0070] Furthermore, it also includes: The first processing unit is used to transfer the similar curves picked up once into the same coordinate system; A calculation processing unit, used for calculating the uniformity of the difference between the starting positions of two adjacent similar curves and the uniformity of the difference between the ending positions of two adjacent similar curves, and obtaining a calculation result; A third merging processing unit, used for selecting to use mean merging or alternative merging according to the calculation result; Among them, when using selective merging, the similar curve close to the acquisition surface where the standard image is located is retained among the two similar curves with the smallest difference uniformity.

[0071] Furthermore, it also includes: A second processing unit is used to determine a collection surface associated with the transition line and adjust the associated area on the collection surface according to the number of the collection surfaces; The third processing unit is used to transfer the image of the associated area on the acquisition surface to the transition line to obtain a transition image.

[0072] Furthermore, it also includes: A dividing line determination unit, used for determining a dividing line on a transition line; A fusion region establishing unit, used to establish a first fusion region and a second fusion region on both sides of the dividing line respectively; A fusion reference curve establishing unit, used for establishing a fusion reference curve, wherein two ends of the fusion reference curve are respectively located in a first fusion area and a second fusion area; A first generating unit, configured to generate a first analysis curve using pixel points of a portion of the fusion reference curve located in the first fusion area; A second generating unit, configured to generate a second analysis curve using pixel points of a portion of the fusion reference curve located in the second fusion area; An analysis unit, used for analyzing the distribution of high frequency parts in the first analysis curve and the second analysis curve; The adjustment unit is used to adjust the distribution of high frequency parts in the first analysis curve and the second analysis curve to be consistent.

[0073] In one example, the unit in any of the above devices can be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or, one or more digital signal processors (DSPs), or, one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0074] For another example, when the units in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call a program. For another example, these units can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0075] Various objects such as various messages / information / equipment / network elements / systems / devices / actions / operations / processes / concepts that may appear in the present invention are named. It can be understood that these specific names do not constitute a limitation on the relevant objects. The names assigned may change with factors such as scenarios, contexts or usage habits. The understanding of the technical meaning of the technical terms in the present invention should be mainly determined from the functions and technical effects embodied / executed in the technical scheme.

[0076] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0077] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0078] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0080] It should also be understood that in various embodiments of the present invention, the first, second, etc. are only used to indicate that multiple objects are different. For example, the first time window and the second time window are only used to indicate different time windows. They should not have any impact on the time window itself, and the first, second, etc. mentioned above should not impose any limitations on the embodiments of the present invention.

[0081] It should also be understood that in the various embodiments of the present invention, unless otherwise specified or there is any logical conflict, the terms and / or descriptions between the different embodiments are consistent and can be referenced to each other, and the technical features in the different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0082] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a computer-readable storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned computer-readable storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0083] The present invention also provides a light field image anti-aliasing system, the system comprising: one or more memories for storing instructions; and One or more processors are used to call and run the instructions from the memory to execute the method as described above.

[0084] The present invention also provides a computer program product, which includes instructions. When the instructions are executed, the terminal device and the network device perform operations of the terminal device and the network device corresponding to the above method.

[0085] The present invention also provides a chip system, which includes a processor for implementing the functions involved in the above content, such as generating, receiving, sending, or processing the data and / or information involved in the above method.

[0086] The chip system may be composed of chips, or may include chips and other discrete devices.

[0087] The processor mentioned in any of the above places can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for executing programs for controlling the above-mentioned feedback information transmission method.

[0088] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wire or wireless means to support the chip system to implement various functions in the above embodiments. Alternatively, the processor and the memory can also be coupled on the same device.

[0089] Optionally, the computer instructions are stored in a memory.

[0090] Optionally, the memory is a storage unit within the chip, such as a register, a cache, etc. The memory can also be a storage unit within the terminal located outside the chip, such as a ROM or other types of static storage devices that can store static information and instructions, RAM, etc.

[0091] It can be understood that the memory in the present invention can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0092] The nonvolatile memory may be a ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory.

[0093] The volatile memory may be a RAM, which is used as an external cache. There are many different types of RAM, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct memory bus RAM.

[0094] The embodiments of this specific implementation method are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, all equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A light field image anti-aliasing method, characterized in that: include: In response to the received instruction, determining that at least two of the multiple objects pointed to by the instruction are at different distances from the image acquisition point; Establish a collection domain based on the object and establish multiple collection surfaces in the collection domain, and any two collection surfaces are set in parallel; The images on all acquisition surfaces are fused onto one acquisition surface and fused to obtain a standard image; Establishing a transition region between two standard images; Determine the middle position of the transition area and establish a transition line at the middle position; Establish transition images on transition lines; The display image is generated using the standard image and the transition image.

2. The light field image anti-aliasing method according to claim 1, characterized in that: The images on all acquisition surfaces are fused into one acquisition surface and the fusion process is performed including: Decomposing the image on the acquisition surface into monochrome images, the monochrome images including red images, green images and blue images; Establish analysis curves on monochrome images; The analysis curve is transferred into the time domain and the frequency domain for decomposition to obtain an analysis curve group, wherein the curves in the analysis curve group have a starting position and a cutoff position; The corresponding analysis curve groups are merged, and the corresponding analysis curve groups come from corresponding monochrome images on different acquisition surfaces.

3. The light field image anti-aliasing method according to claim 2, characterized in that: Before transferring the analysis curve into the time domain and the frequency domain for decomposition, the analysis curve is filtered to filter out the intermediate frequency part and the low frequency part of the analysis curve.

4. The light field image anti-aliasing method according to claim 2, characterized in that: The corresponding analysis curve group is merged and processed including: Pick up a similar curve from the analysis curve group, and the starting position, end position, frequency and amplitude of the similar curve are all within the allowable range; Merge similar curves picked up at one time, including mean merging and selective merging; Each time a similar curve is picked up, only one similar curve is picked up from one analysis curve group.

5. The light field image anti-aliasing method according to claim 4, characterized in that: The merging of similar curves picked up at one time includes: Transfer similar curves picked up at one time into the same coordinate system; Calculate the uniformity of the difference between the starting positions of two adjacent similar curves and the uniformity of the difference between the ending positions of two adjacent similar curves to obtain a calculation result; Choose to use mean merging or select one merging according to the calculation results; Among them, when using selective merging, the similar curve close to the acquisition surface where the standard image is located is retained among the two similar curves with the smallest difference uniformity.

6. The light field image anti-aliasing method according to claim 1, characterized in that: Establishing a transition image on a transition line includes: determining a collection surface associated with the transition line and adjusting the associated area on the collection surface according to the number of the collection surfaces; The image of the associated area on the acquisition surface is transferred to the transition line to obtain a transition image.

7. The light field image anti-aliasing method according to claim 6, characterized in that: After transferring the image of the associated area on the acquisition surface to the acquisition surface, it also includes: Determine the dividing line on the transition line; Establish a first fusion area and a second fusion area on both sides of the dividing line; Establishing a fusion reference curve, wherein two ends of the fusion reference curve are respectively located in a first fusion region and a second fusion region; generating a first analysis curve using pixel points of a portion of the fused reference curve located in the first fused region; generating a second analysis curve using pixel points of the fused reference curve located on a portion of the second fused region; Analyzing the distribution of high frequency parts in the first analysis curve and the second analysis curve; Adjust the distribution of high-frequency parts in the first analysis curve and the second analysis curve to be consistent.

8. A light field image anti-aliasing device, characterized in that: include: an object determination unit, configured to determine, in response to the received instruction, that the multiple objects pointed to by the instruction have at least two objects at different distances from the image acquisition point; A collection domain establishing unit, used to establish a collection domain based on an object and to establish multiple collection surfaces in the collection domain, wherein any two collection surfaces are arranged in parallel; A fusion processing unit, used for fusing the images on all acquisition planes into one acquisition plane and performing fusion processing to obtain a standard image; A transition region establishing unit, used for establishing a transition region between two standard images; A transition line processing unit, used for determining a middle position of a transition area and establishing a transition line at the middle position; A transition image establishing unit, used for establishing a transition image on a transition line; The result output unit is used to generate a display image using the standard image and the transition image.

9. A light field image anti-aliasing system, characterized in that: The system comprises: one or more memories for storing instructions; and One or more processors, configured to call and execute the instructions from the memory to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer readable storage medium comprises: The program, when the program is executed by a processor, the method according to any one of claims 1 to 7 is executed.

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