An Event Camera-Based System and Method for Removing Image Reflection Flares

Abstract

The present invention provides a system and method for removing image reflection flare based on an event camera. The system includes: a light source for providing backlit shooting conditions; a dual-mode camera with an image frame mode and an event mode for capturing image frames and event streams under backlit conditions; a data processing unit for receiving image frames and event streams, denoising and reconstructing the event streams to obtain event pseudo-frames; and a unit for fusing and restoring the image frames with the event pseudo-frames to obtain a restored image with flare removed and an estimated flare, thereby removing reflection flare from the image frames. The present invention solves the technical problem of the inability to remove reflection flare from images taken with traditional cameras in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a system and method for removing image reflection flare based on an event camera. Background Art

[0002] When a light source enters the field of view of a traditional camera, it is reflected multiple times within the lens. As the reflected light accumulates over the camera's exposure time, bright spots or "ghosting" effects appear in the image, commonly referred to as reflection flare. Current methods for removing image flare rely primarily on feature detection techniques to identify and reconstruct the flare area. However, these methods are often limited to specific flare patterns and struggle to detect and remove flare against complex backgrounds.

[0003] An event camera is a sensor designed based on bionic vision that can asynchronously trigger event signals based on changes in brightness at each pixel. When the logarithmic change in brightness exceeds a certain threshold, an event is triggered. Under backlit conditions at night, a stationary event camera can capture illumination fluctuations from the light source while avoiding the appearance of reflection flare. Because reflection flare involves energy attenuation caused by repeated reflections, the intensity fluctuations in these flare areas are often too small to trigger an event. Therefore, event cameras have great potential for removing reflection flare from images taken with traditional cameras.

[0004] Currently, there is a lack of effective methods for removing image reflection flares based on event cameras in both scientific research and application fields. Summary of the Invention

[0005] The present invention provides a system and method for removing image reflection flare based on an event camera, which can solve the technical problem in the prior art that reflection flare in traditional camera images cannot be removed.

[0006] According to one aspect of the present invention, a system for removing image reflection flare based on an event camera is provided, the system comprising:

[0007] Light source, used to provide conditions for backlit shooting;

[0008] Dual-mode camera with image frame mode and event mode for capturing image frames and event streams in backlight conditions;

[0009] The data processing unit is used to receive image frames and event streams, and to denoise and reconstruct the event streams to obtain event pseudo frames; it is also used to fuse and restore the image frames with the event pseudo frames to obtain a restored image with flare removed and an estimated flare, so as to remove the reflected flare from the image frames.

[0010] Preferably, the data processing unit includes a pre-processing module, an event-guided fusion module and a multi-stage restoration module;

[0011] The preprocessing module is used to perform denoising on the event stream to obtain a denoised event stream; and is also used to perform time dimension compression on the denoised event stream to obtain an event pseudo frame;

[0012] The event-guided fusion module is used to fuse the image frame with the event pseudo frame to obtain a spliced feature map;

[0013] The multi-stage restoration module is used to restore the spliced feature map to obtain a restored image with flare removed and an estimated flare.

[0014] Preferably, the event-guided fusion module includes three convolutional layers, an activation layer, an operator module and a splicing submodule;

[0015] The first convolutional layer is used to convolve the image frame to obtain the image frame feature map;

[0016] The second convolutional layer is used to convolve the event pseudo frame rotated 180° to obtain the event feature map;

[0017] The activation layer is used to activate the event feature map to obtain the activated event feature map;

[0018] The operation submodule is used to perform a bitwise multiplication operation on the image frame feature map and the activated event feature map to obtain a multiplied feature map;

[0019] The third convolutional layer is used to convolve the multiplied feature map to obtain a fused feature map;

[0020] The splicing submodule is used to splice the image frame and the fused feature map to obtain a spliced feature map.

[0021] Preferably, the multi-stage restoration module includes an encoder sub-network and a decoder sub-network;

[0022] The encoder sub-network is used to encode the spliced feature map to obtain an encoded feature map;

[0023] The decoder subnetwork is used to decode the encoded feature map to obtain a restored flare-removed image and an estimated flare.

[0024] Preferably, the event stream includes coordinate information of the triggered pixel, time information and polarity information of the event.

[0025] According to another aspect of the present invention, a method for removing image reflection flare based on an event camera is provided, the method comprising:

[0026] When the illumination is less than the preset brightness, the light source is turned on to provide conditions for backlit shooting;

[0027] The dual-mode camera captures image frames and event streams under backlight conditions;

[0028] The data processing unit receives the image frame and the event stream, and performs denoising and reconstruction on the event stream to obtain an event pseudo frame;

[0029] The data processing unit fuses and restores the image frame with the event pseudo frame to obtain a restored image with flare removed and an estimated flare, so as to remove the reflected flare from the image frame.

[0030] Preferably, the preset brightness is 400 lx.

[0031] Preferably, the data processing unit receives the image frame and the event stream, and denoises and reconstructs the event stream to obtain an event pseudo frame; the data processing unit fuses and restores the image frame and the event pseudo frame to obtain a restored image after flare removal and the estimated flare, which includes:

[0032] The preprocessing module in the data processing unit receives the image frame and the event stream, and uses the spatiotemporal correlation discrimination algorithm to denoise the event stream to obtain a denoised event stream; and uses the time dimension compression algorithm to reconstruct the denoised event stream to obtain an event pseudo frame;

[0033] The event-guided fusion module in the data processing unit fuses the image frame with the event pseudo frame to obtain a spliced feature map;

[0034] The multi-stage restoration module in the data processing unit restores the spliced feature maps to obtain a restored image with flare removed and an estimated flare.

[0035] Preferably, a spatiotemporal correlation discrimination algorithm is used to denoise the event stream, and the denoised event stream includes:

[0036] Count the number of events corresponding to each pixel in the event stream within a fixed period; when the number of events exceeds a preset threshold, delete the event corresponding to the current pixel to obtain an event stream with thermal noise eliminated;

[0037] On the basis of obtaining the event stream for eliminating thermal noise, when the time interval between adjacent events of the same pixel is less than a preset time threshold, the latter event is deleted to obtain the event stream for eliminating refractory period noise;

[0038] On the basis of obtaining the event stream with refractory period noise eliminated, when the spatial interval between adjacent events is greater than a preset interval threshold, the adjacent events are deleted to remove background noise, thereby obtaining the denoised event stream.

[0039] Preferably, reconstructing the denoised event stream using a time dimension compression algorithm to obtain an event pseudo frame includes normalizing the number of denoised events on each pixel in the denoised event stream to obtain the event pseudo frame.

[0040] Preferably, the event-guided fusion module in the data processing unit fuses the image frame with the event pseudo frame to obtain a spliced feature map including:

[0041] The first convolutional layer in the event-guided fusion module is used to convolve the image frame to obtain the image frame feature map;

[0042] The second convolutional layer in the event-guided fusion module is used to convolve the event pseudo-frame rotated 180° to obtain the event feature map;

[0043] The activation layer in the event-guided fusion module activates the event feature map to obtain the activated event feature map;

[0044] The operation submodule in the event-guided fusion module performs a bitwise multiplication operation on the image frame feature map and the activated event feature map to obtain a multiplied feature map;

[0045] The third convolutional layer in the event-guided fusion module convolves the multiplied feature maps to obtain a fused feature map;

[0046] The splicing submodule in the event-guided fusion module splices the image frame and the fused feature map to obtain a spliced feature map.

[0047] Preferably, the multi-stage restoration module in the data processing unit restores the spliced feature map to obtain a restored image after flare removal and the estimated flare, including:

[0048] The encoder sub-network in the multi-stage restoration module is used to encode the concatenated feature map to obtain the encoded feature map;

[0049] The decoder subnetwork in the multi-stage restoration module is used to decode the encoded feature map to obtain the restored flare-removed image and the estimated flare.

[0050] Preferably, the event stream includes coordinate information of the triggered pixel, time information and polarity information of the event.

[0051] Applying the technical solution of the present invention, a data processing unit receives image frames and event streams, denoises and reconstructs the event streams, and generates event pseudo-frames. The image frames and event pseudo-frames are then fused and restored to generate a restored, flare-removed image and estimated flare, thereby removing reflected flare from the image frames. This invention can remove reflected flare from traditional camera images, restore image details in the flare area, improve image quality, and enhance adaptability to flare patterns. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are included to provide a further understanding of the embodiments of the present invention, constitute a part of the specification, illustrate the embodiments of the present invention, and together with the description, explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0053] Figure 1 A schematic structural diagram of an image reflection flare removal system based on an event camera according to an embodiment of the present invention is shown;

[0054] Figure 2 Shown Figure 1 Schematic diagram of the structure of the event-guided fusion module and the multi-stage reduction module;

[0055] Figure 3 A flowchart of a method for removing image reflection flare based on an event camera according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0056] It should be noted that, in the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is in no way intended to limit the present invention and its application or use. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0057] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0058] Unless otherwise specifically stated, the relative arrangement of the parts and steps, the numerical expressions and the numerical values set forth in these embodiments do not limit the scope of the present invention. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The techniques, methods and equipment known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the techniques, methods and equipment should be considered as part of the authorization specification. In all examples shown and discussed here, any specific values should be interpreted as being merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following figures, and therefore, once an item is defined in one figure, it does not need to be further discussed in subsequent figures.

[0059] like Figure 1 As shown, the present invention provides a system for removing image reflection flare based on an event camera, the system comprising:

[0060] Light source, used to provide conditions for backlit shooting;

[0061] Dual-mode camera with image frame mode and event mode for capturing image frames and event streams in backlight conditions;

[0062] The data processing unit is used to receive image frames and event streams, and to denoise and reconstruct the event streams to obtain event pseudo frames; it is also used to fuse and restore the image frames with the event pseudo frames to obtain a restored image with flare removed and an estimated flare, so as to remove the reflected flare from the image frames.

[0063] The present invention receives image frames and event streams through a data processing unit, denoises and reconstructs the event streams to generate event pseudo-frames. The image frames and event pseudo-frames are then fused and restored to generate a restored flare-removed image and estimated flare, thereby removing reflected flare from the image frames. This invention can remove reflected flare from traditional camera images, restore image details in the flare area, improve image quality, and enhance adaptability to flare patterns.

[0064] According to one embodiment of the present invention, the data processing unit includes a pre-processing module, an event-guided fusion module, and a multi-stage restoration module;

[0065] The preprocessing module is used to perform denoising on the event stream to obtain a denoised event stream; and is also used to perform time dimension compression on the denoised event stream to obtain an event pseudo frame;

[0066] The event-guided fusion module is used to fuse the image frame with the event pseudo frame to obtain a spliced feature map;

[0067] The multi-stage restoration module is used to restore the spliced feature map to obtain a restored image with flare removed and an estimated flare.

[0068] According to one embodiment of the present invention, Figure 2 As shown, the event-guided fusion module includes three convolutional layers, an activation layer, an operator module, and a splicing module;

[0069] The first convolutional layer is used to convolve the image frame to obtain the image frame feature map;

[0070] The second convolutional layer is used to convolve the event pseudo frame rotated 180° to obtain the event feature map;

[0071] The activation layer is used to activate the event feature map to obtain the activated event feature map; wherein the activation layer can be a sigmoid activation layer;

[0072] The operation submodule is used to perform a bitwise multiplication operation on the image frame feature map and the activated event feature map to obtain a multiplied feature map;

[0073] The third convolutional layer is used to convolve the multiplied feature map to obtain a fused feature map;

[0074] The splicing submodule is used to splice the image frame and the fused feature map to obtain a spliced feature map.

[0075] According to one embodiment of the present invention, Figure 2 As shown, the multi-stage restoration module includes an encoder sub-network and a decoder sub-network;

[0076] The encoder sub-network is used to encode the spliced feature map to obtain an encoded feature map;

[0077] The decoder subnetwork is used to decode the encoded feature map to obtain a restored flare-removed image and an estimated flare.

[0078] According to an embodiment of the present invention, the event stream includes coordinate information of the triggered pixel, time information, and polarity information of the event.

[0079] In this embodiment, the first two stages of the multi-stage restoration module capture extensive contextual information through their wide receptive fields, and the last stage directly operates on the receptive field of the original input image resolution, preserving the fine texture details of the output image.

[0080] like Figure 3 As shown, the present invention also provides a method for removing image reflection flare based on an event camera, the method comprising:

[0081] When the illumination is less than the preset brightness, the light source is turned on to provide conditions for backlit shooting;

[0082] The dual-mode camera captures image frames and event streams under backlight conditions;

[0083] The data processing unit receives the image frame and the event stream, and performs denoising and reconstruction on the event stream to obtain an event pseudo frame;

[0084] The data processing unit fuses and restores the image frame with the event pseudo frame to obtain a restored image with flare removed and an estimated flare, so as to remove the reflected flare from the image frame.

[0085] According to an embodiment of the present invention, the preset brightness is 400 lx.

[0086] According to one embodiment of the present invention, a data processing unit receives an image frame and an event stream, and denoises and reconstructs the event stream to obtain an event pseudo frame; the data processing unit fuses and restores the image frame and the event pseudo frame to obtain a restored image after flare removal and an estimated flare, including:

[0087] The preprocessing module in the data processing unit receives the image frame and the event stream, and uses the spatiotemporal correlation discrimination algorithm to denoise the event stream to obtain a denoised event stream; and uses the time dimension compression algorithm to reconstruct the denoised event stream to obtain an event pseudo frame;

[0088] The event-guided fusion module in the data processing unit fuses the image frame with the event pseudo frame to obtain a spliced feature map;

[0089] The multi-stage restoration module in the data processing unit restores the spliced feature maps to obtain a restored image with flare removed and an estimated flare.

[0090] According to an embodiment of the present invention, a spatiotemporal correlation discrimination algorithm is used to perform denoising on an event stream, and the denoised event stream includes:

[0091] Count the number of events corresponding to each pixel in the event stream within a fixed period; when the number of events exceeds a preset threshold, delete the event corresponding to the current pixel to obtain an event stream with thermal noise eliminated;

[0092] On the basis of obtaining the event stream for eliminating thermal noise, when the time interval between adjacent events of the same pixel is less than a preset time threshold, the latter event is deleted to obtain the event stream for eliminating refractory period noise;

[0093] Based on the event stream from which the refractory period noise is eliminated, if the spatial interval between adjacent events is greater than a preset interval threshold, the adjacent events are deleted to remove background noise, thereby obtaining a denoised event stream. The spatial interval size can be set to 1 pixel.

[0094] According to one embodiment of the present invention, a time dimension compression algorithm is used to reconstruct the denoised event stream to obtain an event pseudo frame, which includes normalizing the number of denoised events on each pixel in the denoised event stream to obtain the event pseudo frame.

[0095] According to an embodiment of the present invention, the event-guided fusion module in the data processing unit fuses the image frame with the event pseudo frame to obtain a spliced feature map including:

[0096] The first convolutional layer in the event-guided fusion module is used to convolve the image frame to obtain the image frame feature map;

[0097] The second convolutional layer in the event-guided fusion module is used to convolve the event pseudo-frame rotated 180° to obtain the event feature map;

[0098] The activation layer in the event-guided fusion module activates the event feature map to obtain the activated event feature map;

[0099] The operation submodule in the event-guided fusion module performs a bitwise multiplication operation on the image frame feature map and the activated event feature map to obtain a multiplied feature map;

[0100] The third convolutional layer in the event-guided fusion module convolves the multiplied feature maps to obtain a fused feature map;

[0101] The splicing submodule in the event-guided fusion module splices the image frame and the fused feature map to obtain a spliced feature map.

[0102] According to one embodiment of the present invention, the multi-stage restoration module in the data processing unit restores the spliced feature map to obtain a restored image after flare removal and an estimated flare, including:

[0103] The encoder sub-network in the multi-stage restoration module is used to encode the concatenated feature map to obtain the encoded feature map;

[0104] The decoder subnetwork in the multi-stage restoration module is used to decode the encoded feature map to obtain the restored flare-removed image and the estimated flare.

[0105] According to an embodiment of the present invention, the event stream includes coordinate information of the triggered pixel, time information, and polarity information of the event.

[0106] In order to further understand the present invention, the method for removing image reflection flare based on an event camera of the present invention is described in detail below, which specifically includes the following steps:

[0107] S1. In a dark room or outdoor environment at night (i.e., illumination less than 400 lx), configure the light source and turn on the light switch;

[0108] S2. Install the dual-mode event camera, fix the dual-mode event camera on a tripod, adjust the dual-mode event camera lens so that the light source appears within the camera's field of view, and record the dual-mode dynamic vision sensor image frames and event stream data;

[0109] S3. Remove noise from the original event stream using a spatiotemporal correlation discrimination algorithm; reconstruct the event pseudo-frame using a time dimension compression algorithm; and restore the restored image frame by rotating the event pseudo-frame 180° and fusing it with the image frame to remove reflection flare from the image frame.

[0110] In summary, the present invention provides a system and method for removing image reflection flare based on an event camera. A data processing unit receives image frames and event streams, denoises and reconstructs the event streams to generate event pseudo-frames. The image frames and event pseudo-frames are then fused and restored to generate a restored image with flare removed and an estimated flare, thereby removing reflection flare from the image frame. This system can remove reflection flare from images taken with traditional cameras, restore image details in the flare area, improve image quality, and enhance adaptability to flare patterns.

[0111] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used herein to describe the spatial positional relationship of a device or feature to other devices or features as shown in the figures. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figures. For example, if the device in the drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0112] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore cannot be understood as limiting the scope of protection of the present invention.

[0113] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A system for removing image reflection flare based on an event camera, characterized in that: The system comprises: Light source, used to provide conditions for backlit shooting; Dual-mode camera with image frame mode and event mode for capturing image frames and event streams in backlight conditions; a data processing unit, configured to receive image frames and event streams, and perform denoising and reconstruction on the event streams to obtain event pseudo frames; and further configured to fuse and restore the image frames with the event pseudo frames to obtain a restored image with flare removed and an estimated flare, thereby removing reflection flare from the image frames; The data processing unit includes a pre-processing module, an event-guided fusion module and a multi-stage restoration module; The preprocessing module is used to perform denoising on the event stream to obtain a denoised event stream; and is also used to perform time dimension compression on the denoised event stream to obtain an event pseudo frame; The event-guided fusion module is used to fuse the image frame with the event pseudo frame to obtain a spliced feature map; The multi-stage restoration module is used to restore the spliced feature map to obtain a restored flare-removed image and an estimated flare; The event-guided fusion module includes three convolutional layers, an activation layer, an operator module, and a splicing module; The first convolutional layer is used to convolve the image frame to obtain the image frame feature map; The second convolutional layer is used to convolve the event pseudo frame rotated 180° to obtain the event feature map; The activation layer is used to activate the event feature map to obtain the activated event feature map; The operation submodule is used to perform a bitwise multiplication operation on the image frame feature map and the activated event feature map to obtain a multiplied feature map; The third convolutional layer is used to convolve the multiplied feature map to obtain a fused feature map; The splicing submodule is used to splice the image frame and the fused feature map to obtain a spliced feature map.

2. The system according to claim 1, wherein: The multi-stage restoration module includes an encoder sub-network and a decoder sub-network; The encoder sub-network is used to encode the spliced feature map to obtain an encoded feature map; The decoder subnetwork is used to decode the encoded feature map to obtain a restored flare-removed image and an estimated flare.

3. The system according to claim 1, wherein: The event stream includes coordinate information of the triggered pixel, time information and polarity information of the event.

4. A method for removing image reflection flare based on an event camera, characterized in that: The method comprises: When the illumination is less than the preset brightness, the light source is turned on to provide conditions for backlit shooting; The dual-mode camera captures image frames and event streams under backlight conditions; The data processing unit receives the image frame and the event stream, and performs denoising and reconstruction on the event stream to obtain an event pseudo frame; The data processing unit fuses and restores the image frame with the event pseudo frame to obtain a restored image with flare removed and an estimated flare, thereby removing the reflected flare from the image frame. The data processing unit receives the image frame and the event stream, and performs denoising and reconstruction on the event stream to obtain an event pseudo frame; the data processing unit fuses and restores the image frame and the event pseudo frame to obtain a restored image after flare removal and an estimated flare, which includes: The preprocessing module in the data processing unit receives the image frame and the event stream, and uses the spatiotemporal correlation discrimination algorithm to denoise the event stream to obtain a denoised event stream; and uses the time dimension compression algorithm to reconstruct the denoised event stream to obtain an event pseudo frame; The event-guided fusion module in the data processing unit fuses the image frame with the event pseudo frame to obtain a spliced feature map; The multi-stage restoration module in the data processing unit restores the spliced feature map to obtain a restored flare-removed image and an estimated flare; The event-guided fusion module in the data processing unit fuses the image frame with the event pseudo frame to obtain the spliced feature map including: The first convolutional layer in the event-guided fusion module is used to convolve the image frame to obtain the image frame feature map; The second convolutional layer in the event-guided fusion module is used to convolve the event pseudo-frame rotated 180° to obtain the event feature map; The activation layer in the event-guided fusion module activates the event feature map to obtain the activated event feature map; The operation submodule in the event-guided fusion module performs a bitwise multiplication operation on the image frame feature map and the activated event feature map to obtain a multiplied feature map; The third convolutional layer in the event-guided fusion module convolves the multiplied feature maps to obtain a fused feature map; The splicing submodule in the event-guided fusion module splices the image frame and the fused feature map to obtain a spliced feature map.

5. The method according to claim 4, characterized in that The preset brightness is 400 lx.

6. The method according to claim 4, characterized in that The event stream is denoised using a spatiotemporal correlation discrimination algorithm. The denoised event stream includes: Count the number of events corresponding to each pixel in the event stream within a fixed period; when the number of events exceeds a preset threshold, delete the event corresponding to the current pixel to obtain an event stream with thermal noise eliminated; On the basis of obtaining the event stream for eliminating thermal noise, when the time interval between adjacent events of the same pixel is less than a preset time threshold, the latter event is deleted to obtain the event stream for eliminating refractory period noise; On the basis of obtaining the event stream with the refractory period noise eliminated, when the spatial interval between adjacent events is greater than a preset interval threshold, the adjacent events are deleted to remove the background noise, thereby obtaining the denoised event stream.

7. The method according to claim 4, characterized in that The denoised event stream is reconstructed using a time dimension compression algorithm to obtain an event pseudo frame, which includes normalizing the number of denoised events on each pixel in the denoised event stream to obtain the event pseudo frame.

8. The method according to claim 4, characterized in that The multi-stage restoration module in the data processing unit restores the spliced feature map to obtain the restored flare-removed image and the estimated flare, including: The encoder sub-network in the multi-stage restoration module is used to encode the concatenated feature map to obtain the encoded feature map; The decoder subnetwork in the multi-stage restoration module is used to decode the encoded feature map to obtain the restored flare-removed image and the estimated flare.

9. The method according to claim 4, characterized in that The event stream includes coordinate information of the triggered pixel, time information and polarity information of the event.

Images