Photographic image processing method and device

Abstract

This disclosure relates to an image processing method and apparatus. An electronic device is provided for processing a series of images acquired from a scene containing static and dynamic objects. The electronic device includes processing circuitry configured to: select a specific image from the series of images containing static objects; generate a motion trajectory of a dynamic object in at least a portion of the images in the series of images; and obtain a final image based on both the specific image and the generated motion trajectory of the dynamic object.

Description

Technical Field

[0001] The present disclosure relates to image processing, and in particular to photographic image processing. Prior Art

[0002] With the increasing popularity of electronic photographic equipment, such as various digital cameras and portable devices equipped with photographic equipment, people are increasingly using electronic photographic equipment to capture photos, videos, etc. of various scenes. In photography, various parameters are often adjusted to achieve a variety of photo effects. One commonly used parameter is shutter speed, which controls the length of exposure when taking a photo. In practice, adjusting shutter speed can achieve different effects. A slow shutter speed reduces the shutter speed and extends the shutter duration to achieve a long exposure, thereby creating special dynamic effects. For example, a slow shutter speed can be used to capture the flow of flowing water or clouds, or to capture the bright trails of moving objects, such as light trails from vehicles, when photographing night scenes. Unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Likewise, unless otherwise indicated, it should not be assumed that problems identified with respect to one or more approaches are recognized as prior art based on this section. Summary of the Invention

[0003] An object of the present disclosure is to improve captured image processing so as to obtain high-quality images with a slow shutter photography effect. In one aspect of the present disclosure, an electronic device for processing a series of images is provided, wherein the series of images is obtained by photographing a scene containing static objects and dynamic objects. The electronic device includes a processing circuit configured to: generate a processed image that does not contain image content related to the dynamic object based on a specific image selected from the series of images containing the static object; generate a motion trajectory of the dynamic object in at least a portion of the images in the series of images; and obtain a final image based on both the processed image and the generated motion trajectory of the dynamic object. In one aspect of the present disclosure, a method for processing a series of images is provided, wherein the series of images is obtained by photographing a scene containing static objects and dynamic objects. The method comprises: generating a processed image that does not contain image content related to the dynamic object based on a specific image containing the static object selected from the series of images; generating a motion trajectory of the dynamic object in at least a portion of the images in the series; and obtaining a final image based on both the processed image and the generated motion trajectory of the dynamic object. In yet another aspect, a method is provided comprising at least one processor and at least one storage device, wherein the at least one storage device stores instructions thereon, which, when executed by the at least one processor, can cause the at least one processor to perform the method as described herein. In yet another aspect, a storage medium storing instructions is provided, which, when executed by a processor, can cause the method described herein to be performed. In yet another aspect, a program product is provided, comprising instructions which, when executed by a processor, cause the processor to perform the method as described herein. Further features of the present invention will become apparent from the following description of exemplary embodiments with reference to the attached drawings. Simple diagram description

[0004] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present invention and, together with the description, serve to explain the principles of the present invention. In the drawings, like reference numerals designate like items. [ FIG1 ] A block diagram showing an electronic device for image processing according to an embodiment of the present disclosure. [FIGS. 2A to 2D] are schematic diagrams showing background content replacement according to an embodiment of the present disclosure. [ FIG3 ] A flowchart showing an image processing method according to an embodiment of the present disclosure. [ FIG. 4A ] illustrates an exemplary process of generating an image with a slow shutter photography effect according to an embodiment of the present disclosure, and [ FIG. 4B ] illustrates an exemplary image with a slow shutter photography effect. [ FIG. 5 ] shows a photographing device according to an embodiment of the present disclosure. [ FIG6 ] A block diagram showing an exemplary hardware configuration of a computer system capable of implementing an embodiment of the present invention. While the embodiments described in this disclosure may be susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and are herein described in detail. However, it should be understood that the drawings and detailed description thereof are not intended to limit the embodiments to the particular forms disclosed, but on the contrary, the intent is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the claims. Implementation Method

[0005] The following describes exemplary embodiments of the present disclosure in conjunction with the accompanying drawings. For the sake of clarity and conciseness, not all features of the embodiments are described in this specification. However, it should be understood that in implementing the embodiments, many implementation-specific settings must be made to achieve the developer's specific goals, such as meeting device and service-related constraints, which may vary depending on the implementation. Furthermore, it should be understood that while development work can be complex and time-consuming, it is a routine task for those skilled in the art who benefit from this disclosure. It should also be noted here that in order to avoid obscuring the present disclosure due to unnecessary details, the accompanying drawings only show processing steps and / or equipment structures that are closely related to at least the solution according to the present disclosure, while other details that are not closely related to the present disclosure are omitted. The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that similar reference numerals and letters in the drawings indicate similar items, and therefore once an item is defined in one drawing, it is not necessary to discuss it again for subsequent drawings. In the present disclosure, the terms "first," "second," etc. are used merely to distinguish between elements or steps, but are not intended to indicate temporal order, priority, or importance. Currently, when shooting with electronic photographic equipment, different effects can be achieved by adjusting the shutter speed. In particular, slow shutter mode is often used to achieve special dynamic effects by extending the shutter time. However, when shooting with slow shutter mode, the exposure time is long, and even the slightest shake during the shooting process can cause problems such as blurring of static objects in the final image. In existing photography techniques, to achieve slow shutter effects, the camera must be fixed on a tripod and then exposed for a long time. However, this method increases the burden on the photographer and does not effectively suppress the negative effects of shake. However, there is currently no software technology for cameras to solve the shaking problem during slow shutter photography. Therefore, improved technology is needed to obtain improved images with slow shutter photography effects. The present disclosure proposes a technology for processing a group of images, particularly a video clip or a group of images captured within a certain time (e.g., equal to a shutter setting time). The technology involves analyzing and processing static and dynamic objects in such a group of images, and generating photos resembling slow-shutter photography effects based on specific static object images and dynamic object trajectories. It should be noted that the disclosed solution is an improved image processing method that simulates the effect of slow shutter photography by acquiring a video clip or a set of images and performing image processing on the video clip / images. This method is independent of the camera's shooting mode, such as the camera's shutter mode setting, particularly the slow shutter shooting mode. Specifically, in the camera's slow shutter shooting mode, the final image is generated based on optical imaging after the shutter time is reached. In other words, the slow shutter shooting mode only produces a single final image. However, the disclosed solution processes a video clip or a set of images. Specifically, the video clip or the set of images can be obtained by continuously shooting with a camera, and the shooting mode, including the shutter setting, can be conventional. Only the shooting time length needs to be appropriately set. This shooting time length can, for example, be equal to a commonly used slow shutter time length or another suitable time length. It should be noted that the present disclosure does not simply perform anti-shake processing on videos, but rather selects, optimizes, and combines the captured video data / a set of images. Even if there is shaking when shooting the video / photo, or even if there may be shaking in the captured video / photo, high-quality photos with slow shutter photography effects can still be obtained. Hereinafter, image processing according to the present disclosure will be described in detail with reference to the accompanying drawings. Figure 1 shows a block diagram of a device for image processing of a series of images according to an embodiment of the present disclosure. As shown in Figure 1, device 10 includes processing circuitry 102, which is configured to generate a processed image that does not contain image content related to dynamic objects based on a specific image selected from the series of images that contains a static object; generate a motion trajectory of the dynamic object in at least a portion of the series of images; and obtain a final image based on both the processed image and the generated motion trajectory of the dynamic object. In embodiments of the present disclosure, a series of images is obtained by capturing a scene containing at least one of a static object and a dynamic object. In some embodiments, the series of images is obtained by capturing images with a camera over a specific time period. For example, the images may be captured continuously or at specific time intervals. In some embodiments, the series of images is obtained by capturing images over a specific time period using a camera under non-stationary conditions. The capture time period, i.e., the duration of the capture, can be appropriately set, for example, corresponding to a shutter speed setting. For example, when a user captures images with a handheld camera, a video clip is captured. This video clip essentially contains multiple frames of data, i.e., multiple images, which can be used as a series of images to be processed. For example, depending on the parameters of the slow shutter mode and the capture duration settings, the number of images in the series to be processed can vary. For example, when the capture parameters are set to 30 frames per second for 2 seconds, the resulting series of images to be processed will contain 30 x 2 = 60 frames of images. It should be noted that the series of images to be processed can be all images captured during the specific time period, or a portion of the images, such as randomly selected or evenly spaced images. In the disclosed embodiments, static and dynamic objects in video footage are processed separately, allowing for various suitable methods to identify and distinguish static and dynamic objects within a collection of images. Specifically, all images can be analyzed, and by comparing pixel information at various locations within the images and allowing for a certain offset, static and dynamic objects can be distinguished throughout the video. In some embodiments, the processing circuitry is configured to identify objects that are present in each image in the series of images and have a positional offset less than a specific threshold as static objects. Specifically, a static object should be one that remains substantially stationary throughout the entire capture process, and thus is present in all frames of the video and has a positional offset within a certain tolerance. This specific threshold / tolerance can be set empirically or derived from analysis of training image sets or previously captured images. In other embodiments, the processing circuitry is configured to identify as dynamic objects objects that do not appear in all images in the series of images, or objects that appear in all images in the series of images but have a positional deviation greater than a specific threshold. Specifically, during the image recognition process, in addition to the identified static objects, other objects in the image can often be considered dynamic objects. Dynamic objects can be, for example, objects moving in the video footage, whose positional deviation is greater than a specific threshold, or objects that enter or leave the video capture range during filming. The threshold here can be a previously specified threshold or a separately set threshold. In particular, the identification of static and dynamic objects can be performed individually across all video footage or at specific intervals. For example, a specific video clip, such as the first or last video clip, can be selected as a reference, with all other video clips compared to it. Furthermore, the identification of static and dynamic objects can be performed by a processing circuit, or by a device external to the processing circuitry of the electronic device, or even by a device external to the electronic device that can access the captured video footage, recognize the image, and provide the recognition result to the processing circuitry of the electronic device. According to embodiments of the present disclosure, processing of static objects is performed based on a specific image containing the static object selected from the series of images. In some embodiments, the specific image is an image in the series of images in which the static object meets specific requirements. Specific conditions are related to the characteristics and requirements of the captured image. Meeting specific requirements includes, for example, achieving the best photographic effect, the clearest image, the best facial expression, the best color, or, even if clarity is not sufficient, ensuring that the demeanor and form of the person meet the requirements. As an example, a specific image is an image selected from a series of images that exhibits relatively good static object representation. For example, among multiple frames contained in a video footage captured by a camera during a specific time period, a frame with relatively good static object representation is selected from the frames contained in the video as the static object frame and serves as the specific image. The "good static object representation" refers to an image that meets specific requirements for the clarity, shape, color, etc. of the static object. Specifically, if there are multiple images that meet the specific requirements, the selected specific image is the best one among them. The selection of a specific image can be performed in a variety of appropriate ways. In some embodiments, the selection can be made from a series of images based on a static object template / model. According to some embodiments, the processing circuit is further configured to compare each image in the series with the static object template and select the image in the series that is most similar to the static object template as the specific image. Static object templates are templates obtained based on various requirements, such as templates with high clarity, good human expressions, good object color representation, good morphology, etc. The proximity is the proximity between the static object in the image and the static object template with respect to at least one of clarity, human expressions, morphology, and color. Of course, the proximity can also be proximity with respect to other types of information, especially information related to the aforementioned specific requirements. In some embodiments, the static object template / model is obtained through training. Specifically, the static object template is a static object data model obtained by training based on a training image set. In some embodiments, the static object template / model is obtained based on a pre-provided training data set. In some embodiments, at least a portion of each captured image can be added to the training data set. In other embodiments, the static object template / model can be dynamically updated, for example, by being retrained when the training data set changes. Changes to the training data set include, but are not limited to, periodically replacing the training data set with a new one, periodically updating the training data set by adding additional training data, and so on. In an embodiment of the present disclosure, processing of static objects includes processing a specific image to remove dynamic object image content therein, thereby obtaining image / frame data containing only static objects as a reference image for obtaining the final image. According to an embodiment of the present disclosure, the processing circuit can be further configured to replace the content related to the dynamic object in the specific image with background content. For example, when removing the dynamic object from a selected specific image of a static object, the pixel content area of ​​the dynamic object can be removed, and the background pixel information in this area can be restored by referencing pixel information at similar locations in other frame data, and this frame data can be used as the reference image for the final image. In some embodiments, the processing circuitry may be further configured to: select, from the series of images, images whose dynamic object positions do not overlap with those in the specific image and whose static object positions have the smallest deviation from those in the specific image; and determine background content based on the content at positions in the selected images that correspond to the dynamic object positions in the specific image. In some examples, if the static object positions in the selected images coincide with those in the specific image, content in the selected images whose positions correspond to and are the same size as those in the specific image is used as the background content. In other examples, if the static object positions in the selected images deviate from those in the specific image, content in the selected images whose positions correspond to those in the specific image and are adjusted based on the deviation is used as the background content. Hereinafter, exemplary processing of a specific image according to an embodiment of the present disclosure will be described with reference to the accompanying drawings. First, based on the specific image of a static object, dynamic objects and portions of static objects are identified in the image data. As shown in Figure 2A, assuming a 2-second capture time and 30 frames per second, and assuming that the 15th frame is a specific image / frame selected from the video data, two static objects, Still Object 1 and Still Object 2, and one dynamic object are identified. It should be noted that the number of static and dynamic objects shown in the figure is exemplary; other numbers are possible. Then, all frames of data in which the dynamic object does not overlap with the position of the dynamic object in the specific image are filtered out from the captured frames. As shown in Figure 2B, as an example, frames 1 to 9 and frames 20 to 59 are filtered out. After that, the position coordinates of the static object selected from the 15th frame data as the specific image are analyzed, and then compared with the corresponding static object position coordinates in each filtered frame data, and a frame data with the smallest static object size and position offset is selected as reference data for subsequent processing, as shown in Figure 2C, for example, the 40th frame data is selected. Then, the content in the 40th frame of data is used to replace the content at the position of the dynamic object in the 15th frame of data selected as the specific image. The replacement based on the filtered 40th frame data can be divided into two cases. In one scenario, if the size and position of the static object in the 40th frame is identical to that in the 15th frame, a clip of the same size is directly captured from the location in the 40th frame corresponding to the location of the dynamic object in the 15th frame (e.g., the same location) and then patched to the corresponding location in the 15th frame. In another scenario, if there is a slight deviation in the size and position of the static object in the 40th and 15th frames, the size deviation of the static object in the two data sets can be calculated. Based on this deviation, the image corresponding to the dynamic object in the 40th frame is transformed accordingly (e.g., slightly shifting the clipping position or scaling it), and then patched to the corresponding location in the 15th frame. This ultimately generates a frame without the dynamic object, which serves as the reference image for obtaining the final image, as shown in Figure 2D. According to embodiments of the present disclosure, processing dynamic objects involves determining the object's motion from a series of images. In some examples, this involves generating a motion trajectory for the object. For example, in a captured video, a dynamic object may be moving throughout the video, or may enter or exit the video midway. Therefore, the object's motion trajectory can indicate traces of the object's movement within the video. According to some embodiments, the processing circuit is further configured to track the movement of a dynamic object in the series of images, from the image in which the dynamic object first appears to the image in which it last appears, to generate a motion trajectory. For example, the entire movement of the dynamic object in the video can be tracked based on an object recognition algorithm to generate a trajectory. According to some embodiments, the trajectory can be obtained by connecting the positions of the dynamic object in each image. According to embodiments of the present disclosure, the motion trajectory of a dynamic object may include a light trail of the dynamic object. In particular, when shooting slow-motion night scenes, it is particularly desirable to obtain light and shadow traces to enhance the aesthetics of the photograph. Therefore, in some embodiments of the present disclosure, the processing circuit is further configured to: obtain optical information of the dynamic object in the series of images, from the image in which the dynamic object first appears to the image in which it last appears; and generate a light trail of the dynamic object based on the motion trajectory of the dynamic object and the optical information. In some embodiments, the optical information includes at least one of brightness information and color information of the dynamic object in each image in the series of images, from the image in which the dynamic object first appears to the image in which it last appears. It should be noted that the optical information may also include other appropriate information, as long as the information can be used to generate an optical trace. In the present disclosure, various appropriate methods can be used to generate optical traces. In some embodiments, various appropriate algorithms can be used to generate optical traces. For example, by analyzing brightness information at various locations of a dynamic object and combining it with the principles of light graffiti, the motion trajectory of the dynamic object can be converted into a light trace. In some embodiments, the processing circuit is further configured to: analyze optical information at various positions on the dynamic object for each image in the series of images from the image where the dynamic object first appears to the image where it last appears, to obtain highlighted portions of the dynamic object; and connect the highlighted portions at the same position on the dynamic object in the image where the dynamic object first appears to the image where it last appears in the series of images, to generate a motion light trail of the dynamic object. In some embodiments, the highlight of a moving object is determined by comparing the object's brightness information with that of the image background. Specifically, in slow shutter photography, whether the object appears in the final image depends on its exposure contribution (exposure time and object brightness information). For a moving object, if the difference between the object's brightness and the road background brightness is not significant, the road exposure contribution will be significantly higher than the object's because the object's position is very short. Consequently, the object will appear faint or even absent in the final image. If the brightness of a part of the object (such as a car headlight) is significantly higher than the road background brightness, this can compensate for the lack of exposure time, allowing the highlight to appear in the final image. This is why, when shooting with a slow shutter speed, only the headlight trails remain, with the rest of the car barely visible. In the disclosed embodiment, a motion trajectory is first obtained by tracking a dynamic object. Each frame of data is then analyzed to determine the road background brightness per unit time (in a 1 / 30 second setting, the time unit for a frame is 1 / 30 second). Combined with the exposure time, the exposure ratio of the road background during the capture process is determined, thereby estimating the total road background brightness. The brightness values ​​of each part of the dynamic object are analyzed and compared with the road background brightness value to determine the position coordinates of the high-brightness areas (if any) on the dynamic object and obtain the color information for these areas. The highlighted areas at the same location / area of ​​the dynamic object in each frame of data are connected to generate a moving light trail with their original color. According to embodiments of the present disclosure, the motion trajectory / moving light trail of the dynamic object generated above can be further processed. In some embodiments, optimization can be performed based on user shooting requirements, including removing some noise to make the generated motion trajectory / moving light trail more continuous and smooth. The noise may be caused by the dynamic object moving slightly in the left and right directions in addition to moving forward, such as a car temporarily changing lanes. In other embodiments, the trajectory of the dynamic object can also be filtered. In some embodiments, the motion trajectory of the dynamic object used to generate the final image refers to the motion trajectory of the dynamic object that appears in more than a predetermined number of images in the series of images. This predetermined number can be appropriately set, such as empirically. As an example, if there may be multiple dynamic objects in the shooting scene, the trajectories of dynamic objects that appear for a shorter time in the captured video can be deleted, thereby effectively avoiding relatively cluttered motion trajectories and highlighting the main long trajectories. According to some embodiments of the present disclosure, a final image can be generated based on a processed image generated from a specific image of a static object and the obtained motion trajectory of a dynamic object. In some embodiments, the motion trajectory of the dynamic object is synthesized into the processed image to obtain the final image. The synthesis operation can be performed in various appropriate ways, for example, by directly superimposing the motion trajectory onto the corresponding position in the specific image of the static object. In the structural example of the above-described device, processing circuit 102 can be in the form of a general-purpose processor or a dedicated processing circuit, such as an ASIC. For example, processing circuit 102 can be constructed from a circuit (hardware) or a central processing device (such as a central processing unit (CPU)). Furthermore, processing circuit 102 can carry a program (software) for operating the circuit (hardware) or the central processing device. This program can be stored in memory (such as stored in memory) or in an externally connected external storage medium, or downloaded via a network (such as the Internet). According to an embodiment of the present disclosure, the processing circuit 102 may include various units for implementing the aforementioned functions, such as a processed image acquisition unit 104 for generating a processed image that does not contain image content related to dynamic objects based on a specific image containing a static object selected from the series of images; a motion trajectory generation unit 106 for generating a motion trajectory of a dynamic object in at least a portion of the series of images; and a synthesis unit 108 for obtaining a final image based on both the processed image and the generated motion trajectory of the dynamic object. Each unit may operate as described above and will not be described in detail here. In particular, the processing circuit 102 may further include an object recognition unit 110, which is used to recognize at least one of a static object and a dynamic object in an image. The operation may be as described above and will not be described in detail here. In particular, the processing circuit 102 may further include a selection unit 112, which is used to select a specific image containing a static object from the series of images. The operation can be as described above and will not be described in detail here. Specifically, the motion trajectory generation unit 106 may include an optical information acquisition unit 1062 for acquiring optical information about the dynamic object from the image in which the dynamic object first appears to the image in which it last appears in the series of images, and a light trail generation unit 1064 for generating a motion light trail of the dynamic object based on the motion trajectory of the dynamic object and the optical information. Each unit may operate as described above and will not be described in detail here. It should be noted that in Figure 1, the object recognition unit 110, selection unit 112, optical information acquisition unit 1062, and light trace generation unit 1064 are depicted with dashed lines to illustrate that these units are not necessarily included in the processing circuit or do not exist. As an example, these units may be within the terminal-side electronic device but outside the processing circuit, or even located outside the electronic device 10. It should be noted that although Figure 1 shows the various units as discrete units, one or more of these units may be combined into a single unit or split into multiple units. It should be noted that the aforementioned units are merely logical modules divided according to the specific functions they implement, and are not intended to limit specific implementation methods. For example, they can be implemented using software, hardware, or a combination of software and hardware. In actual implementation, the aforementioned units can be implemented as independent physical entities, or they can be implemented by a single entity (e.g., a processor (CPU or DSP, etc.), an integrated circuit, etc.). In addition, the aforementioned units are shown with dashed lines in the drawings to indicate that these units may not actually exist, and the operations / functions they implement can be implemented by the processing circuit itself. It should be understood that Figure 1 is merely a schematic diagram of the structure of an electronic device for image processing. Electronic device 10 may also include other possible components, such as memory, a network interface, and a controller, which are not shown for clarity. Specifically, the processing circuitry may be associated with the memory. For example, the processing circuitry may be directly or indirectly connected (e.g., with other components connected in between) to the memory to access image processing-related data. The memory may store various data and / or information generated by the processing circuitry 102. The memory may also be located within the terminal-side electronic device but outside the processing circuitry, or even outside the terminal-side electronic device. The memory may be volatile and / or non-volatile. For example, the memory may include, but is not limited to, random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), and flash memory. The following describes a flowchart of an image processing method according to an embodiment of the present disclosure with reference to FIG3 . This image processing method is intended to process a series of images captured from a scene containing both static and dynamic objects. As shown in FIG3 , in step S301 of the image processing method, a processed image is generated that does not contain image content related to dynamic objects based on a specific image selected from the series of images containing a static object. In step S302, a motion trajectory of the dynamic object in at least a portion of the series of images is generated. Finally, in step S303, a final image is obtained based on both the processed image and the generated motion trajectory of the dynamic object. It should be noted that these steps can be performed by any appropriate device or device component, such as the aforementioned image processing device, the processing circuit within the image processing device, the corresponding components within the processing circuit, and so on. It should be noted that the image processing method according to the embodiments of the present disclosure may also include other steps, such as the various further processing steps described above. Furthermore, these further processing steps can also be performed by appropriate devices or device components and will not be described in detail here. 4A , a basic flowchart of exemplary image processing for achieving a slow shutter photography effect according to an embodiment of the present disclosure will be described below, in which a video clip shot by a user's handheld photography device is analyzed and ultimately a high-quality photo with a slow shutter photography effect is generated. First, all the frame data in the captured video data are analyzed, and the static objects and dynamic objects in the entire video are divided by comparing the pixel information of each position and allowing a certain offset. Next, a frame of data with relatively good performance is selected, and pixels representing dynamic objects are removed from it. Background pixels in this area are then added back using pixel information from similar locations in other frames. This results in a frame containing only static objects, which serves as the reference image for the final image. If shooting is performed at the most common setting of 30 frames per second, each frame represents only 1 / 30 of a second. Even if there is some motion blur during the entire recording process, the clarity of the static objects in that frame is guaranteed. Then, based on the identification of dynamic objects, the motion trajectory of the dynamic objects is tracked in the entire video, and the brightness information of each position of the dynamic objects is combined to generate the light trail of the dynamic objects. Finally, the moving light trails of the dynamic object are combined with the frame containing only the static object to produce the final image. Figure 4B shows the resulting image with a slow shutter photography effect. The box in the lower left corner of the image identifies the stationary car in the image, which is a static object and will be clearly displayed. The box to the right of this box identifies the moving light trails of the moving vehicle in the middle road area, which is a dynamic object. It should be noted that the order of these steps is not limited to this, but can be adjusted appropriately. For example, static frame image processing and the generation of dynamic object motion trajectories can be performed simultaneously, or the static frame image data can be processed after the dynamic object trajectory is obtained. In this way, by analyzing a video clip captured by a user's handheld camera and then applying appropriate image processing, a high-quality photo with a slow shutter effect can be generated, even if there is some shake during the shooting process. The reference image used to synthesize the final photo is automatically selected from the captured video footage. Even if there is shake during the entire shooting process, or even if some video footage is affected by shake, the appropriate image can still be easily and accurately selected, helping to improve the final image quality. It should be noted that the image to be processed can be any appropriate image, such as a raw image obtained by a photographic device, or an image that has undergone specific processing, such as preliminary filtering, anti-aliasing, color adjustment, contrast adjustment, normalization, etc. It should be noted that pre-processing operations may also include other types of pre-processing operations known in the art, which will not be described in detail here. In particular, the disclosed solution can be used in combination with various image processing techniques in existing photographic devices. Specifically, it can be used in combination with various image white balance, exposure compensation, anti-shake processing, ghosting compensation, etc. As an example, after obtaining a final image with a slow shutter photography effect using the disclosed solution, the various aforementioned processing steps can be performed. As another example, an image captured by a user's handheld device can be subjected to the aforementioned processing steps and then subjected to the disclosed processing steps to obtain a further optimized image with a slow shutter photography effect. Of course, the aforementioned processing steps can be performed simultaneously during the capture process. In particular, the technical concept of the present disclosure can preferably be applied to existing photographic equipment through hardware (such as chips, electronic components, etc.), firmware or software. In this way, when the photographic equipment is not fixed, such as when the photographic equipment is handheld or held in other non-fixed ways, wonderful photos with slow shutter photography effects can also be taken, which can reduce the burden / weight of the user in photography and simplify the user's photography operation without using a tripod or the like to fix the photographic equipment. In some embodiments, the image processing electronic device of the present disclosure can be integrated into a photographic device, for example, in the form of an integrated circuit, a processor, or even within the photographic device's existing processing circuitry. Alternatively, it can be removably connected to the photographic device as a separate component, for example, as a separate module, or fixedly integrated with a camera lens that is removably attached to the photographic device. In this way, even if the camera lens is replaced with another device, the captured image can still be processed using the solution of the present disclosure to obtain an image with a slow shutter photography effect. In some embodiments, it can even be set on a remote device with which the photographic device can communicate. In this case, the photographic device can transmit the captured image to the processing device after capturing it, and after the processing device performs image processing, the processed image can be transmitted back to the photographic device for display, or displayed on another device. The processing device can be stored in a device that can be connected to the photographic device for taking pictures, such as a portable electronic device. In some embodiments, the disclosed method can be implemented via software algorithms, allowing for convenient integration into various types of photographic equipment, such as video cameras, still cameras (e.g., SLRs, mirrorless SLRs), and mobile phone cameras. Specifically, the disclosed method can be implemented as a computer program or instruction executed by a processor of a photographic device to perform image processing on captured images. It should be noted that the photographic devices to which the technical solutions of this disclosure can be applied include various types of optical photographic devices, such as lenses mounted on portable devices, camera devices on drones, and camera devices in surveillance equipment. However, photographic devices are not limited to these types; as long as the photographic device is capable of continuously capturing images within a specific time period to obtain corresponding videos / photos, the present disclosure can be used in many applications. For example, the present invention can be used to monitor, identify, and track objects in still images or moving videos captured by a camera, and is particularly advantageous for portable devices equipped with cameras, (camera-based) mobile phones, and the like. It should be noted that while the above description primarily refers to image processing to achieve a slow shutter photography effect, the disclosed solutions can be applied to other situations where image processing is performed to produce similar slow shutter photography effects. In particular, the goal is to obtain an image or video that combines an image of a static object with the motion of a dynamic object. For example, when a short video can be captured, and a combination of static and dynamic objects appears in the video, the concepts of the disclosed solutions can be used to rationally construct the motion of the dynamic object and combine it with the static object to produce the desired short video. According to an embodiment of the present disclosure, a photographic device is also provided, comprising an image acquisition device for acquiring a series of images, the series of images being obtained by photographing a scene containing at least one of a static object and a dynamic object, and the aforementioned electronic device for image processing, for performing image processing on the acquired series of images. According to an embodiment of the present disclosure, the image acquisition device is intended to be any suitable device capable of acquiring such a series of images, and can be implemented in various suitable ways. For example, it can include a camera, a photographic device, etc. to acquire images by photographing a scene, or it can acquire images from other photographic components of the photographic device, or even from a device outside the photographic device. An exemplary implementation of a photographic device according to the present disclosure will be described below. Figure 5 shows a block diagram of a photographic device according to an embodiment of the present disclosure. The photographic device 50 includes an image processing device 502, which can be used to process captured images to obtain a photographic image with a slow shutter photography effect. The compensation device can be implemented in an electronic device, such as the electronic device 10 described above. The photographing device 50 may include a lens unit 504 , which may include various optical lenses known in the art for imaging an object on a sensor through optical imaging. The photographic device may further include an output device for outputting the photographic image with a slow shutter effect obtained by the image processing device. The output device may be in various suitable forms, such as a display device, or a communication device for outputting the photographic image to another device, such as a server or cloud. The photographic device 50 may include a photographic filter 506, which may include various photographic filters / filters known in the art, which may be mounted to the front of the lens. The photographic device 50 may also include a processing circuit 508, which can be used to process the captured image. This can include various pre-processing steps before the image is processed, or various post-processing steps after the image is captured to achieve a slow shutter photography effect, such as noise reduction and further enhancement. In the structural example of the above-mentioned device, the processing circuit 508 can be in the form of a general-purpose processor or a dedicated processing circuit, such as an ASIC. For example, the processing circuit 508 can be constructed from circuits (hardware) or a central processing device (such as a central processing unit (CPU)). In addition, the processing circuit 508 can carry a program (software) for operating the circuits (hardware) or the central processing device. This program can be stored in memory (such as in memory) or in an externally connected external storage medium, or can be downloaded via a network (such as the Internet). In some embodiments, at least one of the lens unit 504, the photographic filter 506, and the processing circuit 508 may be included in an image acquisition device. It should be noted that, although not shown, the image acquisition device may also include other components as long as it can obtain an image to be processed. It should be noted that the photographic filters and processing circuits are depicted with dashed lines to illustrate that these units are not necessarily included in the photographic device 50 and may even be connected and / or communicate with each other through known means outside the photographic device 50. It should be noted that although FIG5 shows the various units as separate units, one or more of these units may be combined into one unit or split into multiple units. Additionally, it should be understood that the aforementioned series of processes and devices can also be implemented via software and / or firmware. When implemented via software and / or firmware, the programs constituting the software are installed from a storage medium or network onto a computer with dedicated hardware, such as the general-purpose personal computer 600 shown in Figure 6. With various programs installed, the computer can perform various functions, among other things. Figure 6 is a block diagram illustrating an example structure of a personal computer that can be used as an information processing device in embodiments of the present disclosure. In one example, the personal computer can correspond to the aforementioned exemplary transmitting device or terminal-side electronic device according to the present disclosure. In FIG6 , a central processing unit (CPU) 601 executes various processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage unit 608 into a random access memory (RAM) 603. RAM 603 also stores data required when CPU 601 executes various processes, etc., as needed. The CPU 601, the ROM 602, and the RAM 603 are connected to one another via a bus 604. An input / output interface 605 is also connected to the bus 604. The following components are connected to the input / output interface 605: an input section 606 including a keyboard, mouse, and the like; an output section 607 including a display such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 608 including a hard drive; and a communication section 609 including a network interface card such as a LAN card and a modem. The communication section 609 performs communication processing via a network such as the Internet. As needed, a drive 610 is also connected to the input / output interface 605. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is installed on the drive 610 as needed, so that a computer program read therefrom is installed in the storage portion 608 as needed. In the case of implementing the above-described series of processing by software, the program constituting the software is installed from a network such as the Internet or a storage medium such as the removable medium 611. Those skilled in the art will appreciate that this storage medium is not limited to the removable medium 611 shown in FIG6 , which stores the program and is distributed separately from the device to provide the program to the user. Examples of removable medium 611 include magnetic disks (including floppy disks (registered trademark)), optical disks (including compact disc read-only memories (CD-ROMs) and digital versatile discs (DVDs)), magneto-optical disks (including minidiscs (MDs (registered trademark)), and semiconductor memories. Alternatively, the storage medium may be ROM 602, a hard disk included in storage section 608, or the like, in which the program is stored and distributed to the user along with the device containing it. It should be noted that the methods and apparatus described herein may be implemented as software, firmware, hardware, or any combination thereof. Some components may, for example, be implemented as software running on a digital signal processor or microprocessor. Other components may, for example, be implemented as hardware and / or dedicated integrated circuits. Furthermore, the methods and systems of the present invention can be implemented in a variety of ways. For example, the methods and systems of the present invention can be implemented using software, hardware, firmware, or any combination thereof. The order of the steps of the method described above is merely illustrative, and unless otherwise specified, the steps of the method of the present invention are not limited to the order specifically described above. Furthermore, in some embodiments, the present invention can be embodied as a program recorded on a recording medium, comprising machine-readable instructions for implementing the method according to the present invention. Therefore, the present invention also encompasses a recording medium storing a program for implementing the method according to the present invention. Such storage media may include, but are not limited to, floppy disks, optical disks, magneto-optical disks, memory cards, memory sticks, and the like. Those skilled in the art will appreciate that the boundaries between the above-described operations are merely illustrative. Multiple operations may be combined into a single operation, a single operation may be distributed among additional operations, and operations may be performed with at least partial overlap in time. Furthermore, alternative embodiments may include multiple instances of a particular operation, and the order of operations may be altered in various other embodiments. However, other modifications, variations, and alternatives are also possible. Accordingly, this specification and drawings should be regarded as illustrative rather than restrictive. In addition, embodiments of the present disclosure may further include the following illustrative examples (EE). EE 1. An electronic device for processing a series of images, the series of images being obtained by capturing a scene containing at least one of a static object and a dynamic object, the electronic device comprising a processing circuit configured to: generating, based on a specific image selected from the series of images and containing a static object, a processed image that does not contain image content related to a dynamic object; generating a motion trajectory of a dynamic object in at least a portion of the series of images; and A final image is obtained based on both the processed image and the generated motion trajectory of the dynamic object. EE 2. The electronic device according to EE 1, wherein the series of images are obtained by shooting with a photographic device over a specific time period when the photographic device is not fixed. EE 3. The electronic device according to EE 1 or 2, wherein the series of images are obtained by photographing the images over a specific time period using a photographic device. EE 4. The electronic device according to EE 1, wherein the specific image is an image in which a static object in the series of images meets specific requirements. EE 5. The electronic device according to EE 4, wherein the electronic device is further configured to: comparing each image in the series of images to a static object template, and An image in the series of images that has the highest degree of proximity to the static object template is selected as an image in the series of images in which the static object meets a specific requirement. EE 6. The electronic device according to EE 5, wherein the proximity is the proximity between the static object in the image and the static object template with respect to at least one of clarity, human expression, shape, and color. EE 7. The electronic device according to EE 5, wherein the static object template is a static object data model trained based on a training image set. EE 8. The electronic device according to EE 1, wherein the processing circuit is further configured to: The movement process of the dynamic object in the series of images is tracked from the image in which the dynamic object first appears to the image in which the dynamic object last appears to generate a motion trajectory. EE 9. The electronic device according to EE 1 or EE 8, wherein the processing circuit is further configured to: Obtaining optical information of a dynamic object in the series of images from the image in which the dynamic object first appears to the image in which the dynamic object last appears, Based on the motion trajectory of the dynamic object and the optical information, a motion light trail of the dynamic object is generated. EE 10. The electronic device according to EE 9, wherein the optical information includes at least one of brightness information and color information of the dynamic object in each image in the series of images, from the image in which the dynamic object first appears to the image in which the dynamic object last appears. EE 11. The electronic device according to EE 1, wherein the processing circuit is further configured to: For each image in the series of images, from the image in which the dynamic object first appears to the image in which the dynamic object last appears, analyzing optical information at each position on the dynamic object to obtain a highlight portion on the dynamic object; The highlight parts at the same position on the dynamic object in the image where the dynamic object first appears and the image where the dynamic object last appears in the series of images are connected to generate a motion light trail of the dynamic object. EE 12. The electronic device according to EE 11, wherein the highlight portion of the dynamic object is determined based on a comparison of brightness information of the dynamic object and brightness information of a background portion of the image. EE 13. The electronic device according to EE 1, wherein the motion trajectory of the dynamic object used to generate the final graphic includes the motion trajectory of the dynamic object that appears in more than a predetermined number of images in the series of images. EE 14. The electronic device according to EE 1 or EE 13, wherein the processing circuit is further configured to: Replacing the image content related to the dynamic object in the specific image with background content to remove the image content related to the dynamic object in the specific image; and The motion trajectory of the dynamic object is synthesized with the specific image after being replaced to generate the final image. EE 15. The electronic device according to EE 14, wherein the processing circuit is further configured to: Filtering out, from the series of images, images whose dynamic object positions do not overlap with the dynamic object positions in the specific image and whose static object positions have the smallest deviation from the static object positions in the specific image; and Background content is determined based on content at locations in the filtered images that correspond to locations of dynamic objects in the specific image. EE 16. An electronic device according to EE 15, wherein the position of the static object in the filtered image is consistent with the position of the static object in the specific image, and the content in the filtered image that has a position corresponding to the position of the dynamic object in the specific image and has the same size as the dynamic object in the specific image is used as the background content. EE 17. An electronic device according to EE 15, wherein there is a deviation between the position of the static object in the filtered image and the position of the static object in the specific image, and content whose position in the filtered image corresponds to the position of the dynamic object in the specific image and is adjusted based on the deviation value is used as the background content. EE 18. The electronic device according to EE 1, wherein the processing circuit is further configured to: Objects that exist in each image of the series of images and whose position offset is less than a certain threshold are identified as static objects. EE 19. The electronic device according to EE 1, wherein the processing circuit is further configured to: An object that does not appear in all images in the series of images or appears in all images in the series of images but has a position shift greater than a certain threshold is identified as a dynamic object. EE 20. An image processing method for processing a series of images, the series of images being obtained by photographing a scene containing static objects and dynamic objects, the image processing method comprising: generating, based on a specific image selected from the series of images and containing a static object, a processed image that does not contain image content related to a dynamic object; generating a motion trajectory of a dynamic object in at least a portion of the series of images; and A final image is obtained based on both the processed image and the generated motion trajectory of the dynamic object. EE 21. The method according to EE 20, wherein the series of images are obtained by shooting over a specific time period using a photographic device when the photographic device is not fixed. EE 22. The method according to EE 20 or 21, wherein the series of images are obtained by photographing the images over a specific time period using a photographic device. EE 23. The method according to EE 20, wherein the specific image is an image in which a static object in the series of images meets specific requirements. EE 24. The method according to EE 23, wherein the method is further configured to: comparing each image in the series of images to a static object template, and An image in the series of images that has the highest degree of proximity to the static object template is selected as an image in the series of images in which the static object meets a specific requirement. EE 25. The method according to EE 24, wherein the proximity is the proximity between the static object in the image and the static object template with respect to at least one of clarity, human expression, shape, and color. EE 26. The method according to EE 24, wherein the static object template is a static object data model trained based on a training image set. EE 27. The method according to EE 20, wherein generating a motion trajectory of the dynamic object in at least a portion of the series of images comprises: The movement process of the dynamic object in the series of images is tracked from the image in which the dynamic object first appears to the image in which the dynamic object last appears to generate a motion trajectory. EE 28. The method according to EE 20 or 27, wherein generating a motion trajectory of the dynamic object in at least a portion of the series of images further comprises: Obtaining optical information of a dynamic object in the series of images from the image in which the dynamic object first appears to the image in which the dynamic object last appears, Based on the motion trajectory of the dynamic object and the optical information, a motion light trail of the dynamic object is generated. EE 29. The method according to EE 28, wherein the optical information comprises at least one of brightness information and color information of the dynamic object in each image in the series of images, from the image in which the dynamic object first appears to the image in which it last appears. EE 30. The method according to EE 20, wherein generating a motion trajectory of the dynamic object in at least a portion of the series of images further comprises: For each image in the series of images, from the image in which the dynamic object first appears to the image in which the dynamic object last appears, analyzing optical information at each position on the dynamic object to obtain a highlight portion on the dynamic object; The highlight parts at the same position on the dynamic object in the image where the dynamic object first appears and the image where the dynamic object last appears in the series of images are connected to generate a motion light trail of the dynamic object. EE 31. The method according to EE 30, wherein the highlight portion of the dynamic object is determined based on a comparison of brightness information of the dynamic object and brightness information of a background portion of the image. EE 32. The method according to EE 20, wherein the motion trajectory of the dynamic object used to generate the final image includes the motion trajectory of the dynamic object that appears in more than a predetermined number of images in the series of images. EE 33. The method according to EE 20 or EE 32, wherein generating a processed image that does not contain image content related to a dynamic object based on a specific image containing a static object selected from the series of images comprises: Replacing the image content related to the dynamic object in the specific image with background content to remove the image content related to the dynamic object in the specific image, In this process, the motion trajectory of the dynamic object is synthesized with the specific image after being replaced to generate the final image. EE 34. The method according to EE 33, wherein replacing image content related to the dynamic object in the specific image with background content comprises: Filtering out, from the series of images, images whose dynamic object positions do not overlap with the dynamic object positions in the specific image and whose static object positions have the smallest deviation from the static object positions in the specific image; and Background content is determined based on content at locations in the filtered images that correspond to locations of dynamic objects in the specific image. EE 35. The method according to EE 34, wherein the position of the static object in the filtered image is consistent with the position of the static object in the specific image, and the content in the filtered image whose position corresponds to the position of the dynamic object in the specific image and whose size is the same as that of the dynamic object in the specific image is used as the background content. EE 36. A method according to EE 34, wherein there is a deviation between the position of a static object in the filtered image and the position of a static object in the specific image, and content whose position in the filtered image corresponds to the position of a dynamic object in the specific image and is adjusted based on the deviation value is used as background content. EE 37. The method according to EE 20, further comprising: Objects that exist in each image of the series of images and whose position offset is less than a certain threshold are identified as static objects. EE 38. The method according to EE 20, further comprising: An object that does not appear in all images in the series of images or appears in all images in the series of images but has a position shift greater than a certain threshold is identified as a dynamic object. EE 39. A photographic device comprising: an image acquisition device for acquiring a series of images, wherein the series of images are obtained by photographing a scene containing at least one of a static object and a dynamic object; and The electronic device for image processing according to any one of EEs 1-19 is used to perform image processing on a series of acquired images. EE 40. A device comprising at least one processor; and At least one storage device, storing thereon instructions, which, when executed by the at least one processor, cause the at least one processor to perform the image processing method according to any one of EEs 20-38. EE 41. A storage medium storing instructions, which, when executed by a processor, enables execution of the image processing method according to any one of EEs 20-38. EE 42. A program product comprising instructions which, when executed by a processor, enable the image processing method according to any one of EEs 20-38 to be performed. While the present disclosure and its advantages have been described in detail, it should be understood that various changes, substitutions, and alterations may be made without departing from the spirit and scope of the present disclosure as defined by the appended claims. Furthermore, the terms "comprises," "comprising," or any other variations thereof, in the embodiments of the present disclosure are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element. Although some specific embodiments of the present disclosure have been described in detail, those skilled in the art will appreciate that these embodiments are merely illustrative and do not limit the scope of the present disclosure. Those skilled in the art will appreciate that the above embodiments may be combined, modified, or substituted without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

[0006] 10: Image processing electronic equipment 102: Processing circuit 104: Image processing unit 106: motion trajectory generation unit 1062: Optical Information Acquisition Unit 1064: Light trace generation unit 108:Synthesis Unit 110: Object recognition unit 112:Selection Unit 300: Methods and Steps 50:Photography Equipment 502: Image processing device 504: Lens unit 506:Photographic Filters 508: Processing circuit 600: General-purpose personal computer 601: Central Processing Unit (CPU) 602: Read-only memory (ROM) 603: Random Access Memory (RAM) 604: Bus 605: Input / Output Interface 606: Input part 607: Output part 608: Storage 609: Communication part 610:Drive 611: Removable Media

Claims

1. An electronic device for processing a series of images, the series of images being acquired from a scene containing at least one of static objects and dynamic objects, the electronic device comprising processing circuitry configured to: generate a processed image that does not contain image content related to dynamic objects, based on a specific image containing static objects selected from the series of images, wherein the specific image is an image of a static object in the series of images that meets specific requirements; generate motion trajectories of dynamic objects in at least a portion of the images in the series of images; and obtain a final image based on both the processed image and the generated motion trajectories of the dynamic objects, wherein... The electronic device is further configured to: compare each image in the series of images with a static object template, and select the image in the series of images with the highest similarity to the static object template as the image in the series of images that meets a specific requirement for the static object, wherein the similarity is the similarity between the static object in the image and the static object template in terms of at least one of sharpness, facial expression, shape, and color.

2. The electronic device according to claim 1, wherein, This series of images was obtained by taking pictures over a specific period of time using photographic equipment that was not fixed in place.

3. The electronic device according to claim 1 or 2, wherein, This series of images was obtained by taking pictures over a specific period of time using photographic equipment.

4. The electronic device according to claim 1, wherein, This static object template is a static object data model trained based on a set of training images.

5. The electronic device according to claim 1, wherein, The processing circuit is further configured to: track the movement of a dynamic object in the series of images from the first image in which the dynamic object appears to the last image in which it appears to generate a motion trajectory.

6. The electronic device according to claim 1 or 5, wherein, The processing circuit is further configured to: acquire optical information of the dynamic object in the series of images from the first image to the last image of the dynamic object; and generate a motion light trail of the dynamic object based on the motion trajectory of the dynamic object and the optical information.

7. The electronic device according to claim 6, wherein, The optical information includes at least one of the brightness and color information of the dynamic object in each image of the series of images, from the first image to the last image.

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