Photographing method, photographing device and storage medium

Abstract

The invention relates to a photographing method, a photographing device and a storage medium. The photographing method comprises the steps that in response to a received photographing instruction, an image processing algorithm used for generating a target image is determined, and the image processing algorithm comprises a plurality of processing flows executed in sequence. In the process of sequentially executing the multiple processing flows, processing time consumed by a first processing flow is determined, and the first processing flow is the processing flow which is executed recently in the multiple processing flows; and determining a second processing flow for generating the target image based on the processing time, and generating the target image based on the second processing flow. Through the method and the device, the problem that processing cannot be returned or processing is overtime due to a complex algorithm is avoided, and the stability of a terminal camera is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of photography, and in particular to a photography method, a photography device, and a storage medium. Background Art

[0002] With the continuous development of terminal imaging technology, taking photos based on image processing algorithms, optimizing imaging quality, and acquiring photographic images have become an important part of the terminal photography field.

[0003] In related technologies, image processing algorithms are complex processes that include multiple stages. For heavyweight image processing algorithms that require a large number of input frames or relatively complex processing of single-frame images, the algorithms are time-consuming, the processing flow is long, and the overall processing process is complex, which affects the stability of the terminal camera system during imaging. Summary of the Invention

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

[0005] According to a first aspect of an embodiment of the present disclosure, a photographing method is provided, comprising: in response to receiving a photographing instruction, determining an image processing algorithm used to generate a target image, wherein the image processing algorithm includes a plurality of processing flows executed sequentially; in the process of sequentially executing the plurality of processing flows, determining a processing time consumed by a first processing flow, wherein the first processing flow is the most recently completed processing flow among the plurality of processing flows; based on the processing time, determining a second processing flow to generate the target image, and generating the target image based on the second processing flow.

[0006] In one embodiment, the second processing flow for generating the target image is determined based on the processing time, and generating the target image based on the second processing flow includes: if the processing time exceeds a time threshold, determining that the second processing flow is a processing flow that has been completed among the multiple processing flows; stopping execution of the unfinished processing flows among the multiple processing flows, using the image obtained by the most recently completed processing flow as the target image, and outputting the target image.

[0007] In one embodiment, the second processing flow for generating the target image is determined based on the processing time, and the target image is generated based on the second processing flow, including: if the processing time does not exceed the time threshold, determining the second processing flow as the processing flow that has not been completed among the multiple processing flows; executing the next processing flow, repeatedly determining the processing time of the next processing flow, and determining the subsequent flow for generating the target image based on the processing time, until the multiple processing flows are completed and the target image is output, or until the processing time of the subsequent flow exceeds the time threshold, ending the image processing algorithm, taking the image obtained by the processing flow whose processing time exceeds the time threshold as the target image, and outputting the target image.

[0008] In one embodiment, determining the processing time consumed by the first processing flow includes: calling back the most recently completed processing flow to determine the processing time consumed by the most recently completed processing flow; determining the second processing flow for generating the target image based on the processing time, and generating the target image based on the second processing flow includes: determining a time threshold corresponding to the most recently completed processing flow, wherein there is a corresponding relationship between the processing flow and the time threshold; determining the second processing flow for generating the target image based on the processing time and the time threshold, and generating the target image based on the second processing flow.

[0009] In one embodiment, the processing flow has a corresponding relationship with the time threshold, and has a matching relationship with the temperature; the determination of the time threshold corresponding to the processing flow that was most recently completed includes: determining the current temperature, and based on the corresponding relationship between the time threshold and the temperature, determining the time threshold corresponding to the processing flow that was most recently completed.

[0010] In one embodiment, the method further includes: if the number of times the same processing flow ends exceeds a number threshold, issuing a prompt message, wherein the prompt message is used to prompt the processing flow that exceeds the number threshold.

[0011] In one embodiment, the multiple processing flows include: a data initialization flow, an image resource processing flow, a core algorithm processing flow, a resource algorithm recycling flow, and a data result return flow.

[0012] In one embodiment, the image processing algorithm includes a multi-frame fusion algorithm for fusing multiple frames of images and determining the fused image as the target image.

[0013] According to a second aspect of an embodiment of the present disclosure, a photographing device is provided, comprising: a determination unit for determining, in response to receiving a photographing instruction, an image processing algorithm used to generate a target image, wherein the image processing algorithm includes a plurality of processing flows executed sequentially; a processing unit for determining, in the process of sequentially executing the plurality of processing flows, a processing time consumed by a first processing flow, wherein the first processing flow is the most recently completed processing flow among the plurality of processing flows, and based on the processing time, determining a second processing flow for generating the target image, and generating the target image based on the second processing flow.

[0014] In one embodiment, the processing unit determines the second processing flow for generating the target image based on the processing time in the following manner: if the processing time exceeds a time threshold, the second processing flow is determined to be a processing flow that has been completed among the multiple processing flows; the execution of the unfinished processing flows among the multiple processing flows is stopped, and the image obtained by the most recently completed processing flow is used as the target image, and the target image is output.

[0015] In one embodiment, the processing unit determines a second processing flow for generating the target image based on the processing time, and generates a target image based on the second processing flow in the following manner: if the processing time does not exceed the time threshold, the second processing flow is determined to be the processing flow that has not been completed among the multiple processing flows; the next processing flow is executed, and the processing time of the next processing flow is repeatedly determined, and based on the processing time, a subsequent flow for generating the target image is determined, until the execution of the multiple processing flows is completed and the target image is output, or until the processing time of the subsequent flow exceeds the time threshold, the image processing algorithm is terminated, and the image obtained by the processing flow whose processing time exceeds the time threshold is used as the target image, and the target image is output.

[0016] In one embodiment, the processing unit determines the processing time consumed by the first processing flow and generates a target image based on the second processing flow in the following manner: calling back the most recently completed processing flow to determine the processing time consumed by the most recently completed processing flow; determining the second processing flow to generate the target image based on the processing time, and generating the target image based on the second processing flow, including: determining a time threshold corresponding to the most recently completed processing flow, wherein there is a corresponding relationship between the processing flow and the time threshold; determining the second processing flow to generate the target image based on the processing time and the time threshold, and generating the target image based on the second processing flow.

[0017] In one embodiment, the processing flow has a corresponding relationship with the time threshold, and has a matching relationship with the temperature; the processing unit determines the time threshold corresponding to the most recently completed processing flow in the following manner: determining the current temperature, and based on the corresponding relationship between the time threshold and the temperature, determining the time threshold corresponding to the most recently completed processing flow.

[0018] In one embodiment, the processing unit is further configured to: issue a prompt message if the number of times the same processing flow ends exceeds a threshold number, wherein the prompt message is used to prompt the processing flow that exceeds the threshold number.

[0019] In one embodiment, the multiple processing flows include: a data initialization flow, an image resource processing flow, a core algorithm processing flow, a resource algorithm recycling flow, and a data result return flow.

[0020] In one embodiment, the image processing algorithm includes a multi-frame fusion algorithm for fusing multiple frames of images and determining the fused image as the target image.

[0021] According to a third aspect of an embodiment of the present disclosure, a photographing device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to: execute the photographing method described in the first aspect or any one of the embodiments of the first aspect.

[0022] According to a fourth aspect of an embodiment of the present disclosure, a storage medium is provided, in which instructions are stored. When the instructions in the storage medium are executed by a processor, the processor is enabled to execute the photographing method in the first aspect or any one of the embodiments of the first aspect.

[0023] The technical solutions provided by the embodiments of the present disclosure can achieve the following beneficial effects: In response to processing an image according to an image processing algorithm, the image to be processed is processed sequentially based on multiple sub-processes within the image processing algorithm. The processing time used by the most recently completed process to process the image is monitored, and based on this processing time, the subsequent algorithm processing process is determined and the target image is output. This disclosure avoids processing failures or processing timeouts due to algorithm complexity, thereby improving the stability of the terminal camera.

[0024] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0026] Figure 1 The block diagram shows a photographing method for generating a target image based on an image processing algorithm according to an exemplary embodiment of the present disclosure.

[0027] Figure 2 It is a block diagram showing a photographing method for generating a target image based on an image processing algorithm according to another exemplary embodiment of the present disclosure.

[0028] Figure 3 is a block diagram showing an image signal processing method according to an exemplary embodiment of the present disclosure.

[0029] Figure 4 It is a block diagram showing an execution process of an image processing algorithm according to another exemplary embodiment of the present disclosure.

[0030] Figure 5 The figure is a flowchart of a photographing method according to an exemplary embodiment.

[0031] Figure 6 It is a block diagram showing a photographing method for generating a target image based on an image processing algorithm according to another exemplary embodiment of the present disclosure.

[0032] Figure 7 The figure is a flowchart showing a method for performing image processing based on processing time and time threshold according to an exemplary embodiment.

[0033] Figure 8 It is a block diagram showing a photographing method for generating a target image based on an image processing algorithm according to another exemplary embodiment of the present disclosure.

[0034] Figure 9 The flowchart of a method for performing image processing based on processing time and time threshold is shown according to yet another exemplary embodiment.

[0035] Figure 10 The present invention is a flowchart showing a method for determining processing time and performing image processing based on the processing time according to an exemplary embodiment.

[0036] Figure 11 The figure is a flowchart showing a method for determining a time threshold according to an exemplary embodiment.

[0037] Figure 12 The figure is a flowchart of an image processing method according to an exemplary embodiment.

[0038] Figure 13 is a block diagram showing a multi-frame image processing method according to another exemplary embodiment of the present disclosure.

[0039] Figure 14The figure is a block diagram of a photographing device according to an exemplary embodiment.

[0040] Figure 15 The figure is a block diagram showing a device for taking photos according to an exemplary embodiment. DETAILED DESCRIPTION

[0041] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different drawings represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present disclosure.

[0042] The photographing method provided by the embodiments of the present disclosure is applicable to scenarios where an image processing algorithm is used for photographing, for example, scenarios such as night scene imaging or high dynamic range imaging that require a multi-frame fusion algorithm for photographing.

[0043] Among them, night scene imaging captures richly detailed images in low-light nighttime scenarios. High dynamic range imaging captures images with high resolution and abundant dark detail in normal exposure scenarios. Both night scene imaging and high dynamic range imaging are essential camera features for current mobile devices.

[0044] In the related art, there are two technical solutions for imaging through image processing algorithms. One is based on RAW domain images (the original images output by the sensor); the other is based on YUV domain images (the images obtained after the original images are converted). The processing goals of both methods are to highly restore the real scene information in the night scene state, or to obtain images with a large amount of details. It can be said that RAW domain image processing is an improvement on YUV domain image processing. When imaging night scenes, the degree of restoration of night scene information is better, and the noise processing is also cleaner. The difference between RAW domain image processing and YUV domain image processing mainly lies in the different process sequences of image signal processing (ISP processing) and image processing algorithms. The processing procedures for multiple frames of images are basically the same.

[0045] The following describes the RAW domain image processing and YUV domain image processing in related technologies:

[0046] (1) Image processing algorithm based on RAW domain: The main feature of this technical solution is to perform multi-frame fusion processing based on RAW domain images. The purpose is to perform multi-frame processing based on the RAW domain images directly output by the sensor to reduce the noise impact of the image signal processing module (ISP module). Figure 1As shown in the block diagram of the method for generating a target image based on an image processing algorithm, the RAW-domain image processing algorithm solution primarily includes the following steps: a. User presses the shutter button: After selecting an image processing algorithm (such as a night scene algorithm) in the terminal camera app, the user clicks the virtual button that issues the photo command to take a photo. b. Night scene exposure parameters: Based on the user-selected photo mode, the terminal adaptively adjusts the exposure parameters for the photo (such as aperture size and flash brightness) and captures the image. c. Sensor multi-frame output: The sensor collects light signals, converts them into electrical signals, and continuously outputs multiple RAW-domain images. d. Image signal processing - bad pixel correction: The image signal processing module is invoked to perform bad pixel correction on the generated multiple RAW-domain images. e. RAW-domain image processing algorithm: The multiple frames with bad pixel correction are processed by the algorithm to output the target image. f. Image signal processing: The fused image is subjected to image signal processing such as noise reduction and white balance, and the RAW-domain image is converted to a YUV-domain image. g. Other single-frame algorithm processing: The converted YUV-domain image is optimized. h. Output: Output the target image.

[0047] (2) The solution of processing images based on the image processing algorithm in the YUV domain: The difference between this solution and the solution of processing images based on the image processing algorithm in the RAW domain is that the order of image signal processing (ISP processing) and algorithm processing is different. In this solution, after acquiring multiple frames of RAW domain images through the sensor, the image signal processing is first performed on the RAW domain images to obtain multiple YUV domain images, and the YUV domain images are then processed by the algorithm. Figure 2 As shown in the block diagram of the method for generating a target image using an image processing algorithm, the image processing method using a YUV-domain image processing algorithm primarily includes the following steps: a. User presses the shutter button. b. Night scene exposure parameters are set. c. Sensor outputs multiple frames. d. Image signal processing. e. YUV-domain image processing algorithm processing. f. Other single-frame processing algorithms are used. g. Image output. The specific implementation details of each step are the same or similar to those of the image processing method using a RAW-domain image processing algorithm and are therefore not discussed in detail.

[0048] The above RAW domain image processing and YUV domain image processing both require image signal processing, such as Figure 3As shown in the block diagram of the image signal processing method, the general process of image signal processing in the related art is: synchronous clock (Sensor-DDR) - bad pixel correction / color focus (BPC / PDPC / BCC) - channel gain (Channel Gains) - high dynamic range (HDR rec / HDR MAC) - green channel balance (Green Imbalance Correction) - Raw domain noise reduction (ABF) - black level correction (Black level Substration) - lens roll off (Lens Roll Off) - white balance (White Balance) - demosaicing (Demosaic) - color correction (Color Correction) - local brightening (GTM) - overall brightening (Gamma) - color space transformation (Color Space Transform) - high frequency noise processing (Hybird Noise Reduction) - down sampling (Down Scaler) - color correction - integrated processing (IPE NPS / PPS) - image output. Among them, the image signal processing processes in RAW domain image processing and YUV domain image processing differ in details. In RAW domain image processing, the RAW domain image needs to be converted into a YUV domain image through image signal processing. Therefore, the image signal processing process in RAW domain image processing also has the function of image format conversion.

[0049] The above RAW domain image processing and YUV domain image processing have the same or similar image processing process based on image processing algorithms, such as Figure 4 As shown in the block diagram of the image processing algorithm execution process in the related art, the general process of processing multiple frame images based on the multi-frame processing algorithm includes the following steps:

[0050] a) Starting the image processing algorithm: in response to a user issuing an instruction to process an image based on the image processing algorithm, starting the image processing algorithm.

[0051] b) Data initialization: Based on the parameters set by the user (such as the size of the image), initialize the various data of the image processing algorithm.

[0052] c) Image resource preprocessing: Perform preprocessing such as noise reduction, cropping, and alignment on the images used for algorithm processing.

[0053] d) Core algorithm processing: Process the pre-processed image based on the image processing algorithm.

[0054] e) Algorithm resource recycling: In response to the completion of various algorithmic processing of the image, the algorithmic resources used to execute different algorithmic processing flows are gradually recycled.

[0055] f) Data result is returned and the algorithm ends: the target image obtained by the image processing algorithm is output and the image processing algorithm ends.

[0056] Among them, the image processing schemes using the YUV domain image processing algorithm and the image processing schemes using the RAW domain image processing algorithm both have relatively good results when outputting high-quality images, but their disadvantages are also quite obvious. If the image processing algorithm is a heavyweight algorithm that requires a large number of frames to be input and processes each frame of the image, or the processing of a single frame of the image is relatively complex, it will result in a long image processing time and a complex image processing process. Therefore, the image processing schemes using the YUV domain image processing algorithm and the image processing schemes using the RAW domain image processing algorithm have the characteristics of high algorithm time consumption, long processing flow, and complex processing process. Any process in the image processing algorithm may be stuck, resulting in the algorithm processing being unable to return or the processing timeout, affecting the stability of the terminal when performing imaging based on the image processing algorithm.

[0057] In one embodiment, a target image is generated based on a multi-frame processing algorithm, and the optical sensors used in the terminal camera all obtain multiple frames of original images through continuous exposure frame by frame. In the imaging process that requires a multi-frame fusion algorithm, such as night scene imaging or high dynamic range imaging, multiple images with different exposures (including normal exposure image EV0, overexposure image EV+ and weak exposure image EV-) are generally used to synthesize a fused image, and this night scene image with a perception effect that breaks through the human eye has also become the focus of current research in the field of image and video. However, for such a heavyweight algorithm that requires a relatively large number of input image frames, long-term algorithm processing will affect the system stability of the terminal camera during imaging. Therefore, how to avoid the algorithm processing from being unable to return or the processing timing out, quickly output the image, and improve the camera stability while ensuring that the image quality effect meets expectations has become a significant problem.

[0058] In view of this, the present disclosure proposes a photo-taking method, which divides the entire image processing algorithm image processing process into multiple sub-processes. After the image processing starts, the processing time of the current process is monitored, and a threshold judgment is made based on the processing time, and then the subsequent process of image processing is determined, thereby avoiding terminal camera failures caused by the algorithm processing being unable to return or processing timeout, and improving the stability of the terminal camera.

[0059] Figure 5 FIG. 1 is a flow chart showing a method for taking photos according to an exemplary embodiment. Figure 5 As shown, the method includes steps S101 to S103.

[0060] In step S101 , in response to receiving a photographing instruction, an image processing algorithm used to generate a target image is determined.

[0061] The image processing algorithm includes multiple processing flows that are executed sequentially.

[0062] Image processing algorithms can be understood as algorithms that improve image quality. For example, they process multiple acquired frames to obtain a target image, including image feature fusion to obtain a multi-frame fused image. Alternatively, image stitching can be performed to combine multiple images from different regions to create a single large image.

[0063] Among them, the processing processes included in the image processing algorithm process are different processing processes in the image processing algorithm process, such as: a sub-process for processing data based on the shooting parameter configuration, a process for pre-processing such as image alignment and cropping, and a process for formally processing images based on the algorithm, etc. The algorithms executed by each sub-process are different.

[0064] In step S102 , during the process of sequentially executing a plurality of processing flows, the processing time consumed by the first processing flow is determined.

[0065] The first processing flow is the most recently completed processing flow among the multiple processing flows.

[0066] In step S103 , a second processing flow for generating a target image is determined based on the processing time, and the target image is generated based on the second processing flow.

[0067] In the disclosed embodiments, the image processing algorithm is divided into multiple sub-processes based on their different stages. These sub-processes are arranged in the order in which they are executed. Based on the order in which the sub-processes are executed, the disclosed embodiments sequentially determine the processing time consumed by processing outflows and further perform image processing based on the processing time.

[0068] In an exemplary embodiment of the present disclosure, the image processing algorithm for the image to be processed during the photography process can be a RAW domain-based image processing algorithm or a YUV domain-based image processing algorithm. In other words, the photography method of the present disclosure can be applied to both RAW domain-based image processing algorithm solutions and YUV domain-based image processing algorithm solutions.

[0069] In an exemplary embodiment of the present disclosure, an image processing algorithm based on a YUV domain image is taken as an example for description. Figure 6 The method of processing YUV domain images based on image processing algorithms to obtain fused images is shown. Figure 6As shown in the block diagram of the method for generating a target image based on an image processing algorithm, the process for performing an image processing algorithm based on YUV domain images in image processing algorithm modes such as night scene imaging or high dynamic range imaging includes the following steps: In response to a user's photo capture command, the terminal receives the command and controls the camera to begin image acquisition. The camera captures the image and generates multiple frames of raw images (RAW domain images). Image signal processing is then performed on the raw images, and the RAW domain images are converted into YUV domain images. The processed multiple frames are then input into the algorithm processing module, where the image processing algorithm is applied to the processed multiple frames to obtain a fused image. The fused image is ultimately output.

[0070] It's understandable that the main difference between RAW-domain image processing and YUV-domain image processing lies in the different order of image signal processing (ISP processing) and image processing algorithm execution, while the algorithm processing process for the image is essentially the same. When performing image processing algorithm processing on RAW-domain images, the present disclosure maintains the same execution methods for each step, and only requires adaptive adjustments to the execution order of the image signal processing (ISP processing) and image processing algorithm execution.

[0071] In the embodiments of the present disclosure, based on the ideal processing time of different sub-processes when executing an image processing algorithm (controlling the overall imaging time within a certain time without affecting the user experience), the maximum value of the ideal processing time of each sub-process can be set to a corresponding time threshold. By obtaining the actual processing of the sub-process and comparing the actual processing time with the corresponding time threshold, a threshold judgment is implemented. When the processing time meets the threshold and when it does not meet the threshold, different subsequent execution processes exist. The following embodiments of the present disclosure illustrate a method for determining and executing the subsequent processing process of the processing algorithm based on the processing time.

[0072] Figure 7 FIG. 1 is a flow chart showing a method for image processing based on processing time according to an exemplary embodiment. Figure 7 As shown, the method includes steps S201 to S202.

[0073] In step S201 , in response to the processing time exceeding the time threshold, it is determined that the second processing flow is a processing flow that has been completed among the multiple processing flows.

[0074] In step S202 , the execution of the unfinished processing flows among the multiple processing flows is stopped, and the image obtained by the most recently completed processing flow is used as the target image, and the target image is output.

[0075] In the embodiment of the present disclosure, the second processing step is a processing flow for finally generating a target image.

[0076] In the disclosed embodiment, a time threshold corresponds to the current process. The time threshold is a critical time value for determining whether the processing time of the current process is abnormal. If the processing time is greater than the time threshold, it indicates that the current process has timed out and there is an abnormality in the process. If the processing time is less than the time threshold, it indicates that the current process is executing normally. By collecting the processing time of the current process and executing the subsequent process of the image processing algorithm based on the processing time and the corresponding time threshold, the problem of algorithm processing failure or processing timeout is avoided during the image processing algorithm.

[0077] In an exemplary embodiment of the present disclosure, Figure 8 As shown in the block diagram of the photographing method for generating the target image based on the image processing algorithm, Figure 8 "Algorithm Processing Entry-Algorithm Processing 4" corresponds to Figure 6 In the "Image Processing Algorithm" section, this disclosure divides the image processing algorithm process into multiple sub-processes through callbacks. After completing the processes of user pressing the shutter button - bottom layer receiving the request - camera outputting the image - image signal processing, etc., the algorithm processing entrance of the image processing algorithm is entered, and algorithm processing 1 - callback interface 1 - algorithm processing 2 - callback interface 2 - algorithm processing 3 - callback interface 3 - algorithm processing 4 - callback interface 4 are executed in sequence. After execution, the target image is output. Each algorithm processing stage corresponds to a sub-process, and the processing time is determined through the callback interface. A threshold judgment is performed based on the processing time and the time threshold built into the callback interface. Based on the judgment result, the subsequent processing process is executed.

[0078] In this disclosed embodiment, if the most recently completed processing flow exceeds the time threshold, it indicates that the processing flow is too long, a processing anomaly exists, and system stability is affected. The image processed by the current processing flow is directly output as the target image. This avoids system stability issues caused by the length of subsequent processing flows and improves the user experience.

[0079] It is understandable that different sub-processes of the image processing algorithm process have different complexities and require different processing times, so different sub-processes correspond to different time thresholds.

[0080] It's understandable that when taking photos based on an image processing algorithm, the captured image is processed by the image signal processing module before the algorithm is processed. After the algorithm is processed, subsequent single-frame image processing is also performed before it can be output as a photographic image. Furthermore, the algorithm selects relatively high-quality images for synthesis. Therefore, if the image processing algorithm is not fully completed, and only the images that have completed the intermediate process are output for subsequent processing and serve as the target image, the resulting photographic image can still meet user expectations to a certain extent.

[0081] In the embodiments of the present disclosure, if the processing time of the most recently completed processing flow does not meet the threshold, the subsequent image processing algorithm will be stopped. Conversely, the most recently completed processing flow will continue to the next processing flow of the image processing algorithm. The following embodiments of the present disclosure describe the subsequent processing flow when the threshold is met.

[0082] Figure 9 FIG. 1 is a flow chart showing a method for image processing based on processing time and time threshold according to another exemplary embodiment. Figure 9 As shown, the present disclosure performs threshold judgment based on the processing time of the processing flow and the time threshold corresponding to the processing flow, and then executes the subsequent processing flow until the target image is output:

[0083] Determine the processing time consumed by the most recently completed processing flow 1, and determine the corresponding time threshold. Determine whether the processing time of the most recently completed processing flow 1 exceeds the time threshold. In response to the processing time exceeding the time threshold, terminate the image processing algorithm, use the processed image obtained by the current processing flow 1 as the target image, and output the target image. In response to the processing time not exceeding the time threshold, execute processing flow 2, determine the processing time consumed by processing flow 2, and determine the corresponding time threshold. Then determine whether the processing time of processing flow 2 exceeds the time threshold... Repeat the above threshold judgment process until entering the processing flow n that completes the image processing algorithm. In response to the processing time of processing flow n not exceeding the time threshold, enter the data result return process, determine the target image from the multi-frame fusion image, and output the target image.

[0084] In the embodiment of the present disclosure, the processing time of the current processing flow meets the time threshold. After entering the next processing flow, the process of obtaining the processing time of the processing flow and performing a threshold judgment on the processing time is repeated. Based on whether the processing time of the subsequent processing flow meets the time threshold, there are two final output results: one is that the processing time of each subsequent sub-processing flow meets the threshold, and the final fused image is output as the target image; the other is that if one of the subsequent multiple sub-processing flows does not meet the threshold, the processing result of the sub-process that does not meet the threshold is used as the target image and output. By splitting the image processing algorithm and performing threshold judgment in stages, the subsequent processing flow and the output target image are determined. This avoids terminal camera failures caused by the inability to return or processing timeout due to the algorithm processing flow being too long, while ensuring image quality, it also improves terminal camera stability.

[0085] In the embodiments of the present disclosure, it is necessary to use a mechanism for monitoring the image processing process to determine the time between the most recently completed processing processes, and then perform a threshold judgment on the processing time and execute subsequent processing processes. The following embodiments of the present disclosure illustrate the method of executing subsequent processing processes by determining the processing time.

[0086] Figure 10 FIG. 1 is a flow chart showing a method for determining a processing time and performing image processing based on the processing time according to another exemplary embodiment. Figure 10 As shown, the method includes steps S301 to S303.

[0087] In step S301 , the most recently completed processing flow is called back to determine the processing time consumed by the most recently completed processing flow.

[0088] In step S302 , a time threshold corresponding to the most recently completed processing flow is determined.

[0089] There is a corresponding relationship between the processing flow and the time threshold.

[0090] In step S303 , a second processing flow for generating a target image is determined based on the processing time and the time threshold, and the target image is generated based on the second processing flow.

[0091] In the embodiment of the present disclosure, Figure 8 As shown, after the image to be processed enters the processing flow of the image processing algorithm, each sub-process of the image processing algorithm process has a corresponding callback interface, and the callback interface is pre-set with the time threshold of the corresponding sub-process. After the sub-process processing is completed, the completed process is called back to the corresponding callback interface based on the callback mechanism. The callback interface determines the time point when the sub-process starts and the time point when the sub-process ends, and then determines the processing time of the sub-process based on the difference between the start time point and the end time point. After obtaining the processing time, the time threshold preset in the callback interface is obtained, and a threshold judgment is performed. The time threshold is compared with the processing time, and the subsequent multi-frame processing process is executed based on the threshold judgment result.

[0092] In the embodiment of the present disclosure, there is a corresponding relationship between the processing flow and the time threshold, and the time threshold is not fixed. The time threshold can be adaptively changed based on the current operating conditions of the terminal. The following embodiment of the present disclosure describes a method for determining the time threshold.

[0093] Figure 11 FIG. 1 is a flow chart showing a method for determining a time threshold according to an exemplary embodiment. Figure 11 As shown, the method includes steps S401 to S402.

[0094] In step S401 , the current temperature is determined.

[0095] The processing flow has a corresponding relationship with the time threshold, and has a matching relationship with the temperature.

[0096] In step S402, based on the correspondence between the time threshold and the temperature, the time threshold corresponding to the current processing flow is determined.

[0097] In the disclosed embodiments, the terminal utilizes different scheduling strategies at different temperatures. At low temperatures, the scheduling strategy is aggressive, allowing the terminal to consume more power. This results in a faster image processing algorithm and a shorter processing time. At high temperatures, to prevent the terminal from overheating, the terminal's scheduling strategy is more conservative, reducing the power consumption released by the terminal. This reduces the speed of the image processing algorithm and increases processing time. Based on the different scheduling strategies for terminals at different temperatures, two or more time thresholds can be set. The time threshold setting is positively correlated with the terminal temperature.

[0098] It is understandable that the processing speed of the image processing algorithm is not only related to the power consumption of the terminal, but also to the number of images during image processing. Different image processing algorithms process different numbers of images when performing image processing. Therefore, different time thresholds can be set for different image processing algorithm methods (such as night scene imaging and high dynamic range imaging).

[0099] In the disclosed embodiments, by making targeted adjustments to the time thresholds corresponding to different processes in the image processing algorithm, incorrect threshold judgments on the processing time of sub-processes in the image processing algorithm are avoided when the terminal operating conditions change, further improving the system stability during the image processing algorithm.

[0100] In the embodiments of the present disclosure, the corresponding data of the image processing algorithm process can be recorded to optimize the image processing algorithm. The following embodiments of the present disclosure further illustrate the method of obtaining the target image based on the image processing algorithm.

[0101] Figure 12 FIG. 1 is a flow chart showing an image processing method according to an exemplary embodiment. Figure 12 As shown, the method includes steps S501 to S502.

[0102] In step S501, the processed data of the image processing algorithm process is acquired and stored.

[0103] In step S502, if the number of times the same processing flow ends exceeds a threshold, a prompt message is issued.

[0104] The prompt information is used to prompt the processing flow of exceeding the number threshold.

[0105] In the embodiment of the present disclosure, abnormal data can be recorded each time an abnormality occurs in the image processing algorithm. The abnormal data includes the corresponding process that does not meet the threshold. After determining that the number of abnormalities in the same process exceeds the threshold, a prompt message can be sent to the cloud server. After receiving the feedback, the cloud server can perform targeted optimization on the algorithm of the corresponding process, thereby improving the user experience.

[0106] In one implementation of the disclosed embodiment, the multiple processing flows include: a data initialization flow, an image resource processing flow, a core algorithm processing flow, a resource algorithm recycling flow, and a data result return flow.

[0107] In an exemplary embodiment of the present disclosure, night scene imaging is performed based on a multi-frame processing algorithm. After the user requests a night scene photo through the camera application, the bottom layer receives the photo request and sets a multi-frame exposure combination EVList to obtain images with different exposures. For example: EV0, EV0, EV0, EV0, EV0, EV0, EV-, EV+, where EV0 is a normal exposure image, EV+ is an over-exposed image, and EV- is a weak exposure image. After obtaining the multi-frame exposure group, the automatic exposure controller (Automatic Exposure Control, AEC) generates the exposure time (Exposure Time) and gain (Gain). The automatic exposure controller converts the exposure time and gain of the multiple frames of images with different exposures into frame length (Frame Length) and number of lines (Line Count) through the sensor (Sensor) module, realizes the conversion of the image's light signal into an electrical signal, and finally outputs the original RAW image. After the original RAW image passes through the image signal processing module, multiple frames of YUV domain images with different exposures are obtained. After the night scene algorithm receives the multiple frames of images, it starts the image processing algorithm.

[0108] In one implementation of the disclosed embodiment, the image processing algorithm includes a multi-frame fusion algorithm for fusing multiple frames of images and determining the fused image as a target image.

[0109] An exemplary embodiment of the present disclosure shows a process for image processing when the image processing algorithm is a multi-frame fusion algorithm. Figure 13As shown in the block diagram of the multi-frame image processing method, the method includes the following steps: After the multi-frame processing algorithm is started, the multi-frame processing algorithm includes a data initialization process: initializing various data for multi-frame image processing based on user-set parameters (such as image size). An image resource processing process: performing preprocessing such as noise reduction, cropping, and alignment on the multi-frame images to be fused. A core algorithm processing process: extracting image features from multiple frames of images with different exposure levels and fusing the extracted target features into a target image. A resource algorithm recycling process: responding to the completion of feature extraction and feature fusion for each frame, the algorithm resources used for feature extraction and fusion are gradually recycled. A data result return process: outputting the fused target image and terminating the multi-frame processing algorithm. Except for the data result return process that ultimately outputs the target image, each of the remaining processes has a corresponding threshold judgment process, including: data initialization threshold judgment, image resource processing threshold judgment, core algorithm processing threshold judgment, and resource algorithm recycling threshold judgment. These processes are used to obtain the processing time of the corresponding process and perform threshold judgment based on the built-in time threshold to determine whether the corresponding processing process has experienced an anomaly.

[0110] In an exemplary embodiment of the present disclosure, the time thresholds for each processing process in multi-frame image processing are designed as follows: data initialization process - 1000ms, image resource preprocessing process - 1000ms, core algorithm processing process - 2000ms, algorithm resource recovery process - 1000ms, and data result return process - 150ms.

[0111] In an embodiment of the present disclosure, multi-frame image processing is divided into multiple sub-stages according to different stages of multi-frame image processing. Each sub-stage has a corresponding time threshold, and the time threshold can be adaptively adjusted based on the operating scenario of the camera terminal. After obtaining multiple frames of images to be processed and starting the multi-frame image processing process, each sub-process is executed in sequence according to the execution order. After the process is executed, the processing time of the sub-process is obtained through a callback, and the processing time of the sub-process is threshold-judged using the corresponding time threshold. If the processing time does not meet the time threshold, the processing result of the sub-process is output as the target image; if the processing time meets the time threshold, the next sub-process is entered, and the above threshold judgment process is repeated until the entire multi-frame image processing process is completed and the target image is output. In response to the processing time of a sub-process not meeting the time threshold, the corresponding processing result is output as the target image. Through the present disclosure, the entire multi-frame image processing process is divided into multiple sub-processes, and a threshold judgment is performed on each sub-process to determine whether to enter the subsequent process. Avoid directly executing the entire multi-frame image processing process, which may cause the multi-frame processing algorithm to be unable to return or time out due to factors such as the large number of image frames to be processed, the complex processing process, and the long processing time. While ensuring the image quality, ensure the smooth completion of the multi-frame image processing process, prevent the algorithm from being unable to return or the multi-frame processing from timeout, and improve the stability of the terminal camera.

[0112] Based on the same concept, the embodiment of the present disclosure further provides a photographing device 100 .

[0113] It will be understood that, in order to implement the aforementioned functions, the camera device 100 provided in the embodiments of the present disclosure includes hardware structures and / or software modules corresponding to each function. In combination with the units and algorithm steps of the various examples disclosed in the embodiments of the present disclosure, the embodiments of the present disclosure can be implemented in hardware or a combination of hardware and computer software. Whether a function is implemented in hardware or in a hardware-driven manner by computer software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementations should not be considered to exceed the scope of the technical solution of the embodiments of the present disclosure.

[0114] Figure 14 FIG. 1 is a block diagram of a photographing device 100 according to an exemplary embodiment. Figure 14 , the device includes a determining unit 101 and a processing unit 102.

[0115] The determining unit 101 is configured to determine an image processing algorithm used to generate a target image in response to receiving a photographing instruction.

[0116] The multi-frame image processing process includes multiple processing flows that are executed sequentially.

[0117] The processing unit 102 is used to determine the processing time consumed by a first processing flow in the process of sequentially executing multiple processing flows, where the first processing flow is the most recently completed processing flow among the multiple processing flows, determine a second processing flow for generating a target image based on the processing time, and generate the target image based on the second processing flow.

[0118] In one embodiment, the processing unit 102 determines a second processing flow for generating a target image based on processing time in the following manner: if the processing time exceeds a time threshold, the second processing flow is determined to be a completed processing flow among the multiple processing flows. The processing unit 102 stops executing the uncompleted processing flows among the multiple processing flows, uses the image obtained by the most recently completed processing flow as the target image, and outputs the target image.

[0119] In one embodiment, the processing unit 102 determines a second processing flow for generating a target image based on the processing time, and generates the target image based on the second processing flow in the following manner: if the processing time does not exceed a time threshold, the second processing flow is determined to be an uncompleted processing flow among the multiple processing flows. The next processing flow is executed, and the determination of the processing time for the next processing flow and the determination of a subsequent process for generating the target image based on the processing time are repeated until the multiple processing flows are completed and the target image is output, or until the processing time of the subsequent process exceeds the time threshold, the image processing algorithm is terminated, the image obtained by the processing flow whose processing time exceeds the time threshold is used as the target image, and the target image is output.

[0120] In one embodiment, the processing unit 102 determines the processing time consumed by the first processing flow by calling back the most recently completed processing flow to determine the processing time consumed by the most recently completed processing flow. Based on the processing time, determining a second processing flow for generating a target image, and generating the target image based on the second processing flow includes: determining a time threshold corresponding to the most recently completed processing flow, wherein the processing flow and the time threshold have a corresponding relationship. Based on the processing time and the time threshold, determining a second processing flow for generating the target image, and generating the target image based on the second processing flow.

[0121] In one embodiment, the corresponding relationship between the processing flow and the time threshold has a matching relationship with the temperature. The processing unit 102 determines the time threshold corresponding to the most recently completed processing flow in the following manner: determining the current temperature and, based on the corresponding relationship between the time threshold and the temperature, determining the time threshold corresponding to the most recently completed processing flow.

[0122] In one embodiment, the processing unit 102 is further configured to: issue a prompt message if the number of times the same processing flow ends exceeds a threshold number of times, where the prompt message is used to prompt the processing flow that exceeds the threshold number of times.

[0123] In one embodiment, the multiple processing flows include: a data initialization flow, an image resource processing flow, a core algorithm processing flow, a resource algorithm recycling flow, and a data result return flow.

[0124] In one embodiment, the image processing algorithm includes a multi-frame fusion algorithm for fusing multiple frames of images and determining the fused image as the target image.

[0125] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0126] Figure 15 FIG2 is a block diagram illustrating an apparatus 200 for photographing, according to an exemplary embodiment. The apparatus 200 may be provided as a terminal. For example, the apparatus 200 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0127] Reference Figure 15 , apparatus 200 may include one or more of the following components: a processing component 202 , a memory 204 , a power component 206 , a multimedia component 208 , an audio component 210 , an input / output (I / O) interface 212 , a sensor component 214 , and a communication component 216 .

[0128] The processing component 202 generally controls the overall operation of the device 200, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. The processing component 202 may include one or more processors 220 to execute instructions to perform all or part of the steps of the above-described method. In addition, the processing component 202 may include one or more modules to facilitate interaction between the processing component 202 and other components. For example, the processing component 202 may include a multimedia module to facilitate interaction between the multimedia component 208 and the processing component 202.

[0129] The memory 204 is configured to store various types of data to support operations on the device 200. Examples of such data include instructions for any application or method operating on the device 200, contact data, phone book data, messages, pictures, videos, etc. The memory 204 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0130] The power component 206 provides power to the various components of the device 200. The power component 206 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device 200.

[0131] The multimedia component 208 includes a screen that provides an output interface between the device 200 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 208 includes a front camera and / or a rear camera. When the device 200 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0132] The audio component 210 is configured to output and / or input audio signals. For example, the audio component 210 includes a microphone (MIC) that is configured to receive external audio signals when the device 200 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 204 or transmitted via the communication component 216. In some embodiments, the audio component 210 further includes a speaker for outputting audio signals.

[0133] I / O interface 212 provides an interface between processing component 202 and peripheral interface modules, such as a keyboard, click wheel, buttons, etc. These buttons may include but are not limited to: a home button, volume buttons, a start button, and a lock button.

[0134] The sensor assembly 214 includes one or more sensors for providing various aspects of the status assessment of the device 200. For example, the sensor assembly 214 can detect the open / closed state of the device 200, the relative positioning of components, such as the display and keypad of the device 200. The sensor assembly 214 can also detect changes in the position of the device 200 or a component of the device 200, the presence or absence of user contact with the device 200, the orientation or acceleration / deceleration of the device 200, and temperature changes of the device 200. The sensor assembly 214 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 214 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 214 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0135] The communication component 216 is configured to facilitate wired or wireless communication between the device 200 and other devices. The device 200 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 216 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 216 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0136] In an exemplary embodiment, the apparatus 200 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0137] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as the memory 204 including instructions, which can be executed by the processor 220 of the apparatus 200 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0138] It is understood that in this disclosure, "plurality" refers to two or more than two, and other quantifiers are similar. "And / or" describes the association relationship of related objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects before and after are in an "or" relationship. The singular forms "a", "the" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0139] It will be further understood that the terms "first," "second," and the like are used to describe various types of information, but such information should not be limited to these terms. These terms are used solely to distinguish information of the same type from one another and do not indicate a particular order or level of importance. In fact, the terms "first," "second," and the like are fully interchangeable. For example, first information could be referred to as second information, and similarly, second information could be referred to as first information without departing from the scope of this disclosure.

[0140] It can be further understood that the terms "center", "longitudinal", "lateral", "front", "back", "up", "down", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this embodiment and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation.

[0141] It is further understood that, unless otherwise specified, “connection” includes a direct connection where there are no other components between the two elements, and also includes an indirect connection where there are other elements between the two elements.

[0142] It is further understood that although operations are described in a particular order in the drawings in the embodiments of the present disclosure, this should not be construed as requiring that the operations be performed in the particular order shown or in a serial order, or that all of the operations shown be performed to obtain the desired results. In certain circumstances, multitasking and parallel processing may be advantageous.

[0143] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein.

[0144] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the scope of the appended claims.

Claims

1. A photographing method, characterized in that: include: In response to receiving a photographing instruction, determining an image processing algorithm used to generate a target image, wherein the image processing algorithm includes a plurality of processing flows executed sequentially; In the process of sequentially executing the multiple processing flows, determining the processing time consumed by a first processing flow, the first processing flow being a processing flow that has been executed most recently among the multiple processing flows; Based on the processing time, a second processing flow for generating the target image is determined, and the target image is generated based on the second processing flow.

2. The method according to claim 1, characterized in that The step of determining a second processing flow for generating the target image based on the processing time, and generating the target image based on the second processing flow, comprises: If the processing time exceeds the time threshold, determining that the second processing flow is a processing flow that has been completed among the multiple processing flows; The execution of the unfinished processing flows among the multiple processing flows is stopped, an image obtained by the most recently completed processing flow is used as a target image, and the target image is output.

3. The method according to claim 1, characterized in that Determining a second processing flow for generating the target image based on the processing time, and generating the target image based on the second processing flow includes: If the processing time does not exceed the time threshold, determining that the second processing flow is an unfinished processing flow among the multiple processing flows; Execute the next processing flow, repeatedly determine the processing time of the next processing flow, and determine the subsequent flow for generating the target image based on the processing time, until the execution of the multiple processing flows is completed and the target image is output, or until the processing time of the subsequent flow exceeds the time threshold, end the image processing algorithm, use the image obtained by the processing flow whose processing time exceeds the time threshold as the target image, and output the target image.

4. The method according to any one of claims 1 to 3, characterized in that The determining the processing time consumed by the first processing flow includes: Calling back the most recently completed processing flow to determine the processing time consumed by the most recently completed processing flow; The step of determining a second processing flow for generating the target image based on the processing time, and generating the target image based on the second processing flow, comprises: Determine a time threshold corresponding to the most recently completed processing flow, wherein there is a corresponding relationship between the processing flow and the time threshold; Based on the processing time and the time threshold, a second processing flow for generating the target image is determined, and the target image is generated based on the second processing flow.

5. The method according to claim 4, characterized in that The processing flow has a corresponding relationship with the time threshold, and has a matching relationship with the temperature; The determining of the time threshold corresponding to the most recently completed processing flow comprises: The current temperature is determined, and based on the corresponding relationship between the time threshold and the temperature, the time threshold corresponding to the most recently completed processing flow is determined.

6. The method according to claim 2, characterized in that The method further comprises: If the number of times the same processing flow ends exceeds the number threshold, a prompt message is issued, and the prompt message is used to prompt the processing flow that exceeds the number threshold.

7. The method according to claim 1, characterized in that The multiple processing flows include: Data initialization process, image resource processing process, core algorithm processing process, resource algorithm recovery process and data result return process.

8. The photographing method according to claim 1, characterized in that: The image processing algorithm includes a multi-frame fusion algorithm, which is used to fuse multiple frames of images and determine the image obtained after fusion as the target image.

9. A photographing device, characterized in that: include: a determining unit, configured to determine, in response to receiving a photographing instruction, an image processing algorithm used to generate a target image, wherein the image processing algorithm includes a plurality of processing flows executed sequentially; A processing unit is used to determine the processing time consumed by a first processing flow in the process of sequentially executing the multiple processing flows, the first processing flow being the most recently completed processing flow among the multiple processing flows, determine a second processing flow for generating the target image based on the processing time, and generate the target image based on the second processing flow.

10. A photographing device, characterized in that: include: processor: a memory for storing processor-executable instructions; Wherein, the processor is configured to: execute the photographing method described in any one of claims 1 to 8.

11. A storage medium, characterized in that: The storage medium stores instructions, and when the instructions in the storage medium are executed by a processor, the processor is enabled to execute the photographing method according to any one of claims 1 to 8.

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