CN115988151A - Method and system for processing video in real time by using low-pixel clock - Google Patents
Method and system for processing video in real time by using low-pixel clock Download PDFInfo
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Abstract
The invention discloses a method and a system for processing a video in real time by using a low pixel clock, and relates to the technical field of image real-time processing. The invention comprises the following steps: s1, an acquisition module acquires image data in real time; s2, constructing a splitting module, wherein the splitting module receives the image data and splits the image data according to a preset rule to obtain at least two groups of preprocessed images; s3, constructing an image processing module, wherein the image processing module receives the preprocessed image and processes image data to obtain output data; s4, constructing a recombination module, receiving the output data, recombining the output data according to a preset rule, and outputting result data; and S5, constructing a display module, receiving the result data and displaying the corresponding real-time image. The invention provides a function of processing a high-pixel video image by splitting the high-pixel image, respectively processing the image and then recombining the image.
Description
Technical Field
The invention relates to the technical field of image real-time processing, in particular to a method and a system for processing a video in real time by using a low-pixel clock.
Background
In recent years, surgical operations have been gradually advanced toward minimally invasive surgery, and endoscopes have become medical instruments indispensable for minimally invasive surgery. As the requirement of the endoscope on the image resolution is continuously increased, the resolution is improved from 2K to 4K, and meanwhile, as the video data volume is multiplied, higher requirements are put forward for a system to process images in real time.
At present, most multimedia processing chips are provided with ISP modules for processing original images acquired by an image sensor, but the ISP modules are designed according to specific specifications, for example, an ISP module processes images of 2M pixels, and can only receive and process images of less than 2M pixels, and if images of more than 2M need to be processed, the multimedia chips cannot work. Meanwhile, ISP functions contained in the multimedia chips are fixed, if a new image processing algorithm exists, the multimedia chips cannot be expanded, and the multimedia chips need to be designed again.
The ISP image processing system based on FPGA design can design a new image algorithm as required, but once the resolution of the received image is improved, for example, a 4K60Hz image is input, the clock processed by the corresponding ISP design module is improved in multiples, so that the design complexity of FPGA is improved, and the clock constraint is more rigorous. If the ISP processing clock is not increased, the ISP module needs to process a plurality of pixels in a unit clock, which increases the complexity of designing each module inside the ISP and is not strong in versatility.
Therefore, the present application is to solve the problem of how to perform real-time processing on a high-pixel image under a low pixel clock condition, and further output a high-quality image.
Disclosure of Invention
The purpose of the invention is as follows: based on the problems mentioned in the background technology, the application proposes to encode and recombine the high-pixel image, split the high-pixel image into at least two parts, respectively process the two parts, recombine the high-pixel image after the processing is finished, and finally output a complete image.
The technical scheme is as follows: a method of processing video in real time using a low pixel clock, comprising the steps of:
s1, constructing an acquisition module, wherein the acquisition module acquires real-time image data;
s2, constructing a splitting module, wherein the splitting module receives the image data and splits the image data according to a preset rule to obtain at least two groups of preprocessed images;
s3, constructing an image processing module, wherein the image processing module receives the preprocessed image and processes the preprocessed image to obtain output data;
s4, constructing a recombination module, receiving the output data, recombining the output data according to a preset rule, and outputting result data;
and S5, constructing a display module, receiving the result data and displaying the corresponding real-time image.
Further, the process of the splitting module processing the image data comprises:
s21a, splitting the image data into at least a left group of data and a right group of data, wherein the left group of data and the right group of data are combined into image data;
and S22a, coding the left and right groups of data respectively to obtain left and right groups of coded data, and sending the left and right groups of coded data to the image processing module for processing.
Further, the process of the splitting module processing the image data comprises:
s21b, splitting the image data into at least two groups of data, namely left image data and right image data; wherein, the left image data and the right image data are set to be partially overlapped, and the overlapped area is set as area data delta L.
Further, the method also comprises the following steps:
s22b, generating repeated region data after the left image data and the right image data are recombined, wherein the repeated region data are region data delta L1 and region data delta L2 respectively;
s22c, constructing a correction module, wherein the correction module is used for processing the area data delta L1 and the area data delta L2.
Further, the flow of processing the area data Δ L by the modification module includes:
s221, images represented by the area data delta L1 and the area data delta L2 are respectively segmented according to a preset rule, and areas at the edge of the images represented by the area data delta L1 and the area data delta L2 are respectively processed;
s222 selects the area data Δ L1 processed in step S221, performs detailed processing on the selected area data Δ L1, and uses the area data Δ L2 processed in step S221 as a correction reference.
Further, the method also comprises the following steps:
s211, constructing a sliding interval module, wherein the sliding interval module is used for controlling the range of the region data delta L, and the sliding interval module is set based on the frequency and the frame number of the video.
A system for real-time processing video using a low pixel clock, using a method for real-time processing video using a low pixel clock according to any one of the above embodiments, comprising: the image sensor is used for outputting image data, the acquisition module is used for receiving the image data and processing the image data through the image processing module, the recombination module receives the processed image data, recombines the processed image data according to a preset rule, outputs result data and sends the result data to the display module for displaying.
Further, the image processing module comprises:
a sliding interval module for controlling the range of the region data Delta L;
and the correction module is used for processing the area at the edge of the image represented by the area data delta L according to a preset rule.
Further, the image sensor transmits in-vivo image data and sends the in-vivo image data to the acquisition module, the splitting module respectively splits the image data in real time by using at least two data channels to obtain left image data and right image data, carries out reconstruction coding and sends the image data to the image processing module through a protocol, the image processing module respectively sends processed data to the reconstruction module after processing is completed, and the image processing module has the working contents that: the sliding interval module sets the range of the region data delta L according to a preset rule, the left image data comprise the region data delta L1, the right image data comprise the region data delta L2, the correction module processes the edge of the image represented by the region data delta L according to the preset rule and performs deduplication, and the recombination module recombines the processed data and restores the size of the preset image.
Has the advantages that:
1. the video image with high pixel can be processed by using the existing module structure such as low pixel clock, and the high-quality video image can be output in real time.
2. By setting the repeated region and further processing the details of the image represented by the split repeated region through the correction module, the focus details in the original video can be reserved.
3. By arranging the sliding interval module, the repeated area can be adjusted, and all the contents of tissues and focuses can be presented better, so that the clinical requirements of doctors can be met.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a flow diagram of the rework module operation of the present invention.
Figure 3 is one embodiment of the present invention.
FIG. 4 is a diagram of a first splitting method of the present invention.
FIG. 5 is a diagram of a second resolution method of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
Example 1
Based on the problems mentioned in the background art, in modern medical surgery, the demand for image resolution is increasing, the resolution is raised from 2K to 4K, but the demand may be higher later, especially relates to the early stage focus discovery, in order to better distinguish early stage pathology, a higher resolution is required to increase the video data volume, so that under the condition of low pixel clock, the image is processed in real time, and then a high quality image is output, this embodiment proposes a method for processing the video in real time by using the low pixel clock under the existing image processing module condition, as shown in fig. 1, including the following steps:
s1, constructing an acquisition module, and acquiring image data in real time by the acquisition module;
s2, constructing a splitting module, wherein the splitting module receives the image data and splits the image data according to a preset rule to obtain at least two groups of preprocessed images;
s3, constructing an image processing module, wherein the image processing module receives the preprocessed image and processes the preprocessed image to obtain output data;
s4, constructing a recombination module, receiving the output data by the recombination module, recombining the output data according to a preset rule, and outputting result data;
and S5, constructing a display module, receiving the result data and displaying the corresponding real-time image.
In order to better illustrate the method, the embodiment is illustrated based on ISP and DDR designed by FPGA as examples, as shown in fig. 2:
step 1: the image acquisition module interactively configures a relevant register of the image sensor through a communication protocol according to an image sensor data manual, so that the image sensor works in a 4K60Hz mode;
step 2: the image acquisition module acquires data output by the image sensor, and divides a data channel into a left part and a right part to be respectively acquired in real time;
and 3, step 3: the image acquisition module carries out recombination coding on the acquired real-time data and sends the data to the ISP through a protocol;
and 4, step 4: the ISP respectively carries out real-time image algorithm processing on the left channel and the right channel, and after the processing is finished, the data is sent to the DDR;
and 5: the DDR recombines the data of the left channel and the right channel to restore the data to be 3840x2160 image size, and sends the restored data to the display module;
and 6: the display module finally displays the 4K60Hz real-time image
Example 2
For example, as mentioned in the background, if the ISP is processing 2M pixel images, it can only receive and process less than 2M pixel images, and if it needs to process more than 2M images, these multimedia chips cannot work. On the basis of embodiment 1, this embodiment provides a splitting method, where a process of processing image data by a splitting module includes:
s21a, splitting the image data into a left group of data and a right group of data, wherein the left group of data and the right group of data are combined into the image data;
and S22a, coding the left and right groups of data respectively to obtain left and right groups of coded data, and sending the left and right groups of coded data to the image processing module for processing.
As shown in fig. 3, the left and right groups of data are respectively processed by ISPs, where ISPs process a single pixel in a unit clock, which simplifies the difficulty of each ISP algorithm module inside, for example, in the process of processing an image inside an ISP, filtering operation is often required to be performed on the image, and the filtering operation requires using a scanning window template, which generally includes templates of 3x3, 5x5, 7x7, etc., where the centers of the scanning window templates are single pixels, and then various filtering operations are performed according to adjacent pixels. By the method, the image is divided into two parts for processing, for example, by taking an input real-time video image of 3840x2160 as an example, each frame of image data is divided into a left part and a right part, and ISP processing is respectively carried out, so that the clock frequency of the system for processing the ISP is reduced, the design of each algorithm module in the ISP is simplified, and meanwhile, the overall delay of the endoscope camera system is reduced, so that the ISP can process the high-pixel video image in real time.
Example 3
Different from the embodiment 2, in the embodiment 2, the image data is divided into two parts, and once a focal region exists at the junction of the two parts, an error is easily generated after recombination, and the error includes a local deviation during system recombination, a system embedded adaptive algorithm, and a pathology at the place is ignored or self-optimization processing is performed, so the second process of processing the image data by the splitting module is provided in the embodiment, and the steps are as follows:
s21b, splitting the image data into at least two groups of data, namely left image data and right image data; wherein, the left image data and the right image data are set to be partially overlapped, and the overlapped area is set as area data delta L.
By the method, when the left image data and the right image data are recombined, redundant original image data exist in the content, namely the data of a partial overlapping area exists, so that all pathological features recorded by the original image data can be completely reserved only by processing the data of the overlapping area.
Example 4
On the basis of embodiment 3, different from the common direct overlapping, since the edges of the images represented by the left image data and the right image data are still incomplete, a focal region still may exist, direct recombination occurs, an image error still exists at the image boundary, and the left image data and the right image data need to be processed;
s22b, generating repeated region data after the left image data and the right image data are recombined, wherein the repeated region data are region data delta L1 and region data delta L2 respectively; namely, the left image data includes region data Δ L1, the right image data includes region data Δ L2, and the region data Δ L1 and the region data Δ L2 are theoretically the same;
and S22c, constructing a correction module, wherein the correction module is used for processing the region data delta L1 and the region data delta L2 and is mainly used for optimizing repeated region data.
Through the above scheme, based on the 3-bit basis of the embodiment, a modification module is constructed for processing the region data Δ L, and the processing scheme may be to eliminate the repeated region data, or to use one of the region data as a reference and use the other for reference, or to process the image at the edge of the image represented by the region data.
Example 5
On the basis of embodiment 4, this embodiment provides a flow of processing area data Δ L of the correction module:
s221, images represented by the area data delta L1 and the area data delta L2 are respectively segmented according to a preset rule, and areas at the edge of the images represented by the area data delta L1 and the area data delta L2 are respectively processed; firstly, processing the region at the edge of the image according to a preset rule or by using a common self-adaptive deep learning algorithm, and reserving pathological details;
s222 selects the area data Δ L1 processed in step S221, performs detailed processing on the selected area data Δ L1, and performs correction using the area data Δ L2 processed in step S221 as a correction reference, that is, using the area data Δ L2 as a reference.
Example 6
On the basis of embodiment 5, in order to enable the correction module to process the area at the edge to retain more details, a deep learnable neural network may be further introduced, comprising the following steps:
step one, constructing a neural network model, and training the neural network model by using a data set;
step two, inputting the regional data delta L1 to the trained neural network model for processing;
introducing a loss function, and calculating the loss ratio of the processed region data delta L1 and the data corresponding to the region data delta L1; setting a threshold, and outputting the processed region data delta L1 when the loss ratio is less than or equal to the threshold; otherwise, performing the step four;
and step four, updating the network parameters of the neural network model, and returning to the step two.
The neural network model process in this embodiment prefers the partitioning of the path, i.e., preserving the detail in the image represented by the region data Δ L.
Example 7
Based on the above technical solution, due to the range of the focus, the video frequency, the frame number, etc. in the image, the region data Δ L is a fixed value that does not actually satisfy the needs of the doctor, and in this implementation, the following steps are provided:
s211, constructing a sliding interval module, wherein the sliding interval module is used for controlling the range of the region data delta L, and the sliding interval module is set based on the frequency and the frame number of the video.
Through the scheme, the range of the area data delta L is adjusted through the sliding interval module, so that the application range of the area data delta L is wider, and further, the depth network model is provided in cooperation with the embodiment 6, and the optimal output of a real-time video can be realized.
Example 8
Through the above technical solution, this embodiment provides a system for processing a video in real time by using a low pixel clock, including: the image sensor is used for outputting image data, the acquisition module is used for receiving the image data and processing the image data through the image processing module, the recombination module receives the processed image data, the processed image data are recombined according to a preset rule, and result data are output and sent to the display module to be displayed.
The image sensor transmits in-vivo image data and sends the in-vivo image data to the acquisition module, the splitting module uses at least two data channels to split the in-vivo image data respectively and carries out recombination coding, the in-vivo image data are sent to the image processing module through a protocol, the processed data are sent to the recombination module respectively after the image processing module finishes processing, the recombination module recombines the processed data, the preset image size is recovered, and the reconstructed data are output to the display module to be displayed.
Example 9
On the basis of embodiment 8, the image processing module further includes:
the sliding interval module is used for controlling the range of the area data delta L; the control parameters of the sliding interval module at least comprise video frame number, frequency and pixel;
and the correction module is used for processing the area image at the edge of the area data delta L according to a preset rule.
The correction module processes the area at the edge of the image represented by the area data Δ L, and takes details as a core.
Example 10
Image sensor transmits internal image data to send to the collection module, and the split module uses two kinds of at least data channel to carry out the split in real time respectively, obtains left image data, right image data to carry out the reorganization and coding, sends the image processing module through the agreement, and the image processing module is handled and is accomplished the back and respectively with the data transmission after handling to the reorganization module, and the work content of image processing module is: the sliding interval module sets the range of the region data delta L according to a preset rule, the left image data comprises region data delta L1, the right image data always comprises region data delta L2, the correction module processes the edge of the image represented by the region data delta L according to the preset rule and performs de-duplication, the recombination module recombines the processed data, recovers the size of the preset image and finally transmits the size of the preset image to the display module for display.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the present application as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include such modifications and variations.
The above is only a preferred embodiment of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention, and such modifications and adaptations are intended to be within the scope of the invention.
Claims (9)
1. A method for processing video in real time using a low pixel clock, comprising the steps of:
s1, constructing an acquisition module, wherein the acquisition module acquires image data in real time;
s2, constructing a splitting module, wherein the splitting module receives the image data and splits the image data according to a preset rule to obtain at least two groups of preprocessed images;
s3, constructing an image processing module, wherein the image processing module receives the preprocessed image and processes the preprocessed image to obtain output data;
s4, constructing a recombination module, receiving the output data, recombining the output data according to a preset rule, and outputting result data;
and S5, constructing a display module, receiving the result data and displaying the corresponding real-time image.
2. The method of claim 1, wherein the process of processing image data by the splitting module in real-time using a low pixel clock comprises:
s21a, splitting the image data into at least a left group of data and a right group of data, wherein the left group of data and the right group of data are combined into image data;
and S22a, coding the left and right groups of data respectively to obtain left and right groups of coded data, and sending the left and right groups of coded data to the image processing module for processing.
3. The method of claim 1, wherein the process of the splitting module processing the image data comprises:
s21b, splitting the image data into at least two groups of data, namely left image data and right image data; wherein, the left image data and the right image data are set to be partially overlapped, and the overlapped area is set as area data delta L.
4. A method for real-time processing of video using a low pixel clock as claimed in claim 3, further comprising the steps of:
s22b, generating repeated region data after the left image data and the right image data are recombined, wherein the repeated region data are region data delta L1 and region data delta L2 respectively;
s22c, constructing a correction module, wherein the correction module is used for processing the area data delta L1 and the area data delta L2.
5. The method for real-time processing of video using low pixel clock as claimed in claim 4, wherein the flow of processing region data Δ L of the modification module comprises:
s221, images represented by the area data delta L1 and the area data delta L2 are respectively segmented according to a preset rule, and areas at the edge of the images represented by the area data delta L1 and the area data delta L2 are respectively processed;
s222 selects the area data Δ L1 processed in step S221, performs detailed processing on the selected area data Δ L1, and uses the area data Δ L2 processed in step S221 as a correction reference.
6. A method for real-time processing of video using a low pixel clock as claimed in claim 3, further comprising the steps of:
s211, constructing a sliding interval module, wherein the sliding interval module is used for controlling the range of the area data delta L and is set based on the frequency and the frame number of the video.
7. A system for real-time processing video by using low pixel clock, which implements a method for real-time processing video by using low pixel clock according to any one of claims 1-6, comprising: the image processing device comprises an image sensor, an acquisition module, a splitting module, an image processing module, a recombination module and a display module, wherein the image sensor is used for outputting image data, the acquisition module is used for receiving the image data, the splitting module is used for splitting the image data, the image processing module is used for processing the split image data, the recombination module is used for receiving the processed image data, recombining the processed image data according to a preset rule, outputting result data and sending the result data to the display module for displaying.
8. The system of claim 7, wherein the image processing module comprises:
a sliding interval module for controlling the range of the region data Delta L;
and the correction module is used for processing the area at the edge of the image represented by the area data delta L according to a preset rule.
9. The system according to claim 8, wherein the image sensor transmits in-vivo image data and transmits the in-vivo image data to the acquisition module, the splitting module splits the in-vivo image data and the right image data in real time using at least two data channels, respectively, and performs re-encoding, and transmits the left image data and the right image data to the image processing module via a protocol, and the image processing module transmits the processed data to the re-encoding module after completing the processing, and the image processing module operates as follows: the sliding interval module sets the range of the region data delta L according to a preset rule, the left image data comprise the region data delta L1, the right image data comprise the region data delta L2, the correction module processes the edge of the image represented by the region data delta L according to the preset rule and performs deduplication, and the recombination module recombines the processed data and restores the size of the preset image.
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