CN111666363A - Method and device for slicing and quality control of mass high-resolution image data - Google Patents
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Abstract
The invention provides a method and a device for slicing and controlling quality of massive high-resolution image data, wherein the method comprises the following steps: preprocessing a plurality of original images to obtain a plurality of images to be processed with geographical coordinate information; determining the total map cutting level of each image to be processed according to the resolution of each image to be processed and the corresponding relation between each preset resolution and the total map cutting level; determining the reference level of each image to be processed according to the corresponding relation between the preset total tangent image level and the reference level; calculating geographic information corresponding to the reference levels of the images to be processed, and grouping the images to be processed according to the geographic information corresponding to the reference levels of the images to be processed to obtain each group of images to be processed; and respectively carrying out image slicing on the reference level of each group of images to be processed to obtain a tile map of each group of images to be processed, and synthesizing the tile map of each group of images to be processed according to the geographic coordinate information in the tile map of each group of images to be processed.
Description
Technical field cleaner
The invention relates to the field of image processing, in particular to a method and a device for slicing and controlling quality of massive high-resolution image data.
Background
With the continuous emission of high-score satellites, the application value of high-score remote sensing data in the fields of military and civil integration, natural resource investigation and urban public service is more prominent. In the future, the remote sensing data with high spatial resolution, high temporal resolution, high spectral resolution and high radiation resolution can play an increasingly important role in cooperation. With the arrival of 'high time-sharing generation', the explosive increase of multi-source heterogeneous multi-temporal multi-scale data volume is aggravated, the resolution of remote sensing image data exceeds 2 meters, the data volume can reach PB level according to different space-time ranges, and how to rapidly release and efficiently browse the data volume becomes a bottleneck problem restricting the application development of the data volume.
At present, the display of high-resolution remote sensing data is mainly realized by 2 modes of establishing a spatial index to realize global static slicing and local dynamic publishing. No matter which mode is adopted for issuing, the problems of partial slicing distortion, pixel loss, poor image edge quality, blank pictures and the like can be caused due to the huge data volume, so that data slicing failure is caused, slicing work progress is delayed, and data display effect is influenced.
Therefore, it is desirable to provide a method for slicing and quality control of massive high-resolution image data to improve the efficiency of the whole slicing process of the image.
Disclosure of Invention
In view of this, the present invention provides a method and an apparatus for slicing and quality control of mass high-resolution image data, so as to improve the efficiency of the whole slicing process of the picture.
In a first aspect, the present invention provides a method for slicing and quality control of mass high-resolution image data, comprising: preprocessing a plurality of original images to obtain a plurality of images to be processed with geographical coordinate information; determining the total map cutting level of each image to be processed according to the resolution of each image to be processed and the corresponding relation between each preset resolution and the total map cutting level; determining the reference level of each image to be processed according to the corresponding relation between the preset total tangent image level and the reference level; calculating geographic information corresponding to the reference levels of the images to be processed, and grouping the images to be processed according to the geographic information corresponding to the reference levels of the images to be processed to obtain each group of images to be processed; and respectively carrying out image slicing on the reference level of each group of images to be processed to obtain a tile map of each group of images to be processed, and synthesizing the tile map of each group of images to be processed according to the geographic coordinate information in the tile map of each group of images to be processed.
In a second aspect, the present invention provides an apparatus for slicing and quality control of mass high-resolution image data, comprising: the image preprocessing unit is used for preprocessing the original images to obtain a plurality of images to be processed with geographical coordinate information; the hierarchy determining unit is used for determining the total cutting map hierarchy of each image to be processed according to the resolution of each image to be processed and the corresponding relation between each preset resolution and the total cutting map hierarchy; determining the reference level of each image to be processed according to the corresponding relation between the preset total tangent image level and the reference level; the image grouping unit is used for calculating the geographic information corresponding to the reference level of each image to be processed and grouping the images to be processed according to the geographic information corresponding to the reference level of each image to be processed to obtain each group of images to be processed; the image slicing unit is used for respectively carrying out image slicing on the reference level of each group of images to be processed to obtain a tile map of each group of images to be processed; and the image synthesis unit is used for synthesizing the tile map of each group of images to be processed according to the geographic coordinate information in the tile map of each group of images to be processed.
In a third aspect, the present invention provides a computer-readable storage medium storing a program including instructions for performing the method for slicing and quality control of mass high-resolution image data as described above.
In a fourth aspect, the present invention provides a computer comprising a readable medium storing a computer program comprising instructions for performing the above-described method for slicing and quality control of mass high resolution video data.
The method and the device for slicing the mass high-resolution image data and controlling the quality of the mass high-resolution image data group the images to be processed according to the geographic information corresponding to the reference levels of the images to be processed, so that high-resolution remote sensing partitioning and blocking slicing, picture verification and result centralized release are realized, the geographic information in the same group has certain similarity, on one hand, the slicing process can be processed in a parallel and efficient manner, on the other hand, the slicing process can be quickly synthesized according to the geographic coordinate information, and the efficiency of the whole image slicing process is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flowchart of a method for slicing and quality control of mass high-resolution image data according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method for slicing and quality control of mass high resolution video data according to a second embodiment of the present invention;
fig. 3 is a block diagram of a device for slicing and quality control of mass high-resolution image data according to a third embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be noted that, in the case of no conflict, the features in the following embodiments and examples may be combined with each other; moreover, all other embodiments that can be derived by one of ordinary skill in the art from the embodiments disclosed herein without making any creative effort fall within the scope of the present disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the disclosure, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. Additionally, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
As shown in fig. 1, a method for slicing and quality controlling a mass of high resolution image data according to a first embodiment of the present invention includes:
step 101: preprocessing a plurality of original images to obtain a plurality of images to be processed with geographical coordinate information;
step 102: determining the total map cutting level of each image to be processed according to the resolution of each image to be processed and the corresponding relation between each preset resolution and the total map cutting level; and determining the reference level of each image to be processed according to the corresponding relation between the preset total tangent image level and the reference level.
Step 103: calculating geographic information corresponding to the reference levels of the images to be processed, and grouping the images to be processed according to the geographic information corresponding to the reference levels of the images to be processed to obtain each group of images to be processed;
step 104: and respectively carrying out image slicing on the reference level of each group of images to be processed to obtain a tile map of each group of images to be processed, and synthesizing the tile map of each group of images to be processed according to the geographic coordinate information in the tile map of each group of images to be processed.
The embodiment groups the to-be-processed images according to the geographic information corresponding to the reference level of each to-be-processed image for mass data, establishes a spatial index, constructs a distributed parallel computing frame and the like, realizes high-resolution remote sensing partitioned slicing, picture verification and result centralized release, performs grouped slicing processing on the basis of the geographic information corresponding to the reference level of each to-be-processed image, has certain similarity on the geographic information in the same group, can process a slicing process in a parallel and efficient manner on one hand, can be quickly synthesized according to geographic coordinate information on the other hand, is beneficial to promoting high-resolution remote sensing resource sharing, forms a data value-added chain of 'data-information-knowledge-decision' and quickly provides comprehensive application services.
Referring to fig. 2, a second embodiment of the present invention provides a method for slicing and quality control of mass high resolution video data
The method is a preferred implementation mode of the method shown in fig. 1, and specifically comprises the following steps:
step 201: receiving original data;
step 202: preprocessing a plurality of original images; the specific data processing may include: data deduplication, coordinate system allocation. Data deduplication refers to combing and submitting the data with repeated numbers to a user to determine the finally used version. The coordinate system configuration refers to adding a geographical coordinate system to each piece of data.
Step 203: obtaining a plurality of images to be processed with geographical coordinate information;
step 204: after the step of obtaining a plurality of images to be processed with geographical coordinate information, performing quality inspection on the plurality of images to be processed according to a preset first quality inspection condition, and continuing data deduplication operation and/or geographical coordinate information configuration operation on the images to be processed which do not meet the first quality inspection condition;
step 205: calculating geographic information corresponding to the reference level of each image to be processed; during specific operation, the reference data can be used for making corresponding vector data according to the size of the 7 th layer picture;
step 206: calculating geographic information corresponding to the reference levels of the images to be processed which meet the first quality inspection condition, performing quality inspection on the geographic information corresponding to the reference levels of the images to be processed according to a preset second quality inspection condition, and performing grouping operation on the images to be processed which meet the first quality inspection condition according to the geographic information corresponding to the reference levels of the images to be processed which meet the second quality inspection condition;
step 207: grouping the images to be processed according to the range of the geographic information corresponding to the reference level of each image to be processed; specifically, the image data grouping may group the image data in accordance with a range of the reference data;
step 208: according to a preset third quality inspection condition, performing quality inspection on each image to be processed after grouping operation; the second quality inspection condition and the third quality inspection condition can be set according to actual requirements;
step 209: taking each image to be processed which meets the third quality inspection condition as each group of images to be processed;
step 210: performing image slicing on each group of images to be processed; the specific slicing mode can refer to the existing flow and is not described again;
step 211: obtaining a tile map of each group of images to be processed;
step 212: randomly selecting a preset number of detection points in a preset position range in the tile map of each group of images to be processed, judging whether the tile map of each group of images to be processed is abnormal according to pixel color difference values of the detection points, and repairing the abnormal tile map when the tile map is determined to be abnormal; carrying out anomaly detection on the repaired tile map again until the repaired tile map is normal;
the quality inspection of the step is mainly to screen common problems of slice distortion, pattern spot loss and the like in a mode of combining program examination and manual verification. Judging whether the processed data are white and black pure color films or multi-color flower films through rgb colors; and judging whether the slice is reasonable from the storage size of the slice. In general, problem slices have several main characteristics:
1) the problem is mostly represented by that some disordered color spots appear on the picture, and the difference between the picture pixel point and the surrounding color value is too large.
2) The speckle is missing (white edge and black edge), and such a problem is mostly represented by the appearance of a large area of white or black area on the picture, resulting in the loss of speckle information.
3) Picture jagging, such a problem is mostly expressed as an irregular jagged pattern on the picture.
The common slicing problems of the above points are examined and processed in the following way; program screening taxonomy summary: for blank pictures: program screening the picture size (< 2kb) to classify as blank picture. For the problem picture: 12 points of 3 x 3 pixels are randomly selected at the edge and the middle position of the picture 4 by a program, and pixel color value differences in each point are screened. Taking the appearance of a (0,0, 0; 1,1,1 or 255,255,255; 254,254,254) color value in a dot classifies it as a blob deletion. The large difference of color values of each pixel in a single point is classified as picture noise and sawtooth. And simultaneously recording the slice sequence (layer number, line number and column number) of the pictures. And directly deleting the blank picture, performing independent slice repair on the slice sequence after the problem picture is verified, and repeatedly checking the picture quality after the slice is finished.
Step 213: synthesizing the tile map of each group of images to be processed according to the geographic coordinate information in the tile map of each group of images to be processed;
step 214: performing quality inspection (quality inspection) according to a preset inspection rule;
step 215: and (5) archiving the results, and summarizing and archiving the slicing results after the quality inspection is passed.
In this embodiment, high resolution image data with a resolution of 2 meters at 1:1 ten thousand parts per million in the whole country is opened one by one, the correctness of the data is checked, and after the data is checked, the amount of the image data at this time is counted to be about 10TB, which includes about 27392 data, and the amount of single image data is about 350 MB. The traditional slicing mode using the GIS platform has extremely low efficiency for the image data of TB level data quantity, high requirement on server resources and high requirement on speciality. The image slicing method has the characteristics of simplicity in operation, controllable progress and the like. The image data volume is huge, the slicing period is long, and distribution and regional deployment of the slicing data at the later stage are facilitated.
In this embodiment, a slice level plan is made according to the data resolution, and in order to ensure the clarity of picture display and the absence of ghost in a picture, the slice level of 2 m resolution data is 0-15 layers. Due to the huge data volume, in order to reduce the pressure of the server, improve the slicing efficiency and ensure that the slicing work is completed on schedule, the image data is grouped by taking the 7 th layer picture size as a reference. The image data are grouped according to the picture size of the 7 th layer or the 8 th layer and respectively subjected to tile map manufacturing as the 7 th layer is taken as the reference, the image cutting level and the manufacturing time can be greatly shortened, the image data can be smoothly divided according to the picture size of the 7 th layer or the 8 th layer; the quality control based on picture elements is completed by each section slice, and according to the technical basis of the inspection and the characteristics of the project, the quality elements of multiple layers of registration, the integral brightness, color, contrast, inner texture of the image, the surface feature edge, mosaic existence, definition and the like of the slice data are mainly inspected in a detailed result inspection mode. The detailed result investigation is mainly performed in a mode of combining program investigation and manual investigation, the slicing data is inspected by using a service, and finally all grouped tile maps are gathered to form a final result. The tile map can be compressed, the disk space is greatly saved on the premise of ensuring the picture quality, meanwhile, approximately 70 percent of network resources are saved during service release, and the service access efficiency is improved
As shown in fig. 3, a third embodiment of the present invention provides an apparatus for slicing and quality control of massive high resolution video data, which is an embodiment of the apparatus corresponding to the method shown in fig. 1 and fig. 2, and the explanation of fig. 1 and fig. 2 can be applied to this embodiment, and specifically includes:
the image preprocessing unit 301 is configured to preprocess the multiple original images to obtain multiple to-be-processed images with geographic coordinate information;
a level determining unit 302, configured to determine a total cutout level of each to-be-processed image according to a resolution of each to-be-processed image and a preset correspondence between each resolution and the total cutout level; determining the reference level of each image to be processed according to the corresponding relation between the preset total tangent image level and the reference level;
an image grouping unit 303, configured to calculate geographic information corresponding to the reference level of each to-be-processed image, and group the to-be-processed images according to the geographic information corresponding to the reference level of each to-be-processed image to obtain each group of to-be-processed images;
an image slicing unit 304, configured to perform image slicing on the reference levels of each group of images to be processed respectively to obtain tile maps of each group of images to be processed;
an image synthesis unit 305, configured to synthesize the tile maps of the sets of images to be processed according to the geographic coordinate information in the tile maps of the sets of images to be processed.
In a specific operation, the image preprocessing unit 301 is further configured to perform a deduplication operation on data of a plurality of original images. The image slicing apparatus further includes: the first quality inspection unit (not shown in the figure) is configured to, after obtaining a plurality of images to be processed with geographic coordinate information, perform quality inspection on the plurality of images to be processed according to a preset first quality inspection condition, so that the image preprocessing unit performs deduplication operation on the image data to be processed which does not meet the first quality inspection condition and/or configures geographic coordinate information operation. The image slicing apparatus further includes a second quality inspection unit (not shown in the figure), configured to, after the image grouping unit calculates geographic information corresponding to the reference levels of the images to be processed that meet the first quality inspection condition, perform quality inspection on the geographic information corresponding to the reference levels of the images to be processed according to a preset second quality inspection condition, so that the image grouping unit performs a grouping operation on the images to be processed that meet the first quality inspection condition according to the geographic information corresponding to the reference levels of the images to be processed that meet the second quality inspection condition. The image slicing apparatus further includes a third quality inspection unit (not shown in the figure) configured to perform quality inspection on each of the to-be-processed images grouped by the image grouping unit according to a preset third quality inspection condition, so that the image grouping unit performs image slicing on each of the to-be-processed images meeting the third quality inspection condition as each of the groups of to-be-processed images. The device for slicing and quality control of massive high-resolution image data further comprises a fourth quality inspection unit (not shown in the figure), which is used for randomly taking a preset number of detection points in a preset position range in the tile map of each group of images to be processed, judging whether the tile map of each group of images to be processed is abnormal according to pixel color difference values of the detection points, and repairing the abnormal tile map when the tile map is determined to be abnormal; and carrying out anomaly detection on the repaired tile map again until the repaired tile map is normal, and triggering the image synthesis unit to act.
In this embodiment, an example of an OGC standard service creation process for providing 2-meter resolution images for facilitating spatial data sharing is given in a certain organization, and 2-meter resolution image data covering the whole country includes over 27000 frames of 1:1 ten thousand standard frames of data, which is about 10 TB. Due to the huge data volume, when the traditional slicing processing method is adopted, the occupancy rates of server resources and storage resources are extremely high, the server has no response due to long-time operation, the slicing efficiency is low, and the problems of partial slicing distortion, pixel loss, poor image edge quality, blank pictures and the like in the slicing process can not be smoothly completed. The image data slicing work is divided into parts by adopting a method of partitioning and partitioning slices, checking pictures and releasing results in a centralized manner through the embodiment:
1) and making a slice level plan according to the data resolution. In order to ensure the definition of picture display and the condition that the picture has no ghost, the graph cutting level of 2 m resolution data is 0-15 layers.
2) Because the data volume is huge, the slicing efficiency is improved and the slicing work is ensured to be completed according to time in order to reduce the pressure of the server. We will group the picture data with reference to the layer 7 picture size.
3) And the cutting is respectively carried out after grouping, and the 7 th layer is taken as a reference, so that the cutting level and the manufacturing time can be greatly shortened, and the cutting work can be smoothly carried out.
4) And finishing quality control based on picture elements by each partition slice.
5) The tile map is compressed, the original png format picture is converted into the jpg format, the disk space is greatly saved on the premise of ensuring the picture quality, meanwhile, the network resources are greatly saved during service release, and the service access efficiency is improved.
6) After the implementation of the mode is completed, the original workload of 8 months is reduced to 2 months, and meanwhile, the problems of slice distortion, pixel deletion, poor image edge quality, image blank and the like are better solved in the picture element quality control process.
The present invention also provides a computer-readable storage medium storing a program including instructions for performing the above-described method.
The invention also provides a computer comprising a readable medium having stored thereon a computer program comprising instructions for carrying out the method as described above. The computer-readable storage medium and the computer have the technical effects corresponding to the method for slicing the mass high-resolution image data and controlling the quality, and are not described in detail again.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for slicing and quality control of massive high-resolution image data is characterized by comprising the following steps:
preprocessing a plurality of original images to obtain a plurality of images to be processed with geographical coordinate information;
determining the total map cutting level of each image to be processed according to the resolution of each image to be processed and the corresponding relation between each preset resolution and the total map cutting level; determining the reference level of each image to be processed according to the corresponding relation between the preset total tangent image level and the reference level;
calculating geographic information corresponding to the reference levels of the images to be processed, and grouping the images to be processed according to the geographic information corresponding to the reference levels of the images to be processed to obtain each group of images to be processed;
and respectively carrying out image slicing on the reference level of each group of images to be processed to obtain a tile map of each group of images to be processed, and synthesizing the tile map of each group of images to be processed according to the geographic coordinate information in the tile map of each group of images to be processed.
2. The method for slicing and quality controlling of mass high resolution video data according to claim 1,
the step of grouping the images to be processed according to the geographic information corresponding to the reference levels of the images to be processed to obtain each group of images to be processed comprises the following steps:
and grouping the images to be processed according to the range of the geographic information corresponding to the reference level of each image to be processed to obtain each group of images to be processed.
3. The method according to claim 2, wherein the overall cutout hierarchy of each of the to-be-processed images is determined according to the resolution of each of the to-be-processed images and a preset correspondence between each of the resolutions and the overall cutout hierarchy; and determining the reference level of each image to be processed according to the corresponding relation between the preset total cutout level and the reference level, wherein the step comprises the following steps of:
the overall cutout level of the image to be processed with the resolution of 2 m is determined to be 15 levels and the reference level is 7 th or 8 th level.
4. The method of mass high resolution video data slicing and quality control according to any one of claims 1-3, wherein prior to the step of synthesizing tile maps for each set of images to be processed according to geographic coordinate information in the tile maps for each set of images to be processed, comprising:
randomly selecting a preset number of detection points in a preset position range in the tile map of each group of images to be processed, judging whether the tile map of each group of images to be processed is abnormal according to pixel color difference values of the detection points, and repairing the abnormal tile map when the tile map is determined to be abnormal;
and carrying out anomaly detection on the repaired tile map again until the repaired tile map is normal, and then executing the step of synthesizing the tile maps of the groups of images to be processed according to the geographic coordinate information in the tile maps of the groups of images to be processed.
5. The method for slicing and quality controlling of mass high resolution video data according to claim 4,
the preprocessing operation on the plurality of original images comprises a data deduplication operation;
after the step of obtaining a plurality of images to be processed with geographical coordinate information, performing quality inspection on the plurality of images to be processed according to a preset first quality inspection condition, and continuing data deduplication operation and/or geographical coordinate information configuration operation on the images to be processed which do not meet the first quality inspection condition;
calculating geographic information corresponding to the reference levels of the images to be processed which meet the first quality inspection condition, performing quality inspection on the geographic information corresponding to the reference levels of the images to be processed according to a preset second quality inspection condition, and performing grouping operation on the images to be processed which meet the first quality inspection condition according to the geographic information corresponding to the reference levels of the images to be processed which meet the second quality inspection condition;
and according to a preset third quality inspection condition, performing quality inspection on each image to be processed after the grouping operation, and performing image slicing on each image to be processed which meets the third quality inspection condition as each group of images to be processed.
6. An apparatus for slicing and quality control of mass high-resolution image data, comprising:
the image preprocessing unit is used for preprocessing the original images to obtain a plurality of images to be processed with geographical coordinate information;
the hierarchy determining unit is used for determining the total cutting map hierarchy of each image to be processed according to the resolution of each image to be processed and the corresponding relation between each preset resolution and the total cutting map hierarchy; determining the reference level of each image to be processed according to the corresponding relation between the preset total tangent image level and the reference level;
the image grouping unit is used for calculating the geographic information corresponding to the reference level of each image to be processed and grouping the images to be processed according to the geographic information corresponding to the reference level of each image to be processed to obtain each group of images to be processed;
the image slicing unit is used for respectively carrying out image slicing on the reference level of each group of images to be processed to obtain a tile map of each group of images to be processed;
and the image synthesis unit is used for synthesizing the tile map of each group of images to be processed according to the geographic coordinate information in the tile map of each group of images to be processed.
7. The apparatus for slicing and quality controlling of mass high resolution video data according to claim 6, wherein the image preprocessing unit is further configured to perform a deduplication operation on data of a plurality of original images;
the image slicing device further comprises a first quality inspection unit, wherein the first quality inspection unit is used for performing quality inspection on a plurality of images to be processed according to a preset first quality inspection condition after the plurality of images to be processed with geographical coordinate information are obtained, so that the image preprocessing unit performs duplication removal operation on the image data to be processed which do not accord with the first quality inspection condition and/or geographical coordinate information configuration operation;
the image slicing device further comprises a second quality inspection unit, wherein the second quality inspection unit is used for performing quality inspection on the geographic information corresponding to the reference level of each image to be processed according to a preset second quality inspection condition after the image grouping unit calculates the geographic information corresponding to the reference level of each image to be processed according to the first quality inspection condition, so that the image grouping unit performs grouping operation on each image to be processed according to the first quality inspection condition according to the geographic information corresponding to the reference level of each image to be processed according to the second quality inspection condition;
the image slicing device further comprises a third quality inspection unit, which is used for performing quality inspection on each image to be processed after the image grouping unit performs grouping operation according to a preset third quality inspection condition, so that the image grouping unit performs image slicing on each image to be processed which meets the third quality inspection condition as each group of images to be processed.
8. The apparatus according to claim 6 or 7, further comprising a fourth quality inspection unit, configured to randomly select a predetermined number of detection points in a predetermined position range in a tile map of each group of images to be processed, determine whether the tile map of each group of images to be processed is abnormal according to pixel color difference values of the detection points, and repair the abnormal tile map when it is determined that the tile map is abnormal; and carrying out anomaly detection on the repaired tile map again until the repaired tile map is normal, and triggering the image synthesis unit to act.
9. A computer-readable storage medium storing a program, characterized in that the program comprises instructions for executing the method according to any one of claims 1-5.
10. A computer comprising a readable medium having a computer program stored thereon, wherein the program comprises instructions for performing the method according to any one of claims 1-5.
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