CN102004750A - Non-redundant massive terrain data organizing and reading method - Google Patents
Non-redundant massive terrain data organizing and reading method Download PDFInfo
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Abstract
The invention relates to a non-redundant massive terrain data organizing and reading method, which is characterized by comprising the following steps of: firstly, performing uniform block division on original terrain data; secondly, constructing a file RowFile and a file ColFile to store vertexes of shared sides between terrain blocks; and finally, constructing a terrain sub-block file to store the inner vertexes of the blocks. A redundant area of the terrain sub-block is singly stored, and different terrain sub-blocks share the redundant area. Meanwhile, the method eliminates data redundancy, well solves the problem of too much waste of storage space, and is a method suitable for organizing and storing massive terrain data.
Description
Technical field
The present invention relates to a kind of tissue and read method of data, belong to the information data field of storage, be specifically related to a kind of at break-even method for organizing of graphic data and read method on a large scale.
Background technology
Along with " proposition of digital earth notion, and the development of the technology of taking photo by plane, the obtainable initial landform data scale in terrain visualization field increases gradually, and pending terrain data scale has reached the TB rank.So therefore googol must be stored on the external memory according to can not all being written into internal memory, is written into partial data when need waiting again and enters internal memory participation drafting.Out-of-core technology commonly used that Here it is.
Most importantly in the Out-of-core technology exactly the initial landform data are reasonably divided and are stored on the external memory.The large-scale terrain data organization method of main flow was divided into for two steps both at home and abroad at present:
1, earlier initial landform is divided into the sub-piece of the less landform of plurality of scales;
2, the more sub-piece of landform is carried out the multiresolution tissue, the multiresolution terrain data of organizing is stored on the external memory.
The first, the initial landform division methods mainly is to use even method of partition, is about to initial landform and is divided into the identical sub-piece of size.For example people such as Zhao You soldier is equally divided into 128 * 64 fritters with 4097 * 2049 landform by rectangular node, every block size is 33 * 33 (Zhao Youbing, Shi Jiaoying, Zhou Ji etc., a kind of fast roaming algorithm of large-scale terrain. computer-aided design (CAD) and graphics journal, 2002,14 (7): 624-628.).This method is simple and effective to be divided into the identical sub-piece of size with megarelief, and sub-piece is as the base unit of data dispatch.
Yet general terrain block division methods inevitably can produce the summit redundancy in terrain block edge, as shown in Figure 1.
The second, the antithetical phrase piece carries out multiresolution and organizes and then mainly use pyramid model, promptly by certain method landform is split into different resolution levels, and terrain data is stored by level, and the method for the most frequently used subdivision level is to use the quaternary tree subdivision.For example wearing people such as morning twilight has just used the tile pyramid to organize landform multiresolution data (to wear morning twilight, Zhang Yongsheng, Deng Xueqing. a kind of massive terrains data organization and management method that is used for real-time visual. system emulation journal, 2005,17 (2): 406-409.).Though use pyramid model to can be good at the sub-piece of landform is split into the hierarchical data of different resolution, this method ubiquity data redundancy is excessive, exchange the drawback in processing time for sacrifice external memory storage space.
Wherein the patent No. 200710051621.2, the Chinese patent of patent name " a kind of terrain data storage means " based on object storage, be terrain data and attribute data thereof to be organized into the landform storage object be stored in based in the object storage system, the landform storage object of adjacent or close terrain data tile is distributed in based on the difference in the object storage system based on object storage equipment.Because this scheme is by the storage of pyramid layered mode, interlayer still can produce redundancy.
Therefore redundancy becomes a kind of technological deficiency, and is especially more outstanding when the storage large-scale data, belongs to a kind of drawback that influences data storage, so need to solve this defective.
Summary of the invention
Technical matters to be solved by this invention provides a kind of break-even large-scale terrain data organization method and read method, this method produces redundant zone to the sub-piece of landform and stores separately, the sub-piece of different terrain is shared redundant area, at occurring redundant defective in the prior art during data storage, solve the excessive problem of waste of storage space.
Technical matters proposed by the invention is to solve like this: construct a kind of break-even large-scale terrain data organization method, it is characterized in that:
(1), earlier the initial landform data is carried out even piecemeal;
(2), make up the summit that file RowFile, file ColFile store the sub-piece common edge of landform;
(3), the internal vertex data construct file of the sub-piece of each landform is stored separately.
According to a kind of break-even large-scale terrain data organization method of the present invention, it is characterized in that: file RowFile is the summit of storing common edge by row.
According to a kind of break-even large-scale terrain data organization method of the present invention, it is characterized in that: file ColFile is the summit of storing common edge by row.
According to a kind of break-even large-scale terrain data organization method of the present invention, it is characterized in that: piecemeal in the following manner: wherein the resolution of original megarelief is M*N, and wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein 1＜k＜min (m, n); The piecemeal number is the P*Q piece, and wherein P*Q is satisfied is ((M-1)/(K-1)) * ((N-1)/(K-1)).
According to above-described a kind of break-even large-scale terrain data organization method, it is characterized in that: for the original megarelief of M*N, the average mark block size is K*K, and the piecemeal number is the P*Q piece,
Wherein file RowFlie has deposited Q+1 row bound data altogether; Its summit coding rule is: number from sequence number 0 on the summit; Summit from the 0th to M-1 is the 0th row bound, and the summit from M to 2M-1 is the 1st row bound, by that analogy, so the capable border of n is the summit (0≤n≤Q) from n*M to (n+1) * M-1.In the row bound file, the row bound of the sub-piece of this landform is formed on K continuous summit of first row bound point beginning of the sub-piece of depositing from it of certain landform.
Wherein file ColFile has deposited P+1 row data boundary altogether, and its summit coding rule is: number from sequence number 0 on the summit; From the summit of the 0th to Q* (K-2)-1 is landform the 0th row border, and the summit from Q* (K-2) to 2Q* (K-2)-1 is the 1st to be listed as the border, by that analogy, so n row border is the summit (0≤n≤P) from n*Q*K* (K-2) to (n+1) * Q*K* (K-2)-1.In row border file, the row border of the sub-piece of this landform is formed on K-2 the continuous summit that first row frontier point of the sub-piece of depositing from it of certain landform begins.
The present invention also comprises a kind of read method of break-even graphic data on a large scale, it is characterized in that: the beginning resolution of megarelief is M*N, and wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein 1＜k≤min (m, n); The piecemeal number is the P*Q piece, and wherein P*Q is satisfied is ((M-1)/(K-1)) * ((N-1)/(K-1)); For the X piece, it is capable that it is in X/P, the X%P row, and wherein X/P is for rounding division downwards, and X%P is for getting surplus operation;
Its initial vertex, coboundary being numbered in RowFile (X/P) * M+ (X%P) * (K-1); Lower boundary initial vertex being numbered in RowFile (X/P+1) * M+ (X%P) * (K-1); Left margin initial vertex being numbered in ColFile (X%P) * Q* (K-2)+(X/P) * (K-2); Right margin initial vertex being numbered in ColFile (X%P+1) * Q* (K-2)+(X/P) * (K-2).
Beneficial effect of the present invention is: this patent is stored the common edge summit of the sub-piece of landform separately, by the sub-blocks of data of form reduction landform with sub-piece of landform and the combination of common edge summit.Relation between sub-piece of landform and the common edge is mapped by the numbering and the numbering of the summit in the common edge file of the sub-piece of landform, searches very convenient.Therefore these method storage data do not have data redundancy fully based on the summit, have overcome the defective about redundancy of the prior art.When differentiating the terrain block data when drawing more, can in internal memory, make up an index structure, write down the summit that each resolution level is comprised, according to index structure the summit of corresponding resolution is written into internal memory and can finishes the multiresolution terrain rendering.So the method for use this patent has not only been eliminated the redundancy on the external memory storage data, and still can realize the requirement that multiresolution is drawn, so this patent has successfully provided a kind of comparatively ideal large-scale terrain data organization and read method.
Description of drawings
Fig. 1 is the structural representation of data redundancy storage in the prior art
Fig. 2 is the synoptic diagram to the piecemeal of original full resolution landform
Fig. 3 is the synoptic diagram of the break-even data store organisation of the present invention
Fig. 4 is a kind of sampled point synoptic diagram of the terrain data about 5*5
The synoptic diagram of the data of the 0th layer of storage when Fig. 4 a is data use triangle fan mode
The synoptic diagram of the data of the 1st layer of storage when Fig. 4 b is data use triangle fan mode
The synoptic diagram of the data of the 0th layer of storage when Fig. 5 a is data use triangle mode
The synoptic diagram of the data of the 1st layer of storage when Fig. 5 b is data use triangle fan mode.
Embodiment
The present invention is described further below in conjunction with accompanying drawing.
Fig. 1 is a kind of structural representation of data storage of prior art, and what the sub-block edge of wherein adjacent landform place represented is to produce redundant summit.
As shown in Figure 2, being is the synoptic diagram of the landform piecemeal of 17*17 to original full resolution.At first landform is carried out even piecemeal in the method, initial landform resolution is M*N (M=N=24+1), and the branch block size is K*K (K=22+1), and 1＜K＜min (m, n); The piecemeal number is P*Q (P=(M-1)/(K-1), Q=(N-1)/(K-1)).
Wherein the sub-piece of each landform is stored with file respectively, owing to comprise identical summit on the sub-piece common edge of per two landform, for fear of redundant storage, in the sub-block file of landform, do not store the summit on the common edge, store these public vertex and make up special file.Make up two files at this, file RowFile is the summit of storing common edge by row, and file ColFile is the summit of storing common edge by row.
Be illustrated in figure 3 as break-even data storage method synoptic diagram, row bound is stored in the file RowFile, and the row border is stored in the file ColFile.The public vertex on ranks border only in RowFile storage once, repeated storage no longer in the row border; And the file of storing the sub-piece of each landform only stores this piece internal vertex and gets final product, and the internal vertex among this Fig. 3 is 3*3 summit.
Therefore this piece landform comprises 16 sub-block files of landform and two landform border files altogether by 18 file storage.As long as know the numbering of current sub-block, just can therefore use this storage means can on external memory, realize complete no datat redundancy by merging the data of sub-block file of landform and landform border file reduction current sub-block.
Below the data read method is set forth:
The resolution of supposing original megarelief is M*N, and wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein 1＜k＜min (m, n); The piecemeal number is the P*Q piece, and wherein P*Q is satisfied is ((M-1)/(K-1)) * ((N-1)/(K-1));
0 to M-1 the summit of wherein depositing among the file RowFlie is the 0th row bound, and the summit from M to 2M-1 is the 1st row bound, by that analogy.The 0th row bound is the 0th coboundary to the P-1 piece of the sub-piece of landform; The 1st row bound is the 0th lower boundary to the P-1 piece, and the P piece is to the coboundary of 2P-1 piece.If know the sub-block number of landform, and it is in several row of several row, just can calculate its coboundary and the lower boundary position in RowFile respectively, therefore can take out data.
In like manner, the summit of 0 to Q* (K-2)-1 of depositing among the file ColFile is landform the 0th row border, and the summit from Q* (K-2) to 2Q* (K-2)-1 is the 1st row border, by that analogy.As long as know the sub-block number of landform, and it is in several row of several row, just can calculate its left margin and the right margin position in ColFile respectively, therefore can take out data.
Given general border data read formula: for original resolution is the megarelief of M*N, and wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein 1＜k＜min (m, n); The piecemeal number is the P*Q piece, and it is ((M-1)/(K-1)) * ((N-1)/(K-1)) that P*Q satisfies; For the X piece, it is capable that it is in X/P, the X%P row, and wherein X/P is for rounding division downwards, and X%P is for getting surplus operation.Therefore, its initial vertex, coboundary being numbered in RowFile (X/P) * M+ (X%P) * (K-1); Lower boundary initial vertex being numbered in RowFile (X/P+1) * M+ (X%P) * (K-1); Left margin initial vertex being numbered in ColFile (X%P) * Q* (K-2)+(X/P) * (K-2); Right margin initial vertex being numbered in ColFile (X%P+1) * Q* (K-2)+(X/P) * (K-2).
Illustrate: the terrain data of 17*17 as shown in Figure 3, M=N=17, K=5, P=Q=4;
The data of the 6th of landform if desired, because block count is 4*4, then the 6th is positioned at the first row secondary series.
Therefore, its initial vertex, coboundary being numbered in RowFile (6/4) * 17+ (6%4) * (5-1)=25;
Its lower boundary initial vertex being numbered in RowFile (6/4+1) * 17+ (6%4) * (5-1)=42;
Its left margin initial vertex being numbered in ColFile (6%4) * 4* (5-2)+(6/4) * (5-2)=27;
Its right margin initial vertex being numbered in ColFile (6%4+1) * 4* (5-2)+(6/4) * (5-2)=39.
So when being written into a certain terrain data, just from RowFile and ColFile, numbering and get four borders, from the storage file of current block, get internal data then by the summit.
With the data organization method of the present invention and the patent No. 200710051621.2, the Chinese patent of patent name " a kind of terrain data storage means based on object storage " does one relatively below:
The scheme of the patent No. 200710051621.2 can produce redundant by the storage of pyramid layered mode between level.
Redundant concrete reason is that the sampled point of 5*5 constitutes terrain data as shown in Figure 4.
Scheme when the use patent No. 200710051621.2:
1., use the triangle fan mode to play up, file layout is shown in Fig. 4 a and Fig. 4 b, Fig. 4 a is the synoptic diagram of the data of the 0th layer storage of data when using the triangle fan mode;
The data that this shows the 0th layer of storage are: 0,4,12,20,24
The synoptic diagram of the data of the 1st layer of storage when Fig. 4 b is data use triangle fan mode;
The data that this shows the 1st layer of storage are: 0,2,3,6,8,10,12,13,16,18,20,22,24
The data of two hierarchical redundancies; 0,4,12,20,24
2., use the triangle mode to play up, file layout shown in Fig. 5 a and Fig. 5 b,
The synoptic diagram of the data of the 0th layer of storage when Fig. 5 a is data use triangle mode;
The data that this shows the 0th layer of storage are: 0,4,20,24
The synoptic diagram of the data of the 1st layer of storage when Fig. 5 b is data use triangle mode;
The data that this shows the 1st layer of storage are: 0,2,3,10,12,14,20,22,24
The data of two hierarchical redundancies: 0,4,20,24;
Use method of the present invention to organize the storage mode of landform as follows:
The data of RowFile storage:
0，1，2，3，4，20，21，22，23，24
The data of ColFile storage:
5，10，15，9，14，19
The data of terrain block file storage:
6，7，8，11，12，13，16，17，18
Play up when using the triangle fan mode:
When representing the data of the 0th layer of resolution:
From RowFile, get sampled point 0,4,20,24;
From the terrain block file, get sampled point 12;
When representing the data of the 1st layer of resolution:
From RowFile, get sampled point 0,2,4,20,22,24;
From ColFile, get sampled point 10,14;
From the terrain block file, get sampled point 6,8,12,16,18;
Play up when using the triangle mode:
When representing the data of the 0th layer of resolution:
From RowFile, get sampled point 0,4,20,24;
When representing the data of the 1st layer of resolution:
From RowFile, get sampled point 0,2,4,20,22,24;
From ColFile, get sampled point 10,14;
From the terrain block file, get sampled point 12;
Therefore, using method of the present invention is complete no datat redundancy on data storage.Therefore solved redundant problem.If use the memory model of this patent, when making up the multiresolution level, can make up a core resident index structure, this index structure indicates each resolution level to need which summit to constitute, and therefore can construct the multiresolution level very easily.This index structure only comprises the call number on summit in addition, and memory cost is very little, and data read is also very convenient.
Claims (7)
1. a break-even large-scale terrain data organization method is characterized in that, carries out according to following manner:
(1), earlier the initial landform data is carried out even piecemeal;
(2), make up the summit of the sub-piece common edge of file RowFile, file ColFile storage landform;
(3), the internal vertex data construct file of the sub-piece of each landform is stored separately.
2. according to the said a kind of break-even large-scale terrain data organization method of claim 1, it is characterized in that: constructed file RowFile is used for the summit of storage line, promptly stores the summit of common edge by row.
3. according to the said a kind of break-even large-scale terrain data organization method of claim 1, it is characterized in that: constructed file ColFile is used for the summit of memory row, promptly stores the summit of common edge by row.
4. according to the said a kind of break-even large-scale terrain data organization method of claim 1, it is characterized in that described partitioned mode is: wherein the resolution of original megarelief is M*N, and wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein 1＜k≤min (m, n); The piecemeal number is the P*Q piece, and wherein P*Q is satisfied is ((M-1)/(K-1)) * ((N-1)/(K-1)).
5. according to the said a kind of break-even large-scale terrain data organization method of claim 1, it is characterized in that: the resolution of original megarelief is M*N, and wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein 1＜k≤min (m, n); The piecemeal number is the P*Q piece, and wherein P*Q is satisfied is ((M-1)/(K-1)) * ((N-1)/(K-1));
Wherein file RowFlie has deposited Q+1 row bound data altogether;
Wherein file ColFile has deposited P+1 row data boundary altogether.
6. according to the said a kind of break-even large-scale terrain data organization method of claim 1, it is characterized in that: the resolution of original megarelief is M*N, and wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein k≤min (m, n); The piecemeal number is the P*Q piece, and wherein P*Q is satisfied is ((M-1)/(K-1)) * ((N-1)/(K-1));
Wherein the summit of file RowFlie is numbered: number from sequence number 0 on the summit; Summit from the 0th to M-1 is the 0th row bound, and the summit from M to 2M-1 is the 1st row bound, by that analogy, so the capable border of n is the summit (0≤n≤Q) from n*M to (n+1) * M-1.In the row bound file, first summit of row bound of the sub-piece of depositing from it of certain landform, then the row bound of the sub-piece of this landform is formed on K continuous summit.
Wherein the summit of file ColFile is numbered: number from sequence number 0 on the summit; From the summit of the 0th to Q* (K-2)-1 is landform the 0th row border, and the summit from Q* (K-2) to 2Q* (K-2)-1 is the 1st to be listed as the border, by that analogy, so n row border is the summit (0≤n≤P) from n*Q*K* (K-2) to (n+1) * Q*K* (K-2)-1.In row border file, first summit, row border of the sub-piece of depositing from it of certain landform, then the row border of the sub-piece of this landform is formed on K-2 continuous summit.
7. the read method of a break-even graphic data on a large scale, it is characterized in that: the resolution of original megarelief is M*N, wherein M*N satisfies (2m+1) * (2n+1); The resolution of the sub-piece of landform of average piecemeal is K*K, i.e. (2k+1) * (2k+1), wherein 1＜k≤min (m, n); The piecemeal number is the P*Q piece, and wherein P*Q is satisfied is ((M-1)/(K-1)) * ((N-1)/(K-1)); For the X piece, it is capable that it is in X/P, the X%P row, and wherein X/P is for rounding division downwards, and X%P is for getting surplus operation;
Its initial vertex, coboundary being numbered in RowFile (X/P) * M+ (X%P) * (K-1);
Lower boundary initial vertex being numbered in RowFile (X/P+1) * M+ (X%P) * (K-1);
Left margin initial vertex being numbered in ColFile (X%P) * Q* (K-2)+(X/P) * (K-2);
Right margin initial vertex being numbered in ColFile (X%P+1) * Q* (K-2)+(X/P) * (K-2).
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