CN106296791A - A kind of efficient texture optimization method rendered towards large scene - Google Patents
A kind of efficient texture optimization method rendered towards large scene Download PDFInfo
- Publication number
- CN106296791A CN106296791A CN201610734672.4A CN201610734672A CN106296791A CN 106296791 A CN106296791 A CN 106296791A CN 201610734672 A CN201610734672 A CN 201610734672A CN 106296791 A CN106296791 A CN 106296791A
- Authority
- CN
- China
- Prior art keywords
- texture
- little
- model
- merged
- ranked
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/04—Texture mapping
Abstract
The present invention relates to geospatial information system technical field, disclose a kind of efficient texture optimization method rendered towards large scene, comprise the following steps: texture corresponding for model to be combined is merged process by (1), form corresponding texture collection；(2) texture concentrates every little texture to set up the mapping relations of the model data being associated with this little texture；(3) texture that texture is concentrated is ranked up；(4) the some little texture that texture is concentrated is merged according to the texture of sizing, form multiple large textures to sizing；(5) by step (3), the model data texture coordinate identified is exchanged with each other；(6) model often magnifying texture corresponding is merged, the model after being merged.Large-scale model is carried out data reorganization by texture mapping technology, significantly reduces the data of rendering objects, decrease the number of times submitted to GPU, effectively alleviate GPU processing pressure, improve the rendering efficiency of scene.
Description
Technical field
The present invention relates to geospatial information system technical field, particularly relate to a kind of towards large scene render efficient
Texture optimization method.
Background technology
First NVIDIA company proposes the general of GPU when on August 31st, 1999 issues GEFORCE 256 graph processing chips
Read.Why GPU is referred to as graphic process unit, and topmost reason is because it can carry out almost all and computer graphical
Relevant data operation, and these are in the patent that the past is CPU.At present, computer graphics is in unprecedented development
Period.In recent years, GPU technology is developing with amazing speed.Rendering rate just doubles for every 6 months.Performance is from 1999
Year, be doubled by 2004 10 times, namely (the 10 power ratios 2 of 2), rendered performance and be greatly promoted！Meanwhile, not only
Arithmetic speed has had and has been obviously improved, and the motility calculating quality and graphical programming is the most gradually improved.In the past, PC
Only have graphics accelerator with rendering work station, and figure can only simply be accelerated to render by graphics accelerator.And at figure
After reason device (GPU) instead of graphics accelerator, just should abandon the outdated ideas of graphics accelerator.
But three-dimensional digital city apply in, high efficiency, real-time rendering magnanimity city model data be one relatively difficult
Problem.Limited due to common computer graphic process unit performance, goes to optimize magnanimity city model data at software view
Rendering efficiency, has just become and has compared urgent problems.
Summary of the invention
The present invention is directed to the shortcoming that in prior art, hardware requirement is high, rendering efficiency is low, it is provided that a kind of towards large scene
The efficient texture optimization method rendered.
In order to solve above-mentioned technical problem, the present invention is addressed by following technical proposals.
A kind of efficient texture optimization method rendered towards large scene, comprises the steps:
(1) texture corresponding for model to be combined is merged process, form corresponding texture collection；
(2) texture concentrates every little texture to set up the mapping relations of the model data being associated with this little texture；
(3) the little texture that texture is concentrated is ranked up, including:
First by textured for institute concentration, determine that wide or high value is the little texture corresponding to maximum, and record should
Little texture；
2. the little texture 1. obtained according to step, determines width or height that its maximum of little texture is；If height the most not
Rotate；If width, then little texture is carried out half-twist counterclockwise so that it is become the height of this little texture；Then after determining
Little texture is ranked up, and, according to the mapping relations of step (2) medium and small texture, is entered by corresponding model data texture coordinate meanwhile
Line identifier；
The most remaining little texture is ranked up according to identical operation, finally realizes the sequence height according to texture of texture collection
The mode that degree successively decreases is ranked up；
(4) the some little texture that texture is concentrated is merged according to the texture of sizing, form multiple to sizing
Large texture；
(5) by step (3), the model data texture coordinate identified is exchanged with each other；
(6) model often magnifying texture corresponding is merged, the model after being merged.
Further, texture collection be multiple different texture put together formed set.
Further, in step (4), texture is according to being that 1024*1024 merges to sizing.
Due to the fact that and have employed above technical scheme that there is significant technique effect:
By efficient texture optimization technology, large-scale D Urban model is carried out data reorganization, and user is entering
When row large scene renders, the model data amount of loading significantly reduces, thus efficiently reduce GPU end model data be loaded into number of times and
Draw batch, greatly improve the rendering efficiency of large scene.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of a kind of efficient texture optimization method rendered towards large scene of the present invention；
Fig. 2 is that to share the model of texture in a kind of efficient texture optimization method rendered towards large scene of the present invention corresponding
Texture collection schematic diagram；
Fig. 3 is that the institute concentrated by texture in a kind of efficient texture optimization method rendered towards large scene of the present invention is textured
According to carrying out the schematic diagram that arranges the most from big to small；
Fig. 4 is the texture schematic diagram after merging in a kind of efficient texture optimization method rendered towards large scene of the present invention.
Detailed description of the invention
With embodiment, the present invention is described in further detail below in conjunction with the accompanying drawings.
As shown in Figures 1 to 4, a kind of efficient texture optimization method rendered towards large scene, comprise the steps:
(1) texture corresponding for model to be combined is merged process, form corresponding texture collection；Texture collection is multiple
Different texture put together formed set；
(2) texture concentrates every little texture to set up the mapping relations of the model data being associated with this little texture；
(3) the little texture that texture is concentrated is ranked up, including:
First by textured for institute concentration, determine that wide or high value is the little texture corresponding to maximum, and record should
Little texture；
2. the little texture 1. obtained according to step, determines width or height that its maximum of little texture is；If height the most not
Rotate；If width, then little texture is carried out half-twist counterclockwise so that it is become the height of this little texture；Then after determining
Little texture is ranked up, and, according to the mapping relations of step (2) medium and small texture, is entered by corresponding model data texture coordinate meanwhile
Line identifier；
The most remaining little texture is ranked up according to identical operation, finally realizes the sequence height according to texture of texture collection
The mode that degree successively decreases is ranked up；
(4) the some little texture that texture is concentrated is merged according to the texture of sizing, form multiple to sizing
Large texture；Texture is according to being that 1024*1024 merges to sizing；
(5) by step (3), the model data texture coordinate identified is exchanged with each other；
(6) model often magnifying texture corresponding is merged, the model after being merged.
After model to be combined is processed by this method by LOD, forming texture collection, the surface being simplified scenery by primary and secondary is thin
Joint reduces the geometric complexity of scene, thus improves drafting efficiency.Then the little texture in texture collection is ranked up, according to
Little texture the longest while being ranked up, and the longest little texture being wide is identified, then carries out rotating and adjust
For height, the coordinate after mark is interchangeable according to the mapping relations created, it is achieved sequence the most from big to small, finally closes
And model, so that load document diminishes, reach to improve the purpose rendered.
By making in aforementioned manners, less in terms of the firmly EMS memory occupation of system, system corresponding speed is very fast, so that
GPU can more process that the time is mutual for the user of system and other real-time application, reduces simultaneously and uses into
This, make common GPU can also carry out some more complicated operations, complete to render work.
Large-scale D Urban model is carried out data reorganization by efficient texture optimization technology by the present invention, uses
Family is when carrying out large scene and rendering, and the model data amount of loading significantly reduces, thus efficiently reduces GPU end model data and be loaded into
Number of times and drafting batch, greatly improve the rendering efficiency of large scene.
In a word, the foregoing is only presently preferred embodiments of the present invention, all equalizations made according to scope of the present invention patent
Change and modification, all should belong to the covering scope of patent of the present invention.
Claims (3)
1. the efficient texture optimization method rendered towards large scene, it is characterised in that comprise the steps:
(1) texture corresponding for model to be combined is merged process, form corresponding texture collection；
(2) texture concentrates every little texture to set up the mapping relations of the model data being associated with this little texture；
(3) the little texture that texture is concentrated is ranked up, including:
First by textured for institute concentration, determine that wide or high value is the little texture corresponding to maximum, and record this little stricture of vagina
Reason；
2. the little texture 1. obtained according to step, determines width or height that its maximum of little texture is；Do not rotate if height；
If width, then little texture is carried out half-twist counterclockwise so that it is become the height of this little texture；Then the little stricture of vagina after determining
Reason is ranked up, and, according to the mapping relations of step (2) medium and small texture, is marked by corresponding model data texture coordinate meanwhile
Know；
The most remaining little texture is ranked up according to identical operation, and the sequence finally realizing texture collection is passed according to the height of texture
The mode subtracted is ranked up；
(4) by texture concentrate some little texture merge according to the texture of sizing, formed multiple give sizing big
Texture；
(5) by step (3), the model data texture coordinate identified is exchanged with each other；
(6) model often magnifying texture corresponding is merged, the model after being merged.
A kind of efficient texture optimization method rendered towards large scene the most according to claim 1, it is characterised in that: texture
Collect the set of formation of putting together for multiple different little textures.
A kind of efficient texture optimization method rendered towards large scene the most according to claim 1, it is characterised in that: step
(4), in, texture is according to being that 1024*1024 merges to sizing.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610734672.4A CN106296791A (en) | 2016-08-25 | 2016-08-25 | A kind of efficient texture optimization method rendered towards large scene |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610734672.4A CN106296791A (en) | 2016-08-25 | 2016-08-25 | A kind of efficient texture optimization method rendered towards large scene |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106296791A true CN106296791A (en) | 2017-01-04 |
Family
ID=57676649
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610734672.4A Pending CN106296791A (en) | 2016-08-25 | 2016-08-25 | A kind of efficient texture optimization method rendered towards large scene |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106296791A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107480305A (en) * | 2017-09-18 | 2017-12-15 | 浙江科澜信息技术有限公司 | A kind of texture information loading method and system |
| CN107578456A (en) * | 2017-09-14 | 2018-01-12 | 奇酷互联网络科技（深圳）有限公司 | Processing method, equipment, mobile terminal and the computer-readable storage medium of texture |
| CN107610197A (en) * | 2017-09-18 | 2018-01-19 | 浙江科澜信息技术有限公司 | A kind of texture merging method and system |
| CN108629826A (en) * | 2018-05-15 | 2018-10-09 | 天津流形科技有限责任公司 | A kind of texture mapping method, device, computer equipment and medium |
| CN108733441A (en) * | 2018-04-11 | 2018-11-02 | 中国电力科学研究院有限公司 | A kind of rendering method for visualizing and system suitable for large scale electric network symbolic device |
| CN108965975A (en) * | 2017-05-24 | 2018-12-07 | 阿里巴巴集团控股有限公司 | A kind of method for drafting and device |
| CN108961382A (en) * | 2018-07-11 | 2018-12-07 | 腾讯科技（深圳）有限公司 | A kind of image rendering method, device and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102663801A (en) * | 2012-04-19 | 2012-09-12 | 北京天下图数据技术有限公司 | Method for improving three-dimensional model rendering performance |
| CN105023234A (en) * | 2015-06-29 | 2015-11-04 | 嘉兴慧康智能科技有限公司 | Figure acceleration method based on storage optimization of embedded system |
-
2016
- 2016-08-25 CN CN201610734672.4A patent/CN106296791A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102663801A (en) * | 2012-04-19 | 2012-09-12 | 北京天下图数据技术有限公司 | Method for improving three-dimensional model rendering performance |
| CN105023234A (en) * | 2015-06-29 | 2015-11-04 | 嘉兴慧康智能科技有限公司 | Figure acceleration method based on storage optimization of embedded system |
Non-Patent Citations (1)
| Title |
|---|
| 孟勇飞: "三维地理要素模型简化方法研究", 《中国优秀硕士学位论文全文数据库基础科学辑》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108965975A (en) * | 2017-05-24 | 2018-12-07 | 阿里巴巴集团控股有限公司 | A kind of method for drafting and device |
| CN108965975B (en) * | 2017-05-24 | 2021-03-23 | 阿里巴巴集团控股有限公司 | Drawing method and device |
| CN107578456A (en) * | 2017-09-14 | 2018-01-12 | 奇酷互联网络科技（深圳）有限公司 | Processing method, equipment, mobile terminal and the computer-readable storage medium of texture |
| CN107480305A (en) * | 2017-09-18 | 2017-12-15 | 浙江科澜信息技术有限公司 | A kind of texture information loading method and system |
| CN107610197A (en) * | 2017-09-18 | 2018-01-19 | 浙江科澜信息技术有限公司 | A kind of texture merging method and system |
| CN107480305B (en) * | 2017-09-18 | 2020-08-11 | 浙江科澜信息技术有限公司 | Texture information loading method and system |
| CN108733441A (en) * | 2018-04-11 | 2018-11-02 | 中国电力科学研究院有限公司 | A kind of rendering method for visualizing and system suitable for large scale electric network symbolic device |
| CN108629826A (en) * | 2018-05-15 | 2018-10-09 | 天津流形科技有限责任公司 | A kind of texture mapping method, device, computer equipment and medium |
| CN108961382A (en) * | 2018-07-11 | 2018-12-07 | 腾讯科技（深圳）有限公司 | A kind of image rendering method, device and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106296791A (en) | A kind of efficient texture optimization method rendered towards large scene | |
| WO2021174659A1 (en) | Webgl-based progressive real-time rendering method for editable large scene | |
| CN107193911B (en) | BIM model-based three-dimensional visualization engine and WEB application program calling method | |
| CN102096897B (en) | Realization of tile cache strategy in graphics processing unit (GPU) based on tile based rendering | |
| CN106570922A (en) | Method for improving three-dimensional model rendering performance | |
| CN106447768B (en) | Method suitable for parallel drawing of three-dimensional model in three-dimensional scene | |
| CN114253724B (en) | BIM model rendering method and system | |
| CN106023297A (en) | Texture dynamic organization method for fine three-dimensional model | |
| CN104267940A (en) | Quick map tile generation method based on CPU+GPU | |
| JP2003271984A (en) | Rendering system, rendering method and its recording medium | |
| CN105957149A (en) | Urban three-dimensional model data preprocessing method suitable for high-efficiency rendering | |
| CN106971417A (en) | A kind of method and system for showing three-dimensional scatter diagram in a browser | |
| CN101394489B (en) | Subtitle rendering efficiency bottle neck automatically positioning method based on template and parameter step length | |
| CN112017254A (en) | Hybrid ray tracing drawing method and system | |
| CN100585636C (en) | Method for drafting pelage-shaped pattern in profile region with accelerative GPU | |
| CN106910239A (en) | A kind of soft shadowses method for drafting based on echo | |
| CN111258554B (en) | Pipeline production flow virtual reality development system | |
| CN111046214B (en) | Method for dynamically processing model | |
| CN101493941B (en) | Graph cuts three-dimensional image segmentation method based on GPU hardware acceleration | |
| CN100476880C (en) | Method and system for producing volume shade | |
| CN108830924B (en) | Scene model display method and terminal | |
| CN109509234B (en) | Urban building group high-definition grid map vectorization-based method | |
| CN109712211B (en) | Efficient body shadow generation method based on OSG | |
| CN111814679A (en) | FPGA-based realization algorithm for voxel-encoder and VFE of voxel 3D network | |
| CN108257075A (en) | A kind of dereference and assemble method of vertical array order |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170104 |