NL2033087A - Lake water quality scalar field volume rendering generation method and storage medium thereof - Google Patents

Lake water quality scalar field volume rendering generation method and storage medium thereof Download PDF

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NL2033087A
NL2033087A NL2033087A NL2033087A NL2033087A NL 2033087 A NL2033087 A NL 2033087A NL 2033087 A NL2033087 A NL 2033087A NL 2033087 A NL2033087 A NL 2033087A NL 2033087 A NL2033087 A NL 2033087A
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color
voxel
water quality
scalar field
value
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NL2033087A
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NL2033087B1 (en
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yuan Alan
Zhao Xizhi
Liao Zhenliang
He Wangjun
Liu Jiping
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Chinese Acad Surveying & Mapping
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/08—Volume rendering
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/005—General purpose rendering architectures
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/50—Lighting effects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06T17/10—Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06T19/20—Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
    • G06T2219/20—Indexing scheme for editing of 3D models
    • G06T2219/2012—Colour editing, changing, or manipulating; Use of colour codes

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Abstract

A lake water quality scalar field volume rendering generation method, and storage medium. thereof. In this method, the volume rendering technology is introduced into the visual analysis of a lake water quality model; a “from. surface to interior” water quality scalar field volume model is constructed; a transfer function is generated based on a frequency distribution histogram; and finally, the light synthesis and image fusion are performed. In this way, the traditional water environment water quality surface visualization is improved into volume rendering expression capable of being sectioned in any layer and any face. It has the advantages of making the color expression of voxel rendering in the same interval finer, improving the accuracy of volume rendering, being capable of expressing local subtle distribution differences and characteristics, and effectively improving the ability of stereo perspective analysis of internal characteristics of water quality models.

Description

LAKE WATER QUALITY SCALAR FIELD VOLUME RENDERING GENERATION METHOD
AND STORAGE MEDIUM THEREOF
TECHNICAL FIELD
The present invention relates to computer graphics and envi- ronmental science, and more particularly, to a lake water quality scalar field volume rendering generation method and a storage me- dium therefor, which mainly uses a computer volume rendering meth- od to analyze the distribution and diffusion law of water pollu- tion substances.
BACKGROUND ART
The study of lake water quality is of great significance to the treatment of lake water pollution. The three-dimensional visu- alization of the lake water quality model is conducive to the study of the distribution and variation of pollutants in the wa- ter. At present, the mainstream method of 3D visualization of lake water quality model is the surface rendering method, including MC (Marching Cubes), Surface Tracking, and other methods, but the problem of line-of-sight occlusion is common. The volume rendering method directly projects voxels to the display plane, which is used to describe objects with specific shapes, and flexibly dis- play the internal structure of objects, with the advantage of data perspective. In order to apply volume rendering technology to the lake water quality research, the transfer function should be de- signed according to the lake water quality model and pollutant characteristics.
Some scholars have studied the volume rendering methods of ocean temperature field and salinity field. The mainstream method uses artificial experience to set the piecewise transfer function and needs to adjust the parameters repeatedly to optimize the voxel coloring method. In most cases, it will encounter the phe- nomenon of "spreading the pie" in the area where the values are concentrated, causing voxels in the same interval to be rendered with the same color, which cannot express local subtle distribu-
tion differences and characteristics. Due to the large scale of atmospheric and marine research, the distribution of macro-scale will not be highlighted. However, the research scale of lake water quality volume rendering is small, and the spatial distribution difference is not significant, especially in shallow lakes. There- fore, it is difficult to visually express the subtle differences and characteristics of the spatial distribution of lake water quality.
SUMMARY
The object of the present invention is to propose a lake wa- ter quality scalar field volume rendering generation method and a storage medium therefor. The volume rendering technology is intro- duced into the visual analysis of the lake water quality model, and a “from surface to interior” water quality scalar field volume model is constructed. The traditional water environment water quality surface visualization is improved into volume rendering expression capable of being sectioned in any layer and any face, which is conducive to studying the status and changes of lake wa- ter quality distribution. It is of great significance to the man- agement and prevention of water pollution.
In order to achieve this object, the present invention adopts the following technical solution:
A lake water quality scalar field volume rendering generation method, characterized by comprising the following steps: step S110: voxel model construction constructing, by linear spatial interpolation, a three- dimensional voxel texture of lake water quality scalar field based on lake water quality scalar field data; step S120: generating transfer function based on frequency distribution histogram counting the distribution of the voxels according to normal- ized values in the three-dimensional voxel model, plotting a fre- quency distribution histogram of water quality concentration sca- lar field data, and designing a color mapping transfer function according to the frequency distribution histogram of the water quality concentration scalar field data; and step $5130: light synthesis and image fusion calculating the color and opacity of each voxel based on the color mapping transfer function, and realizing light synthesis and image fusion according to a ray casting algorithm.
Optionally, step S110 of voxel model construction specifical- ly comprises: substep S111: numeric normalization using the grid scalar field data of algae biomass of lake, they are normalized using the formula (1), wherein the normaliza- tion is to perform min-max normalization to values in the range of [0,1], each value corresponding to a pixel value and corresponding to a three-dimensional grid to form a voxel, det(l, m,n) = vem (1) where (1, m, n) is a coordinate of a voxel point in three- dimensional space; V (1, m, n) is an attribute value of a voxel at (1, m, n); HU is a mean value of the grid scalar field data set of algae biomass of lake; ò is a standard deviation of the grid sca- lar field data set of algae biomass of lake; det (1, m, n) is a normalized attribute value of the voxel at (1, m, n), and the val- ue interval is [0, 1]; substep S112: spatial interpolation resampling the normalized data by linear spatial interpola- tion, to change the discrete data field into a continuous data field, so as to improve the quality of scalar field data; substep S113: voxel texture construction constructing a three-dimensional voxel texture of an irregu- lar region; for an irregular region containing blank voxels, screening out and identifying the voxels with null values and in- valid values; filtering out blank voxels according to the identi- fication in the process of volume rendering, and preparing a valid voxel model for volume rendering of the irregular region.
Optionally, Step S120 of generating transfer function based on the frequency distribution histogram specifically comprises: substep S121: color band initialization dividing the normalized scalar field from small to large equally to determine the number N of division intervals; at the same time, initially setting corresponding color bands, wherein each interval corresponds to one color band (C;—-C;, C;—C5.C;—Cis: ..
Cy=Cy:1), one color band is formed between color Ci and color Cj, and all color bands between color Ci and color Cy constitute a global color band; substep S122: frequency distribution histogram construction counting the number of voxels in each interval as the inter- val frequency (Fi, F..F;...Fy), wherein F; is the frequency of a voxel in the i-th interval; calculating the ratio of the interval frequency value to the total number of voxels as the interval voxel ratio, taking N value intervals of normalized scalar field data as abscissa, and taking the number of voxels in the corre- sponding interval as ordinate to construct the frequency distribu- tion histogram of water quality concentration scalar field data; substep S123: pixel ratio setting taking interval voxel proportion as the proportion of pixels occupying the whole mapping texture, so that the color band in the concentrated distribution area occupies more pixels, ensuring more color grading levels; substep S124: color band dividing setting the hierarchical level of the global color band as P, namely, dividing the global color band into P pixels, and calcu- lating the number of pixels of each color band according to the proportion of pixels occupied in each color band interval; step S125: frequency color band cycle generation circularly generating each color band, which is generated by linear interpolation according to a start color C; and an ending color Ci ; i, wherein the end color of the previous color band is the start color of the next color band. step S126: color mapping transfer function generation according to substeps S121-5125, automatically generating the transfer function for finally synthesizing into the global color band, a color mapping transfer function formula based on numerical frequency statistics, the color mapping transfer function formula comprising formula (3), a color mapping transfer function formula, and formula (4), a calculation formula for an opacity value. i = Int(det* N) , i € [0,N — 1] (2)
(Rummy Cm Bam) = nt «(Nx det —1) + (3) i/%5 Fi
Amn) = det(l, m,n) (4) where 1 represents the i-th interval, namely, the i-th color band, the value interval is [0, N-1], and N represents the total 5 number of intervals; C; is the start color of the i-th color band;
Ci: ; is the ending color of the i-th color band; P represents the total number of pixels of all color bands and is also an adjust- ment constant; F; is the frequency of the voxel in the i-th inter- val; (Ri, wm, mir Gi, m, ms Bil, m, ny) is the color value mapped by the attribute value of the voxel at (1, m, n); and An, m 2; 1s the opacity value mapped by the attribute value of the voxel at (1, m, n), which is proportional to the normalized attribute value.
Optionally, step S130 of light synthesis and image fusion specifically comprises: substep 5131: voxels color and transparency calculation calculating the color and opacity values of each voxel using the transfer functions generated by the formulas (3) and (4) to obtain the color and opacity corresponding to the voxel value; substep 5132: lighting rendering and coloring using ray casting algorithm to perform lighting rendering and coloring on the voxel so as to obtain the color value and opacity of the sampling point; substep $133: light synthesis and image fusion accumulating the color value and opacity of each sampling point in the order from front to back along the direction of the casting ray according to the color value and opacity of the sam- pling point on the casting ray in the ray casting algorithm, to obtain the color value and opacity of the screen pixel point, and complete the light synthesis and image fusion.
The present invention further discloses a storage medium storing computer-executable instructions, characterized in that, the computer-executable instructions, when executed by a pro- cessor, perform the lake water quality scalar field volume render- ing generation method above.
In the present invention, by considering the frequency dis- tribution of a three-dimensional voxel model, i.e. dividing the voxel values into equal parts, calculating a numerical interval of each equal part, counting the number of voxels whose values are located in the interval according to intervals, plotting a fre- quency distribution histogram according to the interval frequency, and generating a transfer function based on the frequency distri- bution histogram. It has the advantages of making the color ex- pression of voxel rendering in the same interval finer, improving the accuracy of volume rendering, being capable of expressing lo- cal subtle distribution differences and characteristics, and ef- fectively improving the ability of stereo perspective analysis of internal characteristics of water quality models.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a flow chart of a lake water quality scalar field volume rendering generation method according to a specific embodi- ment of the present invention;
FIG. 2 is a constructed voxel model of a lake water quality scalar field volume rendering generation method according to a specific embodiment of the present invention;
FIG. 3 is a schematic diagram of color band generation for a lake water quality scalar field volume rendering generation method according to an embodiment of the present invention;
FIG. 4 is a resulting frequency distribution histogram of a lake water quality scalar field volume rendering generation method according to a specific embodiment of the present invention;
FIG. 5 is a schematic diagram of a volume rendering perspec- tive analysis of a lake water quality scalar field volume render- ing generation method according to a specific embodiment of the present invention; and
FIG. 6 is a graph of lake water quality volume rendering changes for a lake water quality scalar field volume rendering generation method according to a specific embodiment of the pre- sent invention.
DETAILED DESCRIPTION OF THE EMBODIMENTS
The present invention will now be described in further detail with reference to the accompanying drawings and examples. It should be understood that the particular embodiments described herein are illustrative only and are not restrictive. It should also be noted that, for ease of description, only some, but not all, of the structures associated with the present invention are shown in the drawings.
The present invention mainly comprises: considering the fre- quency distribution of lake water quality scalar field fully, con- structing the voxel model based on the grid scalar field data of algae biomass of lake, obtaining the frequency distribution histo- gram from counting the frequency distribution, generating the transfer function based on the frequency distribution, realizing the light synthesis and image fusion according to the ray tracing algorithm, reasonably mapping the voxel scalar value into color and transparency, and finally outputting the lake water quality volume rendering model. The present invention realizes the spatial distribution difference refinement expression of lake water quali- ty, and effectively improves the stereo perspective analysis capa- bility of internal characteristics of the water quality model.
Referring to FIG. 1, a flow chart of a lake water quality scalar field volume rendering generation method according to a specific embodiment of the present invention is shown, comprising the following steps: step S110: voxel model construction constructing, by linear spatial interpolation, a three- dimensional voxel texture of lake water quality scalar field based on lake water quality scalar field data.
Specifically, this step comprises the following substeps: substep S111: numeric normalization using the grid scalar field data of algae biomass of lake, they are normalized using the formula (1), wherein the normaliza- tion is to perform min-max normalization to values in the range of [0,1], each value corresponding to a pixel value and corresponding to a three-dimensional grid to form a voxel, det(l, m,n) = ee (1) where (1, m, n) is a coordinate of a voxel point in three- dimensional space; V (1, m, n) is an attribute value of a voxel at
(1, m, n); HU is a mean value of the grid scalar field data set of algae biomass of lake; ò is a standard deviation of the grid sca- lar field data set of algae biomass of lake; det (1, m, n) is a normalized attribute value of the voxel at (1, m, n), and the val- ue interval is [0, 1]. substep S112: spatial interpolation resampling the normalized data by linear spatial interpola- tion, to change the discrete data field into a continuous data field, so as to improve the quality of scalar field data. substep S113: voxel texture construction constructing a three-dimensional voxel texture of an irregu- lar region; for an irregular region containing blank voxels, screening out and identifying the voxels with null values and in- valid values; filtering out blank voxels according to the identi- fication in the process of volume rendering, and preparing a valid voxel model for volume rendering of the irregular region.
Referring to FIG. 2, a constructed voxel model of a lake wa- ter quality scalar field volume rendering generation method ac- cording to a specific embodiment of the present invention is shown. step S120: generating transfer function based on frequency distribution histogram counting the distribution of the voxels according to normal- ized values in the three-dimensional voxel model, plotting a fre- quency distribution histogram of water quality concentration sca- lar field data, and designing a color mapping transfer function according to the frequency distribution histogram of the water quality concentration scalar field data.
Specifically, this step comprises the following substeps: substep S121: color band initialization dividing the normalized scalar field from small to large equally to determine the number N of division intervals; at the same time, initially setting corresponding color bands, wherein each interval corresponds to one color band (C:-C3,; C,-Cs.C; Ci 35 ..Cy—Cy.:i), one color band is formed between color C; and color Cg, and all color bands between color C; and color Cy constitute a global color band.
Referring to FIG. 3, a schematic diagram of color band gener- ation for a lake water quality scalar field volume rendering gen- eration method according to an embodiment of the present invention is shown. substep 8122: frequency distribution histogram construction counting the number of voxels in each interval as the inter- val frequency (F,, F,..Fi...Fy), wherein F; is the frequency of a voxel in the i-th interval; calculating the ratio of the interval frequency value to the total number of voxels as the interval voxel ratio, taking N value intervals of normalized scalar field data as abscissa, and taking the number of voxels in the corre- sponding interval as ordinate to construct the frequency distribu- tion histogram of water quality concentration scalar field data;
Referring to Fig. 4, a resulting frequency distribution his- togram of a lake water quality scalar field volume rendering gen- eration method according to a specific embodiment of the present invention is shown. substep 35123: pixel ratio setting taking interval voxel proportion as the proportion of pixels occupying the whole mapping texture, so that the color band in the concentrated distribution area occupies more pixels, ensuring more color grading levels. substep S124: color band dividing setting the hierarchical level of the global color band as P, namely, dividing the global color band into P pixels, and calcu- lating the number of pixels of each color band according to the proportion of pixels occupied in each color band interval. step 8125: frequency color band cycle generation circularly generating each color band, which is generated by linear interpolation according to a start color C; and an ending color C; , ;, wherein the end color of the previous color band is the start color of the next color band. step S126: color mapping transfer function generation according to substeps S121-S125, automatically generating the transfer function for finally synthesizing into the global color band, a color mapping transfer function formula based on numerical frequency statistics, the color mapping transfer function formula comprising formula (3), a color mapping transfer function formula, and formula (4), a calculation formula for an opacity value. i = Int(det * N),i€[0,N—1] (2) (Rm mn) Bammn)) = rl * (N+ det—1) +C; (3) *Fi/% Fi
Amn) = det(l, m,n) (4) where 1 represents the i-th interval, namely, the i-th color band, the value interval is [0, N-1], and N represents the total number of intervals; C; is the start color of the i-th color band;
Ci+: 1s the ending color of the i-th color band; P represents the total number of pixels of all color bands and is also an adjust- ment constant; F i is the frequency of the voxel in the i-th in- terval; (Ra, m, nv Ga, m, nv Ba, nm, ny) 1s the color value mapped by the attribute value of the voxel at (1, m, n); and An, n, ny is the opacity value mapped by the attribute value of the voxel at (1, m, n), which is proportional to the normalized attribute value. step 5130: light synthesis and image fusion calculating the color and opacity of each voxel based on the color mapping transfer function, and realizing light synthesis and image fusion according to a ray casting algorithm.
Specifically, this step comprises the following substeps: substep 8131: voxels color and transparency calculation calculating the color and opacity values of each voxel using the transfer functions generated by the formulas (3) and (4) to obtain the color and opacity corresponding to the voxel value. substep 5132: lighting rendering and coloring using ray casting algorithm to perform lighting rendering and coloring on the voxel so as to obtain the color value and opacity of the sampling point. substep 5133: light synthesis and image fusion accumulating the color value and opacity of each sampling point in the order from front to back along the direction of the casting ray according to the color value and opacity of the sam- pling point on the casting ray in the ray casting algorithm, to obtain the color value and opacity of the screen pixel point, and complete the light synthesis and image fusion.
Referring to Fig. 5, a schematic diagram of a volume render-
ing perspective analysis of a lake water quality scalar field vol- ume rendering generation method according to a specific embodiment of the present invention is obtained.
Example
The volume rendering method is applied to the three- dimensional visual analysis of water quality in shallow lakes. The transfer function considering the frequency distribution is de- signed, and a “from surface to interior” water quality scalar field volume model is constructed by using the volume rendering method, which can effectively realize the refined simulation and expression of the lake water quality model, and can explore the lake water quality scalar field distribution law and the lake pol- lutant diffusion situation. The traditional water environment wa- ter quality surface visualization is improved into volume render- ing expression capable of being sectioned in any layer and any face by the volume rendering method, which provides the basis for the research of lake water quality distribution and change of shallow lakes.
Taking Chaohu Lake in Anhui Province, China as an example, calculating the o scalar field data of algae biomass in Chaohu
Lake, the scalar field is 330 x 66 x 5 grid points, and each grid point can identify the algae biomass of the water body. The data can be divided into 5 underwater layers for a total of 8 days. The water quality perspective analysis of Chaohu Lake is shown in FIG. 5, and the data for 8 days can be calculated in the following man- ner to obtain the space-time change diagram of algae biomassa in 8 days, as shown in FIG. 6.
Therefore, according to the present invention, based on the volume rendering technology, considering the frequency distribu- tion of the algae biomass voxel model and automatically generating the transfer function method, the visualization and dynamic simu- lation experiments of volume rendering of multi-time series water quality scalar field can be realized, which optimize the effect of fine expression of subtle differences in lake water quality volume rendering, and provides an effective visual analysis method for lake multi-time series water quality change.
In the present invention, by considering the frequency dis-
tribution of a three-dimensional voxel model, i.e. dividing the voxel values into equal parts, calculating a numerical interval of each equal part, counting the number of voxels whose values are located in the interval according to intervals, plotting a fre- quency distribution histogram according to the interval frequency, and generating a transfer function based on the frequency distri- bution histogram. It has the advantages of making the color ex- pression of voxel rendering in the same interval finer, improving the accuracy of volume rendering, being capable of expressing lo- cal subtle distribution differences and characteristics, and ef- fectively improving the ability of stereo perspective analysis of internal characteristics of water quality models.
Further, the present invention discloses a storage medium for storing computer-executable instructions, characterized in that, the computer-executable instructions, when executed by a pro- cessor, perform the lake water quality scalar field volume render- ing generation method above.
Obviously, those skilled in the art should understand that the above-mentioned units or steps of the present invention can be implemented by a general-purpose computing device, which can be concentrated on a single computing device, or they can be imple- mented with program codes executable by a computer device so that they can be stored in a storage device and executed by the compu- ting device, or they can be separately made into individual inte- grated circuit modules, or multiple modules or steps thereof can be fabricated into a single integrated circuit module to imple- ment. Thus, the present invention is not limited to any specific combination of hardware and software.
While the present invention has been described in further de- tail with reference to specific preferred embodiments thereof, it will be understood by those skilled in the art that various chang- es in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the appended claims.

Claims (5)

CONCLUSIESCONCLUSIONS 1. Werkwijze voor het genereren van een scalair veldvolumeweergave van de waterkwaliteit van een meer, gekenmerkt doordat de werkwij- ze de volgende stappen omvat: stap S110: voxel-modelconstructie het construeren, door lineaire ruimtelijke interpolatie, van een driedimensionale voxel-textuur van het scalaire veld van de water- kwaliteit van het meer op basis van scalaire veldgegevens van de waterkwaliteit van het meer; stap S120: het genereren van een overdrachtsfunctie op basis van frequentieverdelingshistogram het tellen van de verdeling van de voxels volgens genormaliseerde waarden in het driedimensionale voxelmodel, het plotten van een frequentiedistributiehistogram van scalaire veldgegevens van de waterkwaliteitsconcentratie en het ontwerpen van een kleurtoewij- zingsoverdrachtsfunctie volgens het frequentiedistributiehistogram van de scalaire veldgegevens van de waterkwaliteitsconcentratie; en stap S130: lichtsynthese en beeldfusie het berekenen van de kleur en opaciteit van elke voxel op basis van de kleurtoewijzingsoverdrachtsfunctie, en het realiseren van lichtsynthese en beeldfusie volgens een ray casting-algoritme.A method of generating a scalar field volume representation of the water quality of a lake, characterized in that the method comprises the steps of: step S110: voxel model construction constructing, by linear spatial interpolation, a three-dimensional voxel texture of the lake water quality scalar field based on lake water quality scalar field data; step S120: generating a transfer function based on frequency distribution histogram counting the distribution of the voxels according to normalized values in the three-dimensional voxel model, plotting a frequency distribution histogram from water quality concentration scalar field data, and designing a color assignment transfer function according to the frequency distribution histogram from the scalar field data of the water quality concentration; and step S130: light synthesis and image fusion calculating the color and opacity of each voxel based on the color assignment transfer function, and performing light synthesis and image fusion according to a ray casting algorithm. 2. Werkwijze voor het genereren van een scalair veldvolumeweergave van de waterkwaliteit van een meer volgens conclusie 1, met het kenmerk, dat: stap S110 van voxel-modelconstructie specifiek omvat: substap S111: numerieke normalisatie met behulp van de scalaire veldgegevens van het raster van algen- biomassa van het meer, worden ze genormaliseerd met behulp van de formule (1), waarbij de normalisatie is om min-max-normalisatie uit te voeren naar waarden in het bereik van [0, 1], waarbij elke waarde overeenkomt met een pixelwaarde en overeenkomt met een driedimensionaal raster om een voxel te vormen,A method of generating a scalar field volume representation of lake water quality according to claim 1, characterized in that : step S110 of voxel model construction specifically comprises: substep S111: numerical normalization using the scalar field data of the grid of algal biomass of the lake, they are normalized using the formula (1), where the normalization is to perform min-max normalization to values in the range of [0, 1], where each value corresponds to a pixel value and corresponds to a three-dimensional grid to form a voxel, det(l,m,n) = Lm (1) waarbij (1, m, n) een coördinaat is van een voxelpunt in de drie- dimensionale ruimte; V (1, m, n) is een attribuutwaarde van een voxel op (1, m, n); p is een gemiddelde waarde van de raster sca- laire veldgegevensset van algenbiomassa van meer; ò is een stan- daarddeviatie van de raster scalaire veldgegevensset van algenbio- massa van meer; det (1, m, n) is een genormaliseerde attribuut- waarde van de voxel op (1, m, n), en het waarde-interval is [0, 1]; substap S112: ruimtelijke interpolatie het opnieuw bemonsteren van de genormaliseerde gegevens door line- aire ruimtelijke interpolatie, om het discrete gegevensveld te veranderen in een continu gegevensveld, om de kwaliteit van sca- laire veldgegevens te verbeteren; substap S113: constructie van voxeltextuur het construeren van een driedimensionale voxeltextuur van een on- regelmatig gebied; voor een onregelmatig gebied dat blanco voxels bevat, het uitfilteren en identificeren van de voxels met nul- waarden en ongeldige waarden; het uitfilteren van lege voxels vol- gens de identificatie in het proces van volumeweergave, en het be- reiden van een geldig voxelmodel voor volumeweergave van het onre- gelmatige gebied.det(l,m,n) = Lm(1) where (1,m,n) is a coordinate of a voxel point in three-dimensional space; V(1, m, n) is an attribute value of a voxel at (1, m, n); p is an average value of the algal biomass raster scalar field data set of more; ò is a standard deviation of the algal biomass raster scalar field dataset of more; det(1, m, n) is a normalized attribute value of the voxel at (1, m, n), and the value interval is [0, 1]; substep S112: spatial interpolation resampling the normalized data by linear spatial interpolation to change the discrete data field into a continuous data field to improve the quality of scalar field data; substep S113: voxel texture construction constructing a three-dimensional voxel texture of an irregular region; for an irregular region containing blank voxels, filtering out and identifying the voxels with zero values and invalid values; filtering out empty voxels according to the identification in the process of volume rendering, and preparing a valid voxel model for volume rendering of the irregular region. 3. Werkwijze voor het genereren van een scalair veldvolumeweergave van de waterkwaliteit van een meer volgens conclusie 2, met het kenmerk, dat: stap S120 van het genereren van een overdrachtsfunctie op basis van het frequentiedistributiehistogram specifiek omvat: substap S121: initialisatie van de kleurenband het gelijk verdelen van het genormaliseerde scalaire veld van klein naar groot om het aantal N delingsintervallen te bepalen; tegelijkertijd in eerste instantie overeenkomstige kleurbanden in- stellen, waarbij elk interval overeenkomt met één kleurband (C,-C;, CarCs ow. Cil wo Cy Ci); één kleurband wordt gevormd tussen kleur C, en kleur C., en alle kleurbanden tussen kleur C; en kleur Cy vormen een globale kleurband;A method of generating a scalar field volume representation of the water quality of a lake according to claim 2, characterized in that : step S120 of generating a transfer function based on the frequency distribution histogram specifically comprises: sub-step S121: initialization of the color band the dividing the normalized scalar field equally from smallest to largest to determine the number N of division intervals; simultaneously initially set corresponding color bands, each interval corresponding to one color band (C 1 -C 2 , CarCs ow. Cil wo Cy Ci); one color band is formed between color C, and color C., and all color bands between color C; and color Cy form a global color band; substap S122: constructie van freguentiedistributiehistogram het aantal voxels in elk interval tellen als de intervalfrequentie (Fy, Fs... Fi...Fy), waarbij F; de frequentie is van een voxel in het i“ interval; het berekenen van de verhouding van de intervalfre-substep S122: construction of frequency distribution histogram counting the number of voxels in each interval as the interval frequency (Fy, Fs...Fi...Fy), where F; is the frequency of a voxel in the i" interval; calculating the interval rate ratio quentiewaarde tot het totale aantal voxels als de intervalvoxel- verhouding, waarbij N waarde-intervallen van genormaliseerde sca- laire veldgegevens als abscis worden genomen, en het nemen van het aantal voxels in het overeenkomstige interval als ordinaat om het frequentieverdelingshistogram te construeren van scalaire veldge-frequency value to the total number of voxels as the interval voxel ratio, taking N value intervals of normalized scalar field data as abscissas, and taking the number of voxels in the corresponding interval as the ordinate to construct the frequency distribution histogram from scalar field data gevens van de waterkwaliteitsconcentratie; substap S123: pixelverhouding instellen het nemen van de interval -voxelverhouding als het aandeel pixels dat de hele afbeeldingstextuur inneemt, zodat de kleurband in het geconcentreerde distributiegebied meer pixels inneemt, wat zorgt voor meer kleurgradatieniveaus; substap S124: kleurband opdelen het instellen van het hiërarchische niveau van de globale kleuren- band als P, namelijk het verdelen van de globale kleurenband in P pixels, en het berekenen van het aantal pixels van elke kleuren- band volgens het aandeel pixels dat in elk kleurbandinterval wordt ingenomen; stap S125: generatie van frequentiekleurenbandcyclus het circulair genereren van elke kleurband, die wordt gegenereerd door lineaire interpolatie volgens een startkleur C; en een eind- kleur Ci+1; waarbij de eindkleur van de vorige kleurband de start- kleur is van de volgende kleurband; en stap S126: generatie van kleurtoewijzing overdrachtsfunctie volgens substappen S121 tot S125, het automatisch genereren van de overdrachtsfunctie voor het uiteindelijk synthetiseren in de glo- bale kleurenband, een kleurtoewijzingsoverdrachtsfunctie formule op basis van numerieke frequentiestatistieken, de kleurtoewij- zingsoverdrachtsfunctie formule die formule (3) omvat, een kleur- toewijzingsoverdrachtsfunctie formule en formule (4), een bereke- ningsformule voor een dekkingswaarde. i=Int(det*N),i€[0,N—1] (2) (Rom Gummy Bammn)) = eit * (N*det—1) +6; (3) 1 Fiwater quality concentration data; substep S123: set pixel ratio taking the interval voxel ratio as the proportion of pixels occupying the entire image texture, so that the color band in the concentrated distribution area occupies more pixels, providing more color gradation levels; substep S124: divide color band setting the hierarchical level of the global color band as P, namely dividing the global color band into P pixels, and calculating the number of pixels of each color band according to the proportion of pixels contained in each color band interval is taken; step S125: frequency color band cycle generation circularly generating each color band, which is generated by linear interpolation according to a starting color C; and a final color Ci+1; wherein the ending color of the previous color band is the starting color of the next color band; and step S126: generation of color assignment transfer function according to substeps S121 to S125, automatically generating the transfer function for finally synthesizing into the global color band, a color assignment transfer function formula based on numerical frequency statistics, the color assignment transfer function formula that formula (3) comprises, a color assignment transfer function formula and formula (4), a calculation formula for a coverage value. i=Int(det*N),i€[0,N—1] (2) (Rom Gummy Bammn)) = eit * (N*det—1) +6; (3) 1 Fi Amn) = det(l, m,n) (4) waarbij i staat voor het i-de interval, namelijk de 1° kleurenband, het waarde-interval is [0, N-1], en N staat voor het totale aantal intervallen; C‚; is de startkleur van de i° kleurband; Ci is de eindkleur van de i° kleurband; P staat voor het totale aantal pixels van alle kleurbanden en is tevens een aanpassingsconstante; F; is de frequentie van de voxel in het if interval; (Ru, m ns Gu, m nr B (1, wm wm) is de kleurwaarde toegewezen door de attribuutwaar- de van de voxel op (1, m, nj); en A1, mn, n) is de dekkingswaarde die is toegewezen door de attribuutwaarde van de voxel op (1, m, nj, die evenredig is met de genormaliseerde attribuutwaarde.Amn) = det(l, m,n) (4) where i represents the ith interval, namely the 1° color band, the value interval is [0, N-1], and N represents the total number intervals; C‚; is the starting color of the i° color band; Ci is the final color of the i° color band; P represents the total number of pixels of all color bands and is also an adjustment constant; F; is the frequency of the voxel in the if interval; (Ru, m ns Gu, m nr B (1, wm wm) is the color value assigned by the attribute value of the voxel at (1, m, nj); and A1, mn, n) is the opacity value assigned by the attribute value of the voxel at (1, m, nj, which is proportional to the normalized attribute value. 4. Werkwijze voor het genereren van een scalair veldvolumeweergave van de waterkwaliteit van een meer volgens conclusie 3, met het kenmerk, dat, stap S130 van lichtsynthese en beeldfusie specifiek omvat: substap S131: voxels kleur- en transparantieberekening het berekenen van de kleur- en opaciteitswaarden van elke voxel met behulp van de overdrachtsfuncties gegenereerd door de formules (3) en (4) om de kleur en opaciteit te verkrijgen die overeenkomen met de voxelwaarde; substap S132: weergave en kleuring van belichting het gebruiken van een ray casting algoritme om belichtingsweergave en kleuring op de voxel uit te voeren om de kleurwaarde en opaci- teit van het bemonsteringspunt te verkrijgen; substap S133: lichtsynthese en beeldfusie accumulatie van de kleurwaarden en opaciteit van elk bemonste- ringspunt in de volgorde van voor naar achter in de richting van de casting ray volgens de kleurwaarde en opaciteit van het bemon- steringspunt op de casting ray in het ray casting algoritme, om de kleurwaarde en dekking van het schermpixelpunt te verkrijgen, en het voltooien van de lichtsynthese en beeldfusie.A method for generating a scalar field volume representation of the water quality of a lake according to claim 3, characterized in that , step S130 of light synthesis and image fusion specifically comprises: substep S131: voxels color and transparency calculation calculating the color and opacity values of each voxel using the transfer functions generated by formulas (3) and (4) to obtain the color and opacity corresponding to the voxel value; substep S132: exposure rendering and coloring using a ray casting algorithm to perform illumination rendering and coloring on the voxel to obtain the color value and opacity of the sampling point; substep S133: light synthesis and image fusion accumulation of the color values and opacity of each sampling point in the order from front to back in the direction of the casting ray according to the color value and opacity of the sampling point on the casting ray in the ray casting algorithm , to obtain the color value and opacity of the screen pixel point, and complete the light synthesis and image fusion. 5. Opslagmedium waarop door een computer uitvoerbare instructies worden opgeslagen, met het kenmerk, dat: de door een computer uitvoerbare instructies, wanneer uitgevoerd door een processor, de werkwijze voor het genereren van een sca-5. A storage medium storing computer-executable instructions, characterized in that : the computer-executable instructions, when executed by a processor, lair veldvolumeweergave van de waterkwaliteit van een meer volgens een van de conclusies 1 tot 4 uitvoeren.perform a lair field volume display of the water quality of a lake according to one of claims 1 to 4.
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