CN107230183A - Image rasterization processing method and processing device - Google Patents
Image rasterization processing method and processing device Download PDFInfo
- Publication number
- CN107230183A CN107230183A CN201610176564.XA CN201610176564A CN107230183A CN 107230183 A CN107230183 A CN 107230183A CN 201610176564 A CN201610176564 A CN 201610176564A CN 107230183 A CN107230183 A CN 107230183A
- Authority
- CN
- China
- Prior art keywords
- data
- image
- image data
- processing
- raw
- 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.)
- Granted
Links
- 238000012545 processing Methods 0.000 title claims abstract description 90
- 238000003672 processing method Methods 0.000 title claims abstract description 14
- 238000013507 mapping Methods 0.000 claims abstract description 41
- 238000000034 method Methods 0.000 claims abstract description 28
- 230000011218 segmentation Effects 0.000 claims description 11
- 230000001934 delay Effects 0.000 claims description 4
- 230000008569 process Effects 0.000 description 13
- 238000010586 diagram Methods 0.000 description 10
- 230000006870 function Effects 0.000 description 4
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000000205 computational method Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000003709 image segmentation Methods 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/20—Linear translation of whole images or parts thereof, e.g. panning
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
- Editing Of Facsimile Originals (AREA)
Abstract
The embodiment of the present invention provides a kind of image rasterization processing method and processing device.This method includes：Obtain raw image data and image manipulation instruction；View data after being handled is carried out to raw image data according to image manipulation instruction；Positional information of the view data relative to raw image data after calculating processing；Destination image data corresponding with positional information is read from raw image data according to positional information.Positional information of the view data relative to raw image data after the embodiment of the present invention is handled by calculating, destination image data corresponding with positional information is read from raw image data according to positional information, it is not required to read each row of data for rotating image from disk relative to the initial row and termination row of original image and is put into internal memory, greatly reduce the occupancy of internal memory, simultaneously, image rasterization processor need to only read mapping point of each pixel of rotation image in original image from disk, improve the processing speed of image rasterization processor.
Description
Technical field
The present embodiments relate to image processing field, more particularly to a kind of image rasterization processing method and
Device.
Background technology
In image rasterization processing procedure, picture syntax parsing module is used to explain image in pdf document
Grammer, obtain image essential information and the image manipulation such as width, height, locating depth, the colour space of image
Instruction (such as rotation, mobile, scaling), and image essential information and image manipulation instruction are stored in
In disk.
Image rasterization processor reads image manipulation instruction to the original graph that is stored in disk from disk
As being handled, for example, image manipulation instruction is rotation, because image rasterization processor can only be by row
View data is read, image rasterization processor needs each row of data for calculating rotated image relative to original
The initial row and termination row of beginning image, and by the data of the initial row of original image and termination row from disk
Deposit internal memory is read out to use for successive image operation processing.Especially when the anglec of rotation be 90 degree or
At 270 degree, the first row and last column of each row of data relative to original image of rotated image, because
This, is required for reading data and the deposit of an original image from disk for postrotational each row of data
Internal memory.
If the pixel of original image is larger, memory source will be caused seriously to be consumed, in addition, also resulting in
The processing speed reduction of image rasterization processor.
The content of the invention
The embodiment of the present invention provides a kind of image rasterization processing method and processing device, to lower the occupancy of internal memory
Rate, improves the processing speed of image rasterization processor.
The one side of the embodiment of the present invention is to provide a kind of image rasterization processing method, including：
Obtain raw image data and image manipulation instruction；
Picture number after being handled is carried out to the raw image data according to described image operational order
According to；
Calculate positional information of the view data relative to the raw image data after the processing；
Mesh corresponding with the positional information is read from the raw image data according to the positional information
Logo image data.
The other side of the embodiment of the present invention is to provide a kind of image rasterization processing unit, including：
Acquisition module, for obtaining raw image data and image manipulation instruction；
Image processing module, at according to described image operational order to the raw image data
View data after reason is handled；
Computing module, for calculating position of the view data relative to the raw image data after the processing
Confidence ceases；
Read module, for being read according to the positional information from the raw image data and institute's rheme
Confidence ceases corresponding destination image data.
Image rasterization processing method and processing device provided in an embodiment of the present invention, image after being handled by calculating
Data are read relative to the positional information of raw image data according to positional information from raw image data
Destination image data corresponding with positional information, is not required to read each row of data phase of rotation image from disk
Initial row and termination row for original image are simultaneously put into internal memory, greatly reduce the occupancy of internal memory, together
When, image rasterization processor need to only read each pixel of rotation image in original image from disk
In mapping point, improve the processing speed of image rasterization processor.
Brief description of the drawings
Fig. 1 is image rasterization process flow figure provided in an embodiment of the present invention；
Fig. 2 is image rasterization process flow figure provided in an embodiment of the present invention；
The image rasterization process flow figure that Fig. 3 provides for another embodiment of the present invention；
The schematic diagram for the original image that Fig. 4 provides for another embodiment of the present invention；
The schematic diagram for the rotated image that Fig. 5 provides for another embodiment of the present invention；
The image rasterization process flow figure that Fig. 6 provides for another embodiment of the present invention；
Fig. 7 does not cut image schematic diagram for what another embodiment of the present invention was provided；
Image schematic diagram after the cutting that Fig. 8 provides for another embodiment of the present invention；
The image rasterization process flow figure that Fig. 9 provides for another embodiment of the present invention；
Figure 10 does not rotate image segmentation schematic diagram for what another embodiment of the present invention was provided；
The rotated image stepwise schematic views that Figure 11 provides for another embodiment of the present invention；
Figure 12 is the structure chart of image rasterization processing unit provided in an embodiment of the present invention.
Embodiment
Fig. 1 is image rasterization process flow figure provided in an embodiment of the present invention, and Fig. 2 is the present invention
The image rasterization process flow figure that embodiment is provided.The embodiment of the present invention is directed to when original image
Pixel is larger, causes memory source seriously to be consumed, in addition, also resulting in image rasterization processor
Processing speed is reduced there is provided image rasterization processing method, and specific method and step is as follows：
Step S101, acquisition raw image data and image manipulation instruction；
The executive agent of the embodiment of the present invention is image rasterization processing unit, image rasterization processing dress
Put and be arranged in grating-based processor, image rasterization processing unit includes picture syntax explanation module and figure
As processor, picture syntax instruction of the picture syntax explanation module to pdf document carries out parsing and obtains original
Image essential information and image manipulation instruction, as shown in Fig. 2 the input of picture syntax explanation module 22 is
Syntax instructions in pdf document 21, the parsing pdf document 21 of picture syntax explanation module 22 obtain original
Image essential information and image manipulation instruction, original image essential information include width, the height of original image
The essential informations such as degree, locating depth, the colour space, image manipulation instruction includes rotation instruction, translation instruction, contracting
Put instruction, cut instruction etc..The input of image processor 24 has raw image data 23 and picture syntax
The analysis result of explanation module 22 is original image essential information and image manipulation instruction, image processor
24 according to image manipulations instruction raw image data 23 is handled, and by raw image data 23,
In original image essential information and image manipulation instruction deposit disk 25, so that subsequent treatment is used.
Step S102, foundation described image operational order are carried out to the raw image data at processing acquisition
View data after reason；
As shown in Fig. 2 image processor 24 is carried out according to image manipulation instruction to raw image data 23
View data after being handled.
View data is believed relative to the position of the raw image data after step S103, the calculating processing
Breath；
For example, image manipulation instruction is specially rotation instruction, image processor 24 is carried out to original image
Rotation image is obtained after rotation, it is determined that mapping point of each pixel of rotation image in original image,
And calculate position of the mapping point relative to first pixel of original image.
Step S104, read from the raw image data and believe with the position according to the positional information
Cease corresponding destination image data.
Read from raw image data position according to the mapping point relative to first pixel of original image
The mapping point on the position is taken, because raw image data is stored in disk, image processor 24
Mapping point of each pixel of rotation image in original image need to be read from disk, is not required to from disk
Middle initial row and termination row of each pixel relative to original image for reading rotation image.
View data is believed relative to the position of raw image data after the embodiment of the present invention is handled by calculating
Breath, destination image data corresponding with positional information is read according to positional information from raw image data,
Be not required to from disk read rotation image each row of data relative to original image initial row and termination row simultaneously
Internal memory is put into, the occupancy of internal memory is greatly reduced, meanwhile, image rasterization processor only need to be from disk
Mapping point of the middle each pixel for reading rotation image in original image, is improved at image rasterization
Manage the processing speed of device.
The image rasterization process flow figure that Fig. 3 provides for another embodiment of the present invention；Fig. 4 is this
Invent the schematic diagram for the original image that another embodiment is provided；Fig. 5 provides for another embodiment of the present invention
The schematic diagram of rotated image.View data is relative to institute after detailed description calculating of the embodiment of the present invention processing
The specific method of the positional information of raw image data is stated, this method step is as follows：
Step S301, using each row data of view data after the processing as target data, determine the mesh
Mark first mapping data of first data of data in the raw image data original relative to described
First deviant of first data of view data；
Original image (rectangle part) is illustrated in figure 4, the image is carried out after 45 degree of rotations counterclockwise
Rotated image as shown in Figure 5 is obtained, each row data is target datas using in Fig. 5, it is assumed that where AB
Some rows of behavior rotated image, the embodiment of the present invention is illustrated with behavior example, every to other
The processing method of a line and the row are that AB processing method is consistent, and specific processing method is：During according to rotation
The transposed matrix M set in PDF determines that AB is expert at first data i.e. point A in Fig. 4 original images
The first mapping point A ', due to A=A ' * M, then A '=A*M ' (M ' is the inverse matrix of Metzler matrix).By
Fig. 4 understands first pixel that point 0 is original image, then can determine that A ' phases according to the A ' calculated
For the first deviant of point 0, it is assumed that the first mapping point A ' coordinate is (x, y), original image
Width be W, then first deviant offset=(W+7) * (y-1)/8 byte.
Step S302, determine any data in the target data in addition to first data in institute
State second deviant of the second mapping data relative to the described first mapping data in raw image data；
Assuming that B points be expert at by AB in any one data in addition to first data i.e. point A, similarly
Second mapping of the B points in raw image data is can determine that according to the mapping relations between point A and point A '
Point B ', and determine point B ' relative to point A ' according to the position relationship between Fig. 4 midpoints A ' and point B '
The second deviant, and second deviant rowOffset=(x+7)/8 byte.
Step S303, according to first deviant and second deviant determine it is described second mapping number
According to the 3rd deviant of first data relative to the raw image data, the 3rd deviant is
Any data in the target data in addition to first data is relative to the raw image data
Positional information.
According to second deviants of the point B ' relative to point A ' and point A ' relative to the first deviant for putting 0
Threeth deviants of the point B ' relative to point 0 can be calculated, the 3rd deviant is equal to the first deviant offset
Plus the second deviant rowOffset, where the 3rd deviant is AB for some rows of rotated image
Positional information of any data relative to raw image data in row in addition to first data.
The embodiment of the present invention calculates target data using each row data of view data after handling as target data
In each mapping point of the data in raw image data, and calculate the mapping point relative to original image number
Obtained in the deviant of first data in, the raw image data stored according to the deviant from disk
Take the corresponding data of mapping point, it is to avoid image rasterization processor reads often going for rotation image from disk
Data relative to original image initial row and termination row and be put into internal memory, greatly reduce the occupancy of internal memory
Rate, meanwhile, image rasterization processor need to only read each pixel of rotation image in original from disk
Mapping point in beginning image, improves the processing speed of image rasterization processor.
The image rasterization processing method that Fig. 6 provides for another embodiment of the present invention；Fig. 7 is another for the present invention
What one embodiment was provided does not cut image schematic diagram；After the cutting that Fig. 8 provides for another embodiment of the present invention
Image schematic diagram.On the basis of the corresponding embodiments of Fig. 3, the embodiment of the present invention is comprised the following steps that：
Step S601, acquisition raw image data and image manipulation instruction, described image operational order include
Rotation instruction and cutting instruction；
On the basis of above-described embodiment, described image operational order specifically includes rotation instruction and cutting refers to
Order, cuts instruction and specifically includes clipping region.
Step S602, according to it is described cut instruction to the raw image data carry out cut obtain effectively figure
As data；
As shown in fig. 7, original image is 62, clipping region is 61, original image 62 and clipping region
61 lap is the effective image after cutting, as shown in figure 8, effective image is represented with 63,
In addition, the corresponding data of original image are raw image data, the corresponding data of effective image are effectively figure
As data.
Step S603, rotation is carried out to the effective image data according to the rotation instruction obtain the place
View data after reason；
Effective image 63 in the embodiment of the present invention is specifically as follows the image in Fig. 4, to effective image number
Rotated according to image of the process of view data after the rotation acquisition processing similarly in Fig. 4 is carried out
Process, here is omitted.
View data is believed relative to the position of the raw image data after step S604, the calculating processing
Breath；
Step S605, read from the raw image data and believe with the position according to the positional information
Cease corresponding destination image data.
Step S604 and step S605 methods corresponding with above-described embodiment are consistent, and here is omitted.
The embodiment of the present invention carries out rotating and can dropping by cutting original image to the image after cutting
The data processing amount of low image rasterization processor.
The image rasterization process flow figure that Fig. 9 provides for another embodiment of the present invention；Figure 10 is this
That invents another embodiment offer does not rotate image segmentation schematic diagram；Figure 11 carries for another embodiment of the present invention
The rotated image stepwise schematic views of confession.On the basis of the corresponding embodiments of Fig. 6, the embodiment of the present invention
Comprise the following steps that：
Step S901, acquisition raw image data and image manipulation instruction, described image operational order include
Rotation instruction and cutting instruction；
Step S902, according to it is described cut instruction to the raw image data carry out cut obtain effectively figure
As data；
Step S903, the size for calculating the effective image data committed memory；
On the basis of above-described embodiment, the size of the data committed memory of effective image 63 is calculated, specifically
Computational methods be the size that the effective image data committed memory is calculated according to formula s=w*h*b/8
S, wherein, w represents the width of the effective image data, and h represents the height of the effective image data,
B represents the locating depth of the raw image data.
In step S904, size and raster image processor according to the effective image data committed memory
The size of image buffer calculates division number；
According to image buffer in the size s and raster image processor of effective image data committed memory
The formula that size bufferSize calculates the division number is n=(s+bufferSize-1)/bufferSize, wherein,
N represents the division number.
Step S905, according to the division number to the effective image data carry out segment processing；
Reasonable assumption, the division number that above-mentioned steps are calculated is 3, as shown in Figure 10, by effective image
63 points are 3 sections.
Step S906, the effective image data after segment processing are carried out with rotation obtain image after the processing
Data, view data includes multiple segmentations after the processing；
Rotation is carried out to the effective image data after segment processing and obtains postrotational image 64, is drawn after rotation
The segmentation divided is constant as shown in figure 11,.
Step S907, each row of data is calculated after the processing in each segmentation of view data relative to described
The positional information of raw image data；
Each row of data is calculated in each segmentation of postrotational image 64 relative to the raw image data
Positional information, computational methods are similarly in the method described in the corresponding embodiments of Fig. 3.
Step S908, read from the raw image data and believe with the position according to the positional information
Cease corresponding destination image data.
The embodiment of the present invention by effective image data carry out segment processing, reduce image rotation during
Shared memory source, is reduced caused by low memory system carries out frequently data disk caching
Time overhead.
Figure 12 is the structure chart of image rasterization processing unit provided in an embodiment of the present invention.The present invention is implemented
The image rasterization processing unit that example is provided can perform the place of image rasterization processing method embodiment offer
Flow is managed, as shown in figure 12, image rasterization processing unit 120 includes acquisition module 121, at image
Module 122, computing module 123 and read module 124 are managed, wherein, acquisition module 121 is used to obtain original
Beginning view data and image manipulation instruction；Image processing module 122 is used for according to described image operational order
View data after being handled is carried out to the raw image data；Computing module 123 is used to calculate
Positional information of the view data relative to the raw image data after the processing；Read module 124 is used
In reading target corresponding with the positional information from the raw image data according to the positional information
View data.
View data is believed relative to the position of raw image data after the embodiment of the present invention is handled by calculating
Breath, destination image data corresponding with positional information is read according to positional information from raw image data,
Be not required to from disk read rotation image each row of data relative to original image initial row and termination row simultaneously
Internal memory is put into, the occupancy of internal memory is greatly reduced, meanwhile, image rasterization processor only need to be from disk
Mapping point of the middle each pixel for reading rotation image in original image, is improved at image rasterization
Manage the processing speed of device.
On the basis of above-described embodiment, computing module 123 is specifically for view data after the processing
Each row data be target data, determine first data of the target data in the original image number
First deviant of the first mapping data relative to first data of the raw image data in；
Determine any data in the target data in addition to first data in the raw image data
In second mapping data relative to described first mapping data the second deviant；It is inclined according to described first
Shifting value and second deviant determine the second mapping data relative to the of the raw image data
3rd deviant of one data, the 3rd deviant be the target data in remove first number
Positional information of any data relative to the raw image data outside.
Described image operational order includes rotation instruction and cuts instruction；Image processing module 122 is specifically used
Instructed according to described cut to raw image data progress cutting acquisition effective image data；Foundation
The rotation instruction carries out rotation to the effective image data and obtains view data after the processing.
Image processing module 122 is additionally operable to calculate the size of the effective image data committed memory；Foundation
The big subtotal of image buffer in the size and raster image processor of the effective image data committed memory
Calculate division number；Segment processing is carried out to the effective image data according to the division number；To segmentation
Effective image data after processing carry out rotation and obtain view data, image after the processing after the processing
Data include multiple segmentations；Computing module 123 is specifically for calculating each of view data after the processing
Positional information of each row of data relative to the raw image data in segmentation.
Computing module 123 according to formula (1) specifically for calculating the effective image data committed memory
Size：
S=w*h*b/8 (1)
Wherein, s represents the size of the effective image data committed memory, and w represents the effective image number
According to width, h represents the height of the effective image data, and b represents the locating depth of the raw image data；
The division number is calculated according to formula (2)：
N=(s+bufferSize-1)/bufferSize (2)
Wherein, n represents the division number, and bufferSize represents that image delays in the raster image processor
Rush the size in area.
Image rasterization processing unit provided in an embodiment of the present invention can be specifically for performing above-mentioned Fig. 1 institutes
The embodiment of the method for offer, here is omitted for concrete function.
The embodiment of the present invention calculates target data using each row data of view data after handling as target data
In each mapping point of the data in raw image data, and calculate the mapping point relative to original image number
Obtained in the deviant of first data in, the raw image data stored according to the deviant from disk
Take the corresponding data of mapping point, it is to avoid image rasterization processor reads often going for rotation image from disk
Data relative to original image initial row and termination row and be put into internal memory, greatly reduce the occupancy of internal memory
Rate, meanwhile, image rasterization processor need to only read each pixel of rotation image in original from disk
Mapping point in beginning image, improves the processing speed of image rasterization processor；By to original image
Cut, the data processing amount of image rasterization processor can be reduced by carrying out rotation to the image after cutting；
By carrying out segment processing to effective image data, shared memory source during image rotation is reduced,
Reduce the time overhead caused by low memory system carries out frequently data disk caching.
In summary, view data is relative to raw image data after the embodiment of the present invention is handled by calculating
Positional information, target figure corresponding with positional information is read from raw image data according to positional information
As data, be not required to read from disk each row of data of rotation image relative to the initial row of original image and
Termination row is simultaneously put into internal memory, greatly reduces the occupancy of internal memory, meanwhile, image rasterization processor is only
Mapping point of each pixel of rotation image in original image need to be read from disk, image is improved
The processing speed of grating-based processor；Each row data of view data are calculated as target data using after processing
Each mapping point of the data in raw image data in target data, and the mapping point is calculated relative to original
The deviant of first data in beginning view data, the original image stored according to the deviant from disk
The corresponding data of mapping point are obtained in data, it is to avoid image rasterization processor reads rotation figure from disk
The each row of data of picture relative to original image initial row and termination row and be put into internal memory, greatly reduce in
The occupancy deposited, meanwhile, image rasterization processor need to only read each picture of rotation image from disk
Mapping point of the vegetarian refreshments in original image, improves the processing speed of image rasterization processor；By right
Original image is cut, and the number of image rasterization processor can be reduced by carrying out rotation to the image after cutting
According to treating capacity；By carrying out segment processing to effective image data, reduce shared by during image rotation
Memory source, reduce because low memory system carry out frequently data disk caching caused by time open
Pin.
In several embodiments provided by the present invention, it should be understood that disclosed apparatus and method,
It can realize by another way.For example, device embodiment described above is only schematical,
For example, the division of the unit, only a kind of division of logic function, can have in addition when actually realizing
Dividing mode, such as multiple units or component can combine or be desirably integrated into another system, or
Some features can be ignored, or not perform.It is another, shown or discussed coupling each other or
Direct-coupling or communication connection can be the INDIRECT COUPLING or communication link of device or unit by some interfaces
Connect, can be electrical, machinery or other forms.
The unit illustrated as separating component can be or may not be it is physically separate, make
It can be for the part that unit is shown or may not be physical location, you can with positioned at a place,
Or can also be distributed on multiple NEs.Can select according to the actual needs part therein or
Person's whole units realize the purpose of this embodiment scheme.
In addition, each functional unit in each embodiment of the invention can be integrated in a processing unit,
Can also be that unit is individually physically present, can also two or more units be integrated in a list
In member.Above-mentioned integrated unit can both be realized in the form of hardware, it would however also be possible to employ hardware adds software
The form of functional unit is realized.
The above-mentioned integrated unit realized in the form of SFU software functional unit, can be stored in a computer
In read/write memory medium.Above-mentioned SFU software functional unit is stored in a storage medium, including some fingers
Order is to cause a computer equipment (can be personal computer, server, or network equipment etc.)
Or processor (processor) performs the part steps of each embodiment methods described of the invention.And it is foregoing
Storage medium include：USB flash disk, mobile hard disk, read-only storage (Read-Only Memory, ROM),
Random access memory (Random Access Memory, RAM), magnetic disc or CD etc. are various can be with
The medium of store program codes.
Those skilled in the art can be understood that, for convenience and simplicity of description, only with above-mentioned each
The division progress of functional module is for example, in practical application, as needed can divide above-mentioned functions
With by different functional module completions, i.e., the internal structure of device is divided into different functional modules, with
Complete all or part of function described above.The specific work process of the device of foregoing description, can be with
With reference to the corresponding process in preceding method embodiment, it will not be repeated here.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than right
It is limited；Although the present invention is described in detail with reference to foregoing embodiments, this area it is common
Technical staff should be understood：It can still modify to the technical scheme described in foregoing embodiments,
Or equivalent substitution is carried out to which part or all technical characteristic；And these modifications or replacement, and
The essence of appropriate technical solution is not set to depart from the scope of various embodiments of the present invention technical scheme.
Claims (10)
1. a kind of image rasterization processing method, it is characterised in that including：
Obtain raw image data and image manipulation instruction；
Picture number after being handled is carried out to the raw image data according to described image operational order
According to；
Calculate positional information of the view data relative to the raw image data after the processing；
Mesh corresponding with the positional information is read from the raw image data according to the positional information
Logo image data.
2. according to the method described in claim 1, it is characterised in that described to calculate image after the processing
Data relative to the raw image data positional information, including：
Each row data using view data after the processing determine the of the target data as target data
First mapping data of one data in the raw image data are relative to the raw image data
First deviant of first data；
Determine any data in the target data in addition to first data in the original image
Second deviant of the second mapping data relative to the described first mapping data in data；
Determine the second mapping data relative to institute according to first deviant and second deviant
The 3rd deviant of first data of raw image data is stated, the 3rd deviant is the number of targets
Any data in addition to first data is believed relative to the position of the raw image data
Breath.
3. method according to claim 2, it is characterised in that described image operational order includes rotation
Turn instruction and cut instruction；
It is described that the raw image data is carried out according to described image operational order after being handled to scheme
As data, including：
Instruction is cut to raw image data progress cutting acquisition effective image data according to described；
Rotation is carried out to the effective image data according to the rotation instruction and obtains picture number after the processing
According to.
4. method according to claim 3, it is characterised in that described according to the rotation instruction pair
The effective image data carry out rotation and obtained after the processing before view data, in addition to：
Calculate the size of the effective image data committed memory；
According to image buffer in the size and raster image processor of the effective image data committed memory
Size calculate division number；
Segment processing is carried out to the effective image data according to the division number；
It is described that the effective image data are carried out after rotating the acquisition processing to scheme according to the rotation instruction
As data, including：
Effective image data after segment processing are carried out with rotation and obtains view data after the processing, it is described
View data includes multiple segmentations after processing；
View data is relative to the positional information of the raw image data, bag after the calculating processing
Include：
Each row of data is calculated after the processing in each segmentation of view data relative to the original image number
According to positional information.
5. method according to claim 4, it is characterised in that the calculating effective image number
According to the size of committed memory, including：
The size of the effective image data committed memory is calculated according to formula (1)：
S=w*h*b/8 (1)
Wherein, s represents the size of the effective image data committed memory, and w represents the effective image number
According to width, h represents the height of the effective image data, and b represents the locating depth of the raw image data；
Image delays in the size and raster image processor according to the effective image data committed memory
The size for rushing area calculates division number, including：
The division number is calculated according to formula (2)：
N=(s+bufferSize-1)/bufferSize (2)
Wherein, n represents the division number, and bufferSize represents that image delays in the raster image processor
Rush the size in area.
6. a kind of image rasterization processing unit, it is characterised in that including：
Acquisition module, for obtaining raw image data and image manipulation instruction；
Image processing module, at according to described image operational order to the raw image data
View data after reason is handled；
Computing module, for calculating position of the view data relative to the raw image data after the processing
Confidence ceases；
Read module, for being read according to the positional information from the raw image data and institute's rheme
Confidence ceases corresponding destination image data.
7. image rasterization processing unit according to claim 6, it is characterised in that the calculating
Module is specifically for using each row data of view data after the processing as target data, determining the target
First mapping data of first data of data in the raw image data are relative to the original graph
As the first deviant of first data of data；Determine to remove first data in the target data
Outside any data in the raw image data second mapping data relative to described first mapping
Second deviant of data；Determine that described second reflects according to first deviant and second deviant
Penetrate threeth deviant of the data relative to first data of the raw image data, the 3rd skew
Be worth is any data in the target data in addition to first data relative to the original image
The positional information of data.
8. image rasterization processing unit according to claim 7, it is characterised in that described image
Operational order includes rotation instruction and cuts instruction；
Described image processing module according to described specifically for cutting instruction to raw image data progress
Cut and obtain effective image data；Rotation is carried out according to the rotation instruction to the effective image data to obtain
Obtain view data after the processing.
9. image rasterization processing unit according to claim 8, it is characterised in that described image
Processing module is additionally operable to calculate the size of the effective image data committed memory；According to the effective image
The size of image buffer calculates division number in the size and raster image processor of data committed memory；
Segment processing is carried out to the effective image data according to the division number；To effective after segment processing
View data carries out rotation and obtains view data after the processing, and view data includes multiple after the processing
Segmentation；
The computing module is specifically for each row of data in each segmentation of view data after the calculating processing
Relative to the positional information of the raw image data.
10. image rasterization processing unit according to claim 9, it is characterised in that the meter
Module is calculated specifically for the size according to formula (1) the calculating effective image data committed memory：
S=w*h*b/8 (1)
Wherein, s represents the size of the effective image data committed memory, and w represents the effective image number
According to width, h represents the height of the effective image data, and b represents the locating depth of the raw image data；
The division number is calculated according to formula (2)：
N=(s+bufferSize-1)/bufferSize (2)
Wherein, n represents the division number, and bufferSize represents that image delays in the raster image processor
Rush the size in area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610176564.XA CN107230183B (en) | 2016-03-24 | 2016-03-24 | Image rasterization processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610176564.XA CN107230183B (en) | 2016-03-24 | 2016-03-24 | Image rasterization processing method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107230183A true CN107230183A (en) | 2017-10-03 |
| CN107230183B CN107230183B (en) | 2020-09-04 |
Family
ID=59931976
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610176564.XA Active CN107230183B (en) | 2016-03-24 | 2016-03-24 | Image rasterization processing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107230183B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109349774A (en) * | 2018-10-29 | 2019-02-19 | 徐悦 | A kind of automatic manicure method and apparatus |
| CN112511765A (en) * | 2020-10-13 | 2021-03-16 | Oppo（重庆）智能科技有限公司 | Image rotation method, image rotation device, storage medium and electronic equipment |
| CN113344775A (en) * | 2021-06-18 | 2021-09-03 | 北京澎思科技有限公司 | Image processing method, image processing device, electronic equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5381163A (en) * | 1990-06-13 | 1995-01-10 | Canon Kabushiki Kaisha | Image processing apparatus |
| CN101520887A (en) * | 2009-03-30 | 2009-09-02 | 北京中星微电子有限公司 | Image zooming method, device and chip |
| US20110222082A1 (en) * | 2010-03-15 | 2011-09-15 | Canon Kabushiki Kaisha | Image processing apparatus, control method, and computer-readable medium |
| CN103440612A (en) * | 2013-08-27 | 2013-12-11 | 华为技术有限公司 | Image processing method and device in GPU vitualization |
-
2016
- 2016-03-24 CN CN201610176564.XA patent/CN107230183B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5381163A (en) * | 1990-06-13 | 1995-01-10 | Canon Kabushiki Kaisha | Image processing apparatus |
| CN101520887A (en) * | 2009-03-30 | 2009-09-02 | 北京中星微电子有限公司 | Image zooming method, device and chip |
| US20110222082A1 (en) * | 2010-03-15 | 2011-09-15 | Canon Kabushiki Kaisha | Image processing apparatus, control method, and computer-readable medium |
| CN103440612A (en) * | 2013-08-27 | 2013-12-11 | 华为技术有限公司 | Image processing method and device in GPU vitualization |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109349774A (en) * | 2018-10-29 | 2019-02-19 | 徐悦 | A kind of automatic manicure method and apparatus |
| CN112511765A (en) * | 2020-10-13 | 2021-03-16 | Oppo（重庆）智能科技有限公司 | Image rotation method, image rotation device, storage medium and electronic equipment |
| CN113344775A (en) * | 2021-06-18 | 2021-09-03 | 北京澎思科技有限公司 | Image processing method, image processing device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107230183B (en) | 2020-09-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| DE112020004625T5 (en) | TRANSPOSED CONVOLUTION WITH SYSTOLIC ARRAY | |
| US8290300B2 (en) | Seam-based reduction and expansion of images with color-weighted priority | |
| US8963960B2 (en) | System and method for content aware hybrid cropping and seam carving of images | |
| US8194974B1 (en) | Merge and removal in a planar map of an image | |
| US8160398B1 (en) | Independent resizing of multiple image regions | |
| JP7059318B2 (en) | Learning data generation method and system for classifier learning with regional characteristics | |
| CN102970456B (en) | Image forming apparatus, image forming apparatus control method, and program | |
| JP5854802B2 (en) | Image processing apparatus, image processing method, and computer program | |
| US8358876B1 (en) | System and method for content aware in place translations in images | |
| US9501811B2 (en) | Resizing an image | |
| EP3779864A1 (en) | Data processing method and computing device | |
| EP3779769B1 (en) | Optical flow computing method and computing device | |
| WO2022206556A1 (en) | Matrix operation method and apparatus for image data, device, and storage medium | |
| CN107230183A (en) | Image rasterization processing method and processing device | |
| CN115330986B (en) | Method and system for processing graphics in block rendering mode | |
| CN106991422A (en) | Character segmentation method, device and computer-readable recording medium and electronic equipment | |
| US8280187B1 (en) | Seam carving and expansion of images with color frequency priority | |
| KR20230172014A (en) | Image processing methods, devices, devices, storage media, program products and programs | |
| CN113538623A (en) | Method and device for determining target image, electronic equipment and storage medium | |
| US8798370B2 (en) | Pattern identifying apparatus, pattern identifying method and program | |
| CN115880362B (en) | Code region positioning method, device, computer equipment and computer readable storage medium | |
| JP2016045600A (en) | Image processing device and image processing method | |
| Galiano et al. | On a fast bilateral filtering formulation using functional rearrangements | |
| US9715715B2 (en) | Efficient cache preloading | |
| EP3686841A1 (en) | Image segmentation method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220621 Address after: 3007, Hengqin international financial center building, No. 58, Huajin street, Hengqin new area, Zhuhai, Guangdong 519031 Patentee after: New founder holdings development Co.,Ltd. Patentee after: Beijing Beida Founder Electronics Co., Ltd. Address before: 100871, Beijing, Haidian District, Cheng Fu Road, No. 298, Zhongguancun Fangzheng building, 9 floor Patentee before: PEKING UNIVERSITY FOUNDER GROUP Co.,Ltd. Patentee before: Beijing Beida Founder Electronics Co., Ltd. |
|
| TR01 | Transfer of patent right |