CN102843519A - Image processing system and method - Google Patents
Image processing system and method Download PDFInfo
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- CN102843519A CN102843519A CN2011101714217A CN201110171421A CN102843519A CN 102843519 A CN102843519 A CN 102843519A CN 2011101714217 A CN2011101714217 A CN 2011101714217A CN 201110171421 A CN201110171421 A CN 201110171421A CN 102843519 A CN102843519 A CN 102843519A
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Abstract
The invention discloses an image processing system and an image processing method. The method comprises the following steps: acquiring a plurality of images taken by an electronic device; acquiring the red green blue (RGB) values of a first pixel point of each image; analyzing the R value, the G value and the B value of the first pixel point of each image respectively to select the R values, the G values and the B values at a preset proportion; computing the average values of the R values, the G values and the B values selected respectively and taking the average values as the average values of the R values, the G values and the B values of the first pixel points of the images; computing the average values of the R values, the G values and the B values of the rest pixel points of the images; and forming a new image according to the average values of the R values, the G values and the B values of all the pixel points of the images. Due to the adoption of the image processing system and the image processing method, the images taken by the electronic device can be processed automatically to form an image with a best average color.
Description
Technical field
The present invention relates to a kind of control system and method, relate in particular to a kind of image processing system and method.
Background technology
Traditional photography machine (like digital camera) only possesses one group of photo-sensitive cell mostly, so, only can obtain the single width image when taking at every turn, can't when single shot, produce several images simultaneously with Multi sensor.Therefore, when the user takes still life with the traditional photography machine, easily because of factors such as focusing situation, light; The photo that can't once promptly take the photograph satisfiedly; Often need repeat to take several photos, can constantly revise shooting quality, therefrom select the image frame an of the best.But shooting process is very consuming time repeatedly, makes that the shooting efficient of traditional photography machine is comparatively not good.
Though the Multi sensor video camera (Multi-Sensor Camera) of sale is arranged at present on the market; But all can only utilize a plurality of photo-sensitive cells in the video camera to obtain many images at one time; Manually from these many images, select the best image of a shooting quality by the user then; The mode of this manual selection is made troubles to the user equally, has reduced the shooting efficient of video camera.
Summary of the invention
In view of above content, be necessary to provide a kind of image processing system and method, its many images that can absorb at one time the Multi sensor video camera are automatically handled, and generate an average color and luster image of the best.
A kind of image processing system, this system comprises:
Image acquiring module is used to obtain many images that a plurality of photo-sensitive cells of electronic equipment absorb at one time;
The pixel acquisition module is used to obtain the RGB numerical value of every first pixel of image;
Pixel is selected module, is used for respectively R value, G value and the B value of every first pixel of image being analyzed, to select R value, G value and the B value of preset ratio;
Pixel mean value calculation module is used for calculating respectively the mean value of selected R value, G value, B value, as the mean value of the R value of these many first pixels of image, G value, B value;
The double counting module is used for according to above-mentioned same procedure, calculates R value, the G value of residual pixel point in these many images, the mean value of B value; And
New image is created module, is used for R value, the G value according to these many all pixels of image, the mean value of B value, sets up a new image, and this new image is presented on the display unit of electronic equipment.
A kind of image treatment method, this method comprises:
The image obtaining step obtains many images that a plurality of photo-sensitive cells of electronic equipment absorb at one time;
The pixel obtaining step obtains the RGB numerical value of every first pixel of image;
Pixel is selected step, respectively R value, G value and the B value of every first pixel of image is analyzed, to select R value, G value and the B value of preset ratio;
Pixel mean value calculation step is calculated the mean value of selected R value, G value, B value respectively, as the mean value of the R value of these many first pixels of image, G value, B value;
The double counting step according to above-mentioned same procedure, is calculated R value, the G value of residual pixel point in these many images, the mean value of B value; And
New image foundation step according to the mean value of the R value of all pixels in these many images, G value, B value, is set up a new image, and this new image is presented on the display unit of electronic equipment.
Preceding method can be carried out by electronic installation, and wherein this electronic installation has and attached one or more processors, memory and be kept at one or more modules, program or the instruction set that is used to carry out these methods in the memory.In certain embodiments, this electronic installation provides the multiple function that comprises radio communication.
The instruction that is used for carrying out preceding method can be included in and be configured to the computer program carried out by one or more processors.
Compared to prior art; Described image processing system and method; Its many images that can absorb at one time the Multi sensor video camera are automatically handled, and generate an average color and luster image of the best, have significantly improved the user and have taken efficiency of operation.
Description of drawings
Fig. 1 is the block diagram of electronic equipment tool of the present invention preferred embodiment.
Fig. 2 is the functional block diagram of image processing system.
Fig. 3 is the flow chart of the preferred embodiment of image treatment method of the present invention.
Fig. 4 is the sketch map that obtains the rgb value of first pixel in many images.
Fig. 5 is a sketch map of from many images of Fig. 4, selecting the R value of preset ratio.
Fig. 6 A is the sketch map of the mean difference of first pixel of image P1 R value in the calculating chart 4.
Fig. 6 B is the sketch map of the mean difference of first pixel of image P5 R value in the calculating chart 4.
Fig. 7 A is the sketch map of mean value of the R value of 10 first pixels of image in the calculating chart 4.
Fig. 7 B is the sketch map of mean value of the G value of 10 first pixels of image in the calculating chart 4.
Fig. 7 C is the sketch map of mean value of the B value of 10 first pixels of image in the calculating chart 4.
Fig. 8 is the sketch map of the mean value of the R value of residual pixel point, G value, B value in 10 images in the calculating chart 4.
The main element symbol description
| |
2 |
| |
20 |
| Memory | ?21 |
| Photo-sensitive cell | ?22 |
| Display unit | ?24 |
| Processor | ?26 |
| Image acquiring module | ?201 |
| The pixel acquisition module | ?202 |
| Pixel is selected module | ?203 |
| Pixel mean value calculation module | ?204 |
| The double counting module | ?205 |
| New image is created module | ?206 |
Following embodiment will combine above-mentioned accompanying drawing to further specify the present invention.
Embodiment
Before introducing the present invention, briefly introduce Multi sensor video camera used among the present invention earlier.
With two photo-sensitive cell video cameras is example, promptly utilizes the prismatic reflection incident light that is coated with optical thin film, prismatic film reflection 50%; 50% sees through; Thereby be divided into two-beam to incident light, and keep two-beam identical spectra characteristic and space polarization characteristic, to produce two width of cloth images simultaneously.In like manner, the prism that three photo-sensitive cell video camera utilizations are coated with optical thin film is divided into three-beam with incident light, like ground floor film reflection 30%; 70% sees through; Second layer film reflection 50%, 50% sees through, and so just is divided into three-beam to incident light; And keep three-beam identical spectra characteristic and space polarization characteristic, to produce three width of cloth images simultaneously.
As shown in Figure 1, be the block diagram of electronic equipment preferred embodiment of the present invention.In the present embodiment, this electronic equipment 2 comprises image processing system 20, memory 21, a plurality of photo-sensitive cell 22 (two are representative shown in the figure), display unit 24 and the processor 26 that links to each other through data/address bus.In the present embodiment, said electronic equipment 2 can be the equipment that video camera or digital camera etc. have shoot function.
Wherein, this memory 21 is used to store the image of a plurality of photo-sensitive cell 22 picked-ups, and the sequencing code of image processing system 20.This image processing system 20 is used for automatic many images that a plurality of photo-sensitive cells 22 of electronic equipment 2 are absorbed at one time to be handled, and generates an average color and luster image of the best, and detailed process is referring to the description of Fig. 3.
In the present embodiment, said a plurality of photo-sensitive cells 22 be in the electronic equipment 2 the sensitization coupling element (Charge Coupled Device, CCD).Said display unit 24 can be the LCD display of electronic equipment 2, is used to show the data such as image of a plurality of photo-sensitive cells picked-ups of electronic equipment 2.
In the present embodiment; Said image processing system 20 can be divided into one or more modules; Said one or more module is stored in the said memory 21 and is configured to and carried out by one or more processors (present embodiment is a processor 26), to accomplish the present invention.For example, consult shown in Figure 2ly, said image processing system 20 is divided into image acquiring module 201, pixel acquisition module 202, pixel and selects module 203, pixel mean value calculation module 204, double counting module 205 and new image to create module 206.The alleged module of the present invention is to accomplish the block of a specific function, is more suitable in describing the implementation of software in electronic equipment 2 than program.
As shown in Figure 3, be the flow chart of the preferred embodiment of image treatment method of the present invention.
Step S10, image acquiring module 201 is obtained many images that a plurality of photo-sensitive cells 22 of electronic equipment 2 absorb at one time, and many images that will this same time picked-up are saved in the memory 21.
Step S11, pixel acquisition module 202 extract many images of this same time picked-up from memory 21, and obtain RGB (Red, Green, Blue) numerical value of every first pixel of image.This RGB numerical value comprises: the R value of first pixel, G value, B value.Consult shown in Figure 4; Present embodiment comprises that with electronic equipment 2 10 photo-sensitive cells are that example describes; Then electronic equipment 2 single shot are obtained 10 images simultaneously; Pixel acquisition module 202 obtains the rgb value of first pixel in these 10 images, i.e. the rgb value of first pixel in every image obtains the rgb value of 10 pixels altogether.
Step S12, pixel select module 203 respectively R value, G value and the B value of every first pixel of image to be analyzed, to select R value, G value and the B value of preset ratio.In the present embodiment, said preset ratio is 80%.Consult shown in Figure 5ly, pixel selects module 203 to select immediate 80% data of R value (being P1, P2, P3, P4, P6, P8, P9, P10), gets rid of the different 20% excessive data of R value difference (being P5, P7).
For example, the computational methods of the R value of said selection preset ratio are following:
At first; Pixel selects module 203 to calculate the difference between the R value of R value and other first pixel of image of every first pixel of image respectively; Then this difference is taken absolute value; The mean value of all differences after calculating takes absolute value obtains the mean difference of first pixel of every image R value.Then, pixel selects module 203 to select 80% minimum R value of mean differences, and 20% R value of mean difference maximum is got rid of.
For example, consult shown in Fig. 6 A, the mean difference of first pixel of image P1 R value=(3+3+10+44+13+39+6+6+4)/9=14.22.
Consult shown in Fig. 6 B, the mean difference of first pixel of image P5 R value=(44+41+47+34+31+83+38+38+48)/9=44.88.
The mean difference of first pixel of the image P5 R value that calculates is 44.88; And the mean difference of first pixel of image P1 R value is 14.22; This result represents the mean difference of the R value of first pixel of image P5, and is bigger than the mean difference of the R value of first pixel of image P1.According to said method calculate the mean difference that can obtain first pixel of other image R value, get rid of the R value of image P5 and first pixel of P7 at last.
In like manner, according to said method, pixel selects module 203 can select the G value and the B value of preset ratio.
Step S13, pixel mean value calculation module 204 is calculated the mean value of selected R value, G value, B value respectively, as the mean value of the R value of these many first pixels of image, G value, B value.
For example, consult shown in Fig. 7 A, the mean value of the R value of first pixel of 8 images after selecting through step S12=(165+162+168+155+152+159+159+169)/8=161 (round numbers).
Consult shown in Fig. 7 B, the mean value of the G value of these 8 first pixels of image=(158+156+160+154+155+154+158+153)/8=156 (round numbers).
Consult shown in Fig. 7 C, the mean value of the B value of these 8 first pixels of image=(197+194+195+190+194+192+196+193)/8=194 (round numbers).
Obtain the RGB mean value (161,156,194) of these 8 first pixels of image when system after, this RGB mean value is the best average color and luster (161,156,194) of these 10 first pixels of image.
Step S14, the method that double counting module 205 is identical according to above-mentioned steps S11-S13 is calculated R value, the G value of residual pixel point in these many images (second pixel, the 3rd pixel ...), the mean value of B value, consults shown in Figure 8.Because computational methods are similar, repeat no more at this.
Step S15, the mean value of the R value of all pixels, G value, B value is set up a new image, and should be presented on the display unit 24 by new image in new image establishment module 206 these many images of basis.Wherein, this new image is the best average color and luster image of electronic equipment 2 picked-up this time.For example, the rgb value of first pixel of new image is R value, the G value of all pixels in these many images, the mean value (161,156,194) of B value.
In other embodiments, this method comprises the steps: that also the new image that new image establishment module 206 will be set up is saved in the memory 21.
What should explain at last is; Above embodiment is only unrestricted in order to technical scheme of the present invention to be described; Although the present invention is specified with reference to preferred embodiment; Those of ordinary skill in the art should be appreciated that and can make amendment or be equal to replacement technical scheme of the present invention, and do not break away from the spirit and the scope of technical scheme of the present invention.
Claims (10)
1. an image processing system is characterized in that, this system comprises:
Image acquiring module is used to obtain many images that a plurality of photo-sensitive cells of electronic equipment absorb at one time;
The pixel acquisition module is used to obtain the RGB numerical value of every first pixel of image;
Pixel is selected module, is used for respectively R value, G value and the B value of every first pixel of image being analyzed, to select R value, G value and the B value of preset ratio;
Pixel mean value calculation module is used for calculating respectively the mean value of selected R value, G value, B value, as the mean value of the R value of these many first pixels of image, G value, B value;
The double counting module is used for according to above-mentioned same procedure, calculates R value, the G value of residual pixel point in these many images, the mean value of B value; And
New image is created module, is used for R value, the G value according to these many all pixels of image, the mean value of B value, sets up a new image, and this new image is presented on the display unit of electronic equipment.
2. image processing system as claimed in claim 1 is characterized in that, said pixel selects module to select the R value of preset ratio to comprise:
Calculate the difference between the R value of R value and other first pixel of image of every first pixel of image respectively, this difference is taken absolute value;
The mean value of all differences after calculating takes absolute value obtains the mean difference of first pixel of every image R value; And
Select the R value of this minimum preset ratio of mean difference.
3. image processing system as claimed in claim 2 is characterized in that, said pixel selects module according to the same procedure of selecting preset ratio R value, selects the G value and the B value of preset ratio.
4. image processing system as claimed in claim 2 is characterized in that, said preset ratio is 80%.
5. image processing system as claimed in claim 1 is characterized in that, said new image is created module and also is used for: the new image that will set up is saved to memory.
6. an image treatment method is characterized in that, this method comprises:
The image obtaining step obtains many images that a plurality of photo-sensitive cells of electronic equipment absorb at one time;
The pixel obtaining step obtains the RGB numerical value of every first pixel of image;
Pixel is selected step, respectively R value, G value and the B value of every first pixel of image is analyzed, to select R value, G value and the B value of preset ratio;
Pixel mean value calculation step is calculated the mean value of selected R value, G value, B value respectively, as the mean value of the R value of these many first pixels of image, G value, B value;
The double counting step according to above-mentioned same procedure, is calculated R value, the G value of residual pixel point in these many images, the mean value of B value; And
New image foundation step according to the mean value of the R value of all pixels in these many images, G value, B value, is set up a new image, and this new image is presented on the display unit of electronic equipment.
7. image treatment method as claimed in claim 6 is characterized in that, said pixel selects to select in the step R value of preset ratio to comprise:
Calculate the difference between the R value of R value and other first pixel of image of every first pixel of image respectively, this difference is taken absolute value;
The mean value of all differences after calculating takes absolute value obtains the mean difference of first pixel of every image R value; And
Select the R value of this minimum preset ratio of mean difference.
8. image treatment method as claimed in claim 7 is characterized in that, the G value of said selection preset ratio is identical with the method for selecting preset ratio R value with the method for B value.
9. image treatment method as claimed in claim 7 is characterized in that, said preset ratio is 80%.
10. image treatment method as claimed in claim 6 is characterized in that, this method also comprises step: the new image that will set up is saved in the memory.
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Application publication date: 20121226 |