CN104113698A - Blurred image processing method and system applied to image capturing device - Google Patents
Blurred image processing method and system applied to image capturing device Download PDFInfo
- Publication number
- CN104113698A CN104113698A CN201410382776.4A CN201410382776A CN104113698A CN 104113698 A CN104113698 A CN 104113698A CN 201410382776 A CN201410382776 A CN 201410382776A CN 104113698 A CN104113698 A CN 104113698A
- Authority
- CN
- China
- Prior art keywords
- image
- capture device
- image capture
- movable information
- processing method
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Studio Devices (AREA)
Abstract
The application discloses a blurred image processing method and system applied to an image capturing device. The blurred image processing method comprises the steps of: recording motion information of the image capturing device; restoring a continuous line formed in the blurred image into pixel points in a brilliant image due to shaking of the image capturing device so as to perform compensation on the blurred image. Recording is carried out once the image capturing action starts and is ended automatically after the action is ended, so that time for feedback and adjustment is unnecessary, and the reaction speed is sensitive. The device motion information during the image capturing process can be recorded completely, image blurring caused by component motion parallel with an optical axis and a relatively great vibration amplitude can be restored appropriately. A focusing system does not move during the shooting, so that no relative displacement of a lens and a light-sensing element is generated, and the imaging of the whole image capturing device is more stable and more reliable. Shooting parameters sets by the user are not adjusted automatically, so that reduction of the imaging effect caused by increase of picture noise is also avoided.
Description
Technical field
The present invention relates to a kind of fuzzy image processing method and system that is applied to image capture device.
Background technology
The anti-shake system of current image capture device is divided into two classes, the anti-shake and electronic flutter-proof of optics.The anti-shake camera of being more common in of optics, in video camera, is divided into again lens group anti-shake anti-shake with photo-sensitive cell.The former anti-shake parts concentrate on camera lens, comprise produced color difference group and feedback processing circuit, more eyeglass makes lens assembling difficulty higher, extremely strict for optical axis deflection required precision in compensating movement, and single-lens cost, volume and weight are all significantly increased; Feedback circuit signal delay, computing required time and feedback action time restriction its compensatory reactionBu Changfanying speed; The confined space in camera lens has limited the amplitude of compensating movement, and then limits the size of the Oscillation Amplitude that can compensate.
The principle that realizes of electronic flutter-proof is that photo-sensitive cell is placed on movable framework, utilize electromagnetism hysteresis, or counter motion after calculating compensation, make photo-sensitive cell keep relative static with target subject within the short time of exposure, owing to can only do the slip that is parallel to focal plane in camera, the component motion that is parallel to optical axis for camera cannot compensate, be limited by addition mobile range and the requirement to Iimaging Stability in camera, for the vibration that amplitude is slightly large, just can not bring into play good effect, and optical center optical axis can depart from photo-sensitive cell center in mobile, cause poor edge imaging to invade final image.
Publication No. is that the patent documentation of CN101266381A has been announced a kind of image stabilizing device, it comprises movable units and controller, described movable units has image device, and can move and rotate when carrying out anti-shake operation, described controller is controlled the movable units for described anti-shake operation, controller obtains the information about the resolution at the lens edge place of the imaging operation for image device, and described controller is controlled for correcting the degree of the described anti-shake operation of the hand shake being caused by rolling according to the resolution at lens edge place.The shortcoming of this technology is to realize comparatively load, and the efficiency of image stabilization is not high.
Summary of the invention
The object of the invention is to overcome above-mentioned deficiency, a kind of fuzzy image processing method and system that is applied to image capture device is provided, it realizes simple, and imaging is stable.
To achieve these goals, the technical solution used in the present invention is:
A fuzzy image processing method that is applied to image capture device, is characterized in that, comprising:
The movable information of image capture device is carried out to record;
According to recorded movable information, make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.
Preferably, wherein, the step that the described movable information to image capture device records comprises: the attitude information of document image capture device, motion velocity information, motion track information.
Preferably, wherein, the step that the described movable information to image capture device records also comprises: described movable information is stored.
Preferably, wherein, the step of the described compensation of carrying out blurred picture also comprises: detect the step of front and back image correlation and resonable degree, and/or detect the step of last synthetic image acceptable degree.
Preferably, wherein, before and after described detection, the step of image correlation and resonable degree adopts: the calculating of color space and transfer algorithm.
Preferably, wherein, the step of the last synthetic image acceptable degree of described detection adopts: Shape context algorithm, Chi-square Test algorithm, and/or dynamic time warping algorithm.
A fuzzy image processing system that is applied to image capture device, is characterized in that, comprising:
Record cell, for carrying out record to the movable information of image capture device;
Compensating unit, for according to recorded movable information, makes the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.
Preferably, wherein, described record cell comprises memory.
Preferably, wherein, described record cell is connected with image capture device by hot shoe.
Preferably, wherein, described record cell is by the movable information of built-in gyroscope document image capture device.
Beneficial effect of the present invention is:
The first, after starting, image capture action starts immediately record, after release, automatically finish, without the time of feedback and adjustment, reaction speed is sensitive.
The second, the equipment moving information during complete documentation image capture, can appropriateness repairs and is parallel to image blurring that the component motion of optical axis and larger vibration amplitude cause.
The 3rd, during shooting, focusing system is without any movement, and camera lens and photo-sensitive cell can not produce any relative displacement, and the imaging of whole image capture device is more reliable and more stable.
The 4th, automatically do not adjust the parameter of taking pictures that user sets, the noise that therefore also just can not increase picture causes imaging effect to decline.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide further understanding of the present application, forms the application's a part, and the application's schematic description and description is used for explaining the application, does not form the improper restriction to the application.In the accompanying drawings:
Fig. 1 is the schematic flow sheet that is applied to the fuzzy image processing method of image capture device of the present invention;
Fig. 2 is the structural representation that is applied to the fuzzy image processing system of image capture device of the present invention;
Fig. 3 is the workflow schematic diagram of the record cell of system shown in Figure 2;
Fig. 4 is the workflow schematic diagram of the compensating unit of system shown in Figure 2.
Embodiment
As used some vocabulary in the middle of specification and claim, censure specific components.Those skilled in the art should understand, and hardware manufacturer may be called same assembly with different nouns.This specification and claims are not used as distinguishing the mode of assembly with the difference of title, but the difference in function is used as the criterion of distinguishing with assembly.If " comprising " mentioned in the middle of specification and claim is in the whole text an open language, therefore should be construed to " comprise but be not limited to "." roughly " refer to that in receivable error range, those skilled in the art can solve the technical problem within the scope of certain error, reach described technique effect substantially.Specification subsequent descriptions is for implementing the application's better embodiment, and right described description is to illustrate that the application's rule is object, not in order to limit the application's scope.The application's protection range is when being as the criterion depending on the claims person of defining.
Embodiment 1
Please refer to Fig. 1, the fuzzy image processing method that is applied to image capture device of the present invention comprises: S100, carries out record to the movable information of image capture device; S200, carries out the compensation of blurred picture according to recorded movable information, make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.In specific embodiment, image capture device is for example various digital photography equipment, digital camera.
Preferably, the step that the described movable information to image capture device records comprises: the attitude information of document image capture device, motion velocity information, motion track information.
Preferably, the step that the described movable information to image capture device records also comprises: described movable information is stored.
Preferably, the described compensation of carrying out blurred picture according to recorded movable information comprises: make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device.Blurred picture for producing because of shake, is comparatively common in time-lapse photography, and cameraman, by light source fast moving between exposure period that brightness is enough, forms the word or the pattern that need.
In specific embodiment, suppose a kind of simplified model: in the background of complete darkness, light source is enough little and be arranged at far place, so in the situation that focusing clutch is suitable, if light source and camera are all static, in the image of finally catching, only there is a single pixel sensitization, it is the size that light source only takies a pixel, if camera shake, original photosensitive unit and photosensitive unit around thereof can be exposed continuously in succession,, in the image of finally catching, originally represent that the single pixel of light source just can become a continuous line.
Therefore, according to the described shake track data identifying, just can extrapolate by corresponding algorithm the single pixel of actual light source representative from described capture-data information, and all the other show as, the pixel of " optical track trace " should be for dark; For the photosensitive pixel after reduction, its brightness should be the brightness sum of each photosensitive pixel in blurred picture, and the pixel that is equivalent to respectively light has been shared the due time for exposure of former pixel, therefore calculate total brightness, is similar to addition.
Color should be associated with the color that the pixel respectively lighting presents, because photographic process belongs to the process of following additive color principle, in above-mentioned simplified model, whole background presents black, therefore bring other colors into pixel in " optical track trace ", only need to adjust brightness; For the situation of many colors, need corresponding color algorithm assistant analysis background colour around, and using having removed the color after background colour as one of reference color of former pixel, after a plurality of reference colors are comprehensive, calculate suitable color as former pixel color.
Preferably, the described compensation of carrying out blurred picture according to recorded movable information also comprises: the step of image correlation and resonable degree before and after detecting, and/or detect the step of last synthetic image acceptable degree.
Preferably, before and after described detection, the step of image correlation and resonable degree adopts: the calculating of color space and transfer algorithm.
The purposes of color space is by common acceptable mode, to simplify colored standard under some standard.In real figure image is processed, the most general model towards hardware is RGB (red, green, blue) model.This model is for colour picture monitor and a large class color video video camera.YUV (simulation PAL) (brightness, aberration R-Y, G-Y) or numeral (YCbCr) color space are applied in modern color TV.Hue, saturation, intensity (HIS) model more meets that people describes and the mode of explain color converts and much in documents, having description from RGB to HSI, and result is as follows:
Wherein,
In formula, the excursion of each amount is [0,1]
Preferably, the step of the last synthetic image acceptable degree of described detection adopts: Shape context (shape context) algorithm, picture shape is not to express with certain region or profile, but characteristic point point set discrete by some and that be evenly distributed is expressed, then each characteristic point of concentrating for point, calculate its corresponding shape histogram, it has recorded this characteristic point to the whole Vector Message of other all characteristic points.Finally the matching problem between picture shape is converted into the Correspondent problem of finding between two characteristic point point sets.
Suppose that the two width images that need to carry out form fit are respectively image f and image g, by rim detection and profile track algorithm, the point set that comprises n characteristic point extracting is respectively P={p1, p2 ... pn} and q1, q2 ... qn}.
For each the characteristic point pi in image f (1 <=i <=n), we need to find a characteristic point qj (1 <=j <=n) who mates Least-cost with it in image g, suppose that the corresponding result of finding out is j=r (i).The similarity problem between computed image shape is just converted into and asks
minimum problems.
In Shape context algorithm, the Edge Feature Points that requirement extracts is evenly distributed as much as possible, because this directly affects the computation structure of shape histogram, therefore need edge image to carry out profile tracking, the result of tracking is to make marginal point carry out queue with edge direction order.
Selected characteristic point is the key link in Shape context, if the characteristic point number of choosing is too much, can make the amount of calculation of algorithm very large, causes time complexity to become large.But the characteristic point number of choosing is very few, can lose a lot of marginal informations, causes retrieval error.In traditional Shape context, the number of characteristic point is generally chosen for 100 or 150.
Embodiment 2
The fuzzy image processing method that is applied to image capture device of the present invention comprises: S100, carries out record to the movable information of image capture device; S200, carries out the compensation of blurred picture according to recorded movable information, make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.In specific embodiment, image capture device is for example various digital photography equipment, digital camera.
Preferably, the step that the described movable information to image capture device records comprises: the attitude information of document image capture device, motion velocity information, motion track information.
Preferably, the step that the described movable information to image capture device records also comprises: described movable information is stored.
Preferably, the described compensation of carrying out blurred picture according to recorded movable information comprises: make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device.Blurred picture for producing because of shake, is comparatively common in time-lapse photography, and cameraman, by light source fast moving between exposure period that brightness is enough, forms the word or the pattern that need.
In specific embodiment, suppose a kind of simplified model: in the background of complete darkness, light source is enough little and be arranged at far place, so in the situation that focusing clutch is suitable, if light source and camera are all static, in the image of finally catching, only there is a single pixel sensitization, it is the size that light source only takies a pixel, if camera shake, original photosensitive unit and photosensitive unit around thereof can be exposed continuously in succession,, in the image of finally catching, originally represent that the single pixel of light source just can become a continuous line.
Therefore, according to the described shake track data identifying, just can extrapolate by corresponding algorithm the single pixel of actual light source representative from described capture-data information, and all the other show as, the pixel of " optical track trace " should be for dark; For the photosensitive pixel after reduction, its brightness should be the brightness sum of each photosensitive pixel in blurred picture, and the pixel that is equivalent to respectively light has been shared the due time for exposure of former pixel, therefore calculate total brightness, is similar to addition.
Color should be associated with the color that the pixel respectively lighting presents, because photographic process belongs to the process of following additive color principle, in above-mentioned simplified model, whole background presents black, therefore bring other colors into pixel in " optical track trace ", only need to adjust brightness; For the situation of many colors, need corresponding color algorithm assistant analysis background colour around, and using having removed the color after background colour as one of reference color of former pixel, after a plurality of reference colors are comprehensive, calculate suitable color as former pixel color.
Preferably, the described compensation of carrying out blurred picture according to recorded movable information also comprises: the step of image correlation and resonable degree before and after detecting, and/or detect the step of last synthetic image acceptable degree.
Preferably, before and after described detection, the step of image correlation and resonable degree adopts: the calculating of color space and transfer algorithm.
The purposes of color space is by common acceptable mode, to simplify colored standard under some standard.In real figure image is processed, the most general model towards hardware is RGB (red, green, blue) model.This model is for colour picture monitor and a large class color video video camera.YUV (simulation PAL) (brightness, aberration R-Y, G-Y) or numeral (YCbCr) color space are applied in modern color TV.Hue, saturation, intensity (HIS) model more meets that people describes and the mode of explain color converts and much in documents, having description from RGB to HSI, and result is as follows:
Wherein,
In formula, the excursion of each amount is [0,1]
Preferably, the step of the last synthetic image acceptable degree of described detection adopts Chi-square Test algorithm.Its principle is: the canonical form of image degradation model can be expressed by the conversion of original image, that is:
y＝Hx+n
X is wherein original image, and H is fuzzy matrix, and n is additive noise.Additive noise is often caused by the electronic devices and components of imaging system, irrelevant with original image itself.And the statistical property of additive noise can obtain by priori.Main concern makes image blurring degradation model herein, here additive noise put aside, therefore, above formula can be reduced to degradation model the convolution of original image and fuzzy model again, that is:
y＝Hx
Adopt χ
2the method of check estimates the distributed model of degraded image, and Chi-square Test is method the most frequently used in hypothesis testing, and its advantage can checked for the distributional assumption of any unknown parameters with it.Probability density distribution the unknown of measured value and sample size is known, and the frequency distribution of measured value can calculate by frequency zones k, the expected frequency that hypothetical probabilities distributes so also just can cicada, and then comparative observation value distributes and hypothesis distribution, by following formula, calculates test statistics:
α wherein
ifrequency distribution for measured value; β
ifrequency for hypothetical probabilities density fonction; K is frequency zones quantity; N
mfor the number of distributed model, be 4 herein.The chi-square test statistic is here used for Test hypotheses model and whether meets measured value, χ
2value will be in 0 between infinity, and the distribution that observation obtains is more irregular, and estimated value will be higher; Otherwise observation sample more meets with expectation sample, χ
2value more levels off to 0.
Embodiment 3
The fuzzy image processing method that is applied to image capture device of the present invention comprises: S100, carries out record to the movable information of image capture device; S200, carries out the compensation of blurred picture according to recorded movable information, make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.In specific embodiment, image capture device is for example various digital photography equipment, digital camera.
Preferably, the step that the described movable information to image capture device records comprises: the attitude information of document image capture device, motion velocity information, motion track information.
Preferably, the step that the described movable information to image capture device records also comprises: described movable information is stored.
Preferably, the described compensation of carrying out blurred picture according to recorded movable information comprises: make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device.Blurred picture for producing because of shake, is comparatively common in time-lapse photography, and cameraman, by light source fast moving between exposure period that brightness is enough, forms the word or the pattern that need.
In specific embodiment, suppose a kind of simplified model: in the background of complete darkness, light source is enough little and be arranged at far place, so in the situation that focusing clutch is suitable, if light source and camera are all static, in the image of finally catching, only there is a single pixel sensitization, it is the size that light source only takies a pixel, if camera shake, original photosensitive unit and photosensitive unit around thereof can be exposed continuously in succession,, in the image of finally catching, originally represent that the single pixel of light source just can become a continuous line.
Therefore, according to the described shake track data identifying, just can extrapolate by corresponding algorithm the single pixel of actual light source representative from described capture-data information, and all the other show as, the pixel of " optical track trace " should be for dark; For the photosensitive pixel after reduction, its brightness should be the brightness sum of each photosensitive pixel in blurred picture, and the pixel that is equivalent to respectively light has been shared the due time for exposure of former pixel, therefore calculate total brightness, is similar to addition.
Color should be associated with the color that the pixel respectively lighting presents, because photographic process belongs to the process of following additive color principle, in above-mentioned simplified model, whole background presents black, therefore bring other colors into pixel in " optical track trace ", only need to adjust brightness; For the situation of many colors, need corresponding color algorithm assistant analysis background colour around, and using having removed the color after background colour as one of reference color of former pixel, after a plurality of reference colors are comprehensive, calculate suitable color as former pixel color.
Preferably, the described compensation of carrying out blurred picture according to recorded movable information also comprises: the step of image correlation and resonable degree before and after detecting, and/or detect the step of last synthetic image acceptable degree.
Preferably, before and after described detection, the step of image correlation and resonable degree adopts: the calculating of color space and transfer algorithm.
The purposes of color space is by common acceptable mode, to simplify colored standard under some standard.In real figure image is processed, the most general model towards hardware is RGB (red, green, blue) model.This model is for colour picture monitor and a large class color video video camera.YUV (simulation PAL) (brightness, aberration R-Y, G-Y) or numeral (YCbCr) color space are applied in modern color TV.Hue, saturation, intensity (HIS) model more meets that people describes and the mode of explain color converts and much in documents, having description from RGB to HSI, and result is as follows:
Wherein,
In formula, the excursion of each amount is [0,1]
Preferably, the step of the last synthetic image acceptable degree of described detection adopts: dynamic time warping algorithm.This calculation ratio juris is Data Matching comparison, acquisition of image data first, then, through end-point detection, find out valid data and other invalid datas to deleting; Then pass through MFCC feature extraction, obtain the feature of image, then, carry out the comparison of Euclidean distance, the minimum corresponding template of distance, is recognition result.
Embodiment 4
Please refer to Fig. 2, a kind of fuzzy image processing system that is applied to image capture device of the present invention comprises: record cell 100, for the movable information of image capture device is carried out to record; Compensating unit 200, for according to recorded movable information, makes the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.Preferably, described image capture device is digital image equipment.
Preferably, described record cell 100 is connected with image capture device by hot shoe, and preferably, described hot shoe is dovetail groove, is the fixed interface groove that described digital image equipment connects various provisional external equipments.
As specific embodiment, in the groove of hot shoe, be equipped with the interface that the power connection of the normal work of these provisional external equipments and audio signal input are provided, these interfaces are all designed to the form in groove of hiding mostly, preferably, described hot shoe is provided with hot shoe lid, there are two parallel metal valleys on hot shoe surface, is used for clamping the fastening bolt of these external equipments.
As specific embodiment, described hot shoe has single contact, double-contact, or three contacts.Contact is different, and function is different, and contact is more, and function is just more, and for example TTL flash of light, must have special contact to respond to, and minimum contact is one, just only draws the function of sudden strain of a muscle, and flash of light output variable needs oneself to control completely.
As specific embodiment, as shown in Figure 3, described record cell 100 is fixedly connected with digital image equipment by hot shoe, and carries out exchanges data by the contact on hot shoe.Certainly, when described record cell 100 and digital image equipment are connected use for the first time, need to carry out some initializing sets, such as connecting digital camera, need to set camera model etc., now, can in described record cell 100, arrange one can be online or the database that uses of off-line, according to described digital camera model, obtains the relevant parameter that initialization needs.
As specific embodiment, at the shutter release button of digital camera, pressed but intermittence that shutter is not opened, the intermittence that starts focusing and trigger shutter at digital camera, complete exchanges data, described camera imports the time for exposure into, described tape deck returns to ready signal after receiving, and described camera is confirmed could start exposure after data have sent and have been correctly received by this ready signal.
Described digital camera discharges the record cell 100 described in shutter synchronous triggering and starts record, preferably, described record cell 100 is by the movable information of built-in gyroscope document image capture device, and the built-in gyroscope of this record cell 100 can carry out sample note at shutter release period.
As specific embodiment, it is the minisize gyroscopes of LY530AL that gyroscope can adopt model, can angle measurement speed reach ± 300 degree/second.LY530AL analog output integrated two single order plate upper filters be used for filtering high-frequency signal: switching capacity low pass filter is (by frequency: 400Hz) He one active filter.The resistance of active filter is 180k Ω, also supports the low pass filter that external ROPT and COPT form.When cabling is longer between LY530AL and ADC, wherein also can adds operational amplifier to strengthen its driving force and meet the requirement of ADC to input signal.
This gyroscope has utilized coriolis force phenomenon, principle is: when object is done periodic vibration or other and moved along X-axis, and it is that Ω z rotatablely moves that XY coordinate system is done angular speed along Z axis, will on this object, produce one along the coriolis force of Y direction, and its vector can be calculated as follows.
In formula: F (t) is coriolis force, m is the quality of this object, and Ω Z is the angular speed of coordinate system rotation, and x (t) is the vector velocity of this object.
As specific embodiment, described gyroscope can obtain the information such as the component motion (as speed, acceleration) of described digital camera on interior three axles of three virtual axle cartesian coordinate systems (this coordinate system reflection be the locus of camera) and self attitude, also can first obtain the relevant information of described record cell 100, owing to having set up virtual coordinate system, the position of described record cell 100 can be first definite.
Because described record cell 100 is connected with described hot shoe in this example, in the camera of same model, the position of described hot shoe can be thought identical, therefore described hot shoe also can be determined in the position of virtual coordinate system; Secondly in the camera of same model, described hot shoe to the distance of described photo-sensitive cell also can be thought identical, and thus, the position of the single pixel unit of described photo-sensitive cell in coordinate system also determined.
In the present embodiment, the single pixel unit of described photo-sensitive cell is because photo-sensitive cell carries out sensitization formation, described photo-sensitive cell can be CCD (Charge-coupled Device, charge coupled cell) each electric capacity in, also can be each field effect transistor in CMOS (Complementary Metal Oxide Semiconductor, complementary metal oxide semiconductors (CMOS)).
And, in described photo-sensitive cell, each photosensitive unit is evenly distributed by certain rule, thus, the i.e. coordinate in coordinate system according to small number of records unit 100, extrapolate whole pixels place coordinate, because the photo-sensitive cell of camera and the relative position of record cell 100 are fixed, therefore can realize by small number of records unit 100, record the object of a myriad of photosensitive unit entire motion information again.
Described record cell 100 is according to the time for exposure of digital camera input before triggering, and automatic decision quits work and exports log file to storage medium, and wait image processing program is taken.
Described compensating unit 200 is for carry out the compensation of blurred picture according to recorded movable information, to have repaired picture rich in detail.As specific embodiment, as shown in Figure 4, described compensating unit 200 reads and identifies pixel unit fuzzy in described image, from described capture-data information, identify shake track data simultaneously, compensating unit 200 mates this shake track data to carry out image restoring processing with described fuzzy pixel unit, obtain image clearly, the image after finally output is repaired.
The blurred picture compensation deals system that is applied to image capture device of the present invention in use, is equipped built-in or is connected with image capture device by data-interface etc.Before image capture action starts, can import the relevant parameters such as action required time into device, and trigger equipment starts writing task; After device is triggered by synchronously must information by the complete attitude that records camera of built-in gyroscope, movement locus, movement velocity etc., according to the operate time of the end record voluntarily of importing into before triggering.
When each image capture completes, device, by automatically preserving the movable information of just having recorded, together writes storage medium with image file.User can select directly in image capture device or photo is imported to start-up routine after computer, the camera motion information that program automatic acquisition is corresponding with this photo.
In image clearly, a certain characteristic point in the middle of object can be corresponding to a single pixel (as: the cubical summit in image, can certainly be any point in its rib, face), and in blurred picture, these characteristic points can form due to the shake of described image capture device continuous line, and this line and camera motion track are closely related, algorithm becomes the corresponding mobile partial reduction that forms line of the coupling by the two a little, the picture rich in detail that finally output has been repaired.
Beneficial effect of the present invention is:
The first, after starting, image capture action starts immediately record, after release, automatically finish, without the time of feedback and adjustment, reaction speed is sensitive.
The second, the equipment moving information during complete documentation image capture, can appropriateness repairs and is parallel to image blurring that the component motion of optical axis and larger vibration amplitude cause.
The 3rd, during shooting, focusing system is without any movement, and camera lens and photo-sensitive cell can not produce any relative displacement, and the imaging of whole image capture device is more reliable and more stable.
The 4th, automatically do not adjust the parameter of taking pictures that user sets, the noise that therefore also just can not increase picture causes imaging effect to decline.
Above-mentioned explanation has illustrated and has described some preferred embodiments of the application, but as previously mentioned, be to be understood that the application is not limited to disclosed form herein, should not regard the eliminating to other embodiment as, and can be used for various other combinations, modification and environment, and can, in application contemplated scope described herein, by technology or the knowledge of above-mentioned instruction or association area, change.And the spirit and scope that the change that those skilled in the art carry out and variation do not depart from the application, all should be in the protection range of the application's claims.
Claims (10)
1. a fuzzy image processing method that is applied to image capture device, is characterized in that, comprising:
The movable information of image capture device is carried out to record;
According to recorded movable information, make the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.
2. processing method according to claim 1, is characterized in that, the step that the described movable information to image capture device records comprises: the attitude information of document image capture device, motion velocity information, motion track information.
3. processing method according to claim 2, is characterized in that, the step that the described movable information to image capture device records also comprises: described movable information is stored.
4. processing method according to claim 3, is characterized in that, the step of the described compensation of carrying out blurred picture also comprises: detect the step of front and back image correlation and resonable degree, and/or detect the step of last synthetic image acceptable degree.
5. processing method according to claim 4, is characterized in that, before and after described detection, the step of image correlation and resonable degree adopts: the calculating of color space and transfer algorithm.
6. processing method according to claim 5, is characterized in that, the step of the last synthetic image acceptable degree of described detection adopts: Shape context algorithm, Chi-square Test algorithm, and/or dynamic time warping algorithm.
7. a fuzzy image processing system that is applied to image capture device, is characterized in that, comprising:
Record cell, for carrying out record to the movable information of image capture device;
Compensating unit, for according to recorded movable information, makes the continuous line forming in blurred picture be reduced into the pixel in picture rich in detail the shake due to image capture device, to carry out the compensation of blurred picture.
8. treatment system according to claim 7, is characterized in that: described record cell comprises memory.
9. treatment system according to claim 8, is characterized in that: described record cell is connected with image capture device by hot shoe.
10. treatment system according to claim 9, is characterized in that, described record cell is by the movable information of built-in gyroscope document image capture device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410382776.4A CN104113698A (en) | 2014-08-06 | 2014-08-06 | Blurred image processing method and system applied to image capturing device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410382776.4A CN104113698A (en) | 2014-08-06 | 2014-08-06 | Blurred image processing method and system applied to image capturing device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104113698A true CN104113698A (en) | 2014-10-22 |
Family
ID=51710322
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410382776.4A Pending CN104113698A (en) | 2014-08-06 | 2014-08-06 | Blurred image processing method and system applied to image capturing device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104113698A (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105163027A (en) * | 2015-09-09 | 2015-12-16 | 韩叔桓 | Shake-eliminating method of camera lens |
| CN105547458A (en) * | 2016-01-04 | 2016-05-04 | 华北理工大学 | Single-mass vibration fuzzy image acquisition and vibration parameter visual measurement experiment platform |
| CN105893515A (en) * | 2016-03-30 | 2016-08-24 | 腾讯科技（深圳）有限公司 | Information processing method and server |
| CN106411493A (en) * | 2015-07-27 | 2017-02-15 | 腾讯科技（深圳）有限公司 | Streetscape acquisition data synchronization method, device and system |
| CN106412495A (en) * | 2015-07-28 | 2017-02-15 | 福特全球技术公司 | Vehicle with hyperlapse video and social networking |
| CN106817534A (en) * | 2015-11-27 | 2017-06-09 | 三星电子株式会社 | Control the imageing sensor and the mobile device including it of gyro sensor |
| CN107040711A (en) * | 2015-11-11 | 2017-08-11 | 佳能株式会社 | Device for image stabilization and its control method |
| CN108737734A (en) * | 2018-06-15 | 2018-11-02 | Oppo广东移动通信有限公司 | Image compensation method and device, computer readable storage medium and electronic equipment |
| CN110493488A (en) * | 2018-05-15 | 2019-11-22 | 株式会社理光 | Video image stabilization method, Video Stabilization device and computer readable storage medium |
| CN110809797A (en) * | 2017-10-03 | 2020-02-18 | 谷歌有限责任公司 | Micro video system, format and generation method |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009017336A (en) * | 2007-07-06 | 2009-01-22 | Seiko Epson Corp | Imaging device and imaging system |
| CN101543053A (en) * | 2007-02-07 | 2009-09-23 | 索尼株式会社 | Image processing device, image picking-up device, image processing method, and program |
| CN103402056A (en) * | 2013-07-31 | 2013-11-20 | 北京阳光加信科技有限公司 | Compensation processing method and system applied to image capture device |
-
2014
- 2014-08-06 CN CN201410382776.4A patent/CN104113698A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101543053A (en) * | 2007-02-07 | 2009-09-23 | 索尼株式会社 | Image processing device, image picking-up device, image processing method, and program |
| JP2009017336A (en) * | 2007-07-06 | 2009-01-22 | Seiko Epson Corp | Imaging device and imaging system |
| CN103402056A (en) * | 2013-07-31 | 2013-11-20 | 北京阳光加信科技有限公司 | Compensation processing method and system applied to image capture device |
Non-Patent Citations (1)
| Title |
|---|
| 李晓: "基于上下文的形状匹配算法研究与实现", 《中国优秀硕士学位论文全文数据库（电子期刊）》 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106411493A (en) * | 2015-07-27 | 2017-02-15 | 腾讯科技（深圳）有限公司 | Streetscape acquisition data synchronization method, device and system |
| CN106412495A (en) * | 2015-07-28 | 2017-02-15 | 福特全球技术公司 | Vehicle with hyperlapse video and social networking |
| CN105163027A (en) * | 2015-09-09 | 2015-12-16 | 韩叔桓 | Shake-eliminating method of camera lens |
| CN107040711A (en) * | 2015-11-11 | 2017-08-11 | 佳能株式会社 | Device for image stabilization and its control method |
| CN106817534A (en) * | 2015-11-27 | 2017-06-09 | 三星电子株式会社 | Control the imageing sensor and the mobile device including it of gyro sensor |
| CN105547458A (en) * | 2016-01-04 | 2016-05-04 | 华北理工大学 | Single-mass vibration fuzzy image acquisition and vibration parameter visual measurement experiment platform |
| CN105893515A (en) * | 2016-03-30 | 2016-08-24 | 腾讯科技（深圳）有限公司 | Information processing method and server |
| CN110809797A (en) * | 2017-10-03 | 2020-02-18 | 谷歌有限责任公司 | Micro video system, format and generation method |
| US11343429B2 (en) | 2017-10-03 | 2022-05-24 | Google Llc | Microvideo system, format, and method of generation |
| US11595580B2 (en) | 2017-10-03 | 2023-02-28 | Google Llc | Microvideo system, format, and method of generation |
| CN110493488A (en) * | 2018-05-15 | 2019-11-22 | 株式会社理光 | Video image stabilization method, Video Stabilization device and computer readable storage medium |
| CN110493488B (en) * | 2018-05-15 | 2021-11-26 | 株式会社理光 | Video image stabilization method, video image stabilization device and computer readable storage medium |
| CN108737734A (en) * | 2018-06-15 | 2018-11-02 | Oppo广东移动通信有限公司 | Image compensation method and device, computer readable storage medium and electronic equipment |
| CN108737734B (en) * | 2018-06-15 | 2020-12-01 | Oppo广东移动通信有限公司 | Image compensation method and apparatus, computer-readable storage medium, and electronic device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104113698A (en) | Blurred image processing method and system applied to image capturing device | |
| CN103402056B (en) | Be applied to the compensation deals method and system of image capture device | |
| CN109671106B (en) | Image processing method, device and equipment | |
| US10277809B2 (en) | Imaging device and imaging method | |
| CN104902182B (en) | A kind of method and apparatus for realizing continuous auto-focusing | |
| CN101742123A (en) | Image processing apparatus and method | |
| CN109194882A (en) | Image processing method, device, electronic equipment and storage medium | |
| CN101790047A (en) | Image processing equipment, image management device and image management method and program | |
| CN108600638B (en) | Automatic focusing system and method for camera | |
| CN101237529A (en) | Imaging apparatus and imaging method | |
| JP2015072324A (en) | Image processor, imaging device and image processing method | |
| CN107800979A (en) | High dynamic range video image pickup method and filming apparatus | |
| US10484591B2 (en) | Focus adjusting apparatus, focus adjusting method, and image capturing apparatus | |
| CN106131441A (en) | Photographic method and device, electronic equipment | |
| CN109714539B (en) | Image acquisition method and device based on gesture recognition and electronic equipment | |
| CN110519485A (en) | Image processing method, device, storage medium and electronic equipment | |
| CN102404495A (en) | Method for adjusting shooting parameters of digital camera | |
| US7755703B2 (en) | Imaging system | |
| US20230106177A1 (en) | Image capture scene recognition control method and apparatus and image capture device | |
| CN103004179A (en) | Tracking device, and tracking method | |
| CN103795927B (en) | Photographing method and system | |
| CN101470248B (en) | Focusing apparatus and method | |
| CN104038689B (en) | Image processing apparatus and image processing method | |
| Bisagno et al. | Virtual camera modeling for multi-view simulation of surveillance scenes | |
| JP6758964B2 (en) | Control device, image pickup device, control method, program, and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20141022 |