CN104065854A - Image processing method and electronic device - Google Patents
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- CN104065854A CN104065854A CN201410273164.1A CN201410273164A CN104065854A CN 104065854 A CN104065854 A CN 104065854A CN 201410273164 A CN201410273164 A CN 201410273164A CN 104065854 A CN104065854 A CN 104065854A
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Abstract
The invention discloses an image processing method and an electronic device to solve the problem of the prior art that high operational pressure is caused to hardware by image registration during noise reduction by means of fusion of multiple frames of images. The method is applied to the electronic device. The electronic device comprises an image acquisition unit and a motion sensing unit, wherein the motion sensing unit is used for detecting the motion parameters of the image acquisition unit. The method comprises the steps of acquiring the ith motion parameter through the motion sensing unit when the image acquisition unit acquires N frames of continuous images, wherein the ith motion parameter is obtained when the image acquisition unit acquires the ith frame of image in the N frames of images, N is an integer larger than or equal to 2, and i is a positive integer smaller than or equal to N; conducting registration on the N frames of images at least according to the first motion parameter to the Nth motion parameter; processing the N frames of images obtained after registration according to the noise reduction algorithm to enable a noise reduction image to be generated.
Description
Technical field
The present invention relates to image processing field, particularly a kind of image processing method and a kind of electronic equipment.
Background technology
Along with the fast development of digital image acquisition technology, not only the image capture device such as digital camera, digital camera is universal, and also can have good image collecting function equipment such as smart mobile phone, panel computer, intelligent watch.But because the size of photo-sensitive cell in equipment is limited, cause the photosensitive area of single pixel less than normal, the photon numbers that can receive in the unit interval is limited, cause the exposure deficiency of photo in the weak environment of light, imaging effect is very poor.
Two kinds of methods that address this problem are at present: one, and prolonging exposure time, makes photo-sensitive cell obtain enough light inputs, can produce the output compared with high s/n ratio, but camera shake when handheld device is carried out IMAQ can cause motion blur; Its two, the output of photo-sensitive cell is gained, but can amplify ground noise simultaneously, cause image to occur obvious noise, have a strong impact on picture quality.
Adopt ISO to take and can realize shorter, clear picture of time for exposure, but or can introduce a large amount of noises, need to carry out noise reduction process to image.Because noise in data image signal produces at random, so can significantly reduce noise by frames fusion noise reduction, but when handheld device shoot multi-frame images, equally easily there is camera shake, in the time of frames fusion, need to carry out image registration by searching for similar pixel like this, this just causes very large computing pressure to device hardware, and ageing very poor.
Summary of the invention
The application provides a kind of image processing method and a kind of electronic equipment, for solve that prior art exists utilize frames fusion noise reduction time image registration hardware is caused compared with the problem of macrooperation pressure, realize according to motion-sensing unit record camera motion parameter, and then fast multiple image has been carried out to registration according to kinematic parameter.
The application provides a kind of image processing method on the one hand, is applied to electronic equipment, and described electronic equipment comprises image acquisition units and motion-sensing unit, and described motion-sensing unit is for detection of the kinematic parameter of described image acquisition units; Described method comprises: in the time that described image acquisition units is obtained continuous N two field picture, obtain i kinematic parameter by described motion-sensing unit, the kinematic parameter that described i kinematic parameter is described image acquisition units in the time obtaining i two field picture in described N two field picture, N is more than or equal to 2 integer, and i is the positive integer that is less than or equal to N; At least according to the 1st kinematic parameter to the N kinematic parameter, described N two field picture is carried out to registration; Described N two field picture according to noise reduction algorithm after to registration is processed, and generates noise reduction image.
Optionally, described N two field picture is that described image acquisition units is obtained under image preview mode, and described noise reduction image is preview image; Described according to noise reduction algorithm the described N two field picture after to registration process, after generating noise reduction image, described method also comprises: show described preview image by the display unit of described electronic equipment.
Optionally, describedly at least according to the 1st kinematic parameter to the N kinematic parameter, described N two field picture is carried out to registration, comprising: according to described the 1st kinematic parameter to described N kinematic parameter, described N two field picture is carried out to registration one time; Determine the features in described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration.
Optionally, describedly described N two field picture is carried out to registration one time according to described the 1st kinematic parameter to described N kinematic parameter, comprising: determine that the k two field picture in described N two field picture is reference frame, k is the positive integer that is less than or equal to N; Determine the transformation matrix between described i two field picture and described k two field picture according to described i kinematic parameter and k kinematic parameter, wherein, i is not equal to k; According to described transformation matrix, described i two field picture is carried out to image conversion processing, so that described i two field picture after treatment is alignd with described k two field picture.
Optionally, the described features of determining in described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration, comprise: determine in described k two field picture that at least one point or at least one block are described features, k is the positive integer that is less than or equal to N; The search pixel portion corresponding with described features in described i two field picture, wherein, i is not equal to k; Generate the second transformation matrix according to the side-play amount between described features and described pixel portion; According to described the second transformation matrix, described i two field picture is carried out to image conversion processing, align so that described i two field picture after treatment is carried out to secondary with described k two field picture.
Optionally, described according to noise reduction algorithm the described N two field picture after to registration process, generate noise reduction image, comprising: calculate the pixel average of the described N two field picture after registration, generate noise reduction image; Wherein, while calculating the pixel average of the described N two field picture after registration, the weight of described i two field picture becomes negative correlativing relation with the image difference value of the k two field picture as with reference to frame with described i two field picture, or the weight of described i two field picture becomes negative correlativing relation with the time domain difference value of described i two field picture and described k two field picture, described k two field picture is the reference frame in described N two field picture.
The application provides a kind of electronic equipment on the other hand, and described electronic equipment comprises image acquisition units and motion-sensing unit, and described motion-sensing unit is for detection of the kinematic parameter of described image acquisition units; Described electronic equipment comprises: kinematic parameter acquisition module, for in the time that described image acquisition units is obtained continuous N two field picture, obtain i kinematic parameter by described motion-sensing unit, the kinematic parameter that described i kinematic parameter is described image acquisition units in the time obtaining i two field picture in described N two field picture, N is more than or equal to 2 integer, and i is the positive integer that is less than or equal to N; Registration module, at least carrying out registration according to the 1st kinematic parameter to the N kinematic parameter to described N two field picture; Noise reduction module, for according to noise reduction algorithm the described N two field picture after to registration process, generate noise reduction image.
Optionally, described N two field picture is that described image acquisition units is obtained under image preview mode, and described noise reduction image is preview image; Described electronic equipment also comprises: display module, for after generating described noise reduction image, shows described preview image by the display unit of described electronic equipment.
Optionally, described registration module comprises: the first registration submodule, for described N two field picture being carried out to registration one time according to described the 1st kinematic parameter to described N kinematic parameter; The second registration submodule, for determining the features of described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration.
Optionally, described the first registration submodule specifically for: determine that the k two field picture in described N two field picture is reference frame, k is the positive integer that is less than or equal to N; And determine the transformation matrix between described i two field picture and described k two field picture according to described i kinematic parameter and k kinematic parameter, wherein, i is not equal to k; And according to described transformation matrix, described i two field picture is carried out to image conversion processing, so that described i two field picture after treatment is alignd with described k two field picture.
Optionally, described the second registration submodule specifically for: determine in described k two field picture that at least one point or at least one block are described features, k is the positive integer that is less than or equal to N; And in described i two field picture, search for the pixel portion corresponding with described features, wherein, i is not equal to k; And generate the second transformation matrix according to the side-play amount between described features and described pixel portion; And according to described the second transformation matrix, described i two field picture is carried out to image conversion processing, so that being carried out to secondary with described k two field picture, described i two field picture after treatment aligns.
Optionally, described noise reduction module specifically for: calculate the pixel average of the described N two field picture after registration, generate noise reduction image; Wherein, described noise reduction module is in the time calculating the pixel average of the described N two field picture after registration, the weight of described i two field picture becomes negative correlativing relation with the image difference value of the k two field picture as with reference to frame with described i two field picture, or the weight of described i two field picture becomes negative correlativing relation with the time domain difference value of described i two field picture and described k two field picture, described k two field picture is the reference frame in described N two field picture.
The one or more technical schemes that provide in the embodiment of the present application, at least have following technique effect or advantage:
1, in the embodiment of the present application, can obtain kinematic parameter when image by motion-sensing unit record image acquisition units, by corresponding N two field picture registration, and then merge noise reduction with the N two field picture of registration according to kinematic parameter, obtain noise reduction image.Search for similar pixel and carry out the mode of registration with respect to simple dependence, carrying out the spent operand of image registration according to kinematic parameter significantly reduces, and the obtaining along with IMAQ carries out in real time of kinematic parameter, and operand reduce will significantly reduce the time of whole image processing, ageing being largely increased.
2, in the embodiment of the present application, in the image preview stage, the multiple image obtaining is merged to noise reduction and obtain preview image, while carrying out multiple image registration due to the kinematic parameter by motion-sensing unit record consuming time seldom, can in the situation that meeting image and processing ageing requirement, significantly reduce the noise of preview image.
3, in the embodiment of the present application, N two field picture is being carried out after a registration according to the kinematic parameter of motion-sensing unit record, again by the features alignment in each two field picture, search for similar pixel N two field picture is carried out to secondary registration, and then obtain better images match result, to avoid the operating error of motion-sensing unit to cause can not mating completely after registration of N two field picture.
4, in the embodiment of the present application, because N two field picture has carried out registration one time by kinematic parameter, pixel-shift amount between N two field picture be zero or side-play amount very little, therefore search for the operand of similar pixel while carrying out secondary registration and significantly reduce, the spent time is also very short.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of image processing method in the embodiment of the present application 1;
Fig. 2 is the refinement schematic flow sheet of step 102 in the embodiment of the present application 1;
Fig. 3 is the refinement schematic flow sheet of step 104 in the embodiment of the present application 1;
Fig. 4 is the refinement schematic flow sheet of step 105 in the embodiment of the present application 1;
Fig. 5 is the schematic block diagram of electronic equipment in the embodiment of the present application 2;
Fig. 6 is the refinement schematic block diagram of registration module 20 in the embodiment of the present application 2.
Embodiment
The application provides a kind of image processing method and a kind of electronic equipment, for solve that prior art exists utilize frames fusion noise reduction time image registration hardware is caused compared with the problem of macrooperation pressure, realize according to motion-sensing unit record camera motion parameter, and then fast multiple image has been carried out to registration according to kinematic parameter.
Below by accompanying drawing and specific embodiment, present techniques scheme is described in detail, be to be understood that the specific features in the embodiment of the present application and embodiment is the detailed explanation to present techniques scheme, instead of restriction to present techniques scheme, in the situation that not conflicting, the technical characterictic in the embodiment of the present application and embodiment can combine mutually.
Embodiment 1
The application provides a kind of image processing method by embodiment 1, is applied to electronic equipment, and this electronic equipment comprises image acquisition units and motion-sensing unit, and motion-sensing unit is for detection of the kinematic parameter of image acquisition units.Specifically, electronic equipment can be the equipment such as digital camera, Digital Video, smart mobile phone, panel computer, intelligent watch, intelligent glasses, image acquisition units is camera, and its photo-sensitive cell can be charge coupled cell (English: Charge-coupled Device; Be called for short: CCD), can be also complementary metal oxide semiconductors (CMOS) (English: Complementary Metal Oxide Semiconductor; Be called for short: CMOS), or other can carry out the sensitive component of photosensitive imaging.Motion-sensing unit can be acceleration transducer, gyroscope, gravity sensitive meter, rotating vector transducer, etc., it can be realized based on hardware, also can realize based on software, in addition, motion-sensing unit can be also multiple sensing units that are separated or integrate, and the embodiment of the present application will not limit.
Referring to Fig. 1, this image processing method comprises the following steps:
Step 101: in the time that image acquisition units is obtained continuous N two field picture, obtain i kinematic parameter by motion-sensing unit, the kinematic parameter that i kinematic parameter is image acquisition units in the time obtaining i two field picture in N two field picture, N is more than or equal to 2 integer, and i is the positive integer that is less than or equal to N;
Step 102: at least according to the 1st kinematic parameter to the N kinematic parameter, N two field picture is carried out to registration;
Step 103: the N two field picture according to noise reduction algorithm after to registration is processed, generates noise reduction image.
Specifically, in step 101, the value of i is from 1 to N, that is: when image acquisition units is obtained each two field picture, and kinematic parameter corresponding to motion-sensing unit record hypograph collecting unit.
In step 102, can calculate the movement locus of image acquisition units according to the kinematic parameter of record, can know accordingly the drift condition that multiple image is mutual, that is: can obtain the transformation matrix between multiple image according to kinematic parameter corresponding to multiple image, can carry out registration to multiple image according to transformation matrix.
In the specific implementation process of step 102, according to the kinematic parameter of record, multiple image is being carried out after registration, can also carry out secondary registration to N two field picture by the mode of searching for similar pixel, because N two field picture has carried out registration one time by kinematic parameter, pixel-shift amount between N two field picture be zero or side-play amount very little, therefore search for the operand of similar pixel while carrying out secondary registration and significantly reduce, the spent time is also very short.
In step 103, the pixel average of calculating the N two field picture after registration can obtain noise reduction image.Wherein, noise reduction algorithm is the specific algorithm that calculates the pixel average of N two field picture, and it can be the arithmetic mean of asking the pixel of N two field picture, can be also the weighted average of asking N two field picture pixel; Also can be to average in the mode of recurrence, that is: the noise reduction image obtaining according to the mean value of image before, as input, averages noise reduction with a new frame; In addition, while averaging, can be calculate taking frame as unit, can be also taking pixel or block of pixels as unit calculating mean value.In the embodiment of the present application, carrying out noise reduction process for which kind of noise reduction algorithm of concrete employing will not limit.
By technique scheme, can obtain kinematic parameter when image by motion-sensing unit record image acquisition units, by corresponding N two field picture registration, and then merge noise reduction with the N two field picture of registration according to kinematic parameter, obtain noise reduction image.Search for similar pixel and carry out the mode of registration with respect to simple dependence, carrying out the spent operand of image registration according to kinematic parameter significantly reduces, and the obtaining along with IMAQ carries out in real time of kinematic parameter, and operand reduce will significantly reduce the time of whole image processing, ageing being largely increased.
Further, in the embodiment of the present application, N two field picture is that image acquisition units is obtained under image preview mode, and noise reduction image is preview image; In step 103: the N two field picture according to noise reduction algorithm after to registration is processed, and after generating noise reduction image, image processing method also comprises:
Display unit by electronic equipment shows preview image.
Specifically,, in the image preview stage, user need to determine according to the effect of preview image the strategy of IMAQ, therefore higher to ageing requirement.In actual implementation process, can obtain according to the hardware operational capability setting preview image stage of electronic equipment the frame per second of image, as in the situation that operational capability is higher, frame per second can be slightly higher, as it is per second to be greater than 30 frames.
Pass through technique scheme, in the image preview stage, the multiple image obtaining is merged to noise reduction and obtain preview image, while carrying out multiple image registration due to the kinematic parameter by motion-sensing unit record consuming time seldom, can in the situation that meeting image and processing ageing requirement, significantly reduce the noise of preview image.
Further, referring to Fig. 2, step 102: at least according to the 1st kinematic parameter to the N kinematic parameter, N two field picture is carried out to registration, comprising:
Step 104: N two field picture is carried out to registration one time according to the 1st kinematic parameter to the N kinematic parameter;
Step 105: determine the features in N two field picture, by the features alignment in each two field picture in N two field picture, so that N two field picture is carried out to secondary registration.Wherein, features can be pixel or block of pixels.
In technique scheme, N two field picture is being carried out after a registration according to the kinematic parameter of motion-sensing unit record, again by the features alignment in each two field picture, search for similar pixel N two field picture is carried out to secondary registration, and then obtain better images match result, to avoid the operating error of motion-sensing unit to cause can not mating completely after registration of N two field picture.And, because N two field picture has carried out registration one time by kinematic parameter, the pixel-shift amount between N two field picture be zero or side-play amount very little, therefore search for the operand of similar pixel while carrying out secondary registration and significantly reduce, the spent time is also very short.
Concrete, referring to Fig. 3, step 104: according to the 1st kinematic parameter to the N kinematic parameter, N two field picture is carried out to registration one time, comprise following content:
Step 1041: determine that the k two field picture in N two field picture is reference frame, k is the positive integer that is less than or equal to N;
Step 1042: determine the transformation matrix between i two field picture and k two field picture according to i kinematic parameter and k kinematic parameter, wherein, i is not equal to k;
Step 1043: according to transformation matrix, i two field picture is carried out to image conversion processing, so that i two field picture after treatment is alignd with k two field picture.
Specifically, in step 1041, the arbitrary two field picture in N two field picture can be served as with reference to frame, all the other frames in N two field picture all with reference frame registration one by one, and then realize the registration of N two field picture, select under normal circumstances the 1st two field picture in time domain as with reference to frame.For convenience of description, might as well be taking the 1st two field picture as reference frame in the following content of the application, but can not be limited the application's protection range with this.
In step 1042, the value of i is the N-1 number that does not comprise k in 1 to N, taking k=1 as example, the value of i is 2,3, N, that is: by kinematic parameter corresponding to each two field picture in the N-1 two field picture of kinematic parameter corresponding to the 1st two field picture and remainder, calculate in the transformation matrix specific implementation process between the 1st two field picture and i two field picture, can carry out computational transformation matrix based on multiple Mathematical Modeling, as rigid body translation model, affine Transform Model, projective transformation model, nonlinear transformation model, etc.Specifically introduce determining of transformation matrix below as an example of rigid body translation model example, and carry out the mode of a registration by transformation matrix, give an example no longer one by one for implementation the embodiment of the present application of other Mathematical Modeling.
User, taking in the process of continuous N two field picture, due to the slight jitter of hand, will produce the skew of location of pixels between N two field picture, and between two two field pictures, the skew of location of pixels is offset corresponding in the locus of image acquisition units when taking two two field pictures.Therefore, can determine the pixel-shift amount between two corresponding two field pictures by the locus side-play amount of definite image acquisition units.
In rigid body translation model, the combination that the spatial position change of image acquisition units can be regarded as translation, rotates and moves forward and backward, accordingly, the transformation matrix of the pixel-shift between description two two field pictures can be made up of translation matrix, spin matrix and zoom factor.Might as well be taking the plane that is parallel to photosurface as x-y face, be that z axle builds coordinate system perpendicular to the direction of photosurface, wherein, translation matrix is for describing the skew up and down in x-y face of the 1st two field picture and i two field picture, spin matrix is for describing the deviation at the two two field picture visual angles of causing due to the rotation of image acquisition units, and zoom factor is for describing the deviation of two two field picture pixels in the degree of depth causing due to the movement of image acquisition units on z direction of principal axis.
Taking the 1st kinematic parameter as (a
1, b
1, c
1), i kinematic parameter is (a
i, b
i, c
i) be example, translation matrix is (t
x, t
y)
t, t
x=a
1-a
i, t
y=b
1-b
i; Spin matrix is
Wherein θ is the anglec of rotation, can obtain according to the transducer of document image collecting unit rotation status, also can be transformed and be solved out by the 1st kinematic parameter and i kinematic parameter; Zoom factor m=f
1(c
1-c
i), be (c
1-c
i) function, m=k (c in simplified model
1-c
i), k is constant.
In step 1043, after the transformation matrices of determining between the 1st two field picture and i two field picture, can carry out image conversion to i two field picture according to this transformation matrix, the i two field picture after conversion is alignd with the 1st two field picture.Continue to use the example of aforementioned rigid body translation model, after determining translation matrix, spin matrix and zoom factor, can be for every bit (x in i two field picture
ij, y
ij) the following processing of do:
A little (x' of institute
ij, y'
ij) form conversion after once align with the 1st two field picture after i two field picture.
Further, referring to Fig. 4, step 105: determine the features in N two field picture, by the features alignment in each two field picture in N two field picture, so that N two field picture is carried out to secondary registration, comprising:
Step 1051: determine in k two field picture that at least one point or at least one block are features, k is the positive integer that is less than or equal to N;
Step 1052: the search pixel portion corresponding with features in i two field picture, wherein, i is not equal to k;
Step 1053: generate the second transformation matrix according to the side-play amount between features and pixel portion;
Step 1054: according to the second transformation matrix, i two field picture is carried out to image conversion processing, align so that i two field picture after treatment is carried out to secondary with k two field picture.
Specifically, in step 1051, features can be pixel, also can be block of pixels, it determines that mode can be to choose at random, also can be to determine according to the focal position in reference frame, or determine by the characteristic portion of analyzing in reference frame, as determined, the people face part in image be features; In addition, features can be only a point or a block of pixels, can be also multiple points or multiple block of pixels.Wherein, choose a point or a block can significantly improve alignment speed as features.
In step 1052, the pixel portion that search is mated with features respectively in the N-1 two field picture beyond reference frame, continues to use the example that the 1st frame is reference frame, the pixel portion that search is mated with features in the 1st frame in i frame, and the value of i is 2 to N.
In step 1053, the pixel portion of mating with the 1st frame features in calculating i frame and the side-play amount of the 1st frame features, be the second transformation matrix.
In step 1054, according to this second transformation matrix, i two field picture is made to image conversion process, can realize the secondary registration of i two field picture and the 1st two field picture, all realize after secondary registration with the 1st two field picture at the 2nd two field picture to the N two field picture, can realize the secondary registration of N two field picture.
In the embodiment of the present application, in the process of an above-mentioned registration and secondary registration, be all that the N-1 two field picture beyond reference frame in N two field picture is alignd with reference frame respectively, and then realize the alignment of N two field picture.In actual implementation process, also can first the 1st two field picture be alignd with the 2nd two field picture, then the 3rd two field picture is alignd with the 2nd two field picture, by that analogy, until N two field picture is alignd with N-1 two field picture, also can realize the alignment of N two field picture.The embodiment of the present application intention protects this to realize the technical scheme of registration.
Further, step 103: the N two field picture according to noise reduction algorithm after to registration is processed, generates noise reduction image, comprising:
Calculate the pixel average of the N two field picture after registration, generate noise reduction image.
Concrete, the pixel average of N two field picture can be calculated in gray scale passage, or calculates in rgb color passage, or calculates in other color channel, and the embodiment of the present application will not limit this.
In addition, from calculation times, the pixel average of calculating N two field picture can be divided into again:
Mode 1, calculates the pixel average of N two field picture in once-through operation, as calculated the arithmetic mean of pixel of N two field picture, or weighted average;
Mode 2, recursive noise reduction mode, being about to the 1st frame and the 2nd frame is averaging, the noise reduction image generating is averaging as input and the 3rd two field picture, by that analogy, until calculate the pixel average of front N-1 two field picture, then the pixel average of front N-1 two field picture is carried out to the calculating of pixel average as input and N two field picture.
Further, while calculating the pixel average of the N two field picture after registration, the weight of i two field picture becomes negative correlativing relation with the image difference value of the k two field picture as with reference to frame with i two field picture, or the weight of i two field picture becomes negative correlativing relation with the time domain difference value of i two field picture and k two field picture, k two field picture is the reference frame in N two field picture.
Specifically, when calculating pixel mean value, the weight that at least can distribute different frame by three kinds of modes:
One, the weight of each frame is identical, is 1/n.
Its two, the weight of each frame is not identical, less with the weight of the larger picture frame of reference frame image difference value, larger with the weight of the less picture frame of reference frame image difference value, manifests with the ghost reducing in noise reduction image.In actual implementation process, the image difference value between two two field pictures can be calculated on gray level image, also can on rgb color passage, independently calculate, and provides the formula of measuring image difference value with the normalized difference of two squares below:
Wherein, Ix and I'x are respectively k two field picture F
k, i two field picture F
ithe upper corresponding pixel value of 2.In actual conditions, can also adopt other formula to carry out the difference value between dimensioned plan picture, the application gives an example no longer one by one.
Its three, the weight of each frame is not identical, less with the weight of the larger picture frame of reference frame time domain difference value, larger with the weight of the less picture frame of reference frame time domain difference value.In the time being applied to recursive noise reduction, the mean value of the 1st frame to the i frame is greater than the weight of i+1 frame as the weight of input, can obviously be suppressed at so the rear picture frame newly obtaining and introduce new noise, improves the effect of noise reduction image.
Wherein, in the time once calculating the mean value of N two field picture, no matter whether the weight of N two field picture is identical, all frame weight sums all equal 1; In the time that recursive fashion is calculated the mean value of N two field picture, the mean value of the 1st frame to the i frame equals 1 as the weight of input and the weight sum of i+1 frame.
In technique scheme, according to time domain difference value between N two field picture and reference frame and/or image difference value, the weight of each two field picture is carried out to differentiation setting, can further optimize the image quality of noise reduction image.
Further, while calculating the pixel average of the N two field picture after registration, according to the least unit of averaging, can be divided into again three kinds of situations:
Situation 1, at registration or after secondary registration, calculates the mean value of N two field picture taking whole frame as unit.
Situation 2, at registration or after secondary registration, search and a pixel that pixel is corresponding in reference frame in the N-1 two field picture beyond reference frame, then calculate the mean value of one group of (N) pixel matching, by that analogy, until obtain the mean value of one group of pixel that in reference frame, each pixel is corresponding, combine to be and merge noise reduction image., the minimum unit taking pixel as averaging.
Situation 3, be divided into n block with reference to frame, at registration or after secondary registration, search and a block of pixels that block is corresponding in reference frame in the N-1 two field picture beyond reference frame, then calculate the mean value of one group of (N) block of pixels matching, by that analogy, until obtain the mean value of one group of block of pixels that in reference frame, each block is corresponding, combine to be and merge noise reduction image., the minimum unit taking block of pixels as averaging.
Further, in the embodiment of the present application, in the time generating noise reduction image according to N two field picture, be greater than the frame of setting threshold with the pixel difference value of reference frame after can rejecting registration, and then avoid individual difference larger frame to introduce much noise.
Embodiment 2
Corresponding with the image processing method in embodiment 1, the application provides a kind of electronic equipment by embodiment 2, and this electronic equipment comprises image acquisition units and motion-sensing unit, and this motion-sensing unit is for detection of the kinematic parameter of image acquisition units; Referring to Fig. 5, electronic equipment comprises:
Kinematic parameter acquisition module 10, for in the time that image acquisition units is obtained continuous N two field picture, obtain i kinematic parameter by motion-sensing unit, the kinematic parameter that i kinematic parameter is image acquisition units in the time obtaining i two field picture in N two field picture, N is more than or equal to 2 integer, and i is the positive integer that is less than or equal to N;
Registration module 20, at least carrying out registration according to the 1st kinematic parameter to the N kinematic parameter to N two field picture;
Noise reduction module 30, for according to noise reduction algorithm the N two field picture after to registration process, generate noise reduction image.
By technique scheme, can obtain kinematic parameter when image by motion-sensing unit record image acquisition units, by corresponding N two field picture registration, and then merge noise reduction with the N two field picture of registration according to kinematic parameter, obtain noise reduction image.Search for similar pixel and carry out the mode of registration with respect to simple dependence, carrying out the spent operand of image registration according to kinematic parameter significantly reduces, and the obtaining along with IMAQ carries out in real time of kinematic parameter, and operand reduce will significantly reduce the time of whole image processing, ageing being largely increased.
Further, N two field picture is that image acquisition units is obtained under image preview mode, and noise reduction image is preview image; Continue referring to Fig. 5, electronic equipment also comprises:
Display module 40, for after generating noise reduction image, shows preview image by the display unit of electronic equipment.
Further, referring to Fig. 6, registration module 20 comprises:
The first registration submodule 21, for carrying out registration according to the 1st kinematic parameter to the N kinematic parameter one time to N two field picture;
The second registration submodule 22, for determining the features of N two field picture, by the features alignment in each two field picture in N two field picture, so that N two field picture is carried out to secondary registration.
Further, the first registration submodule 21 specifically for: determine that the k two field picture in N two field picture is reference frame, k is the positive integer that is less than or equal to N; And determine the transformation matrix between i two field picture and k two field picture according to i kinematic parameter and k kinematic parameter, wherein, i is not equal to k; And according to transformation matrix, i two field picture is carried out to image conversion processing, so that i two field picture after treatment is alignd with k two field picture.
Further, the second registration submodule 22 specifically for: determine in k two field picture that at least one point or at least one block are features, k is the positive integer that is less than or equal to N; And in i two field picture, search for the pixel portion corresponding with features, wherein, i is not equal to k; And generate the second transformation matrix according to the side-play amount between features and pixel portion; And according to the second transformation matrix, i two field picture is carried out to image conversion processing, so that being carried out to secondary with k two field picture, i two field picture after treatment aligns.
Further, noise reduction module 30 specifically for: calculate the pixel average of the N two field picture after registration, generate noise reduction image;
Wherein, noise reduction module 30 is in the time calculating the pixel average of the N two field picture after registration, the weight of i two field picture becomes negative correlativing relation with the image difference value of the k two field picture as with reference to frame with i two field picture, or the weight of i two field picture becomes negative correlativing relation with the time domain difference value of i two field picture and k two field picture, k two field picture is the reference frame in N two field picture.
Various image processing method formulas in image processing method in previous embodiment and instantiation are equally applicable to the electronic equipment of the present embodiment, by the detailed description to image processing method in previous embodiment, those skilled in the art can clearly know the implementation method of electronic equipment in the present embodiment, so succinct for specification, is not described in detail in this.
The one or more technical schemes that provide in the embodiment of the present application, at least have following technique effect or advantage:
1, in the embodiment of the present application, can obtain kinematic parameter when image by motion-sensing unit record image acquisition units, by corresponding N two field picture registration, and then merge noise reduction with the N two field picture of registration according to kinematic parameter, obtain noise reduction image.Search for similar pixel and carry out the mode of registration with respect to simple dependence, carrying out the spent operand of image registration according to kinematic parameter significantly reduces, and the obtaining along with IMAQ carries out in real time of kinematic parameter, and operand reduce will significantly reduce the time of whole image processing, ageing being largely increased.
2, in the embodiment of the present application, in the image preview stage, the multiple image obtaining is merged to noise reduction and obtain preview image, while carrying out multiple image registration due to the kinematic parameter by motion-sensing unit record consuming time seldom, can in the situation that meeting image and processing ageing requirement, significantly reduce the noise of preview image.
3, in the embodiment of the present application, N two field picture is being carried out after a registration according to the kinematic parameter of motion-sensing unit record, again by the features alignment in each two field picture, search for similar pixel N two field picture is carried out to secondary registration, and then obtain better images match result, to avoid the operating error of motion-sensing unit to cause can not mating completely after registration of N two field picture.
4, in the embodiment of the present application, because N two field picture has carried out registration one time by kinematic parameter, pixel-shift amount between N two field picture be zero or side-play amount very little, therefore search for the operand of similar pixel while carrying out secondary registration and significantly reduce, the spent time is also very short.
Those skilled in the art should understand, the application's embodiment can be provided as method, system or computer program.Therefore, the application can adopt complete hardware implementation example, completely implement software example or the form in conjunction with the embodiment of software and hardware aspect.And the application can adopt the form at one or more upper computer programs of implementing of computer-usable storage medium (including but not limited to magnetic disc store, CD-ROM, optical memory etc.) that wherein include computer usable program code.
The application is with reference to describing according to flow chart and/or the block diagram of the method for the embodiment of the present application, equipment (system) and computer program.Should understand can be by the flow process in each flow process in computer program instructions realization flow figure and/or block diagram and/or square frame and flow chart and/or block diagram and/or the combination of square frame.Can provide these computer program instructions to the processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing device to produce a machine, the instruction that makes to carry out by the processor of computer or other programmable data processing device produces the device for realizing the function of specifying at flow process of flow chart or multiple flow process and/or square frame of block diagram or multiple square frame.
These computer program instructions also can be stored in energy vectoring computer or the computer-readable memory of other programmable data processing device with ad hoc fashion work, the instruction that makes to be stored in this computer-readable memory produces the manufacture that comprises command device, and this command device is realized the function of specifying in flow process of flow chart or multiple flow process and/or square frame of block diagram or multiple square frame.
These computer program instructions also can be loaded in computer or other programmable data processing device, make to carry out sequence of operations step to produce computer implemented processing on computer or other programmable devices, thereby the instruction of carrying out is provided for realizing the step of the function of specifying in flow process of flow chart or multiple flow process and/or square frame of block diagram or multiple square frame on computer or other programmable devices.
Specifically, computer program instructions corresponding to information processing method in the embodiment of the present application can be stored in CD, hard disk, on the storage mediums such as USB flash disk, in the time that the computer program instructions corresponding with information processing method in storage medium read or be performed by an electronic equipment, comprise the steps:
In the time that described image acquisition units is obtained continuous N two field picture, obtain i kinematic parameter by described motion-sensing unit, the kinematic parameter that described i kinematic parameter is described image acquisition units in the time obtaining i two field picture in described N two field picture, N is more than or equal to 2 integer, and i is the positive integer that is less than or equal to N;
At least according to the 1st kinematic parameter to the N kinematic parameter, described N two field picture is carried out to registration;
Described N two field picture according to noise reduction algorithm after to registration is processed, and generates noise reduction image.
Optionally, described N two field picture is that described image acquisition units is obtained under image preview mode, and described noise reduction image is preview image; In storage medium, also store other computer instruction, these computer instructions with step: the described N two field picture according to noise reduction algorithm after to registration is processed, generate noise reduction image, after corresponding computer instruction is performed, be performed, in the time being performed, comprise the steps:
Show described preview image by the display unit of described electronic equipment.
Optionally, that store in storage medium and step: at least according to the 1st kinematic parameter to the N kinematic parameter, described N two field picture is carried out to registration, corresponding computer instruction, being specifically performed in process, specifically comprises the steps:
According to described the 1st kinematic parameter to described N kinematic parameter, described N two field picture is carried out to registration one time;
Determine the features in described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration.
Optionally, that store in storage medium and step: described N two field picture is carried out to registration one time according to described the 1st kinematic parameter to described N kinematic parameter, corresponding computer instruction, being specifically performed in process, specifically comprises the steps:
Determine that the k two field picture in described N two field picture is reference frame, k is the positive integer that is less than or equal to N;
Determine the transformation matrix between described i two field picture and described k two field picture according to described i kinematic parameter and k kinematic parameter, wherein, i is not equal to k;
According to described transformation matrix, described i two field picture is carried out to image conversion processing, so that described i two field picture after treatment is alignd with described k two field picture.
Optionally, that store in storage medium and step: determine the features in described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration, corresponding computer instruction, being specifically performed in process, specifically comprises the steps:
Determine in described k two field picture that at least one point or at least one block are described features, k is the positive integer that is less than or equal to N;
The search pixel portion corresponding with described features in described i two field picture, wherein, i is not equal to k;
Generate the second transformation matrix according to the side-play amount between described features and described pixel portion;
According to described the second transformation matrix, described i two field picture is carried out to image conversion processing, align so that described i two field picture after treatment is carried out to secondary with described k two field picture.
Optionally, that store in storage medium and step: the described N two field picture according to noise reduction algorithm after to registration is processed, and generates noise reduction image, and corresponding computer instruction, being specifically performed in process, specifically comprises the steps:
Calculate the pixel average of the described N two field picture after registration, generate noise reduction image;
Wherein, while calculating the pixel average of the described N two field picture after registration, the weight of described i two field picture becomes negative correlativing relation with the image difference value of the k two field picture as with reference to frame with described i two field picture, or the weight of described i two field picture becomes negative correlativing relation with the time domain difference value of described i two field picture and described k two field picture, described k two field picture is the reference frame in described N two field picture.
Although described the application's preferred embodiment, once those skilled in the art obtain the basic creative concept of cicada, can make other change and amendment to these embodiment.So claims are intended to be interpreted as comprising preferred embodiment and fall into all changes and the amendment of the application's scope.
Obviously, those skilled in the art can carry out various changes and modification and the spirit and scope that do not depart from the application to the application.Like this, if these amendments of the application and within modification belongs to the scope of the application's claim and equivalent technologies thereof, the application is also intended to comprise these changes and modification interior.
Claims (12)
1. an image processing method, is applied to electronic equipment, and described electronic equipment comprises image acquisition units and motion-sensing unit, and described motion-sensing unit is for detection of the kinematic parameter of described image acquisition units; Described method comprises:
In the time that described image acquisition units is obtained continuous N two field picture, obtain i kinematic parameter by described motion-sensing unit, the kinematic parameter that described i kinematic parameter is described image acquisition units in the time obtaining i two field picture in described N two field picture, N is more than or equal to 2 integer, and i is the positive integer that is less than or equal to N;
At least according to the 1st kinematic parameter to the N kinematic parameter, described N two field picture is carried out to registration;
Described N two field picture according to noise reduction algorithm after to registration is processed, and generates noise reduction image.
2. the method for claim 1, is characterized in that, described N two field picture is that described image acquisition units is obtained under image preview mode, and described noise reduction image is preview image; Described according to noise reduction algorithm the described N two field picture after to registration process, after generating noise reduction image, described method also comprises:
Show described preview image by the display unit of described electronic equipment.
3. method as claimed in claim 1 or 2, is characterized in that, describedly at least according to the 1st kinematic parameter to the N kinematic parameter, described N two field picture is carried out to registration, comprising:
According to described the 1st kinematic parameter to described N kinematic parameter, described N two field picture is carried out to registration one time;
Determine the features in described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration.
4. method as claimed in claim 3, is characterized in that, describedly described N two field picture is carried out to registration one time according to described the 1st kinematic parameter to described N kinematic parameter, comprising:
Determine that the k two field picture in described N two field picture is reference frame, k is the positive integer that is less than or equal to N;
Determine the transformation matrix between described i two field picture and described k two field picture according to described i kinematic parameter and k kinematic parameter, wherein, i is not equal to k;
According to described transformation matrix, described i two field picture is carried out to image conversion processing, so that described i two field picture after treatment is alignd with described k two field picture.
5. method as claimed in claim 3, is characterized in that, the described features of determining in described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration, comprising:
Determine in described k two field picture that at least one point or at least one block are described features, k is the positive integer that is less than or equal to N;
The search pixel portion corresponding with described features in described i two field picture, wherein, i is not equal to k;
Generate the second transformation matrix according to the side-play amount between described features and described pixel portion;
According to described the second transformation matrix, described i two field picture is carried out to image conversion processing, align so that described i two field picture after treatment is carried out to secondary with described k two field picture.
6. method as claimed in claim 1 or 2, is characterized in that, described according to noise reduction algorithm the described N two field picture after to registration process, generate noise reduction image, comprising:
Calculate the pixel average of the described N two field picture after registration, generate noise reduction image;
Wherein, while calculating the pixel average of the described N two field picture after registration, the weight of described i two field picture becomes negative correlativing relation with the image difference value of the k two field picture as with reference to frame with described i two field picture, or the weight of described i two field picture becomes negative correlativing relation with the time domain difference value of described i two field picture and described k two field picture, described k two field picture is the reference frame in described N two field picture.
7. an electronic equipment, described electronic equipment comprises image acquisition units and motion-sensing unit, described motion-sensing unit is for detection of the kinematic parameter of described image acquisition units; Described electronic equipment comprises:
Kinematic parameter acquisition module, for in the time that described image acquisition units is obtained continuous N two field picture, obtain i kinematic parameter by described motion-sensing unit, the kinematic parameter that described i kinematic parameter is described image acquisition units in the time obtaining i two field picture in described N two field picture, N is more than or equal to 2 integer, and i is the positive integer that is less than or equal to N;
Registration module, at least carrying out registration according to the 1st kinematic parameter to the N kinematic parameter to described N two field picture;
Noise reduction module, for according to noise reduction algorithm the described N two field picture after to registration process, generate noise reduction image.
8. electronic equipment as claimed in claim 7, is characterized in that, described N two field picture is that described image acquisition units is obtained under image preview mode, and described noise reduction image is preview image; Described electronic equipment also comprises:
Display module, for after generating described noise reduction image, shows described preview image by the display unit of described electronic equipment.
9. electronic equipment as claimed in claim 7 or 8, is characterized in that, described registration module comprises:
The first registration submodule, for carrying out registration according to described the 1st kinematic parameter to described N kinematic parameter one time to described N two field picture;
The second registration submodule, for determining the features of described N two field picture, by the described features alignment in each two field picture in described N two field picture, so that described N two field picture is carried out to secondary registration.
10. electronic equipment as claimed in claim 9, is characterized in that, described the first registration submodule specifically for: determine that the k two field picture in described N two field picture is reference frame, k is the positive integer that is less than or equal to N; And determine the transformation matrix between described i two field picture and described k two field picture according to described i kinematic parameter and k kinematic parameter, wherein, i is not equal to k; And according to described transformation matrix, described i two field picture is carried out to image conversion processing, so that described i two field picture after treatment is alignd with described k two field picture.
11. electronic equipments as claimed in claim 9, is characterized in that, described the second registration submodule specifically for: determine in described k two field picture that at least one point or at least one block are described features, k is the positive integer that is less than or equal to N; And in described i two field picture, search for the pixel portion corresponding with described features, wherein, i is not equal to k; And generate the second transformation matrix according to the side-play amount between described features and described pixel portion; And according to described the second transformation matrix, described i two field picture is carried out to image conversion processing, so that being carried out to secondary with described k two field picture, described i two field picture after treatment aligns.
12. electronic equipments as claimed in claim 7 or 8, is characterized in that, described noise reduction module specifically for: calculate the pixel average of the described N two field picture after registration, generate noise reduction image;
Wherein, described noise reduction module is in the time calculating the pixel average of the described N two field picture after registration, the weight of described i two field picture becomes negative correlativing relation with the image difference value of the k two field picture as with reference to frame with described i two field picture, or the weight of described i two field picture becomes negative correlativing relation with the time domain difference value of described i two field picture and described k two field picture, described k two field picture is the reference frame in described N two field picture.
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