CN106096588A - The processing method of a kind of view data, device and mobile terminal - Google Patents

Abstract

Embodiments providing the processing method of a kind of view data, device and mobile terminal, the method includes: obtain the raw image data of camera collection；Human body image data is identified in described raw image data；In described human body image data, detection belongs to the colour of skin view data of human body；Characteristic information according to described human body image data arranges target colour of skin color value for described human body；According to described target colour of skin color value, described colour of skin view data is normalized, it is thus achieved that destination image data.The embodiment of the present invention makes the colour of skin of input to tend to, is even up to the target colour of skin, solves the colour of skin and is controlled by image procossing, and stability in the large is poor, cause the colour of skin under circumstances, show different problem, the colour of skin that output is stable, consistent, meanwhile, the debugging cycle of image procossing is shortened.

Description

The processing method of a kind of view data, device and mobile terminal

Technical field

The present invention relates to the technical field of communication, particularly relate to the processing method of a kind of view data, a kind of picture number According to processing means and a kind of mobile terminal.

Background technology

Along with the fast development of mobile communication technology, the such as mobile terminal such as mobile phone, panel computer have been widely used in Practise, entertain, the aspect such as work, daily life plays the most important role.

It is commonly configured with photographic head in the terminal, and owing to mobile terminal is relative to photographing unit, has easy to carry Etc. characteristic, therefore, many user habits use mobile terminal to take pictures.

Such as autodyning, under the sight such as group photo, people can be taken pictures by user, various owing to can carry out during taking pictures Image procossing, the debugging cycle of these image procossing is long, and meanwhile, the colour of skin is also controlled by image procossing, and stability in the large is poor, Cause the colour of skin under circumstances, show different.

Summary of the invention

In view of the above problems, it is proposed that the present invention in case provide one overcome the problems referred to above or at least in part solve on State processing method and the processing means of corresponding a kind of view data, a kind of mobile terminal of a kind of view data of problem.

First aspect, provides the processing method of a kind of view data in the embodiment of the present invention, including:

Obtain the raw image data of camera collection；

Human body image data is identified in described raw image data；

In described human body image data, detection belongs to the colour of skin view data of human body；

Characteristic information according to described human body image data arranges target colour of skin color value for described human body；

According to described target colour of skin color value, described colour of skin view data is normalized, it is thus achieved that target image number According to.

Second aspect, provides the processing means of a kind of view data in the embodiment of the present invention, including:

Raw image data acquisition module, for obtaining the raw image data of camera collection；

Human body image data identification module, for identifying human body image data in described raw image data；

Broca scale, as data detection module, belongs to the colour of skin of human body for detection in described human body image data View data；

Target colour of skin color value arranges module, is used for the characteristic information according to described human body image data for described human body Position arranges target colour of skin color value；

Normalized module, for being normalized described colour of skin view data according to described target colour of skin color value Process, it is thus achieved that destination image data.

The third aspect, embodiments provides a kind of mobile terminal, and this mobile terminal has and realizes above-mentioned first party The function processing behavior of view data in face.Described function can be realized by hardware, it is also possible to performed corresponding by hardware Software realize.Described hardware or software include one or more module corresponding with above-mentioned functions.

In a possible design, the structure of mobile terminal includes that processor and memorizer, described memorizer are used for Storage supports that R-T unit performs the program of said method, and described processor is configurable for performing to store in described memorizer Program.Described mobile terminal can also include communication interface, for mobile terminal and other equipment or communication.

Wherein, described memorizer is for storing the instruction of the raw image data obtaining camera collection, described original Identifying the instruction of human body image data in view data, in described human body image data, detection belongs to the skin of human body The instruction of color image data, arranges target colour of skin face according to the characteristic information of described human body image data for described human body The instruction of colour, is normalized described colour of skin view data according to described target colour of skin color value, it is thus achieved that target figure Instruction as data；

Described processor is used for:

According to the instruction of the raw image data of described acquisition camera collection, obtain the original image number of camera collection According to；

In described raw image data, human body image data instruction is identified, at described raw image data according to described In identify human body image data；

According to described in described human body image data detection belong to the broca scale of human body as data command, in institute State detection in human body image data and belong to the colour of skin view data of human body；

According to the described characteristic information according to described human body image data, target colour of skin face is set for described human body The instruction of colour, arranges target colour of skin color value according to the characteristic information of described human body image data for described human body；

Described colour of skin view data is normalized according to described target colour of skin color value according to described, it is thus achieved that mesh The instruction of logo image data, is normalized described colour of skin view data according to described target colour of skin color value, it is thus achieved that Destination image data.

The scheme that the present invention provides, user can use mobile terminal, obtains the raw image data of camera collection, from Raw image data identifies human body image data, and then the colour of skin view data of detection home to return to and human body, based on human body The characteristic information of view data arranges target colour of skin color value to human body, according to target colour of skin color value to described broca scale As data are normalized, it is thus achieved that destination image data so that the colour of skin of input can tend to, be even up to the target colour of skin, Solving the colour of skin to be controlled by image procossing, stability in the large is poor, causes the colour of skin under circumstances, shows different asking Topic, the colour of skin that output is stable, consistent, meanwhile, shortens the debugging cycle of image procossing.

The aspects of the invention or other aspects be meeting more straightforward in the following description.

Accompanying drawing explanation

By reading the detailed description of hereafter preferred implementation, various other advantage and benefit common for this area Technical staff will be clear from understanding.Accompanying drawing is only used for illustrating the purpose of preferred implementation, and is not considered as the present invention Restriction.And in whole accompanying drawing, it is denoted by the same reference numerals identical parts.In the accompanying drawings:

Fig. 1 shows the steps flow chart of the processing method embodiment of a kind of view data Figure；

Fig. 2 shows the step stream of the processing method embodiment of another kind of according to an embodiment of the invention view data Cheng Tu；

Fig. 3 shows the structural frames of the processing means embodiment of a kind of view data Figure；

Fig. 4 shows the structural frames of the processing means embodiment of another kind of according to an embodiment of the invention view data Figure；And

Fig. 5 shows the block diagram of the part-structure of mobile phone relevant to mobile terminal according to an embodiment of the invention.

Detailed description of the invention

It is more fully described the exemplary embodiment of the disclosure below with reference to accompanying drawings.Although accompanying drawing shows the disclosure Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure and should be by embodiments set forth here Limited.On the contrary, it is provided that these embodiments are able to be best understood from the disclosure, and can be by the scope of the present disclosure Complete conveys to those skilled in the art.

With reference to Fig. 1, it is shown that the step of the processing method embodiment of a kind of view data Rapid flow chart, specifically may include steps of:

Step 101, obtains the raw image data of camera collection.

In implementing, the embodiment of the present invention can be applied in the terminal, such as, and mobile phone, panel computer, individual Digital assistants, wearable device (such as glasses, wrist-watch etc.) etc..

The operating system of these mobile terminals can include Android (Android), IOS, Windows Phone, Windows Etc..

In embodiments of the present invention, photographic head camera can be configured in the terminal.

These photographic head can be only fitted to the front portion (also known as front-facing camera) of mobile terminal, it is also possible to is arranged in mobile whole End back (also known as post-positioned pick-up head), additionally, the quantity of this photographic head can be single, can also be two or two with On, such as dual camera, etc., this is not any limitation as by the embodiment of the present invention.

In one example, photographic head can include camera lens Lens, pedestal Holder, infrared filter IR, image sensing The parts such as processor Sensor, circuit board.

Wherein, image sensing processor Sensor is a kind of semiconductor chip, and its surface includes hundreds of thousands to millions of The photodiode not waited, when photodiode receives light irradiation, can produce electric charge.

Image sensing processor Sensor can convert light into the signal of telecommunication, then is turned by internal DA (digital-to-analogue conversion) It is changed to digital signal, the imaging plane that plane is view data at image sensing processor Sensor place.

In actual applications, the optical imagery that scenery (SCENE) is generated by the camera lens Lens of photographic head projects image On sensing processor Sensor surface, then turn to the signal of telecommunication, after A/D (analog digital conversion) changes, become digital picture letter Number, by data image signal is compressed and is converted into specific image literary composition by digital signal processing chip DSP or code database Part form, is located by the processor (Central Processing Unit, CPU) of data bus transmission to mobile terminal Reason, then can show at the screen of mobile terminal.

Step 102, identifies human body image data in described raw image data.

So-called human body image data, refers to characterize the view data of people in raw image data.

In the sights such as auto heterodyne, it is usually and a people is taken pictures, therefore, raw image data can identify one Individual human body image data；In the sights such as group photo, it is usually and many individuals are taken pictures, therefore, can in raw image data To identify multiple human body image datas.

In implementing, human body image data can be detected by one or more following modes:

1, based on template or the detection method of profile

Detection method based on template or profile mainly uses the method for template matching and template classification to detect human figure As data.

In one example, the contour feature of human body can be applied during various level template matching to select to wait The target of choosing, the shape appearance typically exhibited by human body is as human body target template, according to the shape matching method of range conversion Mate from coarse to fine.Then, RBF is re-used to verify the target of candidate.

2, detection method based on movable information

Detection method based on movable information is to utilize the periodicity of human motion to carry out the people in inspection image data, typically It is applicable to the pedestrian of detection motion.

In one example, when utilizing people to walk, leg is periodic motion feature, identifies people from image sequence, First view data it is divided into sub-image data and pixel is clustered, in continuous print view data, then mating the class of correspondence And follow the tracks of all kinds of, the time based on class row shape feature changes, and estimates that carrying out initial option may belong to quick multinomial grader The class of people's leg, the class that extraction belongs to leg finally by neutral net is trained, thus judges whether people.

3, detection method based on sliding window

The detection method based on sliding window detection window slip scan in view data by fixed size, these Window is classified device and has been categorized as people and nobody two classes.

In one example, the detection method of sliding window can be divided into two stages, and first stage is the training stage, Second stage is detection-phase.

In the training stage, initially setting up training sample, including positive sample and negative sample, positive sample is exactly the figure including human body As region, negative sample is exactly the image-region not including human body.Then from positive sample and negative sample, extract feature, this feature one As represent with the form of characteristic vector.Finally training grader, this grader is for by the characteristic vector of positive sample and negative sample Characteristic vector make a distinction.

At detection-phase, owing in view data, human's judgment size is indefinite, and being typically of size of of sliding window Certain, in order to the little people of yardstick and the big people of yardstick can be detected, the figure of band inspection image data can be set up As pyramid, use the sliding window of fixed size to slide in each level of pyramid, often slide into a position just by this The characteristics of image input grader extracted in individual window is classified.Grader exports whether this window comprises the letter of people Breath.When all positions and level the most the most scanned by sliding window after, the windows detecting that in each level, position is close arrives People is likely to same person, in order to determine the position of final human body, carries out window fusion and adjacent window is merged into one Window.

4, based on parts or the detection method of local shape

Based on be not or local shape method rely on detection human body not for or local shape, combine this most again A little features limit the position determining final human body according to the geometry of anthropometric dummy.

Certainly, above-mentioned human detection is intended only as example, when implementing the embodiment of the present invention, can set according to practical situation Putting other human detection, this is not any limitation as by the embodiment of the present invention.It addition, in addition to above-mentioned human detection, art technology Personnel can also use other human detection according to actual needs, and this is not any limitation as by the embodiment of the present invention.

Step 103, in described human body image data, detection belongs to the colour of skin view data of human body.

In implementing, human body includes multiple position, such as face, head, arm, shank, etc..

When taking pictures, the partial skin of these human bodies would generally be exposed, is directly displayed in view data, such as, User is when autodyning, and face would generally occupy bigger region.

Therefore, in embodiments of the present invention, HOG (Histogram of Oriented Gradient, direction can be passed through Histogram of gradients) mode such as algorithm, depth image study detects the station diagram picture at human body place in human body image data Data, carry out Face Detection, it is thus achieved that colour of skin view data in this image-region.

As a example by face, Face datection can be carried out in raw image data, it is thus achieved that face image data, at this face View data identifies colour of skin view data.

So-called Face datection, can refer to calibrate the positions and dimensions of face from view data.

In Android, it is provided that a method directly carrying out face detection on bitmap, the two API (Application Programming Interface, application programming interface) is respectively Android.media.FaceDetector and android.media.FaceDetector.Face.

Specifically, extend base class ImageView, become MyImageView, and carry out the bitmap comprising face detected File is usually 565 forms, to ensure that API normally works.

The face being detected needs a confidence measure (confidence measure), and this measure is defined on android.media.FaceDetector.Face.CONFIDENCE_THRESHOLD。

Wherein, FaceDetector object-instantiated can be called findFaces by setFace () simultaneously, and result is deposited In faces, MyImageView is transferred at the midpoint of face.

It follows that add setDisplayPoints () method in MyImageView, it is used at the face being detected Upper labelling renders.

And API returns the information that other are useful, such as, such as eyesDistance, pose can be returned simultaneously, and Confidence, then can position the center of eyes by eyesDistance.

So-called Face Detection, is to choose the process corresponding to human skin pixels in view data.

According to either with or without relating to imaging process, Face Detection can mark off the following two kinds type:

1, Face Detection based on statistics

The key step of Face Detection based on statistics includes color notation conversion space and skin color modeling.

Color space is selected inherently to select the most basic character representation of Face Detection.Skin color modeling is to know about the colour of skin The computer representation known, generally sets up complexion model by training sample set and carries out Face Detection, can be by according to different application Skin color modeling is divided into static and dynamic two classes.

Wherein, for color space, the colour of skin is quite concentrated in the distribution of color space, but can by illumination with ethnic group very Big impact, is affected by intensity of illumination to reduce the colour of skin, and color space is generally converted into brightness and colourity classification certain from RGB Individual color space, such as YCbCr or HSV, then abandon brightness.

For static skin color modeling, the sides such as skin color range, Gaussian density function estimation and statistics with histogram can be passed through Formula sets up complexion model, the most corresponding thresholding of this three, parametrization and the method for imparametrization.

For dynamic skin color modeling, can by complexion model parameter is adjusted to adapt to certain width still image, or, For sequence image, adapt to the image-forming condition mode such as over time and set up complexion model.

2, Face Detection based on physics

Under complicated lighting condition, in such as image, the colour of skin is in specular or shadow region, in order to from imaging mechanism on gram Take illumination and image paid no attention to impact, when Face Detection, it is considered to the interaction of light and skin, it is considered to skin POP is special Property, this Face Detection technology referred to as Face Detection based on physics considering electromagnetic radiation and the mutual physical action of skin.

In a kind of Face Detection mode based on physics, colour of skin inspection can be carried out by the physical model of skin reflex Surveying, such as, dichromatic reflection model can simulate opaque non-uniform dielectric thing according to the reflection characteristic of non-uniform dielectric Body reflection process, to carry out Face Detection.

Certainly, above-mentioned location detection, Face Detection are intended only as example, when implementing the embodiment of the present invention, and can basis Practical situation arranges other location detection, Face Detection, and this is not any limitation as by the embodiment of the present invention.It addition, except above-mentioned portion Outside position detection, Face Detection, those skilled in the art can also use other location detection, Face Detection according to actual needs, This is not any limitation as by the embodiment of the present invention.

Step 104, arranges target colour of skin face according to the characteristic information of described human body image data for described human body Colour.

In actual applications, the colour of skin of the people of different characteristic typically has different features.

Such as, the general colour of skin partially white, black race of the general colour of skin the most yellow, white of the colour of skin of yellow is the most black.

The most such as, for yellow, from stages such as child, teenager, youth, middle age, old age, the color of the colour of skin typically can be by Gradually deepen.

The most such as, for yellow, the colour of skin of male is typically deep than the colour of skin of women.

Additionally, the different human body position of these people, the colour of skin can be slightly different, such as, for yellow, the face of women The colour of skin is generally white than arm.

As a example by RGB color, in target colour of skin color value, R (red) value is generally higher than G (green) value, and G (green) value is general It is (215,177,141), the target colour of skin color of middle age correspondence more than B (blue) value, such as old corresponding target colour of skin color value Value is (249,217,204), juvenile corresponding target colour of skin color value is (253,227,204) etc..

Therefore, for the position of the people of different characteristic, target colour of skin color value can be set, and set up the feature letter of people Breath, mapping relations between human body and target colour of skin color value.

After detecting the position view data at human body place in human body image data, can be according to these mapping relations The target colour of skin color value that inquirer's body region is corresponding.

In one example, the one in the age information of human body image data, gender information, ethnic group information can be identified Or various features information.

Corresponding based on one or more characteristic informations inquirer's body region in age information, gender information, ethnic group information Target colour of skin color value.

Certainly, features described above information is intended only as example, when implementing the embodiment of the present invention, can set according to practical situation Putting other characteristic informations, this is not any limitation as by the embodiment of the present invention.It addition, in addition to features described above information, art technology Personnel can also use further feature information according to actual needs, and this is not any limitation as by the embodiment of the present invention.

Step 105, is normalized described colour of skin view data according to described target colour of skin color value, it is thus achieved that mesh Logo image data.

Be normalized with colour of skin view data by target colour of skin color value, can allow input colour of skin picture number According to the colour of skin tend to, even up to target colour of skin color value, the colour of skin that output is stable, consistent.

In actual applications, Eigen Skin color image can be selected in colour of skin view data by certain selection rule Data；According to target colour of skin color value, Eigen Skin color view data is normalized, it is thus achieved that destination image data.

For example, it is possible to select Eigen Skin color view data according to brightness and/or exposure, screen out some brightness irregularities, The colour of skin view data of overexposure, retains brightness uniformity, does not has the colour of skin view data of overexposure.

Specifically, brightness and/or the exposure of colour of skin view data can be added up by modes such as statistics with histogram.

From colour of skin view data, choose brightness be less than, in default brightness section and/or exposure, the threshold exposure preset View data, as Eigen Skin color view data.

Certainly, it is normalized except selected part colour of skin view data, it is also possible to whole colour of skin view data Being normalized, this is not any limitation as by the embodiment of the present invention.

In one embodiment of the invention, step 105 can include following sub-step:

Sub-step S11, for each position view data, adds up the original colour of skin color in the view data of described position Value；

In implementing, the pixel color value of each pixel in colour of skin view data can be obtained, such as rgb value, calculate The meansigma methods of pixel color value, as original colour of skin color value.

Sub-step S12, uses described original colour of skin color value to calculate normalization coefficient with described target colour of skin color value；

In implementing, normalization coefficient can be calculated based on calculating target colour of skin color value, adjust original skin with this Color color value.

In an example of the embodiment of the present invention, sub-step S12 can include following sub-step:

Sub-step S121, calculates the ratio between described target colour of skin color value and described original colour of skin color value, it is thus achieved that Color adjusts ratio；

As a example by RGB color, it is assumed that target colour of skin color value is (R_sample, G_sample, B_sample), photographic head inputs The original colour of skin color value of colour of skin view data be (R_input, G_input, B_input), then, it is (R that color adjusts ratio_ratio, G_ratio, B_ratio):

R_ratio=R_sample/R_input

G_ratio=G_sample/G_input

B_ratio=B_sample/B_input

Sub-step S122, is multiplied by described adjustment ratio by the pixel color value of each pixel in described colour of skin view data, Obtain pixel color value set.

Sub-step S123, chooses object pixel color value from pixel color value set.

In implementing, can be from pixel color value set, the pixel color value that selected value is maximum, as target picture Element color value.

Certainly, in addition to the pixel color value of selected value maximum, it is also possible to choose other pixel color value as target Pixel color value, this is not any limitation as by the embodiment of the present invention.

As a example by RGB color, it is assumed that adjustment ratio is (R_ratio, G_ratio, B_ratio), then, by (R_ratio, G_ratio, B_ratio) carry out product with each pixel of colour of skin view data, obtain R_{(0,1,2,...,n)}, G_{(0,1,2,..,.n)}, B_{(0,1,2,...,n)}, wherein n is integer.

Statistics R (0,1,2 ... n), G (0,1,2 ... n), B (0,1,2 ... maximum RGB in n)_maxAs target picture Element color value.

Sub-step S124, uses color to adjust ratio and described object pixel color value calculates normalization coefficient.

In implementing, the ratio between default color threshold and object pixel color value can be calculated, as picture Element color-ratio, calculates color and adjusts the product between ratio and pixel color ratio, it is thus achieved that normalization coefficient.

As a example by RGB color, it is assumed that adjustment ratio is (R_ratio, G_ratio, B_ratio), object pixel color value is RGB_max, then normalization coefficient is:

R_ratio*255/RGB_max

G_ratio*255/RGB_max

B_ratio*255/RGB_max

Sub-step S13, is adjusted with described normalization coefficient, it is thus achieved that return on the basis of described original colour of skin color value One changes colour of skin color value；

Sub-step S14, in described raw image data, adjusts described broca scale picture with described normalization colour of skin color value Data, it is thus achieved that destination image data.

In embodiments of the present invention, can be adjusted according to normalization coefficient on the basis of original colour of skin color value, Output normalization colour of skin color value.

As a example by RGB color, it is assumed that original colour of skin color value is (R_input, G_input, B_input), normalization coefficient be (R_ratio*255/RGB_max, G_ratio*255/RGB_max, B_ratio*255/RGB_max), then the normalization colour of skin color value exported (R_final, G_final, B_final) it is:

R_final=R_input*R_ratio*255/RGB_max；

G_final=G_input*G_ratio*255/RGB_max；

B_final=B_input*B_ratio*255/RGB_max；

At present, in the camera module of mobile terminal, can AEC (Automatic Exposure Control, automatically Spectrum assignment) and AWB (Automatic white balance, AWB) stable after, indexed by the exposure of AEC (index) value, and the color temperature value (CCT) of AWB output, remove the color rendition (color that dynamic calculation current scene should use And saturation (color enhancement) parameter correction).

The most just create problem, such as, in different angles, different exposures, and different AWB output, even if AWB Difference little, the color rendition of final utilization and saturation parameters can be inconsistent, and the image colour of skin causing out is inconsistent, Even same person is tested, in different angles, in the case of different light sources, colour of skin difference is the biggest.

Meanwhile, the screen of the mobile terminal of different-colour (warm colour screen, cool colour screen etc.) shows that form is each especially Different.

Therefore, Consumer's Experience is the most bad, the most existing adjustable parameter, and adjustment method, and debugging cycle is the longest, and And it is extremely difficult to expected effect.

The scheme that the present invention provides, user can use mobile terminal, obtains the raw image data of camera collection, from Raw image data identifies human body image data, and then the colour of skin view data of detection home to return to and human body, based on human body The characteristic information of view data arranges target colour of skin color value to human body, according to target colour of skin color value to described broca scale As data are normalized, it is thus achieved that destination image data so that the colour of skin of input can tend to, be even up to the target colour of skin, Solving the colour of skin to be controlled by image procossing, stability in the large is poor, causes the colour of skin under circumstances, shows different asking Topic, the colour of skin that output is stable, consistent, meanwhile, shortens the debugging cycle of image procossing.

With reference to Fig. 2, it is shown that the step of the processing method embodiment of a kind of view data Rapid flow chart, specifically may include steps of:

Step 201, obtains the raw image data of camera collection.

Step 202, carries out image procossing to described raw image data.

In embodiments of the present invention, if camera collection is to view data, then can carry out ISP (Image Signal Processing, image signal processing) process.

Wherein, image procossing includes following at least one:

1, auto-exposure control

Exposure is used to calculate the physical quantity of the luminous flux size arriving camera from scenery.Imageing sensor is only just obtaining True exposure, just can obtain high-quality photo.Over-exposed, image seems the brightest under-exposure, then image seems too Secretly.The size of the luminous flux arriving sensor is mainly determined by two aspect factors: the length of time of exposure and the size of aperture.

Utilize aperture to carry out automatic exposure, mainly control aperture size according to captured scene so that light-inletting quantity is tieed up Hold within the specific limits.The cost being exposed controlling by aperture is higher.

Auto-exposure control algorithmic method generally has two kinds:

A kind of method is to use with reference to brightness value, and image uniform is divided into the subimage of many, each piece of subimage bright Degree is used to arrange with reference to brightness value, and this brightness value can be obtained by the speed arranging shutter.

Another method is, is exposed by the relation between brightness and the exposure value under research different illumination conditions Photocontrol.

2, blank level adjustment

White balance is it can be appreciated that under the conditions of any colour temperature, the reference white captured by photographic head is through the tune of oversampling circuit Whole, remain as white after being allowed to imaging.

AWB be based on the assumption that the meansigma methods of the color of scene fall specific at one in the range of, if measured Deviateing this scope to result, then adjust corresponding parameter, correction is until its average falls into appointment scope.This processing procedure is potentially based on Yuv space, it is also possible to carry out based on rgb space.For Sensor, common processing mode is to be increased by correction R/B Benefit so that UV value falls in the range of an appointment.Thus realize AWB.

3, color rendition processes

The human eye identification to color, is, based on human eye, light is existed three kinds of different sensing units, different sensing lists There is the principle of different response curves in unit to the light of different-waveband, is obtained the perception of color by the synthesis of brain.In general, The concept by RGB three primary colours that can be popular understands decomposition and the synthesis of color.

In theory, if human eye and the sensor (sensor) response to the coloured light of spectrum, if embodiment spectrally, The substantially response to three coloured light, will not make a difference each other, does not has so-called cross effect.But, practical situation is also The most preferable, the trichroism induction system of the human eye response condition to spectrum, is that the response of RGB is not completely self-contained.

On each component of RGB the most devious to the response of spectrum with human eye, be certainly accomplished by it is corrected. The most just in cross effect, the response intensity of each to color equally component is also required to correction, it is common practice to by one Color is once corrected by color correction matrix.

The computing of this colour correction is typically integrated by sensor module or rear end ISP and completes, and posts by amendment is relevant Storage obtains correct correction result.Wherein, also it is the conversion by a 3*3 due to color space conversion from RGB to YUV Matrix realizes, so sometimes the two matrix can combine during ISP processes, is transported by a matrix Calculate and operated the correction of color and the conversion of color space.

4, color enhancement processes

In implementing, the color representation of view data can be strengthened by modes such as regulation saturations.

So-called saturation, refer to is the purity of color in fact, and purity is the highest, shows the distinctest, and purity is relatively low, and performance is then Dulller.

Owing to each pixel of liquid crystal is made up of red, green, blue (RGB) subpixel, backlight by rely on after liquid crystal molecule RGB as Element is combined into random color light.If RGB three primary colors is the most bright-coloured, then the color gamut that display can represent is the widest.As Really display three primary colors is the most bright-coloured, and the color gamut that this display can show is the most narrow, because it cannot show ratio Three primary colors more chromatic colour.Therefore, the method improving color saturation is to improve backlight spectra and trichromatic purity.

5, denoising

In the collection and transmission of view data, image data quality be often subject to various effect of noise and under Fall.

Such as, the sound pollution when imageing sensor obtains view data, owing to data volume at this time is less, noise Directly affect interpolation algorithm below, and make the details of image to embody, both affected the interpolation of image, also affected people's Visual experience.

Therefore in image procossing, the removal of noise is a very important link.

The mode of denoising, it is common that the point of surrounding taking average to substitute original value, this way does not increase Quantity of information, is similar to a fuzzy algorithmic approach.

When detection, comprehensively can judge noise as standard by brightness and color, use interpolation algorithm to compensate, For the bad point that sensor is intrinsic, noise, the mode of shielding is used to abandon its data etc..

Certainly, above-mentioned image procossing is intended only as example, when implementing the embodiment of the present invention, can set according to practical situation Putting other image procossing, as stroboscopic suppresses, this is not any limitation as by the embodiment of the present invention.It addition, in addition to above-mentioned image procossing, Those skilled in the art can also use other image procossing according to actual needs, and this is not limited by the embodiment of the present invention System.

Step 203, identifies human body image data in described raw image data.

Step 204, in described human body image data, detection belongs to the colour of skin view data of human body.

Step 205, arranges target colour of skin face according to the characteristic information of described human body image data for described human body Colour.

Step 206, is normalized described colour of skin view data according to described target colour of skin color value, it is thus achieved that mesh Logo image data.

In embodiments of the present invention, human body image number can be identified from the raw image data after image procossing According to, according to the characteristic information of human body image data after image procossing, target colour of skin color value is set for human body, according to Colour of skin view data after image procossing is normalized by target colour of skin color value, it is thus achieved that destination image data.

For embodiment of the method, in order to be briefly described, therefore it is all expressed as a series of combination of actions, but this area Technical staff should know, the embodiment of the present invention is not limited by described sequence of movement, because implementing according to the present invention Example, some step can use other orders or carry out simultaneously.Secondly, those skilled in the art also should know, description Described in embodiment belong to preferred embodiment, necessary to the involved action not necessarily embodiment of the present invention.

With reference to Fig. 3, it is shown that the knot of the processing means embodiment of a kind of view data Structure block diagram, specifically can include such as lower module:

Raw image data acquisition module 301, for obtaining the raw image data of camera collection；

Human body image data identification module 302, for identifying human body image data in described raw image data；

Broca scale, as data detection module 303, belongs to human body for detection in described human body image data Colour of skin view data；

Target colour of skin color value arranges module 304, is used for the characteristic information according to described human body image data for described Human body arranges target colour of skin color value；

Normalized module 305, for returning described colour of skin view data according to described target colour of skin color value One change processes, it is thus achieved that destination image data.

In one embodiment of the invention, described normalized module 305 can be also used for:

Eigen Skin color view data is selected in described colour of skin view data；

According to described target colour of skin color value, described Eigen Skin color view data is normalized, it is thus achieved that target figure As data.

In one embodiment of the invention, described normalized module 305 can be also used for:

Add up brightness and/or the exposure of described colour of skin view data；

From described colour of skin view data, choose brightness be less than, in default brightness section and/or exposure, the exposure preset The view data of threshold value, as Eigen Skin color view data.

In one embodiment of the invention, described target colour of skin color value arranges module 304 and can be also used for:

Identify one or more features letter in the age information of described human body image data, gender information, ethnic group information Breath；

Corresponding based on one or more characteristic informations inquirer's body region in age information, gender information, ethnic group information Target colour of skin color value.

In one embodiment of the invention, described normalized module 305 can be also used for:

For each colour of skin view data, add up the original colour of skin color value in the view data of described position；

Described original colour of skin color value is used to calculate normalization coefficient with described target colour of skin color value；

It is adjusted with described normalization coefficient on the basis of described original colour of skin color value, it is thus achieved that normalization colour of skin face Colour；

In described raw image data, adjust described colour of skin view data with described normalization colour of skin color value, it is thus achieved that Destination image data.

In one embodiment of the invention, described normalized module 305 can be also used for:

Obtain the pixel color value of each pixel in described colour of skin view data；

Calculate the meansigma methods of described pixel color value, as original colour of skin color value.

In one embodiment of the invention, described normalized module 305 can be also used for:

Calculate the ratio between described target colour of skin color value and described original colour of skin color value, it is thus achieved that color adjusts ratio Example；

The pixel color value of each pixel in the view data of described position is multiplied by described adjustment ratio, it is thus achieved that pixel color Value set；

Object pixel color value is chosen from described pixel color value set；

Use described color to adjust ratio and described object pixel color value calculates normalization coefficient.

In one embodiment of the invention, described normalized module 305 can be also used for:

From described pixel color value set, the pixel color value that selected value is maximum, as object pixel color value.

In one embodiment of the invention, described normalized module 305 can be also used for:

Calculate the ratio between color threshold and the described object pixel color value preset, as pixel color ratio；

Calculate described color and adjust the product between ratio and described pixel color ratio, it is thus achieved that normalization coefficient.

With reference to Fig. 4, it is shown that the processing means embodiment of another kind of according to an embodiment of the invention view data Structured flowchart, specifically can include such as lower module:

Raw image data acquisition module 401, for obtaining the raw image data of camera collection；

Image processing module 402, for carrying out image procossing to described raw image data；

Human body image data identification module 403, for identifying human body image data in described raw image data；

Broca scale, as data detection module 404, belongs to human body for detection in described human body image data Colour of skin view data；

Target colour of skin color value arranges module 405, is used for the characteristic information according to described human body image data for described Human body arranges target colour of skin color value；

Normalized module 406, for returning described colour of skin view data according to described target colour of skin color value One change processes, it is thus achieved that destination image data.

In implementing, described image procossing includes following at least one:

Auto-exposure control, blank level adjustment, color rendition process, color enhancement process, denoising.

For device embodiment, due to itself and embodiment of the method basic simlarity, so describe is fairly simple, relevant Part sees the part of embodiment of the method and illustrates.

The embodiment of the present invention additionally provides mobile terminal, as it is shown in figure 5, for convenience of description, illustrate only and the present invention The part that embodiment is relevant, concrete ins and outs do not disclose, and refer to embodiment of the present invention method part.This terminal can be Including mobile phone, panel computer, PDA (Personal Digital Assistant, personal digital assistant), POS (Point of Sales, point-of-sale terminal), the arbitrarily terminal unit such as vehicle-mounted computer, as a example by terminal is as mobile phone:

Fig. 5 is illustrated that the block diagram of the part-structure of the mobile phone relevant to the terminal of embodiment of the present invention offer.With reference to figure 5, mobile phone includes: radio frequency (Radio Frequency, RF) circuit 510, memorizer 520, input block 530, display unit 540, Sensor 550, voicefrequency circuit 560, Wireless Fidelity (wireless fidelity, WiFi) module 570, processor 580 and Power supply 590 parts such as grade.It will be understood by those skilled in the art that the handset structure shown in Fig. 5 is not intended that the restriction to mobile phone, Can include that ratio illustrates more or less of parts, or combine some parts, or different parts are arranged.

Below in conjunction with Fig. 5 each component parts of mobile phone carried out concrete introduction:

RF circuit 510 can be used for receiving and sending messages or in communication process, the reception of signal and transmission, especially, by base station After downlink information receives, process to processor 580；It addition, be sent to base station by designing up data.Generally, RF circuit 510 Include but not limited to antenna, at least one amplifier, transceiver, bonder, low-noise amplifier (Low Noise Amplifier, LNA), duplexer etc..Additionally, RF circuit 510 can also be communicated with network and other equipment by radio communication. Above-mentioned radio communication can use arbitrary communication standard or agreement, includes but not limited to global system for mobile communications (Global System of Mobile communication, GSM), general packet radio service (General Packet Radio Service, GPRS), CDMA (Code Division Multiple Access, CDMA), WCDMA (Wideband Code Division Multiple Access, WCDMA), Long Term Evolution (Long Term Evolution, LTE), Email, Short Message Service (Short Messaging Service, SMS) etc..

Memorizer 520 can be used for storing software program and module, and processor 580 is stored in memorizer 520 by operation Software program and module, thus perform mobile phone various functions application and data process.Memorizer 520 can mainly include Storage program area and storage data field, wherein, storage program area can store the application journey needed for operating system, at least one function Sequence (such as sound-playing function, image player function etc.) etc.；Storage data field can store what the use according to mobile phone was created Data (such as voice data, phone directory etc.) etc..Additionally, memorizer 520 can include high-speed random access memory, it is also possible to Including nonvolatile memory, for example, at least one disk memory, flush memory device or other volatile solid-state Part.

Input block 530 can be used for receiving numeral or the character information of input, and produce with the user setup of mobile phone with And function controls relevant key signals input.Specifically, input block 530 can include that contact panel 531 and other inputs set Standby 532.Contact panel 531, also referred to as touch screen, can collect user thereon or neighbouring touch operation (such as user uses Any applicable object such as finger, stylus or adnexa operation on contact panel 531 or near contact panel 531), and root Corresponding attachment means is driven according to formula set in advance.Optionally, contact panel 531 can include touch detecting apparatus and touch Two parts of controller.Wherein, the touch orientation of touch detecting apparatus detection user, and detect the signal that touch operation brings, Transmit a signal to touch controller；Touch controller receives touch information from touch detecting apparatus, and is converted into touching Point coordinates, then give processor 580, and order that processor 580 sends can be received and performed.Furthermore, it is possible to use electricity The polytypes such as resistive, condenser type, infrared ray and surface acoustic wave realize contact panel 531.Except contact panel 531, input Unit 530 can also include other input equipments 532.Specifically, other input equipments 532 can include but not limited to secondary or physical bond One or more in dish, function key (such as volume control button, switch key etc.), trace ball, mouse, action bars etc..

Display unit 540 can be used for the various of the information that inputted by user of display or the information being supplied to user and mobile phone Menu.Display unit 540 can include display floater 541, optionally, can use liquid crystal display (Liquid Crystal Display, LCD), the form such as Organic Light Emitting Diode (Organic Light-Emitting Diode, OLED) configure aobvious Show panel 541.Further, contact panel 531 can cover display floater 541, when contact panel 531 detects thereon or attached After near touch operation, send processor 580 to determine the type of touch event, with preprocessor 580 according to touch event Type corresponding visual output is provided on display floater 541.Although in Figure 5, contact panel 531 and display floater 541 It is to realize input and the input function of mobile phone as two independent parts, but in some embodiments it is possible to by touch-control Panel 531 is integrated with display floater 541 and realizes input and the output function of mobile phone.

Mobile phone may also include at least one sensor 550, such as optical sensor, motion sensor and other sensors. Specifically, optical sensor can include ambient light sensor and proximity transducer, and wherein, ambient light sensor can be according to ambient light Light and shade regulate the brightness of display floater 541, proximity transducer can cut out display floater 541 when mobile phone moves in one's ear And/or backlight.As the one of motion sensor, accelerometer sensor can detect (generally three axles) acceleration in all directions Size, can detect that size and the direction of gravity time static, can be used for identify mobile phone attitude application (such as horizontal/vertical screen is cut Change, dependent game, magnetometer pose calibrating), Vibration identification correlation function (such as pedometer, percussion) etc.；Also may be used as mobile phone Other sensors such as the gyroscope of configuration, barometer, drimeter, thermometer, infrared ray sensor, do not repeat them here.

Voicefrequency circuit 560, speaker 561, microphone 562 can provide the audio interface between user and mobile phone.Audio-frequency electric The signal of telecommunication after the voice data conversion that road 560 can will receive, is transferred to speaker 561, speaker 561 is converted to sound Signal exports；On the other hand, the acoustical signal of collection is converted to the signal of telecommunication by microphone 562, voicefrequency circuit 560 turn after receiving It is changed to voice data, then after voice data output processor 580 is processed, through RF circuit 510 to be sent to such as another mobile phone, Or voice data is exported to memorizer 520 to process further.

WiFi belongs to short range wireless transmission technology, and mobile phone can help user's transceiver electronics postal by WiFi module 570 Part, browsing webpage and access streaming video etc., it has provided the user wireless broadband internet and has accessed.Although Fig. 5 shows WiFi module 570, but it is understood that, it is also not belonging to must be configured into of mobile phone, can not change as required completely Omit in the scope of the essence becoming invention.

Processor 580 is the control centre of mobile phone, utilizes various interface and the various piece of the whole mobile phone of connection, logical Cross operation or perform to be stored in the software program in memorizer 520 and/or module, and calling and be stored in memorizer 520 Data, perform the various functions of mobile phone and process data, thus mobile phone is carried out integral monitoring.Optionally, processor 580 can wrap Include one or more processing unit；Preferably, processor 580 can integrated application processor and modem processor, wherein, should Mainly process operating system, user interface and application program etc. with processor, modem processor mainly processes radio communication. It is understood that above-mentioned modem processor can not also be integrated in processor 580.

Mobile phone also includes the power supply 590 (such as battery) powered to all parts, it is preferred that power supply can pass through power supply pipe Reason system is logically contiguous with processor 580, thus realizes management charging, electric discharge and power managed by power-supply management system Etc. function.

Although not shown, mobile phone can also include photographic head, bluetooth module etc., does not repeats them here.

In embodiments of the present invention, the processor 580 included by this terminal also has a following functions:

Obtain the raw image data of camera collection；

Human body image data is identified in described raw image data；

In described human body image data, detection belongs to the colour of skin view data of human body；

Characteristic information according to described human body image data arranges target colour of skin color value for described human body；

According to described target colour of skin color value, described colour of skin view data is normalized, it is thus achieved that target image number According to.

Alternatively, the processor 580 included by this terminal also has a following functions:

Eigen Skin color view data is selected in described colour of skin view data；

According to described target colour of skin color value, described Eigen Skin color view data is normalized, it is thus achieved that target figure As data.

Alternatively, the processor 580 included by this terminal also has a following functions:

Add up brightness and/or the exposure of described colour of skin view data；

From described colour of skin view data, choose brightness be less than, in default brightness section and/or exposure, the exposure preset The view data of threshold value, as Eigen Skin color view data.

Alternatively, the processor 580 included by this terminal also has a following functions:

Identify one or more features letter in the age information of described human body image data, gender information, ethnic group information Breath；

Corresponding based on one or more characteristic informations inquirer's body region in age information, gender information, ethnic group information Target colour of skin color value.

Alternatively, the processor 580 included by this terminal also has a following functions:

For each colour of skin view data, add up the original colour of skin color value in the view data of described position；

Described original colour of skin color value is used to calculate normalization coefficient with described target colour of skin color value；

It is adjusted with described normalization coefficient on the basis of described original colour of skin color value, it is thus achieved that normalization colour of skin face Colour；

In described raw image data, adjust described colour of skin view data with described normalization colour of skin color value, it is thus achieved that Destination image data.

Alternatively, the processor 580 included by this terminal also has a following functions:

Obtain the pixel color value of each pixel in described colour of skin view data；

Calculate the meansigma methods of described pixel color value, as original colour of skin color value.

Alternatively, the processor 580 included by this terminal also has a following functions:

Calculate the ratio between described target colour of skin color value and described original colour of skin color value, it is thus achieved that color adjusts ratio Example；

The pixel color value of each pixel in the view data of described position is multiplied by described adjustment ratio, it is thus achieved that pixel color Value set；

Object pixel color value is chosen from described pixel color value set；

Use described color to adjust ratio and described object pixel color value calculates normalization coefficient.

Alternatively, the processor 580 included by this terminal also has a following functions:

From described pixel color value set, the pixel color value that selected value is maximum, as object pixel color value.

Alternatively, the processor 580 included by this terminal also has a following functions:

Calculate the ratio between color threshold and the described object pixel color value preset, as pixel color ratio；

Calculate described color and adjust the product between ratio and described pixel color ratio, it is thus achieved that normalization coefficient.

Alternatively, the processor 580 included by this terminal also has a following functions:

Described raw image data is carried out image procossing；

Wherein, described image procossing includes following at least one:

Auto-exposure control, blank level adjustment, color rendition process, color enhancement process, denoising.

Those skilled in the art is it can be understood that arrive, for convenience and simplicity of description, and the system of foregoing description, The specific works process of device and unit, is referred to the corresponding process in preceding method embodiment, does not repeats them here.

In several embodiments provided by the present invention, it should be understood that disclosed system, apparatus and method are permissible Realize by another way.Such as, device embodiment described above is only schematically, such as, and described unit Dividing, be only a kind of logic function and divide, actual can have other dividing mode, the most multiple unit or assembly when realizing Can in conjunction with or be desirably integrated into another system, or some features can be ignored, or does not performs.Another point, shown or The coupling each other discussed or direct-coupling or communication connection can be the indirect couplings by some interfaces, device or unit Close or communication connection, can be electrical, machinery or other form.

The described unit illustrated as separating component can be or may not be physically separate, shows as unit The parts shown can be or may not be physical location, i.e. may be located at a place, or can also be distributed to multiple On NE.Some or all of unit therein can be selected according to the actual needs to realize the mesh of the present embodiment scheme 's.

It addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it is also possible to It is that unit is individually physically present, it is also possible to two or more unit are integrated in a unit.Above-mentioned integrated list Unit both can realize to use the form of hardware, it would however also be possible to employ the form of SFU software functional unit realizes.

One of ordinary skill in the art will appreciate that all or part of step in the various methods of above-described embodiment is can Completing instructing relevant hardware by program, this program can be stored in a computer-readable recording medium, storage Medium may include that read only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), disk or CD etc..

One of ordinary skill in the art will appreciate that all or part of step realizing in above-described embodiment method is permissible Instructing relevant hardware by program to complete, described program can be stored in a kind of computer-readable recording medium, on Stating the storage medium mentioned can be read only memory, disk or CD etc..

Above a kind of mobile terminal provided by the present invention is described in detail, for the general technology people of this area Member, according to the thought of the embodiment of the present invention, the most all will change, in sum, This specification content should not be construed as limitation of the present invention.

The embodiment of the invention discloses A1, the processing method of a kind of view data, including: obtain the original of camera collection View data；Human body image data is identified in described raw image data；Detection ownership in described human body image data Colour of skin view data in human body；Characteristic information according to described human body image data arranges mesh for described human body Mark colour of skin color value；According to described target colour of skin color value, described colour of skin view data is normalized, it is thus achieved that target View data.A2, method as described in A1, described return described colour of skin view data according to described target colour of skin color value One change processes, it is thus achieved that the step of destination image data includes: select Eigen Skin color view data in described colour of skin view data； According to described target colour of skin color value, described Eigen Skin color view data is normalized, it is thus achieved that destination image data. A3, method as described in A2, described select the step of Eigen Skin color view data to include in described colour of skin view data: statistics The brightness of described colour of skin view data and/or exposure；Brightness is chosen in default brightness region from described colour of skin view data Between and/or exposure less than the view data of threshold exposure preset, as Eigen Skin color view data.A4, such as A1 or A2 or Method described in A3, the described characteristic information according to described human body image data arranges target colour of skin face for described human body The step of colour includes: identify one or more in the age information of described human body image data, gender information, ethnic group information Characteristic information；Corresponding based on one or more characteristic informations inquirer's body region in age information, gender information, ethnic group information Target colour of skin color value.A5, method as described in A1 or A2 or A3, described according to described target colour of skin color value to described skin Color image data are normalized, it is thus achieved that the step of destination image data includes: for each colour of skin view data, statistics Original colour of skin color value in the view data of described position；Use described original colour of skin color value and described target colour of skin color value Calculate normalization coefficient；It is adjusted with described normalization coefficient on the basis of described original colour of skin color value, it is thus achieved that normalizing Change colour of skin color value；In described raw image data, adjust described colour of skin view data with described normalization colour of skin color value, Obtain destination image data.A6, method as described in A5, the original colour of skin color value in described statistics described colour of skin view data Step include: obtain the pixel color value of each pixel in described colour of skin view data；Calculate the flat of described pixel color value Average, as original colour of skin color value.A7, method as described in A5, the described original colour of skin color value of described employing and described mesh Mark colour of skin color value calculates the step of normalization coefficient and includes: calculate described target colour of skin color value and described original colour of skin color Ratio between value, it is thus achieved that color adjusts ratio；The pixel color value of each pixel in the view data of described position is multiplied by institute State adjustment ratio, it is thus achieved that pixel color value set；Object pixel color value is chosen from described pixel color value set；Use institute State color and adjust ratio and described object pixel color value calculating normalization coefficient.A8, method as described in A7, described from described The step choosing object pixel color value in pixel color value set includes: from described pixel color value set, and selected value is Big pixel color value, as object pixel color value.A9, method as described in A7, the described color of described employing adjusts ratio The step calculating normalization coefficient with described object pixel color value includes: calculate the color threshold and described object pixel preset Ratio between color value, as pixel color ratio；Calculate described color to adjust between ratio and described pixel color ratio Product, it is thus achieved that normalization coefficient.A10, method as described in any one of A1-A9, know from described raw image data described Before not going out the step of human body image data, described method also includes: described raw image data is carried out image procossing；Its In, described image procossing includes following at least one: auto-exposure control, blank level adjustment, color rendition process, color increase Strength reason, denoising.

The present invention implements to also disclose B11, the processing means of a kind of view data, including: raw image data obtains mould Block, for obtaining the raw image data of camera collection；Human body image data identification module, at described original image number Human body image data is identified according to；Broca scale is as data detection module, for detection ownership in described human body image data Colour of skin view data in human body；Target colour of skin color value arranges module, for the spy according to described human body image data Reference breath arranges target colour of skin color value for described human body；Normalized module, for according to the described target colour of skin Described colour of skin view data is normalized by color value, it is thus achieved that destination image data.B12, device as described in B11, Described normalized module is additionally operable to: select Eigen Skin color view data in described colour of skin view data；According to described mesh Described Eigen Skin color view data is normalized by mark colour of skin color value, it is thus achieved that destination image data.B13, such as B12 institute The device stated, described normalized module is additionally operable to: add up brightness and/or the exposure of described colour of skin view data；From institute State and colour of skin view data is chosen brightness in default brightness section and/or exposure less than the picture number of the threshold exposure preset According to, as Eigen Skin color view data.B14, device as described in B11 or B12 or B13, described target colour of skin color value is arranged Module is additionally operable to: identify one or more features in the age information of described human body image data, gender information, ethnic group information Information；Based on the mesh that one or more characteristic informations inquirer's body region in age information, gender information, ethnic group information is corresponding Mark colour of skin color value.B15, device as described in B11 or B12 or B13, described normalized module is additionally operable to: for each Colour of skin view data, adds up the original colour of skin color value in the view data of described position；Use described original colour of skin color value with Described target colour of skin color value calculates normalization coefficient；With described normalization coefficient on the basis of described original colour of skin color value It is adjusted, it is thus achieved that normalization colour of skin color value；In described raw image data, adjust with described normalization colour of skin color value Described colour of skin view data, it is thus achieved that destination image data.B16, device as described in B15, described normalized module is also used In: obtain the pixel color value of each pixel in described colour of skin view data；Calculate the meansigma methods of described pixel color value, as Original colour of skin color value.B17, device as described in B15, described normalized module is additionally operable to: calculate the described target colour of skin Ratio between color value and described original colour of skin color value, it is thus achieved that color adjusts ratio；By each in the view data of described position The pixel color value of pixel is multiplied by described adjustment ratio, it is thus achieved that pixel color value set；From described pixel color value set Choose object pixel color value；Use described color to adjust ratio and described object pixel color value calculates normalization coefficient. B18, device as described in B17, described normalized module is additionally operable to: from described pixel color value set, and selected value is Big pixel color value, as object pixel color value.B19, device as described in B17, described normalized module is also used In: calculate the ratio between color threshold and the described object pixel color value preset, as pixel color ratio；Calculate described Color adjusts the product between ratio and described pixel color ratio, it is thus achieved that normalization coefficient.B20, such as any one of B11-B19 institute The device stated, also includes: image processing module, for described raw image data is carried out image procossing；Wherein, described image Process and include following at least one: auto-exposure control, blank level adjustment, color rendition process, color enhancement process, denoising Process.

The embodiment of the invention also discloses C21, a kind of mobile terminal, including: memorizer and processor；Wherein, deposit described in Reservoir, for storing the instruction of the raw image data obtaining camera collection, identifies human body in described raw image data The instruction of view data, in described human body image data, detection belongs to the instruction of the colour of skin view data of human body, root The instruction of target colour of skin color value is set for described human body according to the characteristic information of described human body image data, according to described Described colour of skin view data is normalized by target colour of skin color value, it is thus achieved that the instruction of destination image data；Described place Reason device is used for: according to the instruction of the raw image data of described acquisition camera collection, obtain the original image of camera collection Data；In described raw image data, human body image data instruction is identified, in described raw image data according to described Identify human body image data；According to described in described human body image data detection belong to the colour of skin picture number of human body According to instruction, in described human body image data, detection belongs to the colour of skin view data of human body；Described in described basis The characteristic information of human body image data arranges the instruction of target colour of skin color value for described human body, according to described human figure As the characteristic information of data arranges target colour of skin color value for described human body；According to described according to described target colour of skin face Described colour of skin view data is normalized by colour, it is thus achieved that the instruction of destination image data, according to the described target colour of skin Described colour of skin view data is normalized by color value, it is thus achieved that destination image data.C22, mobile end as described in C21 End, described processor is additionally operable to: select Eigen Skin color view data in described colour of skin view data；According to the described target colour of skin Described Eigen Skin color view data is normalized by color value, it is thus achieved that destination image data.C23, shifting as described in C22 Dynamic terminal, described processor is additionally operable to: add up brightness and/or the exposure of described colour of skin view data；From described broca scale picture Data are chosen brightness and is less than the view data of the threshold exposure preset in default brightness section and/or exposure, as spy Levy colour of skin view data.C24, mobile terminal as described in C21 or C22 or C23, described processor is additionally operable to: identify described people One or more characteristic informations in the age information of volumetric image data, gender information, ethnic group information；Based on age information, property The target colour of skin color value that one or more characteristic informations inquirer's body region in other information, ethnic group information is corresponding.C25, as Mobile terminal described in C21 or C22 or C23, described processor is additionally operable to: for each colour of skin view data, add up described portion Original colour of skin color value in bit image data；Use described original colour of skin color value to calculate with described target colour of skin color value to return One changes coefficient；It is adjusted with described normalization coefficient on the basis of described original colour of skin color value, it is thus achieved that the normalization colour of skin Color value；In described raw image data, adjust described colour of skin view data with described normalization colour of skin color value, it is thus achieved that mesh Logo image data.C26, mobile terminal as described in C25, described processor is additionally operable to: obtain in described colour of skin view data each The pixel color value of pixel；Calculate the meansigma methods of described pixel color value, as original colour of skin color value.C27, such as C25 institute The mobile terminal stated, described processor is additionally operable to: calculate between described target colour of skin color value and described original colour of skin color value Ratio, it is thus achieved that color adjust ratio；The pixel color value of each pixel in the view data of described position is multiplied by described adjustment Ratio, it is thus achieved that pixel color value set；Object pixel color value is chosen from described pixel color value set；Use described color Adjustment ratio and described object pixel color value calculate normalization coefficient.C28, mobile terminal as described in C27, described processor Being additionally operable to: from described pixel color value set, the pixel color value that selected value is maximum, as object pixel color value.C29、 Mobile terminal as described in C27, described processor is additionally operable to: calculate color threshold and the described object pixel color value preset it Between ratio, as pixel color ratio；Calculate described color and adjust the product between ratio and described pixel color ratio, obtain Obtain normalization coefficient.C30, mobile terminal as described in any one of C21-C29, described memorizer is additionally operable to storage to described original View data carries out the instruction of image procossing；Described processor is additionally operable to: according to described, described raw image data is carried out figure As the instruction processed, described raw image data is carried out image procossing；Wherein, described image procossing includes following at least one Kind: auto-exposure control, blank level adjustment, color rendition process, color enhancement process, denoising.

Claims (10)

1. a processing method for view data, including:

Obtain the raw image data of camera collection；

Human body image data is identified in described raw image data；

In described human body image data, detection belongs to the colour of skin view data of human body；

Characteristic information according to described human body image data arranges target colour of skin color value for described human body；

According to described target colour of skin color value, described colour of skin view data is normalized, it is thus achieved that destination image data.

2. the method for claim 1, it is characterised in that described according to described target colour of skin color value to described broca scale As data are normalized, it is thus achieved that the step of destination image data includes:

Eigen Skin color view data is selected in described colour of skin view data；

According to described target colour of skin color value, described Eigen Skin color view data is normalized, it is thus achieved that target image number According to.

3. method as claimed in claim 2, it is characterised in that described selection Eigen Skin color figure in described colour of skin view data As the step of data includes:

Add up brightness and/or the exposure of described colour of skin view data；

From described colour of skin view data, choose brightness be less than, in default brightness section and/or exposure, the threshold exposure preset View data, as Eigen Skin color view data.

4. the method as described in claim 1 or 2 or 3, it is characterised in that the described feature according to described human body image data is believed The step that breath arranges target colour of skin color value for described human body includes:

Identify one or more characteristic informations in the age information of described human body image data, gender information, ethnic group information；

Based on the mesh that one or more characteristic informations inquirer's body region in age information, gender information, ethnic group information is corresponding Mark colour of skin color value.

5. the method as described in claim 1 or 2 or 3, it is characterised in that described according to described target colour of skin color value to described Colour of skin view data is normalized, it is thus achieved that the step of destination image data includes:

For each colour of skin view data, add up the original colour of skin color value in the view data of described position；

Described original colour of skin color value is used to calculate normalization coefficient with described target colour of skin color value；

It is adjusted with described normalization coefficient on the basis of described original colour of skin color value, it is thus achieved that normalization colour of skin color Value；

In described raw image data, adjust described colour of skin view data with described normalization colour of skin color value, it is thus achieved that target View data.

6. method as claimed in claim 5, it is characterised in that the original colour of skin face in described statistics described colour of skin view data The step of colour includes:

Obtain the pixel color value of each pixel in described colour of skin view data；

Calculate the meansigma methods of described pixel color value, as original colour of skin color value.

7. method as claimed in claim 5, it is characterised in that the described original colour of skin color value of described employing and described target skin Color color value calculates the step of normalization coefficient and includes:

Calculate the ratio between described target colour of skin color value and described original colour of skin color value, it is thus achieved that color adjusts ratio；

The pixel color value of each pixel in the view data of described position is multiplied by described adjustment ratio, it is thus achieved that pixel color value collection Close；

Object pixel color value is chosen from described pixel color value set；

Use described color to adjust ratio and described object pixel color value calculates normalization coefficient.

8. method as claimed in claim 7, it is characterised in that described choose object pixel from described pixel color value set The step of color value includes:

From described pixel color value set, the pixel color value that selected value is maximum, as object pixel color value.

9. a processing means for view data, including:

Raw image data acquisition module, for obtaining the raw image data of camera collection；

Human body image data identification module, for identifying human body image data in described raw image data；

Broca scale, as data detection module, belongs to the broca scale picture of human body for detection in described human body image data Data；

Target colour of skin color value arranges module, is used for the characteristic information according to described human body image data for described human body Target colour of skin color value is set；

Normalized module, for being normalized place according to described target colour of skin color value to described colour of skin view data Reason, it is thus achieved that destination image data.

10. a mobile terminal, including:

Memorizer and processor；

Wherein, described memorizer is for storing the instruction of the raw image data obtaining camera collection, at described original image Identifying the instruction of human body image data in data, in described human body image data, detection belongs to the broca scale of human body As the instruction of data, according to the characteristic information of described human body image data, target colour of skin color value is set for described human body Instruction, according to described target colour of skin color value, described colour of skin view data is normalized, it is thus achieved that target image number According to instruction；

Described processor is used for:

According to the instruction of the raw image data of described acquisition camera collection, obtain the raw image data of camera collection；

In described raw image data, identify human body image data instruction according to described, know in described raw image data Do not go out human body image data；

According to described in described human body image data detection belong to the broca scale of human body as data command, described people In volumetric image data, detection belongs to the colour of skin view data of human body；

According to the described characteristic information according to described human body image data, target colour of skin color value is set for described human body Instruction, according to the characteristic information of described human body image data, target colour of skin color value is set for described human body；

Described colour of skin view data is normalized according to described target colour of skin color value according to described, it is thus achieved that target figure As the instruction of data, according to described target colour of skin color value, described colour of skin view data is normalized, it is thus achieved that target View data.