WO2019023993A1

WO2019023993A1 - Method and device for processing photograph of intelligent terminal

Info

Publication number: WO2019023993A1
Application number: PCT/CN2017/095638
Authority: WO
Inventors: 唐圣杰
Original assignee: 深圳传音通讯有限公司
Priority date: 2017-08-02
Filing date: 2017-08-02
Publication date: 2019-02-07
Also published as: CN111183630B; CN111183630A

Abstract

Provided in the present invention are a method and device for processing a photograph of an intelligent terminal. The processing method comprises the following steps: acquiring at least two photographs under selection having the same target subject being photographed and a sharpness parameter of each photograph under selection; determining whether the sharpness parameter of each photograph under selection is greater than a preset sharpness parameter threshold in the intelligent terminal; if the sharpness parameter of at least one photograph in the photographs under selection is greater than or equal to the sharpness parameter threshold, saving the photograph in the at least one photograph having the greatest sharpness parameter; if the sharpness parameters of the photographs under selection are all less than the sharpness parameter threshold, extracting at least any two photographs in the photographs under selection and performing synthesis thereon to form and save a synthesized photograph. The technical solution of the present invention realizes automatic saving of clear photographs to save the time for a user to perform selection, and performs a sharpening processing on blurred photographs to synthesize a clearer photograph.

Description

Photo processing method and processing device for intelligent terminal

Technical field

The present invention relates to the field of intelligent terminals, and in particular, to a photo processing method and a processing device for an intelligent terminal.

Background technique

At present, most of the smart terminal devices are equipped with a photographing function, and the user can take photos and save the beautiful scenery, characters, and materials information through the photographing function on the smart terminal, which is very convenient. The intelligent terminal is involved in a wide range, and may be a smart phone, a digital camera, a notebook computer, a tablet computer, or the like. During the photo taking process, the user often takes multiple photos of the same target object. However, not every photo has a good visual effect. Due to the limitation of shooting conditions or the shooting performance limitations of the smart terminal itself, many photos will appear. Blurring, skewing, ghosting, etc., require the user to identify, filter, delete, and retain photos with better results. This occupies a large amount of operation time of the user, resulting in the user not being able to concentrate on enjoying the beauty or focusing on other things, causing inconvenience to the user.

The prior art has made an effort in the above technical field. For example, the Chinese invention patent publication (publication number: CN105847664A) discloses a method and device for photographing a mobile terminal, and relates to a signal processing technology to solve a user's third party image editing software. Obtain a photo image with a clear background effect of the subject's target, and operate a complicated problem. The technical solution includes: the mobile terminal includes a dual camera, the method includes: acquiring a main target and a background target from the to-be-viewed area; selecting a main camera and a secondary camera in the dual camera; and controlling the main camera to obtain a main photo image that makes the main target clear Controlling the auxiliary camera to obtain a secondary photo image that blurs the background target; synthesizing the target image according to the main photo image and the auxiliary photo image, wherein the target image includes the subject target whose resolution reaches the preset definition threshold and the blur degree reaches the preset blur degree The background target of the threshold. The technical solution provided by the embodiment of the present invention can be applied to a photographing process of a photo or a video.

Although the above invention has achieved the resolution processing of the photographic subject, the following problems still exist:

1. Clear or blur the main target and background target only during the shooting phase, without processing the clarity of the entire photo;

2. Need to use a dual camera mobile terminal, there are restrictions on hardware configuration;

3. Automated processing of blurred photos is not implemented.

Therefore, how to provide users with automated processing techniques for fuzzy photos and enhance user experience will be a technical problem that needs to be solved.

Summary of the invention

In order to overcome the above technical deficiencies, an object of the present invention is to provide a photo processing method and a processing device for an intelligent terminal, which support screening processing of photographed photos and realize the technical effect of automatic clearing processing of photographs.

A first aspect of the present application discloses a photo processing method of a smart terminal, including the following steps:

Obtaining at least two photos to be screened for the same target object and sharpness parameters of each of the photos to be screened;

Determining whether a sharpness parameter of each of the to-be-screened photos is greater than a sharpness parameter threshold preset in the smart terminal;

And storing, when the sharpness parameter of the at least one photo in the photo to be filtered is greater than or equal to the sharpness parameter threshold, saving a photo having the maximum sharpness parameter in the at least one photo;

When the sharpness parameter of the to-be-screened photo is less than the sharpness parameter threshold, at least any two of the to-be-screened photos are extracted and synthesized to form a composite photo and saved.

In some embodiments of the first aspect of the present application, the step of acquiring at least two to-be-screened photos and the sharpness parameters of each of the to-be-screened photos taken by the same target object includes:

Counting the number of noise, resolution, and grayscale change rate of the photo to be screened;

The number of noises, the resolution, and the grayscale rate of change are weighted and summed to obtain the sharpness parameter.

In some embodiments of the first aspect of the present application, when the sharpness parameter of the to-be-screened photo is less than the sharpness parameter threshold, at least any two of the to-be-screened photos are extracted and synthesized to form A step of synthesizing photos and saving them includes:

Determining whether there is a similarity matching degree of at least two photos to be filtered is greater than a matching degree threshold preset in the smart terminal;

When the similarity matching degree of the at least two photos to be filtered is greater than the matching degree threshold, the noise reduction processing of all the photos to be selected with the similar matching degree being greater than the matching degree threshold;

The synthetic noise reduction processed photo gives a composite photo.

In some embodiments of the first aspect of the present application, determining whether at least two photos have similar matching degrees greater than A step of presetting a matching threshold in the smart terminal includes:

Shrinking the pixels of the photo and converting to a grayscale image;

Calculating a grayscale average of the grayscale image;

Setting a pixel point in the grayscale image that is greater than or equal to the grayscale average value to 1 and a pixel point smaller than the grayscale average value to 0, to obtain a binary sequence;

Determine whether the difference digit of the binary sequence of any two photos is less than a preset number of bits threshold.

In some implementations of the first aspect of the present application, when the synthesized noise reduction processed photo obtains a composite photo, the photo with the pixel resolution greater than a pixel resolution threshold preset in the smart terminal is selected for synthesis. .

In a second aspect of the present application, a photo processing apparatus for a smart terminal is disclosed, the processing apparatus comprising:

a definition calculation module, which calculates a sharpness parameter of each of the photos to be filtered;

a clarity determining module, determining whether a sharpness parameter of each of the to-be-screened photos is greater than a sharpness parameter threshold preset in the smart terminal;

a saving module, when the definition determining module determines that a sharpness parameter of at least one of the photos to be filtered is greater than or equal to the sharpness parameter threshold, saving a photo of the at least one photo having a maximum sharpness parameter ;

a synthesis module, when the clarity determination module determines that the sharpness parameter of the to-be-screened photo is less than the sharpness parameter threshold, extract at least any two of the to-be-screened photos and synthesize to form a composite photo And save.

In some embodiments of the second aspect of the present application, the definition calculation module includes:

a statistical unit that counts the number of noises, the resolution, and the grayscale change rate of the photo to be screened;

And an arithmetic unit that weights the number of noises, the resolution, and the grayscale change rate to obtain the sharpness parameter.

In some embodiments of the second aspect of the present application, the synthesizing module includes:

The similarity determining unit determines whether the similar matching degree of at least two photos to be filtered is greater than a matching degree threshold preset in the smart terminal;

a noise reduction processing unit, when the similarity determination unit determines that the similarity matching degree of the at least two to-be-screened photos is greater than the matching degree threshold, the noise reduction processing of the to-be-screened photos for all similar matching degrees greater than the matching degree threshold;

The synthesis unit synthesizes the photo after the noise reduction process to obtain a composite photo.

In some embodiments of the second aspect of the present application, the similarity determining unit includes:

a scaling unit that reduces pixels of the photo and converts to a grayscale image;

a gradation calculation unit that calculates a gradation average value of the grayscale image;

a binary conversion unit, wherein a pixel point in the grayscale image that is greater than or equal to the grayscale average value is set to 1, and a pixel point that is smaller than the grayscale average value is set to 0, to obtain a binary sequence;

The digit determining unit determines whether the number of differences in the binary sequence of any two photos is less than a predetermined number of bit thresholds.

In some implementations of the second aspect of the present application, the synthesizing unit synthesizes the photo after the noise reduction process, and selects the photo with the pixel resolution greater than a pixel resolution threshold preset in the smart terminal for synthesis. .

After adopting the above technical solution, compared with the prior art, the following beneficial effects are obtained:

1. Realize automatic saving of clear photos, saving user screening operation time;

2. For blurred photos, clear them and synthesize clearer photos.

DRAWINGS

1 is a schematic flow chart of a photo processing method of a smart terminal according to a preferred embodiment of the present invention;

2 is a schematic diagram of a specific process of step S1 in FIG. 1 in accordance with a preferred embodiment of the present invention;

3 is a schematic diagram of a specific process of step S4 of FIG. 1 in accordance with a preferred embodiment of the present invention;

4 is a schematic diagram showing a specific flow of step S4-1 in FIG. 3 in accordance with a preferred embodiment of the present invention;

FIG. 5 is a schematic structural diagram of a photo processing apparatus for a smart terminal according to a preferred embodiment of the present invention; FIG.

6 is a schematic structural view of a definition calculation module in accordance with a preferred embodiment of the present invention;

7 is a schematic structural view of a synthesis module in accordance with a preferred embodiment of the present invention;

Figure 8 is a block diagram showing the structure of a similarity determining unit in accordance with a preferred embodiment of the present invention.

Reference mark:

10-processing device, 11-sharpness calculation module, 111-statistical unit, 112-arithmetic unit, 12-sharpness determination module, 13-save module, 14-synthesis module, 141-similarity judgment unit, 1411-zoom unit , 1412-gradation calculation unit, 1413-binary conversion unit, 1414-digit number determination unit, 142-noise reduction processing unit, 143-synthesis unit.

Detailed ways

The embodiments of the present application are described below by specific embodiments, and those skilled in the art can easily understand other advantages and effects of the present application from the disclosure of the present specification.

In the following description, reference is made to the drawings in the drawings It is understood that other embodiments may be utilized and that changes in mechanical composition, structure, electrical and operation may be made without departing from the spirit and scope of the disclosure. The following detailed description should not be considered as limiting. And the embodiment of the present application The scope of the invention is defined by the appended claims. The terminology used herein is for the purpose of describing particular embodiments. Spatially related terms such as "upper", "lower", "left", "right", "below", "below", "lower", "above", "upper", etc., may be used in the text for ease of explanation The relationship of one element or feature to another element or feature is shown.

Although the terms first, second, etc. are used herein to describe various elements in some instances, these elements should not be limited by these terms. These terms are only used to distinguish one element from another.

In addition, the singular forms "a", "the", and "the" "There is a description of the features, steps, operations, components, components, items, categories, and/or groups, but does not exclude one or more other features, steps, operations, components, components, items, categories, and/or The presence, appearance or addition of a group. The terms "or" and "and/or" are used herein to be construed as inclusive or meaning any one or any combination. Therefore, "A, B or C" or "A, B and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C". Only when a combination of elements, functions, steps or operations is An exception to this definition occurs when some methods are inherently mutually exclusive.

1 is a schematic flowchart of a photo processing method of a smart terminal according to a preferred embodiment of the present invention. The processing method includes the following steps:

S1: Acquire at least two to-be-screened photos taken by the same target object and sharpness parameters of each of the to-be-screened photos.

The photo to be filtered in this embodiment refers to a photo taken by the user for the same target object, and the photo to be filtered is at least two. During the shooting of the target object, the user often takes multiple photos in a short time, or uses the continuous camera function to take multiple photos, which are the photos to be filtered in this embodiment, and the photos to be filtered are received. The effects of shooting conditions may be blurred and unclear. In this step, the resolution parameter calculation is performed on each of the to-be-screened photos, and the resolution calculation manner may be based on one or more of noise, dead pixels, resolution, and gray-scale change rate of the to-be-screened photo. Combination of species. For example, if the sharpness parameter is calculated by noise, the number of noises in the photo to be filtered may be counted, and the larger the number of noises means that the lower the resolution, a numerical parameter may be set minus the number of the noise. Describe the sharpness parameters to compare different photos.

S2: Whether the resolution parameter of at least one of the photos to be filtered is greater than or equal to a sharpness parameter threshold preset in the smart terminal.

In this step, a threshold parameter of the sharpness parameter is preset in the smart terminal as a reference for the sharpness parameter of the photo to be filtered. The selection of the sharpness parameter threshold can be selected according to the subjective visual standard of the user. Select a photo that just meets the definition requirement, calculate a sharpness parameter of the photo as the sharpness parameter threshold; or calculate a sharpness parameter of multiple photos according to a big data statistical manner, according to a certain ratio, for example, clear The 20% standard before the degree parameter arrangement selects the corresponding sharpness parameter threshold. In this step, the corresponding resolution parameter is separately calculated for the photo to be selected obtained in step S1, and the sharpness parameter of each photo is compared with the sharpness parameter threshold to determine whether there is at least one of the to-be-selected The sharpness parameter of the filtered photo is greater than or equal to the sharpness parameter threshold.

S3: When the sharpness parameter of the at least one photo in the photo to be filtered is greater than or equal to the sharpness parameter threshold, save the photo with the maximum sharpness parameter in the at least one photo.

When the sharpness parameter of at least one of the photos to be filtered is greater than or equal to the sharpness parameter threshold, the trigger condition of the step is satisfied, and the photo having the maximum sharpness parameter among the photos satisfying the definition is saved. For example, there are three chapters to be screened, which are photo A, photo B, photo C, and photo D. The sharpness parameter of photo A is 80, the sharpness parameter of photo B is 50, and the sharpness parameter of photo C is 75. The sharpness parameter of the photo D is 60. If the sharpness parameter threshold is 70, then the photo A and the photo C satisfy the condition that is greater than or equal to the sharpness parameter threshold, and the sharpness parameter of the photo A is larger than the photo C, thus saving the photo A.

S4: When the sharpness parameter of the to-be-screened photo is less than the sharpness parameter threshold, extract at least any two of the to-be-screened photos and combine to form a composite photo and save.

When the sharpness parameter of all the photos in the photo to be filtered is smaller than the sharpness parameter threshold, the content of the step is performed, that is, at least any two of the photos to be filtered are extracted for synthesis to form a Combine photos and save them. The step and the step S3 jointly form a judgment result of the value of the resolution parameter of the to-be-screened image, which are respectively two mutually exclusive parts of the judgment result, that is, the resolution parameter of all the photos is small in this step, In other words, all the photos to be filtered are blurred. This step performs a synthesizing operation on the photo to be screened, in order to improve the clarity of the photo and achieve a better viewing effect. The photo to be screened to be synthesized may be two or three or more. The method for synthesizing the photo to be filtered may be based on one of the photos, and the image information in the other photos is extracted for the pixels of the blurred portion in the photo, and the content in all the photos is replaced. Finally, the synthetic photograph can be obtained. Or for the photo to be screened, each photo must have the same pixel size, and then the pixels of each photo are superimposed to form a new photo.

Referring to FIG. 2, it is a schematic diagram of a specific process in step S1 of FIG. 1 in accordance with a preferred embodiment of the present invention. Step S1 includes:

S1-1: Counting the number of noise, the resolution, and the grayscale change rate of the photo to be filtered.

In this step, the number of noise, the resolution, and the grayscale change rate in the photo to be filtered are separately counted. The noise, Refers to foreign pixels that should not appear in the image, usually caused by electronic interference, which looks like the image is dirty and covered with some small rough spots. The number of noises is the number of noises in a photo. The statistical method of the noise is to traverse all the pixels on the photo to determine the pixel difference between each pixel and the surrounding pixels. If the pixel difference of each pixel is large, it is determined that the pixel is noise. The resolution is the number of pixels included in the unit of inch. Think of the whole photo as a large board, and the resolution is the number of intersections of all warp and weft. The higher the resolution, the clearer the picture. The pixels in the photo are digitized information stored in a specific format with the smart terminal, and it is easy to count the resolution of the photo. The gray value refers to the color depth of the dots in the black and white image. The range is generally from 0 to 255, white is 255, and black is 0. The gradation change rate refers to the maximum value of the number of pixels of the gradation value of each row continuously decreasing, and the higher the gradation change rate, the clearer the color limit and the higher the image definition. Since the pixel itself is in a digitized information format, the grayscale rate of change can be derived from the pixel information.

S1-2: Weighting the number of noises, the resolution, and the grayscale change rate to obtain the sharpness parameter.

In this step, a weighted summation operation is performed on the number of noises, the resolution, and the grayscale change rate. For example, in a photo, the number of noise is 80, the resolution is 1 million, and the grayscale change rate is 300. Then, the above three parameters are given different weight coefficients, and the weight coefficient of the number of noise is -3, and the resolution is The weight is 0.0002, and the weight of the gray rate is 1. Then, the above noise number, resolution, and gradation change rate are respectively multiplied by respective weight coefficients and summed to obtain a sharpness parameter of 340.

Referring to FIG. 3, it is a schematic diagram of a specific process in step S4 of FIG. 1 in accordance with a preferred embodiment of the present invention. Step S4 includes:

S4-1: Determine whether there is a similarity matching degree of at least two photos to be filtered that is greater than a matching degree threshold preset in the smart terminal.

In this step, the similarity degree of the screening photos is judged, and when the similarity judgment is performed on the screening photos, at least two photos are involved in the comparison. The step of calculating the similarity matching degree of the to-be-screened photos to be compared, and comparing the similarity matching degree with a preset matching degree threshold in the smart terminal, and determining whether a similar matching degree of at least two photos is greater than The matching degree threshold. Calculating the similarity degree of the to-be-screened photos, performing algorithm calculation on the pixels of the to-be-screened photos to obtain comparable numerical information; a commonly used algorithm has a perceptual hash algorithm and a scale-invariant feature conversion algorithm (SIFT) Wait. The step of the scale-invariant feature conversion algorithm is: scale space extremum detection: searching for image positions on all scales. The Gaussian differential function is used to identify potential points of interest that are invariant to scale and rotation. Key point positioning: At each candidate position, the position and scale are determined by a well-fitting model. The choice of key points depends on their degree of stability; direction determination: based on image locality The gradient direction is assigned to one or more directions for each key point location; the key point description: the local gradient of the image is measured at a selected scale within the neighborhood around each key point.

S4-2: When the similarity matching degree of the at least two photos to be filtered is greater than the matching degree threshold, the noise reduction processing of all the photos to be selected with the similar matching degree being greater than the matching degree threshold.

This step executes the corresponding content according to the judgment result of step S4-2. When the similarity degree of the at least two to-be-screened photos is greater than the matching degree threshold, the triggering condition of the step is satisfied, and then all the similarly matched degrees are greater than the matching degree threshold. The manner of performing noise reduction processing on the to-be-screened photo may be a neighborhood averaging method, a median filtering method, and a wavelet transform method. Taking the neighborhood averaging method as an example, the implementation method is to remove the abrupt pixel points by averaging the pixels in one point and the neighborhood, thereby filtering out certain noise, for example, the pixel of a certain noise is 50, and the adjacent pixels are respectively For 150, 160, 140, and 145, the average of the adjacent pixel points is averaged, and 149 is obtained after rounding off, and then the pixel of the noise is changed to 149.

S4-3: A photo taken after the synthetic noise reduction process is obtained.

In this step, the step S4-2 is followed, and the photos after the noise reduction processing are combined to obtain the composite photograph. The method of synthesizing photographs has been explained in step S4 and will not be described again. If the number of photos processed in step S4-2 is two or more, for example, four photos, the four photos are combined into one photo.

Referring to FIG. 4, it is a schematic diagram of a specific process in step S4-1 of FIG. 3 in accordance with a preferred embodiment of the present invention. The step S4-1 is further refined. The step S4-1 includes:

S4-1-1: The pixels of the photo are reduced and converted into a grayscale image.

This step first reduces the photo to a size of 8x8 for a total of 64 pixels. To reduce the photo, first divide the photo into 8x8 areas, then calculate the average of all the pixels in each area, and then use this average as the pixels of the reduced photo. The effect of reducing the photo is to remove the difference between the various image sizes and the image ratio, and only retain the basic information such as structure, light and dark. Then, the reduced picture is converted into a grayscale picture. Since the gray value is also represented by a value of 0-255, the pixel value of the reduced picture can be directly converted into a gray value.

S4-1-2: Calculate the average value of the gradation of the grayscale image.

In this step, 64 gray values in the grayscale image obtained in step S4-1-1 are averaged to obtain a grayscale average value.

S4-1-3: A pixel point in the grayscale image that is greater than or equal to the grayscale average value is set to 1, and a pixel point that is smaller than the grayscale average value is set to 0, and a binary sequence is obtained.

In this step, the gray value of each pixel in the grayscale image is compared with the grayscale average value based on the grayscale average value. If the gray value of the pixel is greater than or equal to the gray average, the pixel The point is set to 1; if the gray value of the pixel is smaller than the gray average, the pixel is set to zero. Thus, all the pixels of the grayscale image are represented as 0 or 1, and the values of the pixels are arranged in a coordinate order to obtain a binary sequence.

S4-1-4: Determine whether the difference digit of the binary sequence of any two photos is less than a preset number of bits threshold.

Steps S4-1-3 can obtain a binary sequence of all the photos participating in the similar matching degree comparison, and compare the difference of the binary sequences of the photos, the comparison manner is to determine how many bits of the binary sequence of the two photos are different. Taking a binary sequence with a total length of 5 bits as an example, the binary sequence A is 01010, and the binary sequence B is 01001. It can be seen that the binary sequence A is different from the binary sequence B and the two are different. For the present embodiment, the more the number of digits of the binary sequence difference of the photo, the larger the difference in the photos participating in the comparison, so the one-digit threshold must be preset as a criterion for judging the difference of the binary sequence of the photo. If the binary sequence difference digits of the two photos are smaller than the number of digit thresholds, the similar matching degree of the two photos satisfies the requirement.

In some implementations of the first aspect of the present application, when step S4-3 is performed, the photo with the pixel resolution greater than a pixel resolution threshold preset in the smart terminal is selected for synthesis. The improvement conditionally limits the step of synthesizing the noise-reduced photo to obtain a composite photo, that is, selecting a photo with a pixel resolution greater than the pixel resolution threshold for synthesis. The step S4-2 performs noise reduction processing on all the photos whose similar matching degree is greater than the matching degree threshold, and the photos may be multiple sheets, and the resolution thereof changes after the noise reduction processing, so it is necessary to The photos after the noise reduction process are screened, and the photos with higher definition are selected for synthesis. The pixel resolution, that is, the number of pixels in the photo, only when the pixel resolution of the photo is greater than the pixel resolution threshold, means that the photo is relatively clear.

5 is a schematic structural diagram of a photo processing apparatus for a smart terminal according to a preferred embodiment of the present invention. The processing apparatus 10 includes:

- Sharpness calculation module 11

The sharpness calculation module 11 calculates a sharpness parameter of each of the photos to be filtered. The definition calculation module 11 is a software module, and acquires at least two to-be-screened photos taken by the same target object from the smart terminal, and calculates a sharpness parameter of each of the to-be-screened photos. The photo to be screened is stored in the form of digitized information in the smart terminal, specifically, in the form of a matrix of pixel points, each pixel having a value of 0 to 255, representing a different color. The manner of calculating the sharpness parameter of the photo to be filtered may be based on a combination of one or more of noise, dead point, resolution, and grayscale change rate of the photo to be filtered. Taking resolution as an example, the resolution is the number of pixels of a photo. The number of pixels may be different for different photos. The more pixels, the more the image will be able to display the details of the image, and the clearer the definition; The module 11 counts the number of photos to be filtered, and As the sharpness parameter, the number of pixels is used as the sharpness parameter, or the number of the pixels is subjected to a line type operation to obtain a smaller range of values.

- Definition determination module 12

The definition determining module 12 determines whether the sharpness parameter of each of the to-be-screened photos is greater than a sharpness parameter threshold preset in the smart terminal. The definition determining module 12 is a software module, and the sharpness parameter of the to-be-screened photo is obtained from the definition calculation module 11 and compared with a sharpness parameter threshold preset in the smart terminal. The comparison operation performed by the definition judgment module 12, that is, the numerical value comparison operation, is easy to implement. The definition determining module 12 determines whether the sharpness parameter of the photo to be filtered is greater than the sharpness parameter threshold, so as to be a judgment condition for subsequent processing.

- Save module 13

The saving module 13 is configured to save the maximum sharpness parameter in the at least one photo when the sharpness determining module 12 determines that the sharpness parameter of the at least one photo in the to-be-screened photo is greater than or equal to the sharpness parameter threshold. Photo. The operation of the saving module 13 first satisfies the precondition that the resolution determining module 12 determines that the sharpness parameter of at least one of the photos to be filtered is greater than or equal to the sharpness parameter threshold, that is, the resolution requirement is met. The to-be-screened photo can be saved, and the saving module 13 acquires the determination result from the definition determination module 12. When the saving module 13 saves the photo that meets the definition requirement, the photo having the highest sharpness parameter in the photo that meets the definition requirement is selected, that is, only one photo with the highest definition is saved, so that the same target object can be saved. The clearest picture saves the storage space of the smart terminal and saves the user's screening operation time. When the save module 13 saves the photo, it saves according to the data format supported by the smart terminal, such as jpg, png, and the like.

- Synthesis module 14

a synthesizing module 14 , when the resolution determining module 12 determines that the sharpness parameter of the to-be-screened photo is less than the sharpness parameter threshold, extract at least any two of the to-be-screened photos and combine to form a Combine photos and save them. The operation of the synthesizing module 14 must also satisfy the precondition that the resolution determining module 12 determines that the sharpness parameter of the photo to be filtered is smaller than the sharpness parameter threshold, that is, all the photos to be filtered are not Meet the clarity requirements. The synthesizing module 14 extracts at least any two of the to-be-screened photos as a composite material, and then performs a synthesizing operation on the extracted photos to obtain a composite photo. Specific synthetic methods have been set forth in the method examples.

Referring to FIG. 6, which is a schematic structural diagram of a definition calculation module 11 according to a preferred embodiment of the present invention, the definition calculation module 11 includes:

- Statistics unit 111

The statistics unit 111 is configured to count the number of noises, the resolution, and the grayscale change rate of the photo to be filtered. The statistic unit 111 is a software module, and counts three parameters, namely, the number of noises, the resolution, and the gradation change rate. These three parameters can be reflected by the values of the pixel points, so the statistics and comparisons of the pixel values can be performed. The equivalent operation obtains the first off parameter, and the specific calculation method is explained in the method embodiment.

- arithmetic unit 112

The operation unit 112 weights the noise number, the resolution, and the grayscale change rate to obtain the sharpness parameter. The operation unit 112 acquires the parameters of the noise number, the resolution, and the grayscale change rate from the statistical unit 111, and then performs weighted average calculation on the above three parameters to obtain the sharpness parameter. The arithmetic unit 112 implements normalization of a plurality of sharpness parameters to uniformly compare the sharpness parameters of the photograph.

Referring to FIG. 7, a schematic structural diagram of a synthesizing module 14 according to a preferred embodiment of the present invention, the synthesizing module 14 includes:

- Similarity judgment unit 141

The similarity determining unit 141 determines whether the similar matching degree of at least two photos to be filtered is greater than a matching degree threshold preset in the smart terminal. The similarity determining unit 141 first calculates the similarity degree of the filtered photos. Since at least two photos can be compared for the similarity, the similar matching degree must be calculated for at least two photos to be filtered, or three Zhang and above photos to be filtered are calculated. In the prior art, there are mature algorithms for calculating the similarity of photographs. The commonly used algorithms are perceptual hashing algorithm, scale invariant feature transforming algorithm (SIFT), etc., and specific algorithm implementations are not described again. After the similarity judgment unit 141 calculates the similarity matching degree, and compares with the matching degree threshold value, it can be determined whether the photo participating in the similarity matching degree calculation satisfies the similarity requirement for subsequent processing.

- Noise reduction processing unit 142

The noise reduction processing unit 142, when the similarity determination unit 141 determines that the similarity matching degree of at least two photos to be filtered is greater than the matching degree threshold, denoising all the photos to be selected with similar matching degrees greater than the matching degree threshold deal with. The operation of the noise reduction processing unit 142 must first satisfy the precondition that the similarity determination unit 141 determines that the similarity matching degree of at least two photos to be filtered is greater than the matching degree threshold, that is, at least the photos to be filtered. The similarity is higher. Then, the noise reduction processing unit 142 performs noise reduction processing on the photo that satisfies the similar matching degree requirement, and the specific processing manner has been described in the method embodiment. The noise-reduced photos reduce the effect of noise on the sharpness effect.

- Synthesis unit 143

The synthesizing unit 143 synthesizes the photo after the noise reduction processing to obtain a composite photograph. The synthesizing unit 143 acquires the noise-reduced processed photos from the noise reduction processing unit 142, and synthesizes the photos to obtain a composite photo. The manner in which the photos are synthesized has been set forth in the method embodiments.

FIG. 8 is a schematic structural diagram of a similarity determining unit 141 according to a preferred embodiment of the present invention. The similarity determining unit 141 includes:

- Zoom unit 1411

The scaling unit 1411 reduces the pixels of the photo and converts them into grayscale images. The scaling unit 1411 first reduces the photo to a size of 8x8 for a total of 64 pixels. The method of reducing the photo has been explained in the method embodiment. Then, the scaling unit 1411 converts the reduced picture into a grayscale picture. Since the gray value is also represented by a value of 0-255, the pixel value of the reduced picture is directly converted into a gray value.

- Grayscale calculation unit 1412

The gradation calculation unit 1412 acquires the gradation map from the scaling unit 1411, and calculates a gradation average value of the gradation map. The gradation calculation unit 1412 performs an average calculation on the 64 gradation values in the gradation map to obtain a gradation average value.

- Binary conversion unit 1413

The binary conversion unit 1413 sets a pixel point of the grayscale image greater than or equal to the grayscale average value to 1, and a pixel point smaller than the grayscale average value to 0, to obtain a binary sequence. The binary conversion unit 1413 acquires the grayscale image from the scaling unit 1411, and obtains the grayscale average value from the grayscale calculation unit 1412, and then compares the grayscale average value with reference. The gray value of each pixel in the grayscale image. If the gray value of the pixel in the grayscale image is greater than or equal to the grayscale average value, the pixel point is set to 1; if the grayscale value of the pixel in the grayscale image is smaller than the grayscale average value , then set the pixel to 0. The grayscale image is then converted to a 64-bit binary sequence.

- Digit determination unit 1414

The bit number determining unit 1414 determines whether the number of difference bits of the binary sequence of any two photos is smaller than a predetermined number of bit thresholds. The bit number judging unit 1414 compares the difference of the binary sequences of the photographs by comparing how many bits of the binary sequence of the two photographs are different. The comparison and statistical manner of the number of difference bits has been set forth in the method embodiments. The digit count unit 1414 presets a one-digit threshold as a criterion for judging the difference in the binary sequence of the photo. If the binary sequence difference digits of the two photos are smaller than the number of digit thresholds, the similar matching degree of the two photos satisfies the requirement.

In some embodiments of the second aspect of the present application, when the synthesizing unit 143 synthesizes the photo after the noise reduction processing, And synthesizing the photo with the pixel resolution greater than a pixel resolution threshold preset in the smart terminal. In the improvement of the embodiment, the synthesizing unit 143 performs a screening on the photo-reduced photos before the photo is synthesized, and selects the photo with the pixel resolution greater than the pixel resolution threshold, that is, the selection is clearer. The photos are synthesized. The filtering of the synthesizing unit 143 is only for the pixel resolution parameter, so as to save the calculation process, and the specific calculation manner has been explained in the method embodiment.

It should be noted that the embodiments of the present invention are preferred embodiments, and are not intended to limit the scope of the present invention. Any one skilled in the art may use the above-disclosed technical contents to change or modify the equivalent embodiments. Any modification or equivalent changes and modifications of the above embodiments in accordance with the technical spirit of the present invention are still within the scope of the technical solutions of the present invention.

Claims

A photo processing method for a smart terminal, comprising the steps of:

Obtaining at least two photos to be screened for the same target object and sharpness parameters of each of the photos to be screened;

Determining whether a sharpness parameter of each of the to-be-screened photos is greater than a sharpness parameter threshold preset in the smart terminal;

And storing, when the sharpness parameter of the at least one photo in the photo to be filtered is greater than or equal to the sharpness parameter threshold, saving a photo having the maximum sharpness parameter in the at least one photo;

When the sharpness parameter of the to-be-screened photo is less than the sharpness parameter threshold, at least any two of the to-be-screened photos are extracted and synthesized to form a composite photo and saved.
The processing method according to claim 1, wherein

The steps of obtaining at least two photos to be filtered and the sharpness parameters of each of the photos to be filtered taken by the same target object include:

Counting the number of noise, resolution, and grayscale change rate of the photo to be screened;

The number of noises, the resolution, and the grayscale rate of change are weighted and summed to obtain the sharpness parameter.
A processing method according to claim 1 or 2, characterized in that

When the sharpness parameter of the to-be-screened photo is smaller than the sharpness parameter threshold, the step of extracting at least any two of the to-be-screened photos and synthesizing to form a composite photo and saving includes:

Determining whether there is a similarity matching degree of at least two photos to be filtered is greater than a matching degree threshold preset in the smart terminal;

When the similarity matching degree of the at least two photos to be filtered is greater than the matching degree threshold, the noise reduction processing of all the photos to be selected with the similar matching degree being greater than the matching degree threshold;

The synthetic noise reduction processed photo gives a composite photo.
The processing method according to claim 3, characterized in that

The step of determining whether the similarity degree of the at least two photos is greater than a matching degree threshold preset in the smart terminal comprises:

Shrinking the pixels of the photo and converting to a grayscale image;

Calculating a grayscale average of the grayscale image;

Setting a pixel point in the grayscale image that is greater than or equal to the grayscale average value to 1 and a pixel point smaller than the grayscale average value to 0, to obtain a binary sequence;

Determine whether the difference digit of the binary sequence of any two photos is less than a preset number of bits threshold.
The processing method according to claim 3, characterized in that

When the composite noise reduction processed photo obtains a composite photo, the photo with the pixel resolution greater than a pixel resolution threshold preset in the smart terminal is selected for synthesis.
A photo processing device for a smart terminal, characterized in that the processing device comprises:

a definition calculation module, which calculates a sharpness parameter of each of the photos to be filtered;

a clarity determining module, determining whether a sharpness parameter of each of the to-be-screened photos is greater than a sharpness parameter threshold preset in the smart terminal;

a saving module, when the definition determining module determines that a sharpness parameter of at least one of the photos to be filtered is greater than or equal to the sharpness parameter threshold, saving a photo of the at least one photo having a maximum sharpness parameter ;

a synthesis module, when the clarity determination module determines that the sharpness parameter of the to-be-screened photo is less than the sharpness parameter threshold, extract at least any two of the to-be-screened photos and synthesize to form a composite photo And save.
The processing method according to claim 6, wherein

The definition calculation module includes:

a statistical unit that counts the number of noises, the resolution, and the grayscale change rate of the photo to be screened;

And an arithmetic unit that weights the number of noises, the resolution, and the grayscale change rate to obtain the sharpness parameter.
A processing method according to claim 6 or 7, wherein

The synthesis module includes:

The similarity determining unit determines whether the similar matching degree of at least two photos to be filtered is greater than a matching degree threshold preset in the smart terminal;

a noise reduction processing unit, when the similarity determination unit determines that the similarity matching degree of the at least two to-be-screened photos is greater than the matching degree threshold, the noise reduction processing of the to-be-screened photos for all similar matching degrees greater than the matching degree threshold;

The synthesis unit synthesizes the photo after the noise reduction process to obtain a composite photo.
The processing method according to claim 8, wherein

The similarity determining unit includes:

a scaling unit that reduces pixels of the photo and converts to a grayscale image;

a gradation calculation unit that calculates a gradation average value of the grayscale image;

a binary conversion unit, wherein a pixel point in the grayscale image that is greater than or equal to the grayscale average value is set to 1, and a pixel point that is smaller than the grayscale average value is set to 0, to obtain a binary sequence;

The digit determining unit determines whether the number of differences in the binary sequence of any two photos is less than a predetermined number of bit thresholds.
The processing method according to claim 8, wherein

When the synthesizing unit synthesizes the photo of the noise reduction process, the photo with the pixel resolution greater than a pixel resolution threshold preset in the smart terminal is selected for synthesis.