CN108596189A - A kind of general Digital Image Processing frame - Google Patents
A kind of general Digital Image Processing frame Download PDFInfo
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- CN108596189A CN108596189A CN201810335584.6A CN201810335584A CN108596189A CN 108596189 A CN108596189 A CN 108596189A CN 201810335584 A CN201810335584 A CN 201810335584A CN 108596189 A CN108596189 A CN 108596189A
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- image processing
- digital image
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- processing frame
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/56—Extraction of image or video features relating to colour
Abstract
The invention discloses a kind of general Digital Image Processing frames, which is characterized in that includes the following steps：Step 1. reads the feature of digital picture；Step 2. setting convergence target carries out calculation process, monitoring convergence target component to the digital picture feature of input；Step 3. checks whether convergence target component is up to standard, if not up to standard, continue to execute edge filter operation, carries out step 2；Otherwise, terminating edge filtering operation carries out step 4；The result of step 4. output digital image processing.In the application of any Digital Image Processing, the frame of the present invention is a design implementation framework being referred to, the frame has the advantages that restrain certainly, be automatically performed, and has real value in practical applications, in theory have stability and exploitativeness.
Description
Technical field
The present invention relates to a kind of general Digital Image Processing frames, belong to digital image processing field.
Background technology
Patent " frame (the application number based on study for personalized image quality evaluation and optimization：
201610901175.9) ", be it is a kind of for provide for user carry out individuation picture quality optimization it is computer implemented
Method comprising：Computer is received the raw image data that is obtained from image scanner and is marked based on raw image data
Know one or more original image quality features.Computer by one or more user preferences by being applied to one or more originals
Beginning Image quality measures automatically determine one or more objective image quality features.Computer also mesh based on one or more
Logo image qualitative character automatically determines one or more processing parameters.Then computer can use one or more processing
Parameter handles raw image data to generate image.Such as above-mentioned existing patent is typically directed to concrete application and implements
Different algorithms lacks technology implementation framework that can be general.
Invention content
The technical problem to be solved by the present invention is to：Solve the problems, such as how to realize general technology implementation framework.
In order to solve the above-mentioned technical problem, the technical solution of the present invention is to provide a kind of general Digital Image Processing frames
Frame, which is characterized in that include the following steps：
Step 1. reads the feature of digital picture；
Step 2. setting convergence target carries out calculation process, monitoring convergence target component to the digital picture feature of input；
Step 3. checks whether convergence target component is up to standard, if not up to standard, continue to execute edge filter operation, is walked
Rapid 2；Otherwise, terminating edge filtering operation carries out step 4；
The result of step 4. output digital image processing.
Preferably, the feature of the digital picture refers to the digital picture to be calculated based on Pixel of Digital Image value
Feature.
Preferably, the feature of the digital picture includes pixel grey scale feature, color character, provincial characteristics, texture spy
One or more of sign, contour feature, edge feature, corner feature.
Preferably, border template is used to the digital picture in the step 2, carries out the filtering operation of individual element,
A variance yields is preset, and using default variance yields and calculates the difference of variance yields as convergence target component.
Preferably, check that convergence target component criterion whether up to standard is in the step 3：It is primary complete executing
After whole edge filter operates, the difference preset variance yields with calculate variance yields is calculated, if difference still above 0, is not
It is up to standard；Otherwise, as up to standard.
Preferably, the result in the step 4 is content associated with Digital Image Processing,
Preferably, the content associated with Digital Image Processing is a kind of image processing effect or an identification mesh
Mark.
In the application of any Digital Image Processing, frame of the invention is that frame is implemented in a design being referred to
Frame, the frame make any one Digital Image Processing application that can follow this method, realize that adaptive iteration executes, with
Reach design object, has the advantages that restrain certainly, be automatically performed, have real value in practical applications, in theory
There are stability and exploitativeness.
Description of the drawings
Fig. 1 is a kind of flow chart of general Digital Image Processing frame.
Specific implementation mode
In order to make the present invention more obvious and understandable, hereby with preferred embodiment, and attached drawing is coordinated to be described in detail below.
The present invention is a kind of general Digital Image Processing frame, refers to the process flow of a set of processing digital picture, the stream
Journey have general structure, including digital picture feature input, can be with the output of convergent iterative processing method, frame.Such as
Shown in Fig. 1 comprising following steps：
Step 1. read digital picture feature, such as pixel grey scale feature, color character, provincial characteristics, textural characteristics,
One or more of contour feature, edge feature, corner feature etc.；
In instances, a gray-scale image is selected, using its gray-scale pixel values directly as the spy of the digital picture
Sign；
Step 2. setting convergence target carries out calculation process, monitoring convergence target component to the digital picture feature of input；
Convergence target should be the limiting value or boundary value of a certain parameter calculated value, in image per treatment and count in this way
Undated parameter after calculation, calculating parameter value restrain the difference of desired value with it.Restraining the difference of desired value and calculating parameter should be
It gradually reduces, be intended to 0.
In instances, the border template for using the digital picture 3 × 3, carries out the filtering operation of individual element, due to every
After the marginal operation of complete image, the variance of the pixel value of image can all become larger, therefore preset a greater variance value, and
It regard default variance yields as convergence target component with the difference (default variance yields, which subtracts, calculates variance yields) for calculating variance yields；
Step 3. checks whether convergence target component is up to standard, with determine whether to continue can convergent iterative processing side
Method；If not up to standard, edge filter operation is continued to execute, step 2 is carried out；Otherwise, terminating edge filtering operation carries out step 4；
In instances, it after executing primary complete edge filter operation, calculates and presets variance yields and calculate variance yields
Difference (default variance yields subtract calculate variance yields), it is no if difference still above 0, continues to execute edge filter operation
Then with regard to terminating edge filtering operation；
The result of step 4. output digital image processing；
In instances, the digital picture iterated to calculate by multiple edge filter is provided.
By above scheme, the adaptive approach frame that can be executed with iteration by one completes preset processing mesh
Mark.The versatility of the program ensure that the stabilization of algorithm frame and can restrain, and have real value in practical applications, in theory
Have stability and exploitativeness.
Digital picture feature：It refer to the feature of the digital picture to be calculated based on Pixel of Digital Image value.These are special
Sign be calculated by common digital image processing method, such as pixel grey scale feature, color character, provincial characteristics,
Textural characteristics, contour feature, edge feature, corner feature etc..Certainly, it is not limited to that, as long as pixel value can be passed through
The characteristic quantity being calculated all can serve as the feature of digital picture.With the progress of correlative study, more digitized maps are had
As feature extraction comes.
It can convergent iterative processing method：Refer under the frame, the method used can be executed with loop iteration,
And in operation each time, it can determine whether the iteration execution under the frame continues to execute by monitoring some parameter
Or terminate to execute.
The output (i.e. the result of output digital image processing) of frame：Referring to the frame, convergence target, complete can reaching
After convergent iterative processing method, expected results are produced.This result is usually a kind of image processing effect, an identification
Target etc. content associated with Digital Image Processing.
Processing target based on the digital picture feature of frame input of the invention, and output；The processing frame it
Under, it is that iteration is supported to execute that can apply a variety of digital image processing methods, these methods to the digital picture feature of input,
And it can be to some target convergence.
The characteristics of present invention is according to Digital Image Processing, a kind of frame that can be executed with iteration of design, under the frame,
Pixel value based on picture and color character so that any one relevant Digital Image Processing application can follow we
Method realizes that adaptive iteration executes, realizes approaching for design object, to complete design target.
Claims (7)
1. a kind of general Digital Image Processing frame, which is characterized in that include the following steps：
Step 1. reads the feature of digital picture；
Step 2. setting convergence target carries out calculation process, monitoring convergence target component to the digital picture feature of input；
Step 3. checks whether convergence target component is up to standard, if not up to standard, continue to execute edge filter operation, carries out step 2；
Otherwise, terminating edge filtering operation carries out step 4；
The result of step 4. output digital image processing.
2. a kind of general Digital Image Processing frame as described in claim 1, which is characterized in that the digital picture
Feature refers to the feature of the digital picture to be calculated based on Pixel of Digital Image value.
3. a kind of general Digital Image Processing frame as claimed in claim 1 or 2, which is characterized in that the digitized map
The feature of picture includes pixel grey scale feature, color character, provincial characteristics, textural characteristics, contour feature, edge feature, angle point spy
One or more of sign.
4. a kind of general Digital Image Processing frame as described in claim 1, which is characterized in that in the step 2
Digital picture use border template, carry out the filtering operation of individual element, preset a variance yields, and by default variance yields with
The difference of variance yields is calculated as convergence target component.
5. a kind of general Digital Image Processing frame as described in claim 1, which is characterized in that examined in the step 3
It checks and accepts and holds back target component criterion whether up to standard and be：After executing primary complete edge filter operation, calculate default
Variance yields and the difference for calculating variance yields, if difference still above 0, is not up to standard；Otherwise, as up to standard.
6. a kind of general Digital Image Processing frame as described in claim 1, which is characterized in that in the step 4
As a result it is content associated with Digital Image Processing.
7. a kind of general Digital Image Processing frame as claimed in claim 6, which is characterized in that described and digital picture
It is a kind of image processing effect or an identification target to handle associated content.
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| CN201810335584.6A CN108596189A (en) | 2018-04-13 | 2018-04-13 | A kind of general Digital Image Processing frame |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156966A (en) * | 2011-04-11 | 2011-08-17 | 北方工业大学 | Medical image denoising |
| US20120269458A1 (en) * | 2007-12-11 | 2012-10-25 | Graziosi Danillo B | Method for Generating High Resolution Depth Images from Low Resolution Depth Images Using Edge Layers |
| CN104240189A (en) * | 2013-06-17 | 2014-12-24 | 富士通株式会社 | Filtering method and device for restoring anti-aliasing edges |
-
2018
- 2018-04-13 CN CN201810335584.6A patent/CN108596189A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120269458A1 (en) * | 2007-12-11 | 2012-10-25 | Graziosi Danillo B | Method for Generating High Resolution Depth Images from Low Resolution Depth Images Using Edge Layers |
| CN102156966A (en) * | 2011-04-11 | 2011-08-17 | 北方工业大学 | Medical image denoising |
| CN104240189A (en) * | 2013-06-17 | 2014-12-24 | 富士通株式会社 | Filtering method and device for restoring anti-aliasing edges |
Non-Patent Citations (1)
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| 吴一全 等: "改进投影梯度NMF的NSST域多光谱与全色图像融合", 《光学学报》 * |
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Application publication date: 20180928 |