CN1196633A - Device and method for restoration of image - Google Patents
Device and method for restoration of image Download PDFInfo
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- CN1196633A CN1196633A CN 97110080 CN97110080A CN1196633A CN 1196633 A CN1196633 A CN 1196633A CN 97110080 CN97110080 CN 97110080 CN 97110080 A CN97110080 A CN 97110080A CN 1196633 A CN1196633 A CN 1196633A
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- 238000000034 method Methods 0.000 title claims abstract description 60
- 230000007547 defect Effects 0.000 claims abstract description 89
- 239000000758 substrate Substances 0.000 claims description 52
- 230000008439 repair process Effects 0.000 claims description 29
- 230000009471 action Effects 0.000 claims description 12
- 230000003287 optical effect Effects 0.000 claims description 2
- 230000000977 initiatory effect Effects 0.000 claims 2
- 230000002159 abnormal effect Effects 0.000 abstract 1
- 238000010276 construction Methods 0.000 description 4
- 238000012937 correction Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000013459 approach Methods 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000036039 immunity Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 241000234435 Lilium Species 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- 238000010408 sweeping Methods 0.000 description 1
- 210000001835 viscera Anatomy 0.000 description 1
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Abstract
A method for repairing picture able to remove abnormal parts from scanned image is composed of image pick-up unit, image repairing unit, control unit and image output unit. Its repare method includes scanning a calibration paper to obtain base scan lines, finding out reference scan lines, finding out defects on image based on the base and reference scan lines and repairing the defects.
Description
The present invention system is about a kind of image fixing apparatus, it can be to charge coupled device (Charge CoupledDevice, CCD) or contact-type image sensor (Contact Image Sensor, CIS) image of being exported (Image) imposes the action of reparation, removing the black line in the image or the anomaly of heterochromatic line, and then improve the image output quality of device such as scanner.
In today of science prosperity, image processing techniques is also maked rapid progress, with image informations miscellaneous such as photo or picture (Image information) input computer no longer is difficult matter, the simplest and inexpensive manner, promptly be to utilize scanner that image is swept computer, use image processing techniques again, sweeping image is done correction, such as removal of stain, heterochromatic line or the like.
Yet general hand held or platform-type scanner system are considered based on coml, and its price can be too not high; Yet just because the restriction on the cost; the image sensor element of scanner system; manufacturing precision such as CCD and CIS etc. is also not high; so regular meeting causes the phenomenon of image abnormity, for example generation of black line or heterochromatic line in light path (Optical path), because of the flaw of dust, Viscera point or other system itself.Therefore needed badly before the scanner system output image, increase the method for an image repair, the unusual part in the above-mentioned image is eliminated, and image is imposed the work of reparation.
In above-mentioned background of invention, traditional scanner system causes output image to have the anomaly of black line or heterochromatic line because of the flaw of itself, therefore needed badly before the scanner system output image, utilize an image fixing apparatus, unusual part in the above-mentioned image is eliminated, and image imposed the work of reparation, the present invention promptly proposes corrective measure at this demand.
According to above-described purpose, the invention provides a kind of image fixing apparatus, comprise an image pickup (pick-up) unit, an image repair unit, a control unit and an image output unit.Image fixing apparatus during at input picture, utilizes the image repair unit that this image is carried out the action of repairing in image pickup units, more patched image is exported it via the image output unit; Control unit is then controlled the repair action of image repair unit.
Image fixing apparatus provided by the invention is repaired the method for image, the calibration paper (Calibration paper) of system's one calibration usefulness of scanning earlier is to obtain substrate scan line (Base scan line), after finding out reference scan line (Reference scan line), then utilize substrate scan line and reference scan line defect point (Defect point) again, the operation of more all defect points being repaired at last to find out image.
Purpose of the present invention, feature and advantage, will do more detailed elaboration with reference to the accompanying drawings in conjunction with preferred embodiment:
Brief Description Of Drawings:
Fig. 1 is framework (construction) block diagram of the image fixing apparatus of the present invention's exposure;
Fig. 2 is inside structure (construction) block diagram of the image repair unit in the image fixing apparatus;
Fig. 3 describes the operational flowchart of image fixing apparatus in image repair;
Fig. 4 describes in the preferred embodiment of the present invention, scans the operation situation of a substrate scan line (Base scan line);
Fig. 5 is a flow chart, describes the situation of scanning one reference scan line (Reference scanline) in the preferred embodiment;
Fig. 6 describes in the preferred embodiment, in order to ask for the method for dynamic defect degree level (Dynamic defectlevel);
Fig. 7 is in the preferred embodiment, the method for compensating images defect point;
Fig. 8 A describes a typical curve of reference scan line; And
Fig. 8 B describes to use curve approximatioss (Approximate curve) in the situation of asking for block level mean value.
Fig. 1 comprises an image pickup (pick-up) unit 101, an image mending unit 102, an image output unit 103 and a control unit 104 for framework (Construction) block diagram of the image fixing apparatus of the present invention's exposure.Image pickup units 101 can be CCD (Charge Coupled Device) or CIS (Contact Image Sensor), the work that responsible image is collected; The image that image mending unit 102 input picture pickup units 101 are exported via the control of control unit 104, is engaged in the operation of image repair; 103 output images of image output unit are repaired the image after unit 102 is repaired.
Fig. 2 describes in the image fixing apparatus, the internal structure of image mending unit 102 (Construction) block diagram comprises a substrate scan line and picks up that (pick-up) unit 201, a reference scan line pick up (pick-up) unit 202, a defect level is set (set) unit 203, a defect level record cell 204, an image repair unit 205 among the figure.Substrate scan line pickup unit 201 utilizes a calibration paper (Calibrationpaper) to produce a substrate scan line (Base scan line); Behind the image that 202 inputs of reference scan line pickup unit are exported by image pickup units 101, and produce a plurality of reference scan lines (Referencescan line) according to this; Defect level setup unit 203 is imported substrate scan line and reference scan lines, sets the defect level level (Defect level) of image according to this; 204 defect level level according to setting of defect level record cell mark all defect point in this image; At last by image repair unit 205 responsible for rehabilitation images.
All unit of 102 inside, image repair unit all can utilize hardware (Hardware), firmware (Firmware) or software (Software) to finish, but the control of the controlled unit 104 of operational motion palpus is because control unit 104 provides its required sequential control signals such as (Timing).
Fig. 3 describes the operational flowchart of image fixing apparatus in image repair.When image fixing apparatus is being repaired in the image, it must scan a calibration paper (step 301) earlier, in order to find out a substrate scan line (step 302), and after finding out reference scan line (step 303), utilize substrate scan line and reference scan line to find out all defect point (step 304) of image that this image pick-up device forms, and this defect point is carried out the action (step 305) of repairing.
Will be in the explanation backward to substrate scan line, reference scan line, do further elaboration with the obtain manner of image deflects point.
What Fig. 4 described is in the preferred embodiment, scans the operation situation of a substrate scan line.At first make scan line add up to N, and begin scanning (step 401) again after need skipping L bar line, and before scanning, set a parameter i (step 402), to write down the line that is scanned at present, be which the bar line on the scanning paper actually, and behind the line number that obtains desire scanning, sweep the information (information) (step 403) of this line immediately by calibration paper.Judge then whether this line that sweeps needs skips steps (step 404); Do not list calculating (step 405) in if need skip then the relevant information of this line (information), and make the content of this parameter i increase by 1 (step 407), then repeat the above-mentioned information (step 403) that sweeps this line, judge that step (step 404) that whether this line need skip is till the scan line that is swept is required.
When the scan line information (information) that is swept no longer by in the cancellation, image fixing apparatus must be judged the scan line sum that swept whether enough (step 406); If lazy weight, then need to continue again the action that scans, so the content (step 407) of increment parameter i, the operation (step 403) of the scanning that continues.Above-mentioned scanning imaging system repeats always, till the scan line sum reaches N, and utilizes all scan line information (information) to find out substrate scan line (step 408).
Selected calibration paper is lily blank sheet of paper in the preferred embodiment, and to the information (information) of calibration paper scanning 100 (N) bar line looking for the substrate scan line, and need skip 10 (L) bar line during beginning.With preferred embodiment, begin for the Sub_clause 11 line by the scanning line number that paper swept, till the 110th scan line information (information).
In addition, obtain the substrate method of scanning lines in the preferred embodiment, system is with all scan lines that obtained, get respectively at obtaining its mean value in red (R), green (G), blue (B) three channels (Channel), so in fact R, G, B respectively have its substrate scan line, backward also only with the running of a channel with as illustrative purposes.
Before repairing image, still need obtain a reference scan line, and be that benchmark compares with the substrate scan line.Yet obtain the method for reference scan line, in known techniques, existing neighbor point can be done utilization with reference to method (Neighborhood reference), wherein is divided into again with reference to two kinds of function modes of left point (Left reference) and reference right point (Right reference).To be example, if the information (information) of substrate scan line each point is with reference to left some technology:
Pb
0, Pb
1, Pb
2..., Pb
N-1Reference scan line then is:
Pr
0, Pr
1, Pr
2..., Pr
N-1Pr wherein
0=Pb
0, Pr
u=Pb
I-1, i=1 ... n-1; Similar with reference to right point methods to reference left side point.No matter yet be with reference to left side point or with reference to right point methods, although implement easily, also only more effective for the elimination of some relative spikes (Spike) or trough (Valley), so need better reference scan line acquisition methods.
The acquisition that Fig. 5 promptly describes in the preferred embodiment to be proposed has more the adquisitiones of reference value reference scan line, and called after curve approximatioss (Approximate curve).At first image is cut to a plurality of blocks (step 501), next in each image block, find out a plurality of to obtain its level mean value (step 502), then use this level mean value in each block, to find out corresponding points (step 503), and be one group with three corresponding points and draw a curve, in order to represent regional reference scan line (step 504), connect all regional reference scan lines at last, promptly obtain required reference scan line (step 505).
The level of indication in the above-mentioned step 502 is the hue level of picture point; And in the step 503 level mean value with block, in this block, find out a level value and the immediate picture point of level mean value, and be corresponding points with this point, the benefit of doing like this is to increase noise immunity (Noise immunity), the too much block of noise only, otherwise all can obtain gratifying result.Step 504 is that three adjacent corresponding points are obtained a conic section, thus in the image block of these three adjacent corresponding points the point on all reference scan lines, all can utilize this conic section and obtain.So then not only make outside the reference scan line more level and smooth (Smoothing), also more meet the feature of image sensing device, therefore the reference scan line that is obtained is good than neighbor point with reference to method.
Utilize Fig. 8 A and Fig. 8 B that step 502 is done further and explain orally, Fig. 8 A describes a typical curve of reference scan line, and Fig. 8 B then describes to use the curve approximatioss to ask for the situation of block level mean value.Learn by Fig. 8 A, typical reference scan line near two-end-point, remainder in fact is quite level and smooth zone, thus utilize dotted line to mark a zone 800, in Fig. 8 B as the usefulness that elaborates.
In Fig. 8 B, except minimum point A point, zone 800 also is cut into two parts by the A point.Mark six blocks 801,802,803,804,805 among the figure, with 806, wherein block 801 and 802 is each positioned at regional 800 two ends; Block 803 and 804 both sides of ordering in A; Block 802 and 805 lay respectively at block 801 and 803, and between block 804 and 806.In the preferred embodiment, each block is all chosen ten points and is asked for its level mean value.
Because in slope of a curve variation zone greatly, curve approaches to need more point could obtain preferably, therefore near the reference scan line two-end-point, need the more block of cutting, so block density is also bigger; In comparison, the zone that reference scan line is more level and smooth, because the little event of slope variation, so block density is lower.In addition, any point all can be contained among the more than one block on the reference scan line, is example with Fig. 8 B, and block 803 and 804 can comprise identical point.Moreover, when obtaining the information (information) of reference scan line, cut apart at regional minimum or maximum (Local minimum ormaximum), can obtain to approach preferably the result, reason is that regional minimum or maximum are minimum and the peak whereabouts.
After obtaining substrate scan line and reference scan line, must determine required defect level level (Defectlevel) again, can look for defect point in image, the method that can use now has fixedly defect level level (Fixed defect level) and dynamic defect degree level (Dynamic defect level).As its name suggests, fixedly the defect level level promptly is to preestablish (set) defect level level, when the defect level of a picture point surmounts this defect level level, judges that promptly this picture point is a defect point.Fixedly the mode that obtains of defect level level is mostly via experiment, the image deflects degree that can differentiate such as human eye, or the characteristic of image pick-up device sight always and determining.Though this method is very convenient in the use, can't react to some extent the otherness of individual other image pick-up device, CCD or the CIS that scanner use especially, this mode is not the method that ten minutes share.
In the preferred embodiment of the present invention, other proposes a method in order to decision dynamic defect degree level, utilizes the described flow chart of Fig. 6 to be explained at this.At first, obtain the difference (Difference) (step 601) of the substrate scanning element and the reference scan point of image each point, then obtain standard deviation (Standard deviation) σ of all differences
Total(step 602), and the standard deviation of 20 maximum values in this deviate
Top20(step 603) obtains σ at last
TotalWith σ
Top20Mean value, this mean value is dynamic defect degree level.
In fact, there are many methods all can apply to obtain dynamic defect degree level, such as utilizing more corresponding points to obtain the more curve of high order, or utilize whole corresponding points to obtain optimized curve etc.In addition, if σ
TotalWith σ
Top20When too small situation is relatively arranged, should be with σ
Top20Be dynamic defect degree level.
After obtaining image deflects point, can carry out the work of image repair, Fig. 7 promptly describes the flow chart that carries out image is repaired in the preferred embodiment.At first import the difference (step 701) of the substrate scanning element and the reference scan point of each picture point, judge according to this whether this difference surmounts defect level level (step 702).If difference is lower than this defect level level, represent that the hue level of this picture point must not revised, therefore continue the discriminating program (getting back to step 701) of next picture point; If difference is higher than this defect level level, the hue level of representing this picture point needs to revise, at first utilize interpolation method in the neighbor point of this picture point, to obtain the hue level value (step 703) that this need repair picture point, and after the correct channel (channel) of this picture point done correction, revise its hue level value (step 704), more revised result is exported it at last.
Above-mentioned step 704 ties up on the correct channel of picture point, obtain a tone level with interpolation method, obtain the mean value between correct channel (channel) hue level originally and the value of utilizing interpolation method to obtain again, to replace the hue level value of this correct channel (channel) script.Because wherein a channel is after repairing for this picture point, its hue level has the change of certain degree, so the correct channel of this picture point also need be done the correction of some degree, so that picture point obtains better compensation.
In addition, after knowing that this image pick-up device forms the picture point that need do correction in the image, as long as store picture point and its compensation way (because the correct channel of defect point also need be repaired) of required compensation, just can utilize hardware, firmware, software or mixing operational mode to be implemented, to promote the speed of image repair.
Moreover through result of experiment repeatedly, if when the defect point of an image pick-up device mostly is trough (Valley), the utilization neighbor point is with reference to method, cooperates fixedly defect level level or dynamic defect degree level all can obtain good effect; But the defect point at image pick-up device not only has trough, also comprises in the spike strong in number (Spike), and the curve approximatioss that just must utilize the present invention to disclose cooperates dynamic defect degree level can obtain preferable effect.
In the process of above-mentioned repairing image, if the too much situation of picture point of reparation needing to occur, then must stop whole repair procedure, because under the situation that the major part of image all need be revised, represent that the quality of this image pick-up device is on duty mutually, with the work that image is repaired in its execution, it would be better to that to change an image pick-up device comparatively to one's profit.
Comprehensive the above, image fixing apparatus of the present invention increased the method for an image repair before the scanner system output image, the unusual part in the scan image is eliminated, and image imposed the work of reparation, to improve the image output quality of low price scanner system.
The above is preferred embodiment of the present invention only, is not in order to limit the present invention; All other do not break away from the equivalence of being finished under the disclosed spirit and changes or modification, all should be included in the claim scope of the present invention.
Claims (31)
1. image fixing apparatus, this image fixing apparatus comprises at least:
One pick device, input optical signal is in order to produce an image;
One repair apparatus is imported this image, cooperates the capture characteristic of this pick device that this image is carried out image repair work;
One control device is controlled the carrying out of this image repair work of this image fixing apparatus; And
One output device is exported the image after this reparation.
2. image fixing apparatus as claimed in claim 1, wherein, described pick device comprises a charge coupled device CCD.
3. image fixing apparatus as claimed in claim 1, wherein, described pick device comprises a contact-type image sensing device CIS.
4. image fixing apparatus as claimed in claim 1, wherein, described repair apparatus comprises at least:
One substrate scan line pick device is in order to produce a plurality of substrate scan lines;
One reference scan line pick device is in order to produce a plurality of reference scan lines;
One defect level setting device is imported this substrate scan line and this reference scan line, in order to produce the defect level level;
One defect level tape deck is imported this defect level level, in order to write down the defect point of this image; And
One image compensation device is imported this defect point, so that this image is carried out repair.
5. image fixing apparatus as claimed in claim 4, wherein, described substrate scan line pick device, this reference scan line pick device, this defect level setting device, this defect level tape deck can be implemented with the mode that hardware, firmware, software or hardware, firmware, software mix with this image compensation device.
6. an image mending device can carry out the action of image repair to the image sensor element institute output image of tool flaw, and this image mending device comprises at least:
One substrate scan line pick device is in order to produce a plurality of substrate scan lines;
One reference scan line pick device is in order to produce a plurality of reference scan lines;
One defect level setting device is imported this substrate scan line and this reference scan line, in order to produce the defect level level;
One defect level tape deck is imported this defect level level, in order to write down the defect point of this image; And
One image compensation device is imported this defect point, so that this image is carried out repair.
7. image mending device as claimed in claim 6, wherein, described substrate scan line pick device, this reference scan line pick device, this defect level setting device, this defect level tape deck can be implemented with the mode that hardware, firmware, software or hardware, firmware, software mix with this image compensation device.
8. an image mending method can be carried out the action of image repair to the image that the image sensor element of tool flaw is exported, and this image mending method comprises the following step at least:
Scan calibration paper is to obtain the substrate scan line;
Find out reference scan line;
Utilize this substrate scan line and this reference scan line to find out the defect point of this image; And
This defect point of this image is carried out action to this image repair.
9. method as claimed in claim 8, wherein, this calibration paper of described scanning comprises the following step at least to obtain the step of this substrate scan line:
Set one scan line sum;
By scan line of calibration paper scanning;
Repeat the step plural number of described scanning, till this scan line sum reaches this scan line sum;
Obtain the mean scan line of this all scan lines; And
Export this mean scan line, make it become this substrate scan line.
10. method as claimed in claim 9, wherein, the described step that scans this scan line by this calibration paper more comprises to be skipped by the predefined number of scanning lines purpose of calibration paper initiating terminal to a value.
11. method as claimed in claim 8, wherein, the described step of finding out this reference scan line comprises the following step at least:
Be defined as the point of the left of this reference scan line with the point of the left of this substrate scan line;
Each point is toward shifting left a bit, to be defined as the point of this reference scan line on this substrate scan line; And
The repeating said steps plural number is till the most right-hand point of this substrate scan line is defined.
12. method as claimed in claim 8, wherein, the described step of finding out this reference scan line comprises the following step at least:
Be defined as the most right-hand point of this reference scan line with the most right-hand point of this substrate scan line;
On this substrate scan line each point toward dextroposition a bit, to be defined as the point of this reference scan line; And
Repeating said steps plural number is till the point of the left of this substrate scan line is defined.
13. method as claimed in claim 8, wherein, the described step of finding out this reference scan line comprises the following step at least:
This image is cut to plurality of blocks;
Choose plurality of points in each this block;
In each this block, utilize the point of this plural number to obtain level mean value;
Utilize this level mean value in each this block, to find out corresponding points;
Be one group with a plurality of corresponding points and obtain a regional reference scan line; And
This zone reference scan line that connects a plurality of is to become this reference scan line.
14. as the method for claim 13, wherein, the described step of utilizing this level mean value to find out these corresponding points in each this block is to utilize this mean value to find out a bit in this corresponding block, the level of this point and this mean value near the person.
15. method as claimed in claim 8, wherein, the described step of utilizing this substrate scan line and this reference scan line to find out this defect point of this image comprises the following step at least:
Obtain the difference of this substrate scan line with the corresponding point of this reference scan line of this picture point;
Set a defect level level;
When this difference of this picture point surmounts this defect level level, be this defect point.
16. as the method for claim 15, wherein, the step of described setting one defect level level comprises the following step at least:
Obtain the standard deviation of all these differences;
Obtain one than the big difference standard deviation by a plurality of of the maximum in this difference; And
The standard deviation of obtaining these all these differences and mean value than the big difference standard deviation make it become this defect level.
17. as the method for claim 15, wherein, described defect level level is predefined fixedly defect level level.
18. method as claimed in claim 8, wherein, described this defect point to this image is carried out the step of this image repair action, comprises the following step at least:
To the channel that this defect point need be repaired, utilize interpolation method to obtain the due level of this defect point; And
Adjust the level of the correct channel of this defect point.
19. as the method for claim 18, wherein, the step of the level of the correct channel of described this defect point of adjustment comprises the following step at least:
Utilize interpolation method to obtain the interpolation level of this picture point;
Obtain the level of this picture point and the mean value of this interpolation level; And
Utilize this mean value to replace the level of this picture point.
20. an image mending method can be according to the characteristic of the image sensor element of tool flaw, the image that this image sensor element is exported carries out the action to the reparation of image, and this image mending method comprises the following step at least:
Scan calibration paper is to obtain the substrate scan line;
Find out reference scan line;
Set a defect level level;
Utilize this defect level level, find out the defect point of this image with substrate scan line and this reference scan line; And
This defect point of this image is carried out the action of this image repair.
21. as the method for claim 20, wherein, this calibration paper of described scanning comprises the following step at least to obtain the step of this substrate scan line:
Set one scan line sum;
By scan line of calibration paper scanning;
Repeat the step plural number of described scanning, till this scan line sum reaches this scan line sum;
Obtain the mean scan line of this all scan lines; And
Export this mean scan line, make it become this substrate scan line.
22. as the method for claim 21, wherein, the described step that scans this scan line by this calibration paper more comprises to be skipped by the predefined number of scanning lines purpose of calibration paper initiating terminal to a value.
23. as the method for claim 20, wherein, the described step of finding out this reference scan line comprises the following step at least:
Be defined as the point of the left of this reference scan line with the point of the left of this substrate scan line;
Each point is toward shifting left a bit, to be defined as the point of nuclear reference scan line on this substrate scan line; And
The repeating said steps plural number is till the most right-hand point of this substrate scan line is defined.
24. as the method for claim 20, wherein, the described step of finding out this reference scan line comprises the following step at least:
Be defined as the most right-hand point of this reference scan line with the most right-hand point of this substrate scan line;
On this substrate scan line each point toward dextroposition a bit, to be defined as the point of this reference scan line; And
Repeating said steps plural number is till the point of the left of this substrate scan line is defined.
25. as the method for claim 20, wherein, the described step of finding out this reference scan line comprises the following step at least:
This image is cut to the block of a plurality of equal lengths;
Each this block is obtained a level mean value;
Utilize this level mean value in each this block, to find out corresponding points;
Be one group with a plurality of corresponding points and obtain a regional reference scan line; And
This zone reference scan line that connects a plurality of is to become this reference scan line.
26. as the method for claim 25, wherein, the described step of utilizing this level mean value to find out these corresponding points in each this block is to utilize this mean value to find out a bit in this corresponding block, the level of this point and this mean value near the person.
27. as the method for claim 20, wherein, the step of described setting one defect level level comprises the following step at least:
The standard volume of obtaining all these differences is poor;
A plurality of by the maximum in this difference obtain one than the big difference standard deviation; And
The standard deviation of obtaining these all these differences and mean value than the big difference standard deviation make it become this defect level level.
28. as the method for claim 20, wherein, the described step of utilizing this substrate scan line and this reference scan line to find out this defect point of this image comprises the following step at least:
Obtain the difference of this substrate scan line with the corresponding point of this reference scan line of this picture point; And
When this difference of this picture point surmounts this defect level level, be this defect point.
29. as the method for claim 20, wherein, described defect level level is predefined fixedly defect level level.
30. as the method for claim 20, wherein, described this defect point to this image is carried out the step to this image repair action, comprises the following step at least:
To the channel that this defect point need be repaired, utilize interpolation method to obtain the due level of this defect point; And
Adjust the level of the correct channel of this defect point.
31. as the method for claim 30, wherein, the step of the level of the correct channel of described this defect point of adjustment comprises the following step at least:
Utilize interpolation method to obtain the interpolation level of this picture point;
Obtain the level of this picture point and the mean value of this interpolation level; And
Utilize this mean value to replace the level of this picture point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB971100802A CN1185864C (en) | 1997-04-14 | 1997-04-14 | Device and method for restoration of image |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB971100802A CN1185864C (en) | 1997-04-14 | 1997-04-14 | Device and method for restoration of image |
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| Publication Number | Publication Date |
|---|---|
| CN1196633A true CN1196633A (en) | 1998-10-21 |
| CN1185864C CN1185864C (en) | 2005-01-19 |
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|---|---|---|---|
| CNB971100802A Expired - Fee Related CN1185864C (en) | 1997-04-14 | 1997-04-14 | Device and method for restoration of image |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2013127186A1 (en) * | 2012-02-28 | 2013-09-06 | 广州广电运通金融电子股份有限公司 | Paper medium identifying device and identifying method |
| WO2013127185A1 (en) * | 2012-02-28 | 2013-09-06 | 广州广电运通金融电子股份有限公司 | Papery medium authentication device and authentication method thereof |
| CN105894465A (en) * | 2016-03-29 | 2016-08-24 | 江苏普旭软件信息技术有限公司 | Image restoration system based on artificial neural network |
| WO2017149549A1 (en) * | 2016-03-04 | 2017-09-08 | Hewlett-Packard Development Company, L.P. | Correcting captured images using a reference image |
-
1997
- 1997-04-14 CN CNB971100802A patent/CN1185864C/en not_active Expired - Fee Related
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013127186A1 (en) * | 2012-02-28 | 2013-09-06 | 广州广电运通金融电子股份有限公司 | Paper medium identifying device and identifying method |
| WO2013127185A1 (en) * | 2012-02-28 | 2013-09-06 | 广州广电运通金融电子股份有限公司 | Papery medium authentication device and authentication method thereof |
| US9122944B2 (en) | 2012-02-28 | 2015-09-01 | Grg Banking Equipment Co., Ltd. | Paper medium identifying device and identifying method |
| WO2017149549A1 (en) * | 2016-03-04 | 2017-09-08 | Hewlett-Packard Development Company, L.P. | Correcting captured images using a reference image |
| US20180367680A1 (en) * | 2016-03-04 | 2018-12-20 | Shinoji Bhaskaran | Correcting captured images using a reference image |
| CN109155809A (en) * | 2016-03-04 | 2019-01-04 | 惠普发展公司，有限责任合伙企业 | Captured image is corrected using reference picture |
| US10530939B2 (en) * | 2016-03-04 | 2020-01-07 | Hewlett-Packard Development Company, L.P. | Correcting captured images using a reference image |
| CN105894465A (en) * | 2016-03-29 | 2016-08-24 | 江苏普旭软件信息技术有限公司 | Image restoration system based on artificial neural network |
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