CN102045530B - Motion adaptive deinterleaving method based on edge detection - Google Patents
Motion adaptive deinterleaving method based on edge detection Download PDFInfo
- Publication number
- CN102045530B CN102045530B CN201010614172XA CN201010614172A CN102045530B CN 102045530 B CN102045530 B CN 102045530B CN 201010614172X A CN201010614172X A CN 201010614172XA CN 201010614172 A CN201010614172 A CN 201010614172A CN 102045530 B CN102045530 B CN 102045530B
- Authority
- CN
- China
- Prior art keywords
- point
- edge
- interpolation
- candidate
- pixel value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Abstract
The invention relates to a motion adaptive deinterleaving method based on edge detection, which is an electronic image processing method, and comprises the following steps: a step of motion detection; a step of calculating and generating relativity parameters; a step of calculating an edge candidate direction; a step of judging and determining an edge direction; a step of obtaining a pixel value of a point to be interpolated; and a step of obtaining final progressive video. In the motion adaptive deinterleaving method based on edge detection, firstly, a motion adaptive technology is used for dividing an video image into a static region and a dynamic region, then the progressive video is obtained through performing a field copy algorithm on the static region, and an edge detection policy is performed on the dynamic region, so that accurate judgment on an edge direction angle is implemented, an interpolation point of which an edge is determined is interpolated along the edge direction, and a 3-point ELA or 6-point averaging algorithm is used for the interpolation point of which the edge is not sure or not existing so as to obtain the progressive video finally.
Description
Technical field
The present invention relates to a kind of de-interlacing method of the Motion Adaptive based on rim detection, is the method that a kind of electronic image is handled, and is the method that a kind of video image is handled, and is a kind of with the interleaved method of video image processing of lining by line scan that is treated to.
Background technology
Existing radio data system has two kinds of scan modes: a kind of is (Progressive scanning) mode of lining by line scan, and another kind is interlacing scan (Interlaced scanning) mode.Lining by line scan is in each Δ t time, a complete image to be scanned, and it is called as a frame.Interlacing scan is to divide two to carry out the 2:1 interlacing scan one two field picture.Wherein first is called odd field, only scans its odd-numbered line; And second be called even field, only scans its even number line.The advantage of lining by line scan is that image definition is high, image detail is fine and smooth abundant, stable and do not have interline flicker etc.; Shortcoming be need be bigger transmission bandwidth.Interleaved advantage is under fixed-bandwidth, to obtain higher refresh rate with half the data volume, thereby reduces flicker; Shortcoming is that image vertical direction resolution reduces half, has phenomenons such as interline flicker and edge sawtooth.
For the quality that promotes video image often need be converted into progressive with interlaced video, the technology that interlaced video is converted into progressive is called (De-interlacing) technology that deinterleaves again in a lot of practical applications.Difference according to interpolation method can be divided into two big types with the technology of deinterleaving: (intra-field) interpolation deinterleaves in, and (inter-field) interpolation deinterleaves between.
Field interpolation is to utilize same the interior picture element and the correlation of interpolation point to carry out interpolation, and it has, and amount of calculation is little, the realization characteristic of simple, is a kind of most effective technology that deinterleaves, thereby is used widely.Mainly comprise: row iterative method (Line repetition), the row method of average (Line average), interpolation method (Direction-dependent interpolation) along the edge.But field interpolation deinterleaves and can not promote the vertical resolution of picture, but has caused high-frequency information, makes soft edge, also has phenomenons such as sawtooth, flicker simultaneously.
Interpolation is to utilize opposite field pixel or opposite field and the pixel in this to carry out interpolation between, and it need store a field picture information at least, and this has increased the complexity of algorithm usually, but the increase of the algorithm degree of freedom has promoted the quality of De-interlacing.Mainly comprise: the algorithm that deinterleaves of a replica method (Weave), a top-stitching method of average (Inter-field averaging), vertical time domain median filtering method (Vertical-temporal median filtering), Motion Adaptive.Its midfield replica method has the fine effect that deinterleaves with a top-stitching method of average to the stagnant zone in the image sequence, but then can produce pseudomorphism to the moving region.Though vertical time domain median filtering method has implied the self-adaptive processing to stagnant zone and moving region, and has improved the vertical resolution and the image quality of image to a certain extent, vertical detail runs off to some extent, also can introduce aliasing phenomenon.The algorithm that deinterleaves of Motion Adaptive is exactly through detecting the moving region in the video sequence, is stagnant zone and moving region with image division, then different interpolation algorithms is adopted in these two zones.Based on deinterleaving of motion compensation (Motion Compensation), be the algorithm that deinterleaves of a kind of advanced person's Motion Adaptive, can obtain very high-quality image on the basis of motion vector accurately calculating.Although the motion compensation technology of deinterleaving is optimum, if a given motion model, and motion vector can calculate accurately; The technology but motion compensation deinterleaves, design complexity are very high, operand is very big, responsive especially to the motion vector error, real-time is poor.The high-quality technology of deinterleaving generally adopts hardware to realize in order to promote efficient, so cost is than higher.In practical application, in order to reduce development cost, promote efficient, need research high-quality, high efficiency, the more sane technology that deinterleaves.The Chinese patent of publication number CN101699856A is the de-interlacing method of a kind of Motion Adaptive of our development and Design; This method in most of the cases all can obtain result preferably; But handling tiltedly the tiltedly bigger defective of existence during long edge of long edge, particularly low angle; The edge of treated acquisition is easy to generate crenellated phenomena, thereby causes the final video decrease in image quality.Therefore on the basis of this method, how to handle oblique long edge, eliminating sawtooth is a problem that is worth further investigation.
Summary of the invention
Defective to prior art; The objective of the invention is to propose a kind of de-interlacing method of the Motion Adaptive based on rim detection; The present invention at first is divided into stagnant zone and moving region through motion detection with video, then the point of the interpolation in the moving region is carried out rim detection, if movement edge point then carries out the edge interpolation; Otherwise average interpolation, finally obtain high-quality progressive.
The objective of the invention is to realize like this: a kind of de-interlacing method of the Motion Adaptive based on rim detection; At first obtain 4 continuous video data; Be respectively former frame odd field, former frame even field, present frame odd field and present frame even field; Interlaced video data to present frame odd field and present frame even field carries out interpolation, and it is separately converted to two frame progressive data, and said method comprises the steps:
Judge whether interpolation point is the step in motor point: if " denying " then show that this point is a rest point, the value of this point is directly filled by the previous field respective pixel values and is obtained, if " being " then get into next step;
Produce relevance parameter; And produce a plurality of candidate's edge directions thus and confirm the step that this point is a marginal point: the left of putting edge of living in from interpolation to right-hand to counting a plurality of points successively; By a plurality of dot generation relevance parameter, produce a plurality of candidate's edge directions thus and confirm marginal point;
Judge whether the candidate edge is the step of real edges: if " denying " then show that this point is non-border movement point; Directly adopt the ELA algorithm or on average obtain this pixel value around 6 of this point; If " be " then show it is the border movement point, get into next step;
Obtain the step of interpolation point pixel value along the edge direction interpolation: the pixel value that the motor point, edge is obtained this point along edge direction travel direction interpolation;
Finally obtain the step of progressive: produce progressive by border movement point, non-border movement point and rest point; Adopt the edge interpolation to obtain this pixel value to the motor point, edge; Adopt ELA or 6 average algorithms to obtain this pixel value for non-border movement point; Adopt a replication strategy to obtain this pixel value for rest point, finally obtain progressive.
The beneficial effect that the present invention produces is: the present invention is a kind of high-quality technology that deinterleaves; The present invention at first uses the motion detection factor that the interpolation point is divided into motor point or rest point; Then border movement point or non-border movement point are further divided in the motor point through edge detection algorithm; Adopt a replication strategy to go interlacing to handle to rest point at last; Adopt the edge interpolation to go interlacing to handle to the motor point, edge, adopt ELA or on average to go the interlacing processing at 6, finally obtain progressive non-border movement point.Test shows, the present invention is a kind of high-quality technology that deinterleaves, and when handling tiltedly long edge, can eliminate sawtooth fully, obtains clear, smooth, natural edge, reaches more perfect treatment effect; When handling short and other zone, effect is suitable with former algorithm, is a kind of outstanding deinterlacing technique, but owing to adopted the algorithm of recursive detection, this method is when going interlacing to handle, and efficient is lower than former algorithm.This technology also can be used as a basic ancillary technique of other algorithm and technology, finally reaches the purpose that promotes efficient and quality.
Description of drawings
Below in conjunction with accompanying drawing and embodiment the present invention is described further.
Fig. 1 is the FB(flow block) of the embodiment of the invention one described method;
Fig. 2 is an interpolation point sketch map;
Fig. 3 is inserted into point edge direction sketch map.
Embodiment
Embodiment one:
Present embodiment is a kind of de-interlacing method of the Motion Adaptive based on rim detection, and said method comprises the steps:
Judge whether interpolation point is the step in motor point: be used for judging through the motion detection factor whether interpolation point is the motor point; If " deny " then show that this point is a rest point; The value of this point is directly filled by the previous field respective pixel values and is obtained, if " being " then get into next step;
Calculate to generate the step of relevance parameter: the possible direction of interpolation being put edge of living in here be divided into left to right-hand to; This step is used to calculate the relevance parameter of these all probable edges of point, and these parameters will be used for the auxiliary detection of accomplishing this point edge;
The step of calculated candidate edge direction: be used for being calculated and being produced a plurality of probable edge directions by relevance parameter, these probable edge directions will be used as candidate's edge direction, carry out next step meticulousr rim detection;
Judge whether candidate's edge direction is the step of real edges direction: i.e. technology through rim detection; Candidate's edge direction to all detects; If " deny " then show that this point is non-border movement point; Directly adopt ELA algorithm or on average to obtain this pixel value at 6, if " being " then show it is the border movement point gets into next step;
Obtain the step of interpolation point pixel value along the edge direction interpolation: the pixel value that is used for the motor point, edge is obtained along edge direction travel direction interpolation this point;
Finally obtain the step of progressive: be used for producing progressive by border movement point, non-border movement point and rest point; Adopt the edge interpolation to obtain this pixel value to the motor point, edge; Adopt ELA or 6 average algorithms to obtain this pixel value for non-border movement point; Adopt a replication strategy to obtain this pixel value for rest point, finally obtain progressive;
The concrete realization of present embodiment is such: at first obtain 4 continuous video data; Be respectively former frame odd field, former frame even field, present frame odd field and present frame even field; And be designated as
respectively;
;
;
; Wherein
,
is respectively current odd field and current even field.This technology finally is will
and
two interlaced video datas be separately converted to two frame progressive data, and this two frames progressive is called odd-numbered frame and even frame.For the odd-numbered frame or the even frame that generate; The corresponding row that corresponding odd field or Even Fields number can intactly be put in the frame is gone; And even number of lines certificate in the odd-numbered frame and the odd-numbered line data in the even frame; Be to need to calculate to produce, the algorithm of its generation is realized through the present invention.For simplicity, only describe the production process of odd-numbered frame here, the production process of even frame is equal to the production process of odd-numbered frame.Wherein each pixel relation can be referring to sketch map 2, and the variable that relates to is wherein named as follows:
This method is at first carried out the motor point and is detected; The state that just detects
; Be static or motion, adopt following strategy here:
If the inequality of (1) and (2) above satisfying simultaneously; Then the status indication with
is non-marginal point; Its value is duplicated by
and is obtained, otherwise this gets into next step processing for the motor point.Wherein,
(similarity threshold 1) and
(similarity threshold 2) is called similarity threshold; The interval of
is that 1 to 10 o'clock effect is best, and the interval of
is that 10 to 30 o'clock effects are best.
Next step of motion detection is the relevance parameter of calculating on the edge direction of motor point, and the edge direction of interpolation point is as shown in Figure 3.Relevance parameter is the absolute value sum of a certain direction respective pixel value difference of interpolation point lastrow and next line edge; Travel through these relevance parameter; With the directions at 2 the minimum value parameters places in 2 in left side and right side as candidate's edge direction; Here this some left side is divided into 5 directions, the computing formula of all directions relevance parameter is:
Wherein
Same, the relevance parameter of 5 directions in calculating right side, computing formula is:
Wherein
Relevance parameter on the vertical direction, computing formula is:
After relevance parameter was calculated, what need carry out was exactly confirming of candidate direction.In fact, have only on the edge of just can obtain minimum relevance parameter on the direction, so candidate direction should be chosen from the direction at little relevance parameter place.Here used following method: the relevance parameter that the traversal left side is all; Find wherein minimum value
and time minimum value
, and write down its direction
and
respectively; The all relevance parameter in traversal right side; Find out wherein minimum value
and time minimum value
; And write down its direction
and
respectively, and with these 4 directions and vertical direction together as candidate's edge direction.if
and
; Then this shows that this point edge direction is a vertical direction; Interpolation point adopts the generation of ELA algorithm, and (ELA is an algorithm known; Detailed description is arranged in the Chinese patent of publication number CN101699856A), and this point is labeled as non-marginal point; Otherwise this point exist left hand edge anti-to or the right hand edge direction, this point is labeled as marginal point.
Next step is that the correction of accomplishing candidate direction reaches definite.The direction that from all candidate direction, has the minimum relatedness parameter belongs to the pixel that direction finding is looked into down the next line relevant position along it, if this pixel is a marginal point; Then continue to search,, can both find marginal point in that this side up if search multirow continuously along this direction; Show that then this direction is exactly real edge direction, the interpolation point of this direction is carried out edge direction filtering interpolation, otherwise; Show that then this direction is not the direction at this edge, need other 3 candidate direction to carry out above-mentioned detection, their detection is in proper order; Another candidate direction of the same side, the direction that opposite side minimum relatedness parameter is corresponding, another candidate direction of opposite side.If exist the direction more than 2 to satisfy condition, show that then the edge direction of this point is difficult to confirm, adopt the ELA algorithm or up and down 6 average algorithms obtain the pixel value of interpolation point; If all directions do not satisfy condition, show that then there is not edge direction in this point, adopt 6 average algorithms to obtain the pixel value of interpolation point, finally accomplish confirming of edge direction.
More particularly at first start with from the relevance parameter of minimum; Promptly compare <img file=" 556021DEST_PATH_IMAGE025.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 84 " /> and <img file=" 840372DEST_PATH_IMAGE029.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 96 " /> if. <img file=" 252899DEST_PATH_IMAGE025.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 84 " /> < <img file=" 280897DEST_PATH_IMAGE029.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 96 " />; Then check that along <img file=" 400163DEST_PATH_IMAGE027.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 100 " /> direction finding next line is positioned at the pixel of <img file=" 589836DEST_PATH_IMAGE035.GIF " he=" 26 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 208 " />, <img file=" DEST_PATH_IMAGE036.GIF " he=" 26 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 226 " />, <img file=" 489659DEST_PATH_IMAGE037.GIF " he=" 26 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 226 " />; If the pixel of these three positions has at least one to be marginal point; Then continue to search along this direction; If search multirow (it is capable to be made as 3-8 usually) continuously; Can both find marginal point in that this side up; Show that then this direction is exactly real edge direction, the interpolation point of this direction is carried out edge direction filtering interpolation.Otherwise; Show that then this direction is not the direction at this edge, <img file=" 55769DEST_PATH_IMAGE028.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 97 " /> direction is accomplished above-mentioned detection.If <img file=" 48783DEST_PATH_IMAGE028.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 97 " /> neither its edge direction, then continue <img file=" 409357DEST_PATH_IMAGE031.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 112 " />, <img file=" 796476DEST_PATH_IMAGE032.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 109 " /> accomplish identical calculating.If exist the direction more than 2 to satisfy condition, show that then the edge direction of this point is difficult to confirm, adopt the ELA algorithm or up and down 6 average algorithms obtain the pixel value of interpolation point; If all directions do not satisfy condition, show that then there is not edge direction in this point, adopt 6 average algorithms to obtain the pixel value of interpolation point.If <img file=" 166278DEST_PATH_IMAGE029.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 96 " /> < <img file=" 994556DEST_PATH_IMAGE025.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 84 " /> then accomplishes definite work of above-mentioned edge direction according to the order of <img file=" 791611DEST_PATH_IMAGE031.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 112 " />, <img file=" 400447DEST_PATH_IMAGE032.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 109 " />, <img file=" 573939DEST_PATH_IMAGE027.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 100 " />, <img file=" 771571DEST_PATH_IMAGE028.GIF " he=" 22 " img-content=" drawing " img-format=" jpg " inline=" no " orientation=" portrait " wi=" 97 " />.
Finally, handle, accomplished calculating, obtain final progressive all interpolation points through detection to all candidate direction.
What should explain at last is; Below only unrestricted in order to technical scheme of the present invention to be described; Although with reference to the preferred arrangement scheme the present invention is specified, those of ordinary skill in the art should be appreciated that can be to technical scheme of the present invention (such as increasing the rank of judging; Or carry out motor point difference or the like with other modes) make amendment or be equal to replacement, and do not break away from the spirit and the scope of technical scheme of the present invention.
Claims (6)
1. de-interlacing method based on the Motion Adaptive of rim detection; At first obtain 4 continuous video data; Be respectively former frame odd field, former frame even field, present frame odd field and present frame even field, the interlaced video data of present frame odd field and present frame even field is carried out interpolation, it is separately converted to two frame progressive data; It is characterized in that said method comprises the steps:
Judge whether interpolation point is the step in motor point: if " denying " then show that this point is a rest point, the value of this point is directly filled by the previous field respective pixel values and is obtained, if " being " then get into next step;
Produce relevance parameter; And produce a plurality of candidate's edge directions thus and confirm the step that this point is a marginal point: the left of putting edge of living in from interpolation to right-hand to counting a plurality of points successively; By a plurality of dot generation relevance parameter, produce a plurality of candidate's edge directions thus and confirm marginal point;
Judge whether the candidate edge is the step of real edges: if " denying " then show that this point is non-border movement point; Directly adopt the ELA algorithm or on average obtain this pixel value around 6 of this point; If " be " then show it is the border movement point, get into next step;
Obtain the step of interpolation point pixel value along the edge direction interpolation: the pixel value that the motor point, edge is obtained this point along edge direction travel direction interpolation;
Finally obtain the step of progressive: produce progressive by border movement point, non-border movement point and rest point; Adopt the edge interpolation to obtain this pixel value to the motor point, edge; Adopt ELA or 6 average algorithms to obtain this pixel value for non-border movement point; Adopt a replication strategy to obtain this pixel value for rest point, finally obtain progressive.
2. the de-interlacing method of a kind of Motion Adaptive based on rim detection according to claim 1 is characterized in that, saidly judges that whether interpolation point is that the step in motor point is: if satisfy
Wherein,
3. the de-interlacing method of a kind of Motion Adaptive based on rim detection according to claim 2 is characterized in that the interval of said similarity threshold 1 is 1 to 10, and the interval of similarity threshold 2 is 10 to 30.
4. the de-interlacing method of a kind of Motion Adaptive based on rim detection according to claim 1; It is characterized in that; Said generation relevance parameter; And the step that produces a plurality of candidate's edge directions thus is: relevance parameter is interpolation point lastrow and the next line absolute value sum along a certain direction respective pixel value difference, travels through these relevance parameter, with the directions at 2 in left side and 2 minimum value parameters places, right side as candidate's edge direction.
5. the de-interlacing method of a kind of Motion Adaptive based on rim detection according to claim 1 is characterized in that, whether the said candidate's of judgement edge direction is that the step of real edges direction is: the direction that from all candidate direction, has the minimum relatedness parameter; Belong to the pixel that direction finding is looked into down the next line relevant position along it,, then continue to search along this direction if this pixel is a marginal point; If search multirow continuously, can both find marginal point in that this side up, show that then this direction is exactly real edge direction; Interpolation point to this direction carries out edge direction filtering interpolation, otherwise, show that then this direction is not the direction at this edge; Need other 3 candidate direction to carry out above-mentioned detection; Their detection is another candidate direction of the same side, the direction that opposite side minimum relatedness parameter is corresponding in proper order; Another candidate direction of opposite side; If exist the direction more than 2 to satisfy condition, show that then the edge direction of this point is difficult to confirm, adopt the ELA algorithm or up and down 6 average algorithms obtain the pixel value of interpolation point; If all directions do not satisfy condition, show that then there is not edge direction in this point, adopt 6 average algorithms to obtain the pixel value of interpolation point, finally accomplish confirming of edge direction.
6. the de-interlacing method of a kind of Motion Adaptive based on rim detection according to claim 5 is characterized in that, said multirow is 3 to 8 row.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010614172XA CN102045530B (en) | 2010-12-30 | 2010-12-30 | Motion adaptive deinterleaving method based on edge detection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010614172XA CN102045530B (en) | 2010-12-30 | 2010-12-30 | Motion adaptive deinterleaving method based on edge detection |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102045530A CN102045530A (en) | 2011-05-04 |
| CN102045530B true CN102045530B (en) | 2012-05-23 |
Family
ID=43911245
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201010614172XA Active CN102045530B (en) | 2010-12-30 | 2010-12-30 | Motion adaptive deinterleaving method based on edge detection |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102045530B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101773616B1 (en) * | 2011-05-16 | 2017-09-13 | 엘지디스플레이 주식회사 | Image processing method and stereoscopic image display device using the same |
| CN102946504B (en) * | 2012-11-22 | 2015-02-18 | 四川虹微技术有限公司 | Self-adaptive moving detection method based on edge detection |
| CN104580975B (en) * | 2013-10-10 | 2018-03-30 | 无锡华润矽科微电子有限公司 | A kind of adaptive-interpolation in-field deinterlacing method |
| WO2016154970A1 (en) * | 2015-04-01 | 2016-10-06 | 中国科学院自动化研究所 | Method and system for image interpolation based on edge detection |
| CN106027943B (en) * | 2016-07-11 | 2019-01-15 | 北京大学 | A kind of video interlace-removing method |
| CN107071326B (en) * | 2017-04-26 | 2020-01-17 | 西安诺瓦星云科技股份有限公司 | Video processing method and device |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100571333C (en) * | 2007-04-04 | 2009-12-16 | 华为技术有限公司 | Method and device thereof that a kind of video image is handled |
| CN101309385B (en) * | 2008-07-09 | 2010-09-08 | 北京航空航天大学 | Alternate line eliminating process method based on motion detection |
| CN101640783B (en) * | 2008-07-30 | 2011-07-27 | 展讯通信（上海）有限公司 | De-interlacing method and de-interlacing device for interpolating pixel points |
-
2010
- 2010-12-30 CN CN201010614172XA patent/CN102045530B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN102045530A (en) | 2011-05-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102045530B (en) | Motion adaptive deinterleaving method based on edge detection | |
| CN103369208B (en) | Self adaptation interlace-removing method and device | |
| CN1270526C (en) | Device and method for using adaptive moving compensation conversion frame and/or semi-frame speed | |
| Kang et al. | Motion compensated frame rate up-conversion using extended bilateral motion estimation | |
| CN101600061B (en) | Video motion-adaptive de-interlacing method and device therefor | |
| CN110889895B (en) | Face video super-resolution reconstruction method fusing single-frame reconstruction network | |
| CN102025960B (en) | Motion compensation de-interlacing method based on adaptive interpolation | |
| CN101953167A (en) | Reduce the image interpolation of halation | |
| CN101699856B (en) | De-interlacing method with self-adapting motion | |
| CN102509311B (en) | Motion detection method and device | |
| Chen et al. | True motion-compensated de-interlacing algorithm | |
| CN101600062B (en) | In-field deinterlacing method based on enhanced edge adaptivity | |
| CN101340539A (en) | Deinterlacing video processing method and system by moving vector and image edge detection | |
| CN106027943B (en) | A kind of video interlace-removing method | |
| EP1267575B1 (en) | A method for converting the scanning format of images, a system and computer program product therefor | |
| CN111294545B (en) | Image data interpolation method and device, storage medium and terminal | |
| CN201222771Y (en) | High speed edge self-adapting de-interlaced interpolation device | |
| CN101437137B (en) | Field interpolation method | |
| CN102497523B (en) | Median-filtering de-interlacing method | |
| CN107124617B (en) | Method and system for generating random vector in motion estimation motion compensation | |
| CN105915835B (en) | One kind can hard-wired frame frequency lifting method | |
| CN105611214A (en) | Method for de-interlacing through intra-field linear interpolation based on multidirectional detection | |
| CN103905747A (en) | Medical image bad pixel point repairing method and system | |
| US8405767B2 (en) | Image processing device | |
| CN201509247U (en) | Image processing apparatus for deciding pixel value of interpolation position |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |