CN100518244C - Self-adapted filtering method for mobile image - Google Patents
Self-adapted filtering method for mobile image Download PDFInfo
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Abstract
The utility model relates to a method of self-adaptive filtering for motion image, which comprises the following steps: setting the gain of high-frequency signal after filtering according to the displayed image resolution and the amplitude value of system noise; calculating the corresponding point spread function of the retention time and response time; calculating the adaptive parameter of the corresponding filter of the different motion vector values; calculating the motion vector values of all pixels on every frame image; utilizing the motion adaptive filter to filter the video image in the horizontal direction and the vertical direction successively. The utility model has the advantages that the fuzzy problem of motion image on keeping type display can be improved effectively through motion image adaptive filter; the filter structure with adjustable parameter and fixed order number is very simple; the elimination of noise influence on filtering image quality can be realized easily through effective adjustment self-adaptive parameter and the overflow problem after filtering is avoided.
Description
Technical field
The present invention relates to a kind of image filtering method, especially relate to a kind of self-adapted filtering method for mobile image at the motion image blurring problem.
Background technology
Current flat-panel monitor keeps the long demonstration time in a frame time usually, and for example, LCD is after delegation's vision signal has scanned, and the shown monochrome information of pixel can remain to scanning next time and just upgrade, and promptly keeps a frame time.This maintenance display mode can make shown moving image thicken when human eye is watched, and the speed of moving image is fast more fuzzy serious more.The fuzzy problem of this moving image is not that image source or display itself produce image lesion, and its vision accompany movement level and smooth with human eye (smoothpursuit eye movement) is relevant.Can produce a kind of level and smooth vision accompany movement during the object of human eye in watching motion, thereby make the image of moving object remain on amphiblestroid central authorities.For the maintenance display, the image that shows in a frame time is static getting, but the level and smooth vision accompany movement of human eye this moment still can keep smooth motion on the moving image track that shows.Therefore in a frame time, the monochrome information that human eye perceived be on the display image movement locus integration of adjacent image point monochrome information on time domain and spatial domain and.Fast more when the movement velocity of object, then the adjacent image point that integration comprised is many more, thereby image is fuzzy more.
For current LCD, the slower response time of liquid crystal molecule also is one of factor that causes motion image blurring.Therefore solving LCD motion image blurring problem can start with from three aspects: the one, and the response time, the 2nd of accelerating liquid crystal, a frame retention time, the 3rd of shortening LCD TV, the vision accompany movement that the motion compensation human eye is level and smooth.EP0657860A2 discloses a kind of self-adapting compensation method of motion image blurring, promptly according to the movement velocity of moving image, adjusts the width of filter.This method can part the motion image blurring that produced of the level and smooth vision accompany movement of compensation human eye.But this compensation method also comes with some shortcomings: the one, and it is inconsistent with the image blurring high-frequency suppressing that produces that its high frequency strengthens part, and the elimination effect of motion image blurring is general after the filtering; The 2nd, this method can not suppress the influence that picture noise strengthens high frequency effectively.
Summary of the invention
Technical problem: at the motion image blurring problem of maintenance display, the invention provides a kind of self-adapted filtering method for mobile image, this method can be adjusted the frequency response of filter according to the fog-level self adaptation of moving image, this method can be adjusted high-frequency gain according to the picture material noise simultaneously, prevent the influence of noise to picture quality, this method can also be adjusted filter freguency response according to image content features, prevent because the picture material that Filtering Processing causes is overflowed (promptly, the half-tone information of display image content is higher than 255 grades of gray scales or is lower than 0 grade of gray scale), thus the display quality of moving image on the maintenance display effectively improved.
Technical scheme: technical scheme of the present invention increases a moving image adaptive-filtering unit 2 as shown in Figure 1 in the video circuit of maintenance display; The vision signal 1 that is transferred to the maintenance display at first is input to moving image adaptive-filtering unit 2; Moving image adaptive-filtering unit 2 mainly is made up of two parts, comprise: motion vector estimation unit 6 and sef-adapting filter unit 4, motion vector estimation unit 6 goes out the motion vector information of each display element of present frame according to a plurality of adjacent video frames calculated signals, motion vector information that calculates and the vision signal of input 1 are input to sef-adapting filter unit 4 simultaneously, sef-adapting filter unit 4 is adjusted filter parameter and current display element vision signal is carried out filtering according to the motion vector information of each pixel, filtered vision signal further outputs in the maintenance display ranks drive circuit 5, realizes the demonstration of video image.
Self-adapted filtering method for mobile image provided by the present invention, can be as shown in fig. 1, be independent of maintenance display ranks drive circuit 5, also can be included in the maintenance display ranks drive circuit 5, can also combine with other vision signal intensifier circuits, for example, the video frame rate multiple circuit unit 3 that some displays comprised (promptly, the 50Hz or the 60Hz video frame rate of standard are converted to 100Hz or 120Hz video frame rate), this moment, motion vector estimation unit 6 can be shared with video frame rate multiple circuit unit 3, as shown in phantom in Figure 1, the calculated value of motion vector estimation unit 6 is input to video frame rate multiple circuit unit 3 and sef-adapting filter unit 4 simultaneously.
Motion vector estimation unit 6 provided by the present invention can adopt current various general estimation of motion vectors algorithm, for example full search block matching method.Block-based motion vector value can be directly inputted to sef-adapting filter unit 4, also can further adopt approach based on linear interpolation, makes the motion vector precision reach single pixel, and then is input to sef-adapting filter unit 4.
Sef-adapting filter provided by the present invention unit 4 comprises the adjustable sef-adapting filter of parameter on one five rank, shown in following formula (1),
n′
i＝-k·n
i-2-l·n
i-1+(1+2·k+2·l)·n
i-l·n
i+1-k·n
i+2 (1)
Wherein, n
iThe expression position is at the brightness value of the single display element of i, parameter k and the l self adaptation adjustable parameter that expression is relevant with motion vector value and picture material respectively.As shown in Figure 2, the frequency response characteristic of sef-adapting filter strengthens for the high frequency signal, parameter k can adjust the gain of high frequency, and increase along with the k value, the gain of high frequency also increases thereupon, as first frequency response curve 7, second frequency response curve 8, the 3rd frequency response curve 9 among the figure; Parameter l can be adjusted the gain of HFS, and along with the increase of l value, the gain of HFS also increases thereupon, as figure medium frequency response curve the 3rd frequency response curve 9, the 6th frequency response curve 12, the 9th frequency response curve 15.Formula (1) is depicted as one dimension high frequency agc filter, it can be used for the motion image blurring filtering of two dimension, the solution of the present invention is: motion vector is decomposed into level and vertical both direction, and this does not carry out filtering in level and vertical direction to utilize formula (1); Can also utilize horizontal motion vector and formula (1), only video image be carried out horizontal direction filtering.Formula (1) can carry out filtering at image luminance information, also can carry out filtering at R, G, three kinds of colors of B respectively.
In order to compensate the fuzzy problem of display image under the different motion speed condition, need to understand the pairing point spread function of motion image blurring (point spread function).For the maintenance display, can be similar to the hypothesis human eye to the level and smooth accompany movement of moving image at the uniform velocity following, so can be similar to point spread function with sliding filter, row formula specific as follows (2):
Wherein, dx represents the motion vector absolute value of present picture element correspondence.Formula (2) can be regarded as along the motion vector direction, the one dimension sliding filter relevant with motion vector value.For two-dimensional motion vector, it is decomposed into level and vertical direction, thereby can utilizes formula (2) to be similar to respectively in level and vertical direction.
Filtering method is specially:
Step a) is determined parameter l in the formula 1 to adopt higher l value when video image resolution is higher, the lower l value of employing when video image resolution is low according to resolution of displayed images and system noise amplitude, when system noise is higher, reduce the l value, when system noise is low, improve the l value;
Step b) is calculated maintenance display point spread function, at first calculate respectively with the approximate point spread function of sliding filter at the different motion vector, secondly, according to the liquid crystal response curve of measuring, calculate gauss of distribution function, at last, sliding filter and gauss of distribution function are carried out convolution and then obtain point spread function;
Parameter k in the formula 1 of step c) calculating different motion vector values correspondence, 5 rank filter functions of point spread function and different motion vector correspondence are carried out convolution, optimum k value is calculated in search, make the maximum of corresponding frequency response curve amplitude the most approaching or equal 1, for preventing that picture material from overflowing, can set k value higher limit;
The filter step of moving image adaptive-filtering unit (2) is:
Step d) is calculated the motion vector value of every all pixels of two field picture, and the two-dimensional data matrix that two-dimensional motion vector is resolved into level and vertical direction is stored in calculator memory or the RAM chip;
The filtering of step e) video image horizontal direction takes absolute value the horizontal motion vector, utilizes corresponding optimal coefficient to carry out filtering, and filtered pixel is saved as display brightness information; When video image is the interlaced picture content, promptly finish;
When step f) was the progressive image content when video image, the filtering of video image vertical direction took absolute value the movement in vertical direction vector, utilizes corresponding optimal coefficient to carry out filtering, and filtered pixel is saved as display brightness information.
Moving image adaptive-filtering unit is a processing unit independently, or is embedded in the maintenance display ranks drive circuit 5, or combines with other vision signal intensifier circuits.
Motion vector estimation unit adopts piece match search method, the motion vector information based on image block that calculates is input to the sef-adapting filter unit, or further utilize linear interpolation method, the precision of motion vector information is brought up to single pixel, and then be input to the sef-adapting filter unit.
The sef-adapting filter unit carries out filtering according to two-dimensional motion vector to image, its method is: two-dimensional motion vector is decomposed into level and vertical direction, absolute value according to the motion vector horizontal direction carries out filtering to image at first in the horizontal direction, then in vertical direction, image is carried out filtering once more according to the absolute value of motion vector vertical direction.
Moving image adaptive-filtering unit is used for the image processing system of digital camera, reduces because the problem of image blurring that motion causes.
For LCD, the slower response time of liquid crystal also is one of reason of motion image blurring, correlative study shows, when the liquid crystal response time less than a frame during retention time, motion image blurring mainly is that adopt formula (2) can be similar to point spread function preferably this moment because the retention time determines.Longer when the liquid crystal response time, near or greater than a frame during retention time, need to consider of the influence of liquid crystal response time to point spread function.But, since between the different gray scales of LCD and rising edge all different with the response time of trailing edge conversion, can't go to be similar to the point spread function of liquid crystal response time with unified formula.Consider that the liquid crystal response time shows as the increase and decrease of luminance signal to the influence of display image, the present invention adopts Gaussian Profile to go the point spread function of approximate liquid crystal response time.Shown in the row formula specific as follows (3):
Wherein, Δ is a liquid crystal response curve width, and α satisfies and to turn to after the one-dimension array all coefficients and be 1 formula (3) is discrete.Formula (2) and formula (3) convolution just can be obtained the approximate point spread function of LCD.
For the maintenance display,, just can determine the parameter k in the formula (1), l according to point spread function.With the LCD is example, resolution and picture noise intensity according to display image are at first determined parameter l, and concrete scheme is: adopt bigger l value when the display image resolution is higher, as 1～2, opposite resolution adopts lower l value when low, as 0～1; The influence of interchannel noise is opposite, when definite noise is big, for example can reduce the l value, reduce by 0.5～1, the l value can be reduced to 0 in some cases, this moment, high-frequency signal did not produce gain, and for current Digital Television, interchannel noise is very low, therefore can use big l value, promptly determine that according to image resolution-ratio the l value gets final product.
After definite parameter l and approximate point spread function, can calculate different motion vector values corresponding parameters k.Concrete grammar is: progressively increase the k value, and the frequency response curve after computing formula (1), (2), (3) convolution, to satisfy on the frequency response curve on all Frequency points the maximum of amplitude the most approaching or when equaling 1 when certain k value, is optimum k value.Because all pixels all adopt 5 rank filters, therefore can be placed in calculator memory in the mode of look-up table the k value of different motion vector correspondence or hardware-core such as ROM in.
When motion vector value was big, the parameters calculated k of said method institute value was higher, easily cause filtering at this moment after image overflow.Scheme of the present invention is: limit the higher limit of k value, capping value when promptly the k value of calculating when search surpasses higher limit; Also can limit the motion vector higher limit of compensation, promptly, adopt the pairing k value of motion vector higher limit to carry out filtering when motion vector during greater than higher limit; Can also the pixel that motion vector value is higher than higher limit not carried out filtering, be about to parameter k, l and be made as 0.
Method provided by the present invention also can be used in other image blurring signal compensation apparatus.For example in digital camera, at first utilize multiple image or the transducer of taking continuously, calculate to take in the exposure process and cause the ground camera displacement vector, utilize filter provided by the present invention to compensate the blurred picture of taking then in the motion vector direction because hand is shaken.
Beneficial effect: the invention has the beneficial effects as follows: utilize changeable parameters, fixedly the filter of exponent number carries out one dimension or two-dimensional filtering to video image, and is simple in structure; Auto-adaptive parameter can calculate definite in advance, is easy to the design and the realization of fast algorithm; Adjust the influence that parameter can effectively suppress noise on filtering picture quality by self adaptation; By the parameter higher limit is set, can effectively suppress the influence of image overflow problem to picture quality.
Description of drawings
Fig. 1 is the Avaptive filtering system block diagram.
Fig. 2 is moving image sef-adapting filter frequency response characteristic figure.
Fig. 3 is a moving image sef-adapting filter calculation of parameter flow chart.
Fig. 4 is a moving image adaptive-filtering flow chart.
Have among the above figure: vision signal 1, moving image adaptive-filtering unit 2, video frame rate multiple circuit unit 3, sef-adapting filter unit 4, maintenance display ranks drive circuit 5, motion vector estimation unit 6, first frequency response curve 7, second frequency response curve 8, the 3rd frequency response curve 9, the 4th frequency response curve 10, the 5th frequency response curve 11, the 6th frequency response curve 12, the 7th frequency response curve 13, the 8th frequency response curve 14, the 9th frequency response curve 15.
Embodiment
In preferred embodiment shown in Figure 1, moving image adaptive-filtering unit 2 is embedded between the vision signal 1 and maintenance display ranks drive circuit 5 of maintenance display, vision signal 1 is input to motion vector estimation unit 6 and sef-adapting filter unit 4 respectively, the motion vector information that motion vector estimation unit 6 is calculated is input to sef-adapting filter unit 4, sef-adapting filter unit 4 utilizes motion vector information that video image is carried out filtering, and filtered video information is input in the maintenance display ranks drive circuit 5.The filter parameter of sef-adapting filter unit 4 can calculate in advance, as shown in Figure 3, the steps include:
Step (a) is determined parameter l according to resolution of displayed images and system noise amplitude, resolution of displayed images is divided three classes: high definition (being higher than 1280 * 720), SD (between 1280 * 720 and 720 * 576), low resolution (being lower than 720 * 576), the scope of corresponding parameter l is respectively: 3～1,2～0.5,1～0, when the system transmissions noise is low, can select higher parameter l value, for example, this moment high definition can to set the l value be 3, when noise is higher, can select lower parameter l value, for example, this moment high definition can to set the l value be 1;
Step (b) is calculated maintenance display point spread function, with the LCD is example, LCD retention time corresponding point spread function is that width is the sliding filter of present picture element motion vector value, liquid crystal response curve corresponding point spread function is that Δ is the gauss of distribution function of liquid crystal response curve width, and above-mentioned sliding filter and gauss of distribution function convolution are the point spread function of present picture element;
Step (c) is calculated different motion vector values corresponding parameters k, concrete grammar is: for different motion vector absolute values, optimum k value is calculated in search respectively, the 5 rank filters that the point spread function under the different motion vector absolute value condition and the present invention soon proposes carry out convolution, the most approaching or when equaling 1 when the maximum of the amplitude on all Frequency points of the frequency response curve after the convolution, be optimum k value, occur overflowing for fear of filtering rear video image, k value higher limit can be set, for example: the higher limit that the k value is set is 4, the k value of calculating when search is greater than 4 the time, and then the k value with the present picture element correspondence is set at 4.
Precalculated optimum k value can be present in the internal memory of computer with the form of look-up table or be present in the rom chip of curing.According to the motion vector information of input, the step that the 2 pairs of video images in moving image adaptive-filtering unit carry out filtering is specially as shown in Figure 4:
Step (d) is calculated the motion vector value of every all pixels of two field picture, present frame is divided into 16 * 16 or 8 * 8 pixel block, adopt all direction search method between present frame and former frame, to search for the best match position of calculating each pixel block, motion vector based on pixel block can be input to sef-adapting filter unit 4, also can be to the further linear interpolation of motion vector value, make motion vector value be accurate to single pixel, and then being input to sef-adapting filter unit 4, the two-dimensional data matrix that two-dimensional motion vector resolves into level and vertical direction is stored in calculator memory or the RAM chip;
The filtering of step (e) video image horizontal direction, at first horizontal motion vector two-dimensional data matrix is taken absolute value for each pixel, in look-up table, search optimum k value according to the motion vector absolute value, after determining filter coefficient, just can utilize that each adjacent two pixel carries out filtering about horizontal direction, and filtered numerical value be saved as the display brightness information of present picture element;
The filtering of step (f) video image vertical direction, at first movement in vertical direction vector two-dimensional data matrix is taken absolute value for each pixel, in look-up table, search optimum k value according to the motion vector absolute value, after determining filter coefficient, just can utilize that each adjacent two pixel carries out filtering about vertical direction, and filtered numerical value is saved as the display brightness information of present picture element, also can omit the filtering of video image vertical direction in some applications, for example, can only carry out filtering in the horizontal direction for SD interlaced video image.
Second preferred embodiment of the present invention is, moving image adaptive-filtering unit 2 can be integrated in other vision signal intensifier circuits, motion vector estimation unit 6 is shared in video frame rate multiple circuit unit 3 and sef-adapting filter unit 4 as shown in phantom in Figure 1, the motion vector information that video frame rate multiple circuit unit 3 utilizes the vector unit 6 of doing exercises to calculate carries out the video image frame interpolation, thereby realize the video displaying frame rate multiplication, video after the multiplication is input to sef-adapting filter unit 4, utilize the motion vector information of input, video after the 4 pairs of multiplications in sef-adapting filter unit carries out filtering, and filtered video is input in the maintenance display ranks drive circuit 5.
The 3rd preferred embodiment of the present invention is that moving image adaptive-filtering unit 2 can be used in other image blurring signal compensation apparatus.For example in digital camera, at first utilize multiple image or the transducer of taking continuously, calculate to take in the exposure process and cause ground camera displacement vector (corresponding to motion vector estimation unit among Fig. 1 6), utilize filter provided by the present invention to compensate (sef-adapting filter unit 4 in corresponding to Fig. 1) to the single frames blurred picture of taking then in the motion vector direction because hand is shaken.
Claims (5)
1. self-adapted filtering method for mobile image, it is characterized in that this method increases a moving image adaptive-filtering unit (2) in the video circuit of maintenance display, moving image adaptive-filtering unit (2) mainly is made up of two parts, comprise: motion vector estimation unit (6) and sef-adapting filter unit (4), sef-adapting filter unit (4) comprises the adjustable sef-adapting filter of parameter on one five rank, shown in following formula 1:
n′
i＝-k·n
i-2-l·n
i-1+(1+2·k+2·l)·n
i-l·n
i+1-k·n
i+2
Wherein, n
iThe expression position is at the brightness value of the single display element of i, n
i' being output, parameter k and the l self adaptation adjustable parameter that expression is relevant with motion vector value and picture material respectively, the filter parameter of sef-adapting filter unit (4) can calculate in advance, the steps include:
Step a) is determined parameter l in the formula 1 according to resolution of displayed images and system noise amplitude, resolution of displayed images is divided three classes: high definition (being higher than 1280 * 720), SD (between 1280 * 720 and 720 * 576), low resolution (being lower than 720 * 576), the scope of corresponding parameter l is respectively: 3～1,2～0.5,1～0, when the system transmissions noise is low, select higher parameter l value, when noise is higher, select lower parameter l value;
Step b) is calculated maintenance display point spread function, at first calculate sliding filter respectively at the different motion vector, secondly, according to the liquid crystal response curve of measuring, calculate gauss of distribution function, at last, sliding filter and gauss of distribution function are carried out convolution then obtain point spread function, sliding filter is provided by formula 2:
Wherein, dx represents the motion vector absolute value of present picture element correspondence, n
jThe expression position is at the brightness value of the single display element of j, n
j" be output, gauss of distribution function is provided by formula 3:
Wherein, Δ is a liquid crystal response curve width, and α satisfies and to turn to after the one-dimension array all coefficients and be 1 formula 3 is discrete;
Step c) is calculated parameter k in the formula 1 of different motion vector values correspondence, is about to point spread function and formula 1 and carries out convolution, makes the maximum of corresponding frequency response curve amplitude the most approaching or equal 1, overflows for preventing picture material, sets k value higher limit;
The filter step of moving image adaptive-filtering unit (2) is:
Step d) is calculated the motion vector value of every all pixels of two field picture, and the two-dimensional data matrix that two-dimensional motion vector is resolved into level and vertical direction is stored in calculator memory or the RAM chip;
The filtering of step e) video image horizontal direction takes absolute value the horizontal motion vector, utilizes formula 1 to carry out filtering, and filtered pixel is saved as display brightness information; When video image is the interlaced picture content, promptly finish;
When step f) was the progressive image content when video image, the filtering of video image vertical direction took absolute value the movement in vertical direction vector, utilizes formula 1 to carry out filtering, and filtered pixel is saved as display brightness information.
2. according to the described self-adapted filtering method for mobile image of claim 1, it is characterized in that: moving image adaptive-filtering unit (2) is a processing unit independently, or be embedded in the maintenance display ranks drive circuits (5), or combine with other vision signal intensifier circuits.
3. according to the described self-adapted filtering method for mobile image of claim 1, it is characterized in that: motion vector estimation unit (6) adopts piece match search method, the motion vector information based on image block that calculates is input to sef-adapting filter unit (4), or further utilize linear interpolation method, the precision of motion vector information is brought up to single pixel, and then be input to sef-adapting filter unit (4).
4. according to the described self-adapted filtering method for mobile image of claim 1, it is characterized in that: adaptive-filtering unit (4) carry out filtering according to two-dimensional motion vector to image, its method is: two-dimensional motion vector is decomposed into level and vertical direction, absolute value according to the motion vector horizontal direction carries out filtering to image at first in the horizontal direction, when video image is the progressive image content, then in vertical direction, image is carried out filtering once more according to the absolute value of motion vector vertical direction.
5. according to the described self-adapted filtering method for mobile image of claim 1, it is characterized in that: moving image adaptive-filtering unit (2) is used for the image processing system of digital camera, reduces because the problem of image blurring that motion causes.
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