CN108632501B - Video anti-shake method and device and mobile terminal - Google Patents
Video anti-shake method and device and mobile terminal Download PDFInfo
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- H04N5/14—Picture signal circuitry for video frequency region
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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- H04N5/14—Picture signal circuitry for video frequency region
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Abstract
A video anti-shake method and device and a mobile terminal are provided. The method comprises the following steps: acquiring motion estimation information of an input video image; carrying out smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result; for the input video image of the nth frame, carrying out black edge detection on the video image with the preset output size based on the initial filtering result of the input video image of the nth to n + M1-1 frames; when the video image with the preset output size has a black edge, adjusting the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames, and performing smoothing filtering again until the video image with the preset output size does not have the black edge; and when the video image with the preset output size has no black edge, updating the final filtering result of the input video image of the n-th to n + M1-1-th frames, and outputting the final filtering result of the input video image of the n-th frame according to the preset output size. By applying the scheme, the phenomenon of harsh dragging of a video picture can be avoided when the black edge is restrained.
Description
Technical Field
The invention relates to the technical field of video processing, in particular to a video anti-shake method and device and a mobile terminal.
Background
Video anti-shake, i.e. removing unwanted frame-to-frame shake in video to obtain a natural, smooth and stable video.
In actual video anti-shake, the following three steps are typically included: motion estimation, motion smoothing and motion compensation. Wherein: and motion estimation, namely estimating motion information of the video image. And motion smoothing, namely performing smooth filtering on the motion information of the estimated video image to obtain a new smooth video image motion track. And motion compensation, namely obtaining compensation information of the current video frame according to the estimated motion track of the video image and the smoothed motion track, and correcting the current video frame.
Since some areas of the corrected video frame are areas which do not exist in the original video frame, namely black edges, in practical application, an output size smaller than an input size needs to be agreed in advance, and then the filtering process is constrained in the motion smoothing process, so that no black edges appear in the agreed output size.
However, in the existing video anti-shake method, when black edge constraint is performed, a video picture is often dragged suddenly, so that the effect of the video picture after image stabilization is poor.
Disclosure of Invention
The invention aims to solve the problem of avoiding the harsh dragging phenomenon of a video picture when black edge constraint is carried out.
In order to solve the above problem, an embodiment of the present invention provides a video anti-shake method, where the method includes: acquiring motion estimation information of an input video image; carrying out smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result; for the input video image of the nth frame, carrying out black edge detection on the video image with a preset output size based on the initial filtering result of the input video image of the (n) th to (n + M1-1) th frames, wherein M1 is the size of a window for black edge detection, n is any input video image, and n and M1 are both positive integers; when the video image with the preset output size has a black edge, adjusting a smoothing factor of the input video image of the (n) th to (n + M1-1) th frames, and performing smoothing filtering again until the video image with the preset output size has no black edge; and when the video image with the preset output size has no black edge, taking the filtering result of the input video image of the n-th frame to the n + M1-1 frame as the final filtering result of the input video image of the n-th frame to the n + M1-1 frame, and outputting the final filtering result of the input video image of the n-th frame according to the preset output size.
Optionally, the performing smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result includes: calculating a smoothing factor corresponding to the input video image of the kth frame based on the motion estimation information of the input video image of the kth frame, wherein k is a positive integer; and performing smooth filtering on the input video image of the kth frame based on the calculated smoothing factor corresponding to the input video image of the kth frame.
Optionally, the calculating a smoothing factor corresponding to the input video image of the k frame based on the motion estimation information of the input video image of the k frame includes: performing linear fitting on motion estimation information of input video images of the k-N to k + M-1 frames, and taking the slope of a fitted straight line as speed information of the input video images of the k frame, wherein N + M is the size of a linear fitting window, N and M are positive integers, and N is less than k; calculating a fitting error between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the kth-N to k + M-1 frame as noise information of the input video image of the kth frame; and calculating a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame.
Optionally, the calculating a fitting error between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the k-N to k + M-1 th frame as noise information of the input video image of the k-th frame includes: calculating the correlation between the fitted straight line and a curve corresponding to the motion estimation information of the input video image of the (k-N) th to (k + M-1) th frames; and calculating the noise information of the input video image of the k frame based on the calculated value of the correlation.
Optionally, the calculating a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame includes: and calculating a smoothing factor corresponding to the input video image of the kth frame by adopting a preset fuzzy control system based on the speed information and the noise information of the input video image of the kth frame.
Optionally, the calculating, by using a preset fuzzy control system, a smoothing factor corresponding to the kth frame of input video image based on the speed information and the noise information of the kth frame of input video image includes: and taking the speed information and the noise information of the input video image of the kth frame as the input information of the fuzzy control system, calling a membership function corresponding to the preset input information by the fuzzy control system, and calculating a smoothing factor corresponding to the input video image of the kth frame according to the corresponding relation between the membership function corresponding to the input information and the smoothing factor.
Optionally, the performing smooth filtering on the input video image of the kth frame based on the calculated smoothing factor corresponding to the input video image of the kth frame includes: obtaining a smooth filtering result of the input video image of the (k-1) th frame; and carrying out weighted average on the smooth filtering result of the input video image of the k-1 frame and the motion estimation information of the input video image of the k-1 frame to the k + M-1 frame to obtain the smooth filtering result of the input video image of the k frame, wherein M is the size of a smooth filtering window.
Optionally, the black edge detection on the video image of the preset output size based on the initial filtering result of the input video image of the n-th to n + M1-1-th frames includes: calculating a rectification value of the input video image of the n-th to n + M1-1 frames based on the initial filtering result of the input video image of the n-th to n + M1-1 frames; and performing black edge detection on the video image with the preset output size based on the correction values of the input video image of the n-th to n + M1-1-th frames.
Optionally, when the video image of the preset output size has a black edge, adjusting a smoothing factor of the n-th to n + M1-1-th frame video images includes: when the video image with the preset output size has a black edge, reducing the value of a preset adjusting coefficient, wherein the adjusting coefficient is more than or equal to 0 and less than or equal to 1; and taking the product of the reduced value of the adjusting coefficient and the smoothing factor of the input video image of the current (n) th to (n + M1-1) th frames as the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames in the next smoothing filtering process.
Optionally, the method further comprises: and when the video image with the preset output size has no black edge, increasing the smoothing factor of the input video image of the (n) th to n + M1-1 th frames until the maximum value of the smoothing factor when the video image with the preset output size has no black edge is obtained, and performing smooth filtering on the input video image of the (n) th to n + M1-1 th frames by using the maximum value of the smoothing factor to obtain a final filtering result of the input video image of the (n) th to n + M1-1 th frames.
The embodiment of the invention also provides a video anti-shake device, which comprises: an acquisition unit adapted to acquire motion estimation information of an input video image; the filtering unit is suitable for carrying out smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result; the black edge detection unit is suitable for carrying out black edge detection on a video image with a preset output size based on the initial filtering result of the n-th to n + M1-1-th frame video images, M1 is the size of a window for black edge detection, n is any one frame input video image, and n and M1 are positive integers; a first adjusting unit, adapted to adjust the smoothing factor of the n-th to n + M1-1-th frame video image when the video image of the preset output size has a black edge, and perform smoothing filtering again by the filtering unit until the video image of the preset output size detected by the black edge detecting unit has no black edge; and the output unit is suitable for taking the filtering result of the input video image of the n-th to n + M1-1 frames as the final filtering result of the input video image of the n-th to n + M1-1 frames of the video image of the n-th to n + M1-1 frames when the video image of the preset output size has no black edge, and outputting the final filtering result of the input video image of the n-th frame according to the preset output size.
Optionally, the filtering unit includes: the first smoothing factor calculating subunit is suitable for calculating a smoothing factor corresponding to the kth frame of input video image based on the motion estimation information of the kth frame of input video image, wherein k is a positive integer; and the filtering subunit is adapted to perform smooth filtering on the input video image of the kth frame based on the calculated smoothing factor corresponding to the input video image of the kth frame.
Optionally, the smoothing factor calculating subunit includes: the linear fitting module is suitable for performing linear fitting on motion estimation information of input video images of a k-N to k + M-1 frame, and taking the slope of a fitted straight line as speed information of the input video images of the k frame, wherein N + M is the size of a linear fitting window, N and M are positive integers, and N is less than k; the error fitting module is suitable for calculating a fitting error between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the kth-N to k + M-1 frame as noise information of the input video image of the kth frame; and the smoothing factor calculation module is suitable for calculating a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame.
Optionally, the error fitting module is adapted to calculate a correlation between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the (k-N) th to (k + M-1) th frames; and calculating noise information of the input video image of the k frame based on the calculated value of the correlation.
Optionally, the smoothing factor calculating module is adapted to calculate a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame by using a preset fuzzy control system.
Optionally, the fuzzy control system is adapted to use the speed information and the noise information of the input video image of the kth frame as the input information of the fuzzy control system, and the fuzzy control system calls a membership function corresponding to the preset input information and a corresponding relationship between the membership function corresponding to the input information and a smoothing factor to calculate the smoothing factor corresponding to the input video image of the kth frame.
Optionally, the filtering subunit is adapted to obtain a smooth filtering result of the input video image of the (k-1) th frame; and carrying out weighted average on the smooth filtering result of the input video image of the k-1 frame and the motion estimation information of the input video image of the k-1 frame to the k + M-1 frame to obtain the smooth filtering result of the input video image of the k frame, wherein M is the size of a smooth filtering window.
Optionally, the black edge detection unit includes: a rectification value operator unit adapted to calculate a rectification value of the input video image of the n-th to n + M1-1 frames based on the initial filtering result of the input video image of the n-th to n + M1-1 frames; and the black edge detection subunit is suitable for performing black edge detection on the video image with the preset output size based on the correction values of the input video images of the n-th to n + M1-1-th frames.
Optionally, the first adjusting unit includes: an adjustment coefficient reduction subunit adapted to reduce a value of a preset adjustment coefficient when a black edge appears in the video image of the preset output size, the adjustment coefficient being greater than or equal to 0 and less than or equal to 1; and the second smoothing factor calculation subunit is used for taking the product of the reduced value of the adjusting coefficient and the smoothing factor of the input video image of the current (n) th to (n + M1-1) th frames as the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames in the next smoothing filtering process.
Optionally, the apparatus further comprises: a second adjusting unit, adapted to increase the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames when the video image of the preset output size has no black edge until obtaining the maximum value of the smoothing factor when the video image of the preset output size has no black edge; the output unit is suitable for enabling the result of smoothing filtering on the input video image of the n th frame to the n + M1-1 th frame by using the maximum value of the smoothing factor to be used as the final filtering result of the input video image of the n th frame to the n + M1-1 th frame.
The embodiment of the invention also provides a mobile terminal which comprises any one of the video anti-shake devices.
Compared with the prior art, the embodiment of the invention has the advantages that:
by adopting the scheme, for the input video image of the nth frame, black edge detection is carried out on the video image with the preset output size based on the initial filtering result of the input video image of the nth to n + M1-1 frames, and when the video image with the preset output size has a black edge, the smoothing factor of the input video image of the nth to n + M1-1 frames is adjusted, and smoothing filtering is carried out again until the video image with the preset output size has no black edge, and then the final filtering result of the input video image of the nth frame is output, so that the video image is prevented from generating a harsh dragging phenomenon in the black edge constraint process, and the video after image stabilization looks smoother and natural.
Furthermore, the smoothing factor corresponding to the input video image of the kth frame is calculated by performing straight line fitting on the motion estimation information of the input video image of the kth-N to k + M-1 frames, so that the fitting noise and speed information can more accurately represent the actual motion condition of the kth frame, and the subjective intention motion of the input video image can be better followed.
Further, the smoothing factor is calculated by using the fuzzy control system, so that the calculation amount can be reduced, and the calculation complexity can be simplified.
Further, the degree of smoothing may be increased by obtaining a smoothing filtering result of the input video image of the k-th frame by performing weighted averaging on the motion estimation information of the input video image of the k-th to k + M-1-th frames.
Drawings
FIG. 1 is a flowchart illustrating a video anti-shake method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for calculating a smoothing factor according to an embodiment of the present invention;
FIG. 3 is a flow chart of another video anti-shake method according to an embodiment of the invention;
FIG. 4 is a diagram illustrating a membership function curve corresponding to noise information according to an embodiment of the present invention;
FIG. 5 is a graph illustrating a membership function relationship corresponding to velocity information according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a video anti-shake apparatus according to an embodiment of the present invention.
Detailed Description
In the existing video anti-shake method, when the black edge detection is performed on the current frame input video image, the black edge detection is performed only by using the initial filtering result of the current frame input video image, and when the output video image has a black edge, the smoothing factor of the current frame input video image is adjusted and filtering is performed again, so that the video image often has a harsh dragging phenomenon.
In view of the above problems, an embodiment of the present invention provides a video anti-shake method, where black edge detection is performed on a video image of a preset output size based on an initial filtering result of an input video image of n to n + M1-1 frames, and when a black edge occurs in the video image of the preset output size, a smoothing factor of the input video image of the n to n + M1-1 frames is adjusted and smoothing filtering is performed again until no black edge occurs in the video image of the preset output size, and a final filtering result of the input video image of the n frame is output, so that a video image is prevented from being dragged suddenly during a black edge constraint process, and the video after image stabilization looks smoother and natural.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Referring to fig. 1, an embodiment of the present invention provides a video anti-shaking method, which may include the following steps:
and step 11, acquiring motion estimation information of the input video image.
In a specific implementation, the motion estimation information of only one or more frames of the input video image may be obtained each time, the motion estimation information of all frames of the input video image may be obtained after multiple times of obtaining, or the motion estimation information of all frames of the input video image may be obtained at one time, which is not limited specifically.
In an embodiment of the present invention, the motion estimation information of the input video image, that is, the motion vector information of each frame of the input video image, may be translational motion information of each frame of the input video image, or may be motion information of other directions of each frame of the input video image.
And step 12, performing smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result.
Taking smooth filtering of motion estimation information of a kth frame input video image as an example, in a specific implementation, a smoothing factor corresponding to the kth frame input video image may be calculated based on the motion estimation information of the kth frame input video image, and then, smooth filtering of the kth frame input video image may be performed based on the calculated smoothing factor corresponding to the kth frame input video image.
In a specific implementation, the smoothing factor corresponding to the input video image of the kth frame may be calculated by various methods, and is not limited in particular.
In a specific implementation, after obtaining a smoothing factor corresponding to the input video image of the kth frame, the input video image of the kth frame may be subjected to smoothing filtering by using a plurality of methods, which is not limited specifically.
In an embodiment of the present invention, when performing the smooth filtering on the kth frame of input video image, a smooth filtering result X (k-1) of the kth-1 frame of input video image may be obtained first, and then a formula (1) is adopted to perform weighted averaging on the smooth filtering result X (k-1) of the kth-1 frame of input video image and the motion estimation information Z (k) to Z (k + M-1) of the kth to k + M-1 frame of input video image, so as to obtain a smooth filtering result X (k) of the kth frame of input video image:
wherein, Z (i) is the motion estimation information of the input video image of any frame from the k frame to the k + M-1 frame, and M is the size of the smoothing filtering window.
In specific implementation, the value of M may be set according to actual situations, typically, M > 1, for example, M may be set to 2 or 3. It will be appreciated that the larger the value of M, the more delay is introduced into the smoothing filtering, and the more motion estimation information of the input video image needs to be stored when performing the smoothing filtering.
In a specific implementation, when the number of frames of the input video image after the current frame is less than M-1, the motion information of the last frame can be used as the motion information of the frame lacking later to obtain the motion information of the current frame to the M-1 frame after the current frame.
In a specific implementation, when performing smoothing filtering on the motion estimation information of the input video image of the kth frame, the smoothing filtering operation may be performed after obtaining the motion estimation information of the input video image of the kth to k + M-1 frames, or the smoothing filtering operation may be performed after obtaining the motion estimation information of all frames of the input video image.
And step 13, for the input video image of the nth frame, performing black edge detection on the video image with a preset output size based on the initial filtering result of the input video image of the nth frame to the n + M1-1 frame, wherein M1 is the window size of the black edge detection, n is any one frame of the input video image, and n and M1 are positive integers.
In an embodiment of the present invention, the correction value corr (n) to corr (n + M1-1) of the input video image of the n to n + M1-1 frames may be calculated based on the initial filtering result of the input video image of the n to n + M1-1 frames, and then the input video image of the n to n + M1-1 frames may be corrected based on the correction value of the input video image of the n to n + M1-1 frames, so as to perform black edge detection on the video image of the preset output size after correction.
The value of M1 can be set according to actual conditions, typically, M1 > 1, for example, M1 can be set to 3 or 4. It will be appreciated that the greater the value of M1, the greater the delay introduced in black edge detection.
In a specific implementation, when performing black edge detection on the input video image of the nth frame, the black edge detection operation may be performed after obtaining the initial filtering results of the input video images of the n to n + M1-1 th frames, or the smoothing filtering operation may be performed after obtaining the initial filtering results of all frames of the input video image.
And step 14, when the video image with the preset output size has a black edge, adjusting the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames, and performing smoothing filtering again until the video image with the preset output size has no black edge.
In particular implementations, the smoothing factor of the input video image for frames n through n + M1-1 may be adjusted by a variety of methods.
In an embodiment of the present invention, the value of the smoothing factor may be adjusted by a preset adjustment coefficient. Specifically, when the video image of the preset output size has a black edge, the value of the preset adjustment coefficient coef may be reduced to coef1, and the product of the reduced value coef1 and the smoothing factors K (n) to K (n + M1-1) of the current frame n to n + M1-1 input video image is used as the smoothing factors K1(n) to K1(n + M1-1) of the frame n to n + M1-1 input video image in the next smoothing filtering process.
Where 1 is not less than coef1 is not less than 0, and the initial value of coef is 1. K1(n) ═ K (n) × coef1, K1(n +1) ═ K (n +1) × coef 1; k1(n +2) ═ K (n +2) × coef 1; … …, respectively; k1(n + M1-1) ═ K (n + M1-1) × coef 1.
The input video images of the n-th to n + M1-1 frames are re-smoothed based on the smoothing factors K1(n) to K1(n + M1-1), and black edge detection is performed. If the video image with the preset output size has black edges, the value of coef1 is reduced to coef2, and the product of coef2 and K1(n) to K1(n + M1-1) is used as the smoothing factors K2(n) to K2(n + M1-1) of the input video image of the n-th to n + M1-1 frames in the next smoothing filtering process.
And repeating the process until the video image with the preset output size has no black edge.
In a specific implementation, the adjustment coefficient coef may be decreased by the same magnitude each time, or may be decreased by different magnitudes, and how to decrease the adjustment coefficient coef specifically does not limit the embodiment of the present invention.
In a specific implementation, when the number of frames of the input video image after the current frame is less than M1-1, the motion information of the last frame may be utilized as the motion information of the frame missing later to obtain the motion information of the current frame to the M1-1 frame after the current frame.
And step 15, when the video image with the preset output size has no black edge, taking the filtering result of the input video image of the n-th frame to the n + M1-1 frame as the final filtering result of the input video image of the n-th frame to the n + M1-1 frame, and outputting the final filtering result of the input video image of the n-th frame according to the preset output size.
That is, the smoothing factors corresponding to the video image with the preset output size without black edges are substituted into formula (1), so as to obtain the final filtering results of the input video images of the n-th to n + M1-1-th frames respectively. And updating the filtering results of the input video images of the n to n + M1-1 frames, and executing the steps 13 to 15 to obtain the final filtering result of the input video images of the n +1 frame. The repeated execution can obtain the final filtering result of each frame of input video image.
And outputting the final filtering result of each frame of input video image according to the preset output size, so as to obtain a smooth and natural video image.
Fig. 2 is a method for calculating a smoothing factor according to an embodiment of the present invention. Referring to fig. 2, the method may include the steps of:
and 21, performing linear fitting on motion estimation information of input video images of the k-N to k + M-1 frames, and taking the slope of a linear line after fitting as speed information of the input video images of the k frame, wherein N + M is a linear fitting window, N and M are positive integers, and N is less than k.
In the specific implementation, the motion estimation information of the input video image of the k-N to k + M-1 frame is subjected to straight line fitting, and the expression of the fitted straight line approximates discrete data consisting of the motion estimation information of the input video image of the k-N to k + M-1 frame, so that the slope of the fitted straight line can be used as the speed information of the input video image of the k frame. And step 22, calculating a fitting error between the fitted straight line and a curve corresponding to the motion estimation information of the input video image of the kth-N to k + M-1 frame as noise information of the input video image of the kth frame.
In a specific implementation, the correlation between the fitted straight line and the curve corresponding to the motion estimation information of the input video image of the (k-N) th to (k + M-1) th frames may be calculated, and then the fitting error, that is, the noise information of the input video image of the (k) th frame may be calculated based on the calculated correlation value.
And step 23, calculating a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame.
In an embodiment of the present invention, a preset fuzzy control system may be adopted to calculate a smoothing factor corresponding to the input video image of the k frame.
Specifically, the speed information and the noise information of the input video image of the kth frame are used as the input information of the fuzzy control system, the fuzzy control system calls a membership function corresponding to the preset input information and a corresponding relation between the membership function corresponding to the input information and a smoothing factor, and the smoothing factor corresponding to the input video image of the kth frame is calculated.
Fig. 3 is a schematic diagram of a membership function corresponding to speed information velocity of a k-th frame of input video image, and fig. 4 is a schematic diagram of a membership function corresponding to noise information noise of the k-th frame of input video image. Table 1 shows a corresponding relationship between the speed information velocity and the noise information noise of the input video image of the kth frame and the smoothing factor.
TABLE 1
For example, referring to table 1, when the noise of the input video image of the k-th frame is ML and the speed is ML, the corresponding smoothing factor is 0.84. When the noise of the input video image of the k-th frame is MH and the speed is H, the corresponding smoothing factor is 0.86. In these, L, ML, M, H, MH and VH are not clear values.
According to the speed information and the noise information of the input video image of the kth frame, the fuzzy control system calls a preset membership function and the corresponding relation between the membership function and the smoothing factor to calculate the smoothing factor of the input video image of the kth frame.
In specific implementation, the N + M frame window is only used for performing straight line fitting, and then noise and speed information of the N + M frame window are estimated to determine a final smoothing factor so as to perform adaptive filtering, when motion estimation information of a k-N to k + M-1 frame input video image cannot be obtained, straight line fitting may not be performed, and a preset empirical value is selected as a smoothing factor corresponding to the k-th frame input video image, such as 0.95.
Referring to fig. 5, an embodiment of the present invention further provides a video anti-shake method, where the method may include the following steps:
For steps 501 and 502, reference may be made to the above description of steps 11 and 12, respectively, and details are not repeated here.
In step 503, n is 1.
That is, from the 1 st frame input video image, the subsequent operation is performed.
And step 504, performing black edge detection on the video image with the preset output size based on the initial filtering result of the input video image of the (n) th to (n + M1-1) th frames.
And 505, judging whether the video image with the preset output size has a black edge.
That is, it is determined whether or not the output video image generated based on the initial filtering result of the input video image of the (n + M1-1) th frame has a black border.
When the video image with the preset output size has a black edge, step 506 is executed, otherwise step 508 is executed.
In a specific implementation, the smoothing factor may be reduced by reducing the preset adjustment coefficient, which is specifically referred to the above description about step 14 and will not be described herein again.
And step 507, performing smoothing filtering again on the input video images of the n-th to n + M1-1-th frames based on the reduced smoothing factor.
After step 507 is executed, step 505 is still executed, i.e. whether a black border appears is detected again.
In a specific implementation, the smoothing factor of the input video image of the n-th to n + M1-1-th frames can be increased by increasing a preset adjustment coefficient. Of course, the smoothing factor of the input video image of the n-th to n + M1-1-th frames can be directly increased, and the specific increasing mode is not limited.
In a specific implementation, the smoothing factor may be increased by the same amplitude each time, or may be increased by different amplitudes, and how to increase the smoothing factor is not limited to the present invention.
In step 509, it is determined whether the increased smoothing factor reaches the maximum value of the smoothing factor when no black edge appears in the video image with the preset output size.
In a specific implementation, when a preset adjustment coefficient is used to increase a smoothing factor, if the adjustment coefficient reaches the maximum value, and the video image of the preset output size still has no black edge, the increased smoothing factor reaches the maximum value of the smoothing factor when the video image of the preset output size has no black edge. Or a maximum value of the smoothing factor may be preset according to an actual situation, and when the increased smoothing factor is equal to the preset maximum value, the video image of the preset output size still has no black edge, and then the increased smoothing factor reaches the maximum value of the smoothing factor when the video image of the preset output size has no black edge.
When the increased smoothing factor reaches the maximum value of the smoothing factor when no black edge appears in the video image of the preset output size, step 510 is executed. When the increased smoothing factor does not reach the maximum value of the smoothing factor when no black edge appears in the video image with the preset output size, the step 508 is continuously executed, namely, the smoothing factor of the input video image of the n-th to n + M1-1 frames is continuously increased.
And 510, updating the final filtering result of the input video image of the n-th to n + M1-1 frames according to the result of smoothing filtering the input video image of the n-th to n + M1-1 frames by using the maximum value of the smoothing factor.
That is, the input video image of the n-th to n + M1-1 frames is subjected to smooth filtering by using the maximum value of the smoothing factor, and the obtained smooth filtering result is used as the final filtering result of the input video image of the n-th to n + M1-1 frames.
The degree of smoothing of the smoothing filter can be further increased by increasing the smoothing factor to a maximum value.
And 511, outputting the final filtering result of the input video image of the nth frame according to the preset output size.
As can be seen from the above, the video anti-shake method provided in the embodiment of the present invention adaptively levels the smoothing factor of the smoothing filter by obtaining the motion information of the video image according to the motion information of the video image, and removes shake while moving as much as possible according to the subjective intention of the video image. And when the black edge detection is carried out, when the video image output according to the smooth filtering result of the input video image of the n + M1-1 frame generates the black edge, the smooth filtering result of the input video image of the n frame is adjusted, so that the harsh dragging phenomenon of the output video image can be avoided, and the stabilized video is smoother and more natural.
In an embodiment of the present invention, the subjective intended motion of the video image is a motion performed by a user subjective control video image. For example, a user holds a camera to perform a horizontal movement from left to right, which is a subjective intention movement of a video image, and the horizontal movement inevitably includes vertical shaking that is not a subjective intention movement of the video image.
In order to make those skilled in the art better understand and implement the present invention, the following describes in detail a video anti-shake apparatus and a mobile terminal corresponding to the above video anti-shake method.
Referring to fig. 6, an embodiment of the present invention provides a video anti-shake apparatus 60, where the video anti-shake apparatus 60 may include: an acquisition unit 61, a filtering unit 62, a black edge detection unit 63, a first adjustment unit 64, and an output unit 65. Wherein:
the acquiring unit 61 is adapted to acquire motion estimation information of an input video image;
the filtering unit 62 is adapted to perform smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result;
the black edge detection unit 63 is adapted to perform black edge detection on a video image of a preset output size based on initial filtering results of n-th to n + M1-1-th frame video images, where M1 is a window size of black edge detection, n is any one of input video images, and n and M1 are positive integers;
the first adjusting unit 64 is adapted to adjust the smoothing factor of the n-th to n + M1-1-th frame video image when the video image of the preset output size has a black edge, and perform smoothing filtering again by the filtering unit until the video image of the preset output size detected by the black edge detecting unit has no black edge;
the output unit 65 is adapted to, when the video image of the preset output size has no black edge, take the filtering result of the input video image of the n-th to n + M1-1 frames as the final filtering result of the input video image of the n-th to n + M1-1 frames of the video image of the n-th to n + M1-1 frames, and output the final filtering result of the input video image of the n-th frame according to the preset output size.
In a specific implementation, the filtering unit 62 may include: a first smoothing factor calculation subunit 621 and a filtering subunit 622. Wherein:
the first smoothing factor calculating subunit 621 is adapted to calculate a smoothing factor corresponding to a kth frame of input video image based on motion estimation information of the kth frame of input video image, where k is a positive integer;
the filtering subunit 622 is adapted to perform smoothing filtering on the input video image of the kth frame based on the calculated smoothing factor corresponding to the input video image of the kth frame.
In an embodiment of the present invention, the smoothing factor calculating subunit 621 may include: a line fitting module (not shown), an error fitting module (not shown), and a smoothing factor calculation module (not shown). Wherein:
the linear fitting module is suitable for performing linear fitting on motion estimation information of input video images of a k-N to k + M-1 th frame, and taking the slope of a fitted straight line as speed information of the input video images of the k frame, wherein N + M is the size of a linear fitting window, N and M are positive integers, and N is less than k;
the error fitting module is suitable for calculating a fitting error between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the kth-N to k + M-1 frame as noise information of the input video image of the kth frame;
and the smoothing factor calculation module is suitable for calculating the smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame.
In specific implementation, the error fitting module is adapted to calculate a correlation between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the (k-N) th to (k + M-1) th frames; and calculating noise information of the input video image of the k frame based on the calculated value of the correlation.
In a specific implementation, the smoothing factor calculating module is adapted to calculate a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame by using a preset fuzzy control system.
In a specific implementation, the fuzzy control system is adapted to use speed information and noise information of the input video image of the kth frame as input information of the fuzzy control system, and the fuzzy control system calls a membership function corresponding to the preset input information and a corresponding relationship between the membership function corresponding to the input information and a smoothing factor to calculate the smoothing factor corresponding to the input video image of the kth frame.
In a specific implementation, the filtering subunit is adapted to obtain a smooth filtering result of the input video image of the (k-1) th frame; and carrying out weighted average on the smooth filtering result of the input video image of the k-1 frame and the motion estimation information of the input video image of the k-1 frame to the k + M-1 frame to obtain the smooth filtering result of the input video image of the k frame, wherein M is the size of a smooth filtering window.
In a specific implementation, the black edge detection unit 63 may include: a correction value calculation operator unit 631 and a black edge detection subunit 632. Wherein:
the rectification value operator unit 631 is adapted to calculate the rectification values of the input video images of the n-th to n + M1-1 frames based on the initial filtering results of the input video images of the n-th to n + M1-1 frames;
the black edge detection subunit 632 is adapted to perform black edge detection on a video image of a preset output size based on the corrected values of the input video images of the n-th to n + M1-1-th frames.
In a specific implementation, the first adjusting unit 64 may include: an adjustment coefficient reduction subunit 641 and a second smoothing factor calculation subunit 642. Wherein:
the adjustment coefficient reducing subunit 641 is adapted to reduce a value of a preset adjustment coefficient when a black edge appears in the video image of the preset output size, where the adjustment coefficient is greater than or equal to 0 and less than or equal to 1;
the second smoothing factor calculating subunit 642 is adapted to take the product of the reduced value of the adjustment coefficient and the smoothing factor of the input video image of the current (n) th to (n + M1-1) th frames as the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames in the next smoothing filtering process.
In a specific implementation, the video anti-shake apparatus 60 may further include: a second adjusting unit (not shown). The second adjusting unit is suitable for increasing the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames when the video image of the preset output size has no black edge until the maximum value of the smoothing factor when the video image of the preset output size has no black edge is obtained;
the output unit 65 is adapted to smooth the result of filtering the input video image of the n-th to n + M1-1-th frames by using the maximum value of the smoothing factor as the final filtering result of the input video image of the n-th to n + M1-1-th frames.
The embodiment of the present invention further provides a mobile terminal, which may include the video anti-shake apparatus 60 in the above embodiment.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: ROM, RAM, magnetic or optical disks, and the like.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (15)
1. A video anti-shake method, comprising:
acquiring motion estimation information of an input video image;
carrying out smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result;
for the input video image of the nth frame, carrying out black edge detection on the video image with a preset output size based on the initial filtering result of the input video image of the (n) th to (n + M1-1) th frames, wherein M1 is the size of a window for black edge detection, n is any input video image, and n and M1 are both positive integers;
when the video image with the preset output size has a black edge, adjusting a smoothing factor of the input video image of the (n) th to (n + M1-1) th frames, and performing smoothing filtering again until the video image with the preset output size has no black edge;
when the video image with the preset output size has no black edge, taking the filtering result of the input video image of the n-th frame to the n + M1-1 frame as the final filtering result of the input video image of the n-th frame to the n + M1-1 frame, and outputting the final filtering result of the input video image of the n-th frame according to the preset output size;
the performing smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result includes: calculating a smoothing factor corresponding to the input video image of the kth frame based on the motion estimation information of the input video image of the kth frame, wherein k is a positive integer; based on the calculated smoothing factor corresponding to the input video image of the kth frame, carrying out smoothing filtering on the input video image of the kth frame;
the calculating a smoothing factor corresponding to the input video image of the k frame based on the motion estimation information of the input video image of the k frame includes: performing linear fitting on motion estimation information of input video images of the k-N to k + M-1 frames, and taking the slope of a fitted straight line as speed information of the input video images of the k frame, wherein N + M is the size of a linear fitting window, N and M are positive integers, and N is less than k; calculating a fitting error between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the kth-N to k + M-1 frame as noise information of the input video image of the kth frame; calculating a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame;
the performing smooth filtering on the input video image of the kth frame based on the calculated smoothing factor corresponding to the input video image of the kth frame includes: obtaining a smooth filtering result of the input video image of the (k-1) th frame; and carrying out weighted average on the smooth filtering result of the input video image of the k-1 frame and the motion estimation information of the input video image of the k-1 frame to the k + M-1 frame to obtain the smooth filtering result of the input video image of the k frame, wherein M is the size of a smooth filtering window.
2. The video anti-shake method according to claim 1, wherein the calculating a fitting error between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the k-N to k + M-1 th frame as noise information of the input video image of the k-th frame comprises:
calculating the correlation between the fitted straight line and a curve corresponding to the motion estimation information of the input video image of the (k-N) th to (k + M-1) th frames;
and calculating the noise information of the input video image of the k frame based on the calculated value of the correlation.
3. The video anti-shake method according to claim 1, wherein the calculating a smoothing factor corresponding to the input video image of the k frame based on the speed information and the noise information of the input video image of the k frame comprises:
and calculating a smoothing factor corresponding to the input video image of the kth frame by adopting a preset fuzzy control system based on the speed information and the noise information of the input video image of the kth frame.
4. The video anti-shake method according to claim 3, wherein the calculating, by the predetermined blur control system, the smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame comprises:
and taking the speed information and the noise information of the input video image of the kth frame as the input information of the fuzzy control system, calling a membership function corresponding to the preset input information by the fuzzy control system, and calculating a smoothing factor corresponding to the input video image of the kth frame according to the corresponding relation between the membership function corresponding to the input information and the smoothing factor.
5. The video anti-shake method according to claim 1, wherein the black-edge detection of the video image of the preset output size based on the initial filtering result of the input video image of the n-th to n + M1-1 frames comprises:
calculating a rectification value of the input video image of the n-th to n + M1-1 frames based on the initial filtering result of the input video image of the n-th to n + M1-1 frames;
and performing black edge detection on the video image with the preset output size based on the correction values of the input video image of the n-th to n + M1-1-th frames.
6. The video anti-shake method according to claim 1, wherein the adjusting the smoothing factor of the n-th to n + M1-1-th frame video images when the video images of the preset output size appear black edges comprises:
when the video image with the preset output size has a black edge, reducing the value of a preset adjusting coefficient, wherein the adjusting coefficient is more than or equal to 0 and less than or equal to 1;
and taking the product of the reduced value of the adjusting coefficient and the smoothing factor of the input video image of the current (n) th to (n + M1-1) th frames as the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames in the next smoothing filtering process.
7. The video anti-shake method of claim 1, further comprising:
and when the video image with the preset output size has no black edge, increasing the smoothing factor of the input video image of the (n) th to n + M1-1 th frames until the maximum value of the smoothing factor when the video image with the preset output size has no black edge is obtained, and performing smooth filtering on the input video image of the (n) th to n + M1-1 th frames by using the maximum value of the smoothing factor to obtain a final filtering result of the input video image of the (n) th to n + M1-1 th frames.
8. A video anti-shake apparatus, comprising:
an acquisition unit adapted to acquire motion estimation information of an input video image;
the filtering unit is suitable for carrying out smooth filtering on the motion estimation information of the input video image to obtain an initial filtering result;
the black edge detection unit is suitable for carrying out black edge detection on a video image with a preset output size based on the initial filtering result of the n-th to n + M1-1-th frame video images, M1 is the size of a window for black edge detection, n is any one frame input video image, and n and M1 are positive integers;
a first adjusting unit, adapted to adjust the smoothing factor of the n-th to n + M1-1-th frame video image when the video image of the preset output size has a black edge, and perform smoothing filtering again by the filtering unit until the video image of the preset output size detected by the black edge detecting unit has no black edge;
the output unit is suitable for taking the filtering result of the input video image of the n-th to n + M1-1 frames as the final filtering result of the input video image of the n-th to n + M1-1 frames of the video image of the n-th to n + M1-1 frames when the video image of the preset output size has no black edge, and outputting the final filtering result of the input video image of the n-th frame according to the preset output size;
the filtering unit includes: the first smoothing factor calculating subunit is suitable for calculating a smoothing factor corresponding to the kth frame of input video image based on the motion estimation information of the kth frame of input video image, wherein k is a positive integer; the filtering subunit is adapted to perform smooth filtering on the kth frame input video image based on the calculated smoothing factor corresponding to the kth frame input video image;
the smoothing factor calculating subunit includes: the linear fitting module is suitable for performing linear fitting on motion estimation information of input video images of a k-N to k + M-1 frame, and taking the slope of a fitted straight line as speed information of the input video images of the k frame, wherein N + M is the size of a linear fitting window, N and M are positive integers, and N is less than k; the error fitting module is suitable for calculating a fitting error between the fitted straight line and a curve corresponding to motion estimation information of the input video image of the kth-N to k + M-1 frame as noise information of the input video image of the kth frame; the smoothing factor calculation module is suitable for calculating a smoothing factor corresponding to the input video image of the kth frame based on the speed information and the noise information of the input video image of the kth frame;
the filtering subunit is suitable for acquiring a smooth filtering result of the input video image of the (k-1) th frame; and carrying out weighted average on the smooth filtering result of the input video image of the k-1 frame and the motion estimation information of the input video image of the k-1 frame to the k + M-1 frame to obtain the smooth filtering result of the input video image of the k frame, wherein M is the size of a smooth filtering window.
9. The video anti-shake apparatus according to claim 8, wherein the error fitting module is adapted to calculate a correlation between the fitted straight line and a curve corresponding to the motion estimation information of the input video image of the (k-N) th to (k + M-1) th frames; and calculating noise information of the input video image of the k frame based on the calculated value of the correlation.
10. The video anti-shake apparatus according to claim 8, wherein the smoothing factor calculating module is adapted to calculate the smoothing factor corresponding to the input video image of the k frame based on the speed information and the noise information of the input video image of the k frame by using a preset fuzzy control system.
11. The video anti-shake apparatus according to claim 10, wherein the fuzzy control system is adapted to use the speed information and the noise information of the input video image of the kth frame as the input information of the fuzzy control system, and the fuzzy control system calls the membership function corresponding to the preset input information and the corresponding relationship between the membership function corresponding to the input information and the smoothing factor to calculate the smoothing factor corresponding to the input video image of the kth frame.
12. The video anti-shake apparatus of claim 8, wherein the black edge detection unit comprises:
a rectification value operator unit adapted to calculate a rectification value of the input video image of the n-th to n + M1-1 frames based on the initial filtering result of the input video image of the n-th to n + M1-1 frames;
and the black edge detection subunit is suitable for performing black edge detection on the video image with the preset output size based on the correction values of the input video images of the n-th to n + M1-1-th frames.
13. The video anti-shake apparatus of claim 8, wherein the first adjustment unit comprises:
an adjustment coefficient reduction subunit adapted to reduce a value of a preset adjustment coefficient when a black edge appears in the video image of the preset output size, the adjustment coefficient being greater than or equal to 0 and less than or equal to 1;
and the second smoothing factor calculation subunit is used for taking the product of the reduced value of the adjusting coefficient and the smoothing factor of the input video image of the current (n) th to (n + M1-1) th frames as the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames in the next smoothing filtering process.
14. The video anti-shake apparatus of claim 8, further comprising: a second adjusting unit, adapted to increase the smoothing factor of the input video image of the (n) th to (n + M1-1) th frames when the video image of the preset output size has no black edge until obtaining the maximum value of the smoothing factor when the video image of the preset output size has no black edge;
the output unit is suitable for enabling the result of smoothing filtering on the input video image of the n th frame to the n + M1-1 th frame by using the maximum value of the smoothing factor to be used as the final filtering result of the input video image of the n th frame to the n + M1-1 th frame.
15. A mobile terminal characterized by comprising the video anti-shake apparatus according to any one of claims 8 to 14.
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