Patent Publication Number: US-10791270-B2

Title: Image stabilization apparatus capable of accurately estimating an offset component of an angular velocity sensor, optical apparatus, and image stabilization method

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a Continuation of International Patent Application No. PCT/JP2017/027248, filed on Jul. 27, 2017, which claims the benefit of Japanese Patent Application No. 2016-158340, filed on Aug. 12, 2016, both of which are hereby incorporated by reference herein in their entirety. 
    
    
     BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The present invention relates to an image stabilization apparatus, an optical apparatus, and an image stabilization method. 
     Description of the Related Art 
     There has conventionally been known an optical apparatus that includes an image stabilization apparatus (or image blur correction apparatus) configured to correct an image blur. A correction amount is obtained based on a detection result of an angular velocity sensor (gyro sensor) and a motion vector calculated by analyzing a blur between image frames. 
     Panoramic imaging is also known as a sophisticated imaging method. The panoramic imaging is a technique for generating a vertically or horizontally oriented image with a wide angle of view through continuous capturing by panning the camera and by combining consecutively captured images in the panning direction. An alignment in combining the images generally uses the motion vector, but uses the output from the gyro sensor for a scene when the motion vector cannot be calculated. Then, the output from the gyro sensor, in particular, the integration error caused by the offset noise of the gyro sensor negatively influences the alignment accuracy. 
     Japanese Patent No. 5663897 discloses an image stabilization apparatus configured to calculate an offset noise of a gyro sensor mounted on a camera side using a motion vector. Japanese Patent Laid-Open No. 2010-220002 discloses an imaging apparatus configured to reset a high-pass filter at a predetermined period so as to prevent electric charges from being saturated in a capacitor serving as the high-pass filter that filters a gyro signal in panoramic imaging. 
     The image stabilization apparatus disclosed in Japanese Patent No. 5663897 can successfully calculate the offset noise of the gyro sensor unless the image stabilization apparatus is provided to the interchangeable lens, or when the image stabilization apparatus is provided to it but is not driven. However, when the image stabilization apparatus is driven, it is necessary to acquire the position signal of the image stabilization apparatus and the offset noise of the gyro sensor cannot be accurately calculated. 
     Japanese Patent Laid-Open No. 2010-220002 uses the high-pass filter for the gyro signal and cuts a panning signal in the panning for a longer period than a period of the cutoff frequency of the filter. 
     With the foregoing problems in mind, it is an object of the present invention to provide an image stabilization apparatus, an optical apparatus, and an image stabilization method, each of which can accurately estimate an offset component of an angular velocity sensor. 
     SUMMARY OF THE INVENTION 
     An image stabilization apparatus according to one aspect of the present invention includes a processor programmed to function as a first acquirer configured to acquire angular velocity data of an angular velocity sensor, a second acquirer configured to acquire data relating to a position of a correction lens to be driven so as to correct a blur in a captured image, a third acquirer configured to acquire a motion vector calculated based on the captured image, and an estimator configured to estimate an offset component of the angular velocity sensor based on the angular velocity data, the data relating to the position, and the motion vector. The data relating to the position is generated based on the angular velocity data. 
     An image stabilization method according to another aspect of the present invention includes a first acquiring step configured to acquire angular velocity data of an angular velocity sensor, a second acquiring step configured to acquire data relating to a position of a correction lens to be driven so as to correct a blur in a captured image, a third acquiring step configured to acquire a motion vector calculated based on the captured image, and an estimating step configured to estimate an offset component of the angular velocity sensor based on the angular velocity data, the data relating to the position, and the motion vector. The data relating to the position is generated based on the angular velocity data. 
     Further features of the present invention will become apparent from the following description of exemplary embodiments (with reference to the attached drawings). 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of an optical apparatus including an image stabilization apparatus according to one embodiment of the present invention. 
         FIG. 2  is a block diagram of a lens system controller. 
         FIG. 3  is an explanatory diagram of an estimated model. 
         FIG. 4  is a block diagram of a camera system controller. 
         FIG. 5  is a block diagram of an estimator. 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     Referring now to the accompanying drawings, a description will be given of embodiments according to the present invention. In each figure, corresponding elements will be designated by the same reference numerals, and a duplicate description thereof will be omitted. 
       FIG. 1  is a block diagram of a lens interchangeable type digital camera (referred to as a camera hereinafter)  1  which is an illustrative optical apparatus including an image stabilization apparatus according to one embodiment of the present invention. The camera  1  includes an interchangeable lens  100  and a camera body  200 . This embodiment discusses a lens interchangeable type digital camera as an illustrative optical apparatus, but the present invention is not limited to this embodiment. For example, the optical apparatus may be an imaging apparatus in which a lens and a camera body are integrated with each other. 
     A zoom unit  101  has a zoom lens that performs zooming. A zooming controller  102  controls driving of the zoom unit  101 . A diaphragm driving controller  104  controls driving of a diaphragm unit  103 . An image stabilization unit  105  includes a correction lens movable to correct an image blur. An image stabilization controller  106  controls driving of the image stabilization unit  105 . A focus unit  107  includes a focusing lens. A focusing controller  108  controls driving of the focus unit  107 . An operation unit  109  instructs the operation of the interchangeable lens  100 . A hand shake detector (camera shake detector)  110  is an angular velocity sensor, such as a gyro sensor, and detects angular velocity data corresponding to a hand shake amount applied to the interchangeable lens  100 . The angular velocity data is output as a voltage. A lens system controller  111  controls the entire interchangeable lens  100 . A lens communication controller  112  controls a communication with the camera body  200 . 
     A shutter driving controller  202  drives the shutter unit  201 . An imaging unit  203  converts an object image formed by the interchangeable lens  100  into an electric signal. A captured signal processor  204  converts the electric signal output from the imaging unit  203  into an image signal (captured image). An image signal processor  205  processes the image signal output from the captured signal processor  204  according to the application. A display unit  206  displays a necessary image based on the signal output from the image signal processor  205 . A memory (storage unit)  207  stores various data such as image information. A power supply  208  supplies the power to necessary components according to the application. An operation unit  209  instructs the operation of the camera body  200 . A hand shake detector  210  is an angular velocity sensor, such as a gyro sensor, and detects angular velocity data corresponding to a hand shake amount applied to the camera body  200 . A motion vector calculator  211  analyzes a blur between frames in the image signal and calculates a motion vector. The motion vector calculator  211  can prevent an erroneous calculation of the motion vector caused by an image noise and remove a blur component other than a hand shake by dividing the image into a plurality of blocks and by calculating the entire motion vector from a plurality of motion vectors calculated for each block. An electronic image stabilization controller  212  controls the electronic image stabilization by cutting out an image. A camera system controller (image stabilization apparatus)  213  controls the entire camera body  200 . The camera communication controller  214  controls a communication with the interchangeable lens  100 . 
     A description will now be given of an operation of the camera  1  using the operation units  109  and  209 . The operation units  109  and  209  have image stabilization switches that can select an image stabilization mode. When the image stabilization switch is turned on, the lens system controller  111  and the camera system controller  213  instruct the image stabilization operation to the image stabilization controller  106  and the electronic image stabilization controller  212 , respectively. The image stabilization controller  106  and the electronic image stabilization controller  212  perform the image stabilization operation until the image stabilization switch is turned off. 
     The operation unit  209  includes a shutter release button configured so that a first switch SW 1  and a second switch SW 2  are sequentially turned on in accordance with a press amount. This embodiment turns on the first switch SW 1  when the shutter release button is approximately half-pressed, and turns on the second switch SW 2  when the shutter release button is fully pressed. When the first switch SW 1  is turned on, the focusing controller  108  drives the focus unit  107  for focusing, and the diaphragm driving controller  104  drives the diaphragm unit  103  to set a proper exposure amount. When the second switch SW 2  is turned on, a captured image is acquired and stored in the memory  207 . 
     The operation unit  209  includes a motion image recording switch. When the motion image recording switch is turned on, motion image capturing starts, and when the switch is turned on again in the motion image recording, the imaging ends. When the first switch SW 1  and the second switch SW 2  are turned on in the motion image recording, a still image is captured in the motion image recording. 
     The operation unit  209  includes a reproduction mode selection switch that can select a reproduction mode. In the reproduction mode, the image stabilization operation stops. 
       FIG. 2  is a block diagram of the lens system controller  111 . The A/D converter  301  converts the angular velocity data output from the hand shake detector  110  into digital data. A high-pass filter  302  blocks the low-frequency component in the angular velocity data. An integrator  303  integrates the angular velocity data in which the low-frequency component is blocked mainly by the pseudo integration by the low-pass filter and converts it into angle data. A sensitivity multiplier  304  converts the angle data into a shift amount (first image stabilization amount) of the correction lens in the image stabilization unit  105 . A value corresponding to the focal length is used for the sensitivity. 
     An estimator  310  acquires angular velocity data detected by the hand shake detector  110 , position data of the correction lens in the image stabilization unit  105 , and a motion vector calculated by the motion vector calculator  211 . The estimator  310  estimates an offset component, a sensitivity, and each error variance value of the hand shake detector  110  based on the acquired data. An offset unit  305  removes the offset component estimated by the estimator  310  from the angular velocity data output from the hand shake detector  110 . The integrator  306  integrates angular velocity data in which the offset component has been removed mainly by the pseudo integration by the low-pass filter and converts it into angle data. A sensitivity multiplier  307  converts the angle data into a shift amount of the correction lens in the image stabilization unit  105  (second image stabilization amount). A value corresponding to the focal length is used for the sensitivity. The shift amount output from the sensitivity multiplier  307  also reflects the correction amount by the sensitivity adjustment of the hand shake detector  110 , and absorbs the sensitivity scattering. Using the shift amount output from the sensitivity multiplier  307  can improve the image stabilization performance. The shift amount output from the sensitivity multiplier  307  is calculated based on the angular velocity data in which the low-frequency component is not blocked by the high-pass filter. The image stabilization based on the shift amount output from the sensitivity multiplier  307  can correct an image blur in a frequency component lower than that based on the shift amount output from the sensitivity multiplier  304 . 
     A selector  308  selects one of the shift amounts output from the respective sensitivity multipliers. The selector  308  selects the shift amount output from the sensitivity multiplier  307  in order to increase the image stabilization performance in the still image capturing, and selects the shift amount output from the sensitivity multiplier  304  because this is not the case in the non-still image capturing. A limiter  309  limits the shift amount selected by the selector  308  so that it falls within a movable range of the correction lens in the image stabilization unit  105 . 
     The image stabilization controller  106  includes an A/D converter  106   a , a PID controller  106   b , and a driver  106   c . A position detector  113  detects the position of the correction lens in the image stabilization unit  105  and outputs it as a voltage. The A/D converter  106   a  converts the data output from the position detector  113  into digital data. The PID controller  106   b  controls the position of the correction lens in the image stabilization unit  105 . The driver  106   c  converts the shift amount into the voltage and supplies the current to the image stabilization unit  105 . 
     Referring now to  FIG. 3 , a description will be given of a method for simultaneously estimating the offset component and the sensitivity of the angular velocity sensor based on the angular velocity data, the position data, and the motion vector.  FIG. 3  is an explanatory diagram of the estimated model. 
     When an angular velocity W is applied to the imaging apparatus, the angular velocity sensor mounted on the imaging apparatus initially calculates a signal by multiplying the angular velocity W by the sensitivity A of the angular velocity sensor. Next, it adds an offset component B of the angular velocity sensor having individual scattering to the calculated signal. A high-frequency component in the signal to which the offset component B is added is cut off by the low-pass filter L(s) and detected as angular velocity data G, where s is a complex number in the Laplace transform. The low-pass filter L(s) is provided in the angular velocity sensor in  FIG. 3 , but may be provided outside the angular velocity sensor. The angular velocity data G is converted into an image stabilization angular velocity by the image stabilization controller I(s) and detected as a position signal (position data) H. 
     The angular velocity W applied to the imaging apparatus is simply integrated into a true shake angle of the entire imaging apparatus. This signal cannot be detected. The position signal H is subtracted from the shake angle of the entire imaging apparatus and becomes a shake residue angle, and the difference between the frames of the shake angle is detected as the motion vector V. 
     In  FIG. 3 , a transfer characteristic from the angular velocity W to the motion vector V is expressed by the following expression (1).
 
 V=W−sH   (1)
 
     In  FIG. 3 , a transfer characteristic from the angular velocity W to the gyro data G is expressed by the following expression (2).
 
 G=L ( s )( AW+B )  (2)
 
     The expression (2) can be expressed by the following expression (3) by removing the angular velocity W that cannot be detected from the expression (1).
 
 G=AL ( s )( sH+V )+ L ( s ) B   (3)
 
     Since the frequency band of the hand shake is generally 20 Hz or less and the cutoff frequency of the low-pass filter L(s) is mainly 100 Hz, the expression (3) can be expressed by the following expression (4) since L(s) is approximated to 1.
 
 G=A ( sH+V )+ B   (4)
 
     While the continuous system has been described, a discrete system will be explained below. In the discrete system, where it is assumed that y(k) is angular velocity data G(k), x(k) is term ΔH(k)+V(k), and (A(k), B(k)) is an estimation parameter θ(k) T , the expression (4) is expressed by the following expression (5). Herein, A(k) is the sensitivity of the angular velocity sensor, B(k) is the offset component of the angular velocity sensor, and k is a discrete time. 
     
       
         
           
             
               
                 
                   
                     
                       
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     A new variable z(k) is expressed by the following expression (6). 
     
       
         
           
             
               
                 
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     From the expressions (4) to (6), the following state expression (7) is derived. 
     
       
         
           
             
               
                 
                   
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     Herein, ε is a system noise parameter representing a fluctuation component of the estimation parameter, and ω is an observation noise parameter. 
     From the expression (7), the sensitivity A(k) and the offset component B(k), which are the estimation parameters that can be expressed as the state variables, can be estimated from the angular velocity data G(k), the position signal H(k), and the motion vector V(k). Properly designing the system noise parameter c can estimate the sensitivity A(k) and the offset component B(k) including their temperature variation components. 
     As described above, if it is assumed that y is the angular velocity data G as the detected value, and x is sH+V as a sum of the position signal H and the motion vector V, the expression (4) becomes a simple linear model as y=Ax+B and can be replaced with a problem of determining a slope A and y-intercept B based on the detection value. The slope A is the sensitivity of the angular velocity sensor, and the y-intercept is the offset component of the angular velocity sensor. 
     The hand shake detector  210  in the camera body  200  is used for an alignment in the image combination in the camera body  200 , for determining the panning of the camera body  200 , and the like. The offset error and the sensitivity error become an issue for the hand shake detector  210 , similar to the hand shake detector  110 . A description will now be given of a method of estimating the offset component and the sensitivity of the hand shake detector  210 . 
       FIG. 4  is a block diagram of the camera system controller  213 .  FIG. 4  omits the estimator  310 . The estimator  405  estimates the offset component and the sensitivity of the hand shake detector  210  through the above estimation processing based on the angular velocity data, the position data, and the motion vector. Since the position data is detected within the interchangeable lens  100 , the detected data is notified to the camera body  200  via the lens communication controller  112  and the camera communication controller  214 . Hence, the estimation processing by the estimator  405  is subject to the communication speed. When the position data cannot be received at a high rate due to the influence of other communications, the low-frequency position data can be detected but the high-frequency position data cannot be detected. Accordingly, this embodiment generates the high-frequency position data in a pseudo manner using the hand shake detector  210 , combines the generated position data and the actually detected low-frequency position data, and generates pseudo position data of the correction lens in the image stabilization unit  105 . 
     An A/D converter  401  converts the angular velocity data output from the hand shake detector  210  into digital data. A high-pass filter  402  blocks a low-frequency component in the angular velocity data. An integrator  403  converts the angular velocity data from which the low-frequency component has been removed into a pseudo shift amount (pseudo image stabilization amount). A low-pass filter  404  blocks the high-frequency component in the position data. Combining the output of the integrator  403  and the output of the low-pass filter  404  generates the position data of the correction lens in the image stabilization unit  105  in a pseudo manner. An integrator  406  integrates the angular velocity data from which an accurately estimated offset component is removed, and converts it into an angle signal. The angle signal represents a moving angle of the camera body  200 , and is used for the panning determination of the camera body  200 , for the alignment in the image combination, and the like. 
     Referring now to  FIG. 5 , a description will be given of an internal configuration of the estimator  405 .  FIG. 5  is a block diagram of the estimator  405 . The estimator  405  includes an average value calculator (first acquirer)  501 , an image stabilization angular velocity calculator (second acquirer)  502 , a unit converter (third acquirer)  503 , low-pass filters  504  and  505 , and a Kalman filter (estimator)  506 . 
     The estimation processing in the estimator  405  is sampled at 30 Hz or 60 Hz which is the slowest sampling motion vector among the detected data. The angular velocity data and the position data are sampled at several kHz in each A/D converter, but using an exposure gravity center timing signal output from the captured signal processor  204  can make a synchronization with the motion vector. 
     The average value calculator  501  acquires the angular velocity data from the A/D converter  401  and calculates an interframe average value between exposure gravity centers of the angular velocity data. The image stabilization angular velocity calculator  502  obtains the pseudo position data of the correction lens in the image stabilization unit  105  from the integrator  403  and the low-pass filter  404 , and calculates the interframe image stabilization angular velocity from the difference between the exposure gravity centers in the position data. The unit converter  503  acquires a motion vector from the motion vector calculator  211  and converts a unit of the motion vector into an angular velocity. The data output from the average value calculator  501  is input to the low-pass filter  504 , and the data that is the sum of the data output from the image stabilization angular velocity calculator  502  and the data output from the unit converter  503  is input to the low-pass filter  505 . Therefore, aliasing can be reduced. The data output from the low-pass filters  504  and  505  are input to the Kalman filter  506 . The Kalman filter  506  estimates the offset component and the sensitivity of the hand shake detector  210 . It also calculates an estimated error variance value indicating the reliability of the estimation result. 
     A description will now be given of filtering for estimating the estimation parameter θ using the Kalman filter  506 . 
     Initially, a Kalman gain is calculated using the following expression (8). 
     
       
         
           
             
               
                 
                   
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     Next, the estimated parameter θ is calculated using the following expression (9).
 
θ( k )=θ( k− 1)+ K ( k ){ y ( k )− z   T ( k )·θ( k− 1)}  (9)
 
     Finally, the estimated error variance value is calculated using the following expression (10). 
     
       
         
           
             
               
                 
                   
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     Herein, k is a discrete time (number of filtering steps), K is a Kalman gain (1×2 matrix) and P is an estimated error covariance matrix (2×2 matrix). In addition, σ ω  is angular velocity data observation noise variance (scalar quantity), and R ε  is a system parameter (2×2 matrix) considering the temperature variation of the estimation parameter θ. An initial value of the estimated error covariance matrix P may be set to a predetermined value. Setting an excessively large value may diverge the estimation result, and thus it becomes a parameter that needs to be tuned according to the observed noise. 
     The angular velocity data observation noise variance σ ω  may use an observation-noise actual measurement value of the angular velocity data but as shown in the expressions (8) and (10), the larger it is the more slowly the estimation converges and the smaller it is the faster the estimation converges. On the other hand, the larger it is the more stable the filter is, the smaller it is the more likely the estimation result diverges. Hence, it may be considered as a tuning parameter for determining the convergence speed of the filter. 
     The estimated error variance value is an index that indicates how much the estimation parameter θ(j) at a predetermined time j varies from k=0 to j, and is a value equivalent to the reliability of the estimation parameter θ at the time j. 
     This embodiment estimates the estimation parameter θ using the Kalman filter, but the present invention is not limited to this embodiment. For example, the estimation parameter θ may be estimated using the sequential least-squares method. However, the sequential least squares method does not consider the observation noise or the system noise (estimation parameter variation component) and the filtering robustness is low. Therefore, it cannot handle with the temperature variation of the parameter, and the estimated value converges to a certain value. It is thus desirable to use the Kalman filter in the actual design. 
     This embodiment combines the high-frequency position data generated in a pseudo manner using the hand shake detector  210  and the actually detected low-frequency position data, and generates the pseudo position data of the correction lens in the image stabilization unit  105 . When the communication speed is sufficiently high (acquisition sampling of the position data is faster than the generation speed of the motion vector), it is unnecessary to use the pseudo high-frequency position data (the output signal from the integrator  403 ). As the communication speed becomes lower than the generation speed of the motion vector, the cutoff frequencies of the high-pass filter  402  and the low-pass filter  404  may be decreased and the ratio of the output signal from the integrator  403  to the position data may be increased. In some cases, the output signal from the integrator  403  may be used as position data. 
     In a signal band of about 5 Hz to 10 Hz, which is a main band of the hand shake, the position data generated in a pseudo manner based on the angular velocity data output from the hand shake detector  210  is approximately equal to position data output from the interchangeable lens  100 . However, on the lower frequency side, when the camera body  200  is panning, a control for preventing an edge contact of the image stabilization unit  105  is peculiar to the interchangeable lens  100  and it is difficult to reproduce the actually detected position data. According to this embodiment, the camera system controller  213  serves as a determiner configured to determine the panning of the camera body  200  based on the output signal from the hand shake detector  210  or the motion vector calculator  211 , and thereby to determine whether the estimation processing of the estimator  405  is to be updated. More specifically, when the signal output from the hand shake detector  210  or the motion vector calculator  211  is greater than the predetermined value and is output for a period longer than the predetermined period, the camera system controller  213  determines that the camera body  200  is panning. Meanwhile, the camera system controller  213  stops updating the Kalman filter  506  or does not cause the estimator  405  to update the estimation processing. On the other hand, if the camera system controller  213  determines that the camera body  200  is not panning, the camera system controller  213  causes the estimator  405  to update the estimation processing. Thereby, the offset component of the hand shake detector  210  can be estimated only with a highly accurate model signal (x(k) in the expression (5)) and the estimation accuracy can be improved. 
     While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions. 
     The present invention can provide an image stabilization apparatus, an optical apparatus, and an image stabilization method, each of which can accurately estimate an offset component of an angular velocity sensor.