JP2006311108A - Image processor, image processing method, image processing program and camera - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processor using a recognition result of a subject to correct photographed image data. <P>SOLUTION: A digital still camera 10 which processes the image data 24a obtained by imaging the subject includes an image recognition section 32 which detects a plurality of faces included in a field from the image data 24a, evaluates the respective faces, determines a reference face for correction of the image data 24a according to the evaluation, and determines a correction quantity for the image data 24a based upon the reference face, and a digital signal processing sectioni 36 which corrects the image data 24a based upon the correction quantity. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an image processing method, an image processing program, and a camera for correcting image data.

2. Description of the Related Art Conventionally, there has been a technique for capturing an image of an object scene with an image sensor and acquiring image data, and recognizing a subject, for example, a face included in the acquired image data. There is a technique for performing automatic exposure control, focusing, strobe control, and the like based on a recognized subject using this technique. Patent Document 1 describes that a face image is recognized and focusing or strobe control is performed.
JP 2003-92700 A

  The above prior art discloses that a subject is recognized and photographing operations such as automatic exposure control, focusing, and strobe control are performed. However, this technique only uses the result of recognizing the subject for the shooting operation of the camera.

  SUMMARY OF THE INVENTION An object of the present invention is to provide an image processing apparatus, an image processing method, an image processing program, and a camera that eliminate such drawbacks of the prior art and use a result of recognizing a subject for correcting captured image data. And

  In order to solve the above-described problems, the present invention is an image processing apparatus that processes image data obtained by capturing an image of a scene, and detects a plurality of subjects included in the scene from the image data. Means for evaluating each of a plurality of subjects, and in accordance with the evaluation, a reference subject determining unit for determining a subject as a reference for correction of the image data, and a correction amount for determining a correction amount of the image data based on the reference subject The image forming apparatus includes a determination unit and a correction unit that corrects the image data based on the correction amount. This correction means can correct the gradation of image data, for example. The gradation includes a brightness gradation and a color gradation.

  According to the present invention, when a plurality of subjects are recognized when the subject is recognized and the image data is corrected, the subject is selected based on the evaluation value of the subject, that is, the importance, and the image data is corrected. I do. For this reason, it is possible to prevent correction and excessive correction even though correction is not necessary.

  In order to solve the above-described problems, the present invention performs evaluation of a subject and subject detection means for detecting a subject included in the scene from the image data in the image processing apparatus, and according to the evaluation, A correction amount determination unit that determines a correction amount and a correction unit that corrects image data based on the correction amount are included.

  According to this, when recognizing a subject and performing image correction, it is possible to perform correction by adjusting the correction amount according to the importance of the subject.

  The subject is preferably an area including a face. The evaluation can be an evaluation value related to at least one of the size of the subject, the size of the face included in the subject, the brightness of the subject, and the brightness of the face included in the subject.

  According to the present invention, when recognizing a subject and correcting image data based on the recognition result, when a plurality of subjects are detected or a subject that does not need to be corrected is detected, The subject's evaluation is determined from the area and brightness. In accordance with the determined importance, a subject as a correction reference is determined and a correction amount of image data is determined. For this reason, it is possible to avoid correcting an object that does not need to be corrected or to perform excessive correction, and to correct image data appropriately.

  Next, an embodiment in which an image processing apparatus according to the present invention is applied to a digital still camera will be described in detail with reference to the accompanying drawings. In this embodiment, a scene is captured by a digital still camera, and a subject (face) included in the scene is recognized using the captured data. At this time, depending on the situation, a plurality of subjects may be detected.

  In that case, determine the importance of each subject according to the size of the subject and the brightness of the subject, determine the amount of image correction (for example, brightness correction) based on the subject with high importance, and perform the correction. Do. Correction (brightness correction by gradation correction) is performed so that the subject with the highest importance is appropriate. As a result, it is possible to correctly select the subject to be corrected, and when correction is not necessary, it is possible to prevent correction from being performed or to prevent excessive correction, and to perform image correction appropriately. Can be done.

  An image processing apparatus according to an embodiment processes image data obtained by capturing an image of a scene, and includes a subject detection unit that detects a plurality of subjects included in the scene from the image data, and a plurality of subjects A reference subject determination unit that performs evaluation for each subject and determines a subject as a reference for correction of image data according to the evaluation, and a correction amount determination unit that determines a correction amount of the image data based on the importance of the reference subject And correction means for correcting the image data based on the correction amount.

  The subject detection means detects a face as a subject in this configuration example. The reference subject determining means uses a plurality of detected face sizes, that is, the face area and the face brightness as evaluation targets, and finally evaluates a product of the evaluation value related to the area and the evaluation value related to the brightness. Value. Based on the final evaluation value, a face to be corrected is selected from a plurality of faces. The correction unit corrects the brightness of the image data by gradation conversion in consideration of the final evaluation value.

  Note that the evaluation method is not limited to this, and the entire person including the face and the torso may be evaluated as a subject other than the method of evaluating from the face alone. Moreover, you may evaluate only in any one of an area and brightness other than the method of making the evaluation value the product of the evaluation value regarding an area, and the evaluation value regarding brightness. The sum of the evaluation value related to the area and the evaluation value related to the brightness may be used as the final evaluation value.

  Furthermore, in this embodiment, the face area is used as the face size as the evaluation value, but the face area is not limited to the face area, and the vertical or horizontal length of the face may be used as the evaluation value. This is because the face area and the vertical or horizontal length of the face have a correlation.

  As a result of the evaluation, one object is finally selected in the present embodiment. However, in the present invention, the number of objects to be selected is not limited to one and may be plural. As a method for determining a correction amount when a plurality of selections are made, for example, the correction amount can be determined from an average value of evaluation values (importance levels) of a plurality of subjects. Further, the subject is not limited to a person, and the evaluation may be performed using a car or a building as a subject other than the person.

  FIG. 1 is a block diagram of a digital still camera 10 which is an embodiment of an imaging apparatus according to the present invention. Incident light from the subject is collected by the lens 12. The size of the light beam collected by the lens 12 is limited by the diaphragm unit 14. A driving unit 16 is provided to move the lens 12 to focus or drive the diaphragm unit 14.

  Incident light that has passed through the lens 12 and the diaphragm unit 14 is photoelectrically converted by the imaging device 20 including a CCD (Charge Coupled Device) and output to the analog signal processing unit 22 as a signal 20a. The analog signal processing unit 22 performs signal processing such as CDS (Correlated Double Sampling), reduces noise included in the signal 20a, and outputs the signal 22a to the AD conversion circuit 24. The AD conversion circuit 24 converts the signal 22a into a digital signal and outputs it to the memory 30 as an image signal (image data) 24a. The image signal 24a is stored in the memory 30.

  The processing of the image signal 24a stored in the memory 30 is different between the preliminary shooting and the main shooting. Preliminary shooting is when the shutter of the operation unit 32 is half-pressed, photometry and distance measurement are performed for the main shooting, the lens 12 and the aperture unit 14 are set, and then the shutter is fully moved. Real shooting is performed when pressed.

  The image signal 24a obtained by the preliminary photographing is read out by the system control unit 34, and processing for photometry is performed by a known method. As a result of photometry, for example, when it is determined that the backlight is in the backlit state, the system control unit 34 causes the strobe 48 to emit light.

  The system control unit 34 performs these processes and controls the entire electronic camera 10 based on the control program. The system control unit 34 includes a CPU (Central Processing Unit: not shown) that executes these processes and predetermined control, and a ROM (Read Only Memory, not shown) that stores control programs, control parameters, and the like. And RAM (Random Access Memory, not shown) which is a working memory.

  The system control unit 34 controls the lens 12, the diaphragm unit 14, and the image sensor 20 via the drive unit 16 at the time of shooting. The drive unit 16 supplies a control signal and a timing signal to the lens 12, the diaphragm unit 14, and the image sensor 20. Further, the system control unit 34 controls the strobe 48.

  The image signal 24a obtained by the main photographing is read by the image recognition unit 32. The image recognition unit 32 detects a subject included in the scene from the image signal 24a, and performs evaluation for each of the plurality of subjects when there are a plurality of subjects. The image recognizing unit 32 sets the product of the area evaluation value and the brightness evaluation value as the evaluation value, with the face area and the face brightness as evaluation targets. Based on this evaluation value, a subject that is a reference for correction of the image signal 24a is determined, and further, a correction amount of the image signal 24a is determined based on the importance of the determined reference subject.

  The system control unit 34 corrects the image signal 24a based on the determined correction amount. This correction process is performed by further changing a so-called gradation conversion curve (gamma correction curve) according to the determined correction amount. Details of these processes will be described later.

  In this embodiment, the reference subject and the correction amount are determined based on the image data obtained at the time of the main photographing. However, the present invention is limited to this. However, these determinations may be made based on image data obtained at the time of preliminary shooting.

  The image signal 24a obtained by the main photographing is also read by the digital signal processing unit 36. The digital signal processing unit 36 performs image processing such as auto white balance processing on the image signal 24a according to the image processing parameter. In the present embodiment, the gradation conversion is performed after the auto white balance process. The image 36a subjected to these processes is stored in the memory 30.

  The image 36a stored in the memory 30 is read from the memory 30 and stored in the memory card 38b via the card interface (card I / F) 38a. The image 36a read from the memory 30 is also displayed on a liquid crystal display (LCD: Liquid Crystal Display) 40b or a finder (EVF: Electric View Finder, electronic view finder) 40c via the image composition unit 40a. The image synthesis unit 40a is for synthesizing the image 36a and various information (camera operating state, brightness of the object scene, etc.) to be displayed on the liquid crystal display unit 40b or the finder 40c.

  The lens 12, the diaphragm unit 14, the drive unit 16, and the imaging device 20 constitute an image imaging unit. The image recognition unit 32 is a subject detection unit, a reference subject determination unit, and a correction amount determination unit. The system control unit 34 is correction means. The functions of the subject detection unit, the reference subject determination unit, the correction amount determination unit, and the correction unit can be executed by a program.

  An outline of the operation of the digital still camera 10 will be described with reference to FIG. When the operator looks into the subject from the finder 40c or the display unit 40b and half-presses the shutter of the operation unit (not shown), the system control unit 34 detects a signal indicating that the shutter is half-pressed, and the imaging device 20 The incident light from the subject is converted into a signal 20a. The signal 20a is sequentially extracted by a clock generated from the driving unit 16, and the analog signal processing unit 22 performs processing such as reducing noise included in the signal 20a. The signal 22 a output from the analog signal processing unit 22 is converted into an image signal 24 a which is a digital signal by the AD conversion circuit 24, and the image signal 24 a is sent to the memory 30.

  The system control unit 34 reads the image signal 24a from the memory 30, and performs photometry based on the image signal 24a. Whether to perform backlight correction is determined based on the image signal 24a. As a result of these, the exposure value is determined, and it is also determined whether or not the strobe 48 is caused to emit light. The system control unit 34 drives the lens 12 and the diaphragm unit 14 via the drive unit 16 according to the determination, and prepares for the actual photographing.

  When the operator fully presses the shutter, the system control unit 34 detects a signal indicating that the shutter is fully pressed, and causes the image sensor 20 to convert incident light from the subject into a signal 20a. At this time, the flash 48 emits light if necessary. Similarly to the preliminary shooting, the signal 20a is converted into an image signal 24a, and the image signal 24a is sent to the memory 30.

  The image signal 24a is read by the image recognition unit 32. The image recognition unit 32 detects the subject and evaluates the importance of the subject. Based on this evaluation value, a subject as a reference for correction is determined, and further, a correction amount of the image signal 24a is determined from the importance of the subject as a reference. The system control unit 34 corrects the image signal 24a.

  The image signal 24 a is also input to the digital signal processing unit 36, and after processing such as white balance processing and the above correction processing, the processed image signal 36 a is stored in the memory 30. The image signal 36a may be displayed on the display unit 40b according to an instruction from the operation unit.

  Next, object detection, evaluation, and correction for the image signal 24a performed by the image recognition unit 32 and the system control unit 34 will be described with reference to the drawings. In the present embodiment, the subject is a face, and face detection is performed. The image recognition unit 32 first detects a face image from the image signal 24a. The detection of the face image is performed by a known method described in Patent Document 1 or the like. For example, this is performed as follows.

  The image signal 24a of the subject imaged by the image sensor 20 is stored in the memory 30. The image signal 24a is taken into the image recognition unit 32 in a certain predetermined unit (unit of one frame or several bytes). Next, the image signal is compared with various types of data representing facial features stored in the image recognizing unit 32 in advance (template data such as facial contours, eyes, nose, mouth, ears, etc.). This comparison method is performed based on various algorithms. As a result, for example, a portion of the image signal 24a having a degree of coincidence with a predetermined level of data representing a feature is determined as a face image.

  2A and 2B show examples of recognized face images. FIG. 2 (a) shows a case where a plurality of persons 44a, 44b, 44c, 44d are present in the object scene 42a. The image recognition unit 32 detects a plurality of face images 46a, 46b, 46c, 46d. FIG. 2 (a) also shows other objects that are not subjects, such as the landscape 50. FIG. FIG. 2B shows a case where one person 44e is present in the object scene 42b. The image recognition unit 32 detects the face image 46e.

  FIG. 3 (a) shows another example of the recognized face image. FIG. 3A shows a case where one person 44f is photographed small in the object scene 42c. The image recognition unit 32 detects the face image 46f. For comparison, FIG. 2 (b) is shown again in FIG. 3 (b). FIG. 3B shows a case where a single person 44e is photographed large in the object scene 42b.

  The image recognition unit 32 may set detection frames 45a to 45f surrounding the face images 46a to 46f after detecting the face images 46a to 46f. FIGS. 2 (a), 2 (b), 3 (a), and 3 (b) show detection frames 45a to 45f. The detection frames 45a to 45f calculate the areas of the detection frames 45a to 45f instead of directly obtaining the areas of the face images 46a to 46f when evaluating the areas of the face images 46a to 46f as described later. The importance of the images 46a to 46f may be determined. This is because the size relationship between the areas of the face images 46a to 46f and the size relationship between the detection frames 45a to 45f are considered to be the same.

  In addition, when a person other than a person is a detection target, data corresponding to the detection target (for example, a building, a car, etc.) may be prepared as template data.

  After recognizing the face image, the image recognition unit 32 performs evaluation for each of the plurality of faces when there are a plurality of faces. The image recognition unit 32 obtains the area and brightness for each of a plurality of faces, with the face area and the brightness of the face as evaluation targets. As the face brightness, for example, an average value of the brightness of pixels included in the face is employed. An evaluation value (importance) is obtained from the area and brightness. The product of the importance obtained from the area and the importance obtained from the brightness is defined as the importance of each face.

  An example of the relationship between the face area and the brightness and importance of the face is shown in FIG. 4 (a) and 4 (b) show the relationship between the face area and the importance level, and the relationship between the face brightness and the importance level, respectively. In the figure, the horizontal axis represents the face area and the brightness of the face, and the vertical axis represents the importance. The maximum value is, for example, 1.0, and the minimum value is, for example, 0.0.

  Regarding the relationship between the area of the face and the importance, it is considered that the importance is higher as the area is larger, so the graph as shown in FIG. 4 (a) is adopted. When the value is smaller than a certain value 54a, the importance is set to “0”. When the value is larger than a certain value 54b, the importance is set to “1”. The reason why the importance level is uniformly “0” when the value is smaller than 54a is that the subject whose area is below a certain level is of little interest to the photographer, and the importance level is uniformly set to “0”. This is because it is considered to meet the photographer's intention or desire. When the value is larger than 54b, the reason why the importance is uniformly set to “1” is that the subject having an area of a certain degree or more is equally interested in the photographer, and the importance is uniformly set to “1”. This is because it is considered to be in line with the photographer's intention or desire.

Regarding the relationship between the brightness of the face and the importance, it is considered that the importance is low if the brightness is too low or too high, so a graph as shown in FIG. 4B is adopted. If the value is smaller than a certain value 56a and larger than a certain value 56b, the importance is set to “0”. The reason why the importance is uniformly set to “0” is that the photographer is less interested or unpreferable if the brightness is too low or too high. It is because it is considered that it is in line with the photographer's intention or desire, the importance relating to the area and the importance relating to the brightness are assigned to each of the face images 46a to 46d according to FIGS. Ask for 46f. Furthermore, the product is obtained for each face.

  When there are a plurality of subjects (faces), the face having the highest importance level among the importance levels for each face is used as a reference for correction for the image signal 24a. In the case of FIG. 2 (a), the face image 46b has the largest area. It is also assumed that the product of the importance regarding brightness is the largest among the face images 46a, 46b, 46c, and 46d. In this case, since the importance of the face image 46b is the highest, the face image 46b is a face that is a reference for correction. Note that the importance of the determined face image 46b is used to determine the correction amount as will be described later.

  On the other hand, as shown in FIGS. 2 (b) and 3 (a), when there is only one face, the face images 46e and 46f are used as correction reference faces. Then, for the face images 46e and 46f, the importance related to the area and the importance related to the brightness are obtained from FIGS. 4A and 4B, and the product of these importance is obtained. The importance of the face images 46e and 46f is used to determine the correction amount.

  Next, determination of the correction amount will be described. When the importance used for determining the correction amount is obtained as described above, the correction amount of the image signal 24a is determined from the relationship between the importance and the correction amount shown in FIG. The horizontal axis in FIG. 5 is the importance, and the vertical axis is the correction amount, which takes a value between 0% and 100%.

  The image recognition unit 32 determines a correction amount from the relationship of FIG. 5 and outputs the determined correction amount to the system control unit 34. The correction amount is increased as the importance is increased. If the value is smaller than a certain value 52a, the importance is set to “0”. When the value is larger than a certain value 52b, the importance is set to “1”.

  The system control unit 34 receives the correction amount and corrects the image signal 24a. In this correction process, the image signal 24a is changed according to the gradation conversion curve to obtain the image signal 36a. In this embodiment, the correction is performed according to the determined correction amount between the gradation conversion curve corresponding to the correction amount of 0% and the gradation conversion curve that is the target value corresponding to the correction amount of 100%. FIG. 6 shows a gradation conversion curve 58a corresponding to a correction amount of 0% and a gradation conversion curve 58b that is a target value corresponding to a correction amount of 100%. The gradation conversion curve corresponds to a so-called gamma correction curve.

  The correction of the present invention is not limited to the correction related to the gradation conversion curve, and other corrections such as color conversion processing (color vividness processing), spatial frequency processing (image sharpness processing). You may use for the correction | amendment regarding etc.

  When the correction amount is determined as described above, when the correction amount is 0%, the gradation conversion curve 58a is used, and when the correction amount is 100%, the gradation conversion curve 58b is used. Is used, and a gradation conversion curve (not shown) between the gradation conversion curve 58a and the gradation conversion curve 58b is used when the correction amount is between 0% and 100%. For example, output data 60b, 60d, 60c (image signal 36a) is obtained for input data 60a (image signal 24a) when the correction amount is 0%, 100%, or otherwise.

  Next, processing steps of subject detection, evaluation, and correction for the image signal 24a performed by the image recognition unit 32 and the system control unit 34 will be described with reference to FIG. The image recognition unit 32 receives the image signal 24a from the memory 30 (step S1). The image recognition unit 32 detects the subject from the image signal 24a (step S2). Next, the image recognition unit 32 determines how many subjects are detected (step S3).

  When the detection number n is 0, image correction is not performed, so the process proceeds to step S7, and the image signal 24a is not converted and output to the memory 30 as the image signal 36a (step S7).

  On the other hand, when the detection number n is greater than 1, the process proceeds to step S4, and the importance is calculated from the size and brightness of each subject. The product of the two calculated importance levels is set as the importance level of the subject (step S4). Based on the calculated importance, the subject having the highest importance is set as the reference subject. The correction amount of the image signal 24a is determined from the importance of the reference subject (step S5). The system control unit 34 receives the correction amount, determines a gradation conversion curve, and converts the image signal 24a using the determined gradation conversion curve (step S6). The image signal 36a obtained by the conversion is output to the memory 30 (step S7).

  When the detection number n is 1, the process proceeds to step S8, and importance is calculated from the size and brightness of one subject. The product of the two calculated importance levels is set as the importance level of the subject (step S8). The image recognition unit 32 determines the correction amount of the image signal 24a from the importance of the subject (step S9). Thereafter, step S6 described above is performed.

  According to the present embodiment, when a plurality of subjects are detected, the evaluation of the subject is determined from the area, brightness, and the like. In accordance with the determined importance, a subject to be corrected is determined and a correction amount of image data is determined. For this reason, it is possible to avoid correcting an object that does not need to be corrected or to perform excessive correction, and to correct image data appropriately.

  In the above-described embodiment, the image data is corrected when stored in the memory 30, but the present invention is not limited to storing in the memory 30, and is displayed on a display, for example, during playback. It is also possible to correct the data displayed or printed out when printing or printing out to a printer. In this case, it is preferable to perform correction suitable for these. For example, it is preferable to use a gradation conversion curve suitable for display display or printer output as the gradation conversion curve.

  In the above embodiment, the same correction amount is uniformly applied to the image data of the entire screen. However, the present invention is not limited to this, and different corrections are made for different items in the screen. It is good also as setting quantity. For example, the correction amount may be changed between the person and the background, or between the persons, the correction amount may be changed according to the importance of the person.

1 is a block diagram of a digital still camera which is an embodiment of an imaging apparatus according to the present invention. It is explanatory drawing which shows an example of the recognition result of the to-be-photographed object by this invention. . It is explanatory drawing which shows an example of the recognition result of the to-be-photographed object by this invention. . It is a graph which shows the relationship between the area of a face and importance, and the relationship between the brightness of a face and importance. It is a graph which shows the relationship between importance and correction amount. It is a graph which shows the example of a predetermined gradation conversion curve It is a flowchart which shows the process step of the correction | amendment with respect to the detection of the to-be-photographed object, evaluation, and image signal which an image recognition part and a system control part perform.

Explanation of symbols

10 Digital still camera
12 Lens
14 Aperture
16 Drive unit
20 Image sensor
30 memory
32 Image recognition unit
34 System controller
36 Digital signal processor
44a ~ 44f People
45a to 45f detection frame
46a-46f face image
48 Strobe

Claims (11)

In an image processing apparatus that processes image data obtained by imaging a scene, the apparatus includes:
Subject detection means for detecting a plurality of subjects included in the scene from the image data;
A reference subject determination unit that performs evaluation for each of the plurality of subjects and determines the subject as a reference for correction of the image data according to the evaluation;
Correction amount determining means for determining a correction amount of the image data based on the reference subject;
An image processing apparatus comprising: correction means for correcting the image data based on the correction amount.   The image processing apparatus according to claim 1, wherein the correction amount determination unit performs the evaluation on the reference subject and determines the correction amount of the image data based on the evaluation. Processing equipment. In an image processing apparatus that processes image data obtained by imaging a scene, the apparatus includes:
Subject detection means for detecting a subject included in the scene from the image data;
A correction amount determining means for evaluating the subject and determining a correction amount of the image data according to the evaluation;
An image processing apparatus comprising: correction means for correcting the image data based on the correction amount.   4. The image processing apparatus according to claim 1, wherein the correction unit corrects a gradation of the image data.   5. The image processing apparatus according to claim 1, wherein the subject is an area including a face.   The image processing apparatus according to claim 1, wherein the evaluation includes the size of the subject, the size of the face included in the subject, the brightness of the subject, and the face included in the subject. An image processing apparatus characterized by an evaluation value relating to at least one of the brightness values.   7. An image processing apparatus according to claim 1, further comprising: an image capturing unit that captures an image of the object scene, acquires the image data, and outputs the acquired image data. camera. In an image processing method for processing image data obtained by imaging an object scene, the method includes:
Detecting a plurality of subjects included in the scene from the image data;
Performing an evaluation for each of the plurality of subjects, and determining the subject as a reference for correction of the image data according to the evaluation;
Determining a correction amount of the image data based on the reference subject;
And a step of correcting the image data based on the correction amount. In an image processing method for processing image data obtained by imaging an object scene, the method includes:
Detecting a subject included in the object scene from the image data;
Evaluating the subject and determining a correction amount of the image data according to the evaluation;
And a step of correcting the image data based on the correction amount. A computer for processing the image data obtained by imaging the object scene,
Means for detecting a plurality of subjects included in the object scene from the image data;
Means for evaluating each of the plurality of subjects and determining the subject as a reference for correction of the image data according to the evaluation;
Means for determining a correction amount of the image data based on the reference subject;
An image processing program for causing a function to correct the image data based on the correction amount. A computer to process the image data obtained by imaging the object scene,
Means for detecting a subject included in the object scene from the image data;
Means for evaluating the subject and determining a correction amount of the image data according to the evaluation;
An image processing program for causing a function to correct the image data based on the correction amount.