JP2011193277A - Apparatus and method for processing image and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To recover image data deterioration caused due to lens characteristics while reducing a load on a user even if there is a difference in the lens characteristics because of manufacture variation. <P>SOLUTION: An adjustment image region extracting part 208 extracts from image data an image region corresponding to a recovery item of the image data. A recovery filter adjusting part 207 adjusts a recovery filter in response to an adjusting operation of the recovery item. A recovery processing part 209 performs recovery processing of the image region using the adjusted recovery filter. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a technique for recovering image data deteriorated due to lens characteristics or the like.

It is known that when an object is photographed in an image input device such as a digital camera, image data is more deteriorated than an actual object due to the influence of aberrations such as a lens. As a technique for recovering this deterioration, a technique using a recovery filter calculated from a point spread function (PSF) of an optical system is known (for example, see Patent Document 1). Specifically, when the recovery filter is R, the deteriorated image data is O, and the recovered image data is S, it can be expressed as Equation 1.
S = O * R (Formula 1)
Here, * is a convolution integral. A recovery filter for recovering the deteriorated image data is held in advance in the image input device.

  In addition, a method is known in which a user performs an operation while confirming parameters for recovering the deterioration from image data (see, for example, Patent Document 2). As a result, it is possible to adjust the manufacturing variation of the lens and the adjustment to the user's preference. Furthermore, a method for calculating an adjustment amount of a parameter by analyzing image data is also known (see, for example, Patent Document 3).

JP 2001-197354 A JP 2006-081058 A JP 2006-020275 A

  However, in a general lens used in a digital camera or the like, it is inevitable that the lens characteristics differ from those at the time of designing due to a slight assembly error at the time of lens manufacture. In addition, these assembly errors have different characteristics for each lens. For this reason, even if the recovery filter is held in advance as in the technique disclosed in Patent Document 1, the actual lens characteristics may be different. Accordingly, there are cases where the lens is overrecovered or insufficiently recovered for each lens.

  In addition, as in the technique disclosed in Patent Document 2, when a user operates a parameter while confirming image data, the user needs to determine an image area for confirming the image data. Therefore, the user must determine which image area can be used for efficient recovery. Further, as in the technique disclosed in Patent Document 3, when calculating the parameter adjustment amount by analyzing the image data, it is possible to recover the chromatic aberration of magnification having the characteristic that the edge color is blurred, but other image quality is also possible. Deterioration cannot be recovered.

  Therefore, an object of the present invention is to recover image data degradation due to lens characteristics while reducing the load on the user even if there is a difference in lens characteristics due to manufacturing variations.

  An image processing apparatus according to the present invention includes an extraction unit that extracts an image area corresponding to a recovery item of image data from the image data, an adjustment unit that adjusts a recovery filter according to an adjustment operation of the recovery item, and the adjustment unit And recovery means for performing recovery processing of the image area extracted by the extraction means by the recovery filter adjusted in accordance with the above.

  According to the present invention, even if there is a difference in lens characteristics due to manufacturing variations, it is possible to restore degradation of image data due to lens characteristics while reducing the load on the user.

It is a figure which shows the hardware constitutions of the image processing apparatus which concerns on embodiment of this invention. It is a figure which shows the structure of the image process part which is the main functions of the image processing apparatus which concerns on embodiment of this invention. It is a figure which shows an example of the user interface displayed by the user interface part in the 1st Embodiment of this invention. It is a flowchart which shows the image processing method performed by the image processing apparatus which concerns on embodiment of this invention. It is a flowchart which shows the detail of a developing process. It is a figure which shows the table | surface which matched the recovery item used as selection object, the recovery method, and the bad influence by manufacturing dispersion | variation. It is a flowchart which shows the detail of the extraction process of the adjustment image area | region suitable for a recovery item. It is a figure which shows the table | surface which matched the recovery item and the search range of image data. It is a figure for demonstrating the search range of image data. It is a flowchart which shows the detail of the calculation process of an evaluation value. It is a figure which shows the table | surface which matched the recovery item and the extraction frequency. It is a flowchart which shows the detail of the adjustment process of a recovery filter. It is a figure which shows the table | surface which matched the recovery item and the adjustment parameter. It is a figure for demonstrating the adjustment method of the recovery filter in the case where "amplitude characteristic" is selected as a parameter, and the case where "phase characteristic" is selected. It is a figure which shows an example of the user interface in the 2nd Embodiment of this invention. It is a flowchart which shows the detail of the extraction process of the adjustment image area | region of step S406 in the 2nd Embodiment of this invention. It is a figure for demonstrating the area | region which belongs to the image data used as the object of the adjustment image area | region extraction process. It is a figure which shows the several set for adjusting a parameter with respect to four search ranges.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments to which the invention is applied will be described in detail with reference to the accompanying drawings.

  FIG. 1 is a diagram illustrating a hardware configuration of an image processing apparatus according to an embodiment of the present invention. As shown in FIG. 1, in the image processing apparatus according to the present embodiment, a display 102, a keyboard 103, and a mouse 104 are connected to a personal computer 101. The constituent elements of the personal computer 101 include a CPU 105, a RAM 106, a ROM 107, a data storage unit 108 such as a hard disk, and a display unit 109 for displaying image data on the display 102. These components are connected via a system bus 110 for transmitting and receiving data.

  FIG. 2 is a diagram illustrating a configuration of an image processing unit which is a main function of the image processing apparatus according to the present embodiment. In FIG. 2, reference numeral 201 denotes an image processing unit. The image processing unit 201 includes a user interface unit 202, an adjustment parameter reading unit 203, a recovery filter reading unit 204, a RAW image reading unit 205, a development processing unit 206, a recovery filter adjustment unit 207, an adjustment image region extraction unit 208, and a recovery processing unit. 209, an image display unit 210 and a recovery filter output unit 211. These functions included in the image processing unit 201 are functions realized when a necessary program is expanded on the RAM 106 from the ROM 107 or the data storage unit 108 and the CPU 105 executes the program.

  The user interface unit 202 displays a user interface on the display 102. The adjustment parameter reading unit 203 reads the parameter changed by the user operation into the RAM 106. The recovery filter reading unit 204 reads the recovery filter from the ROM 107 or the data storage unit 108 into the RAM 106. The RAW image reading unit 205 reads RAW image data (hereinafter simply referred to as image data) from the ROM 107 or the data storage unit 108 into the RAM 106. The development processing unit 206 performs development processing of image data. The recovery filter adjustment unit 207 adjusts the recovery filter. The adjustment image area extraction unit 208 extracts an adjustment image area described later. A recovery processing unit 209 performs image data recovery processing. The image display unit 210 displays the image data developed by the development processing unit 206. The recovery filter output unit 211 outputs the recovery filter to the data storage unit 108.

  FIG. 3 is a diagram illustrating an example of a user interface displayed by the user interface unit 202. Reference numeral 301 denotes a user interface. Reference numeral 302 denotes an entire image display unit for displaying an entire image. An adjustment image display unit 303 displays an adjustment image area. Reference numeral 304 denotes a recovery item selection button. Reference numeral 305 denotes an adjustment bar for the user to perform a recovery item adjustment operation. Reference numeral 306 denotes an apply button for applying the process. Reference numeral 307 denotes a cancel button. The adjusted image display unit 303 is a configuration serving as an application example of the presenting means of the present invention.

  FIG. 4 is a flowchart showing an image processing method executed by the image processing apparatus according to this embodiment. In step S <b> 401, the RAW image reading unit 205 reads image data into the RAM 106. In step S <b> 402, the recovery filter reading unit 204 reads the recovery filter into the RAM 106. In step S403, the development processing unit 206 performs the development process on the image data read in step S401 using the recovery filter read in step S402. In step S404, the image display unit 210 displays the image data developed in step S403 on the entire image display unit 302 in FIG.

  The user operates the button corresponding to the recovery item to be adjusted from the recovery item selection button 304. In response, in step S405, the recovery filter adjustment unit 207 selects a recovery item corresponding to the operated button. In step S406, the adjusted image area extraction unit 208 extracts an adjusted image area suitable for the recovery item selected in step S405 from the image data. Next, the user operates the adjustment bar 305 to adjust the parameters. In response, in step S407, the recovery filter adjustment unit 207 adjusts the recovery filter according to the adjusted parameter. Step S406 is a processing example of the extraction means of the present invention, and step S407 is a processing example of the adjustment means of the present invention. Step S405 is a processing example of the selection means of the present invention.

  In step S408, the development processing unit 206 performs the development process on the image data of the adjusted image area extracted in step S406, using the recovery filter adjusted in step S407. In step S409, the recovery filter adjustment unit 207 determines whether the cancel button 307 has been pressed. If the cancel button 307 has not been pressed, the process proceeds to step S410. On the other hand, when the cancel button 307 is pressed, the process ends. In step S410, the recovery filter adjustment unit 207 determines whether the apply button 306 has been pressed. If the apply button 306 has been pressed, the process proceeds to step 411. On the other hand, if the apply button 306 has not been pressed, the process returns to step S405. In step S411, the recovery filter adjustment unit 207 calculates the recovery filter of the all-image display unit 302 in FIG. 3 based on the parameter adjusted in step S407. In step S412, the recovery filter output unit 211 outputs the recovery filter calculated in step S411 to the data storage unit 108.

Next, the development processing in step S403 and step S408 will be described in detail with reference to the flowchart of FIG. FIG. 5 is a flowchart showing details of the development processing. In step S501, the development processing unit 206 performs white balance processing on the image data. In step S502, the development processing unit 206 performs a demosaicing process on the image data that has been subjected to the white balance process in step S501. In step S503, the development processing unit 206 determines whether to perform image data recovery processing. When the recovery process is performed, the process proceeds to step S504. On the other hand, when the recovery process is not performed, the process proceeds to step S505. In step S504, the development processing unit 206 performs image data recovery processing as shown in Expression 2 using the recovery filter read in step S402 of FIG. 4 or the recovery filter corresponding to the adjusted parameter.
S = O * R (Formula 2)
However, R is a recovery filter, O is degraded image data, S is image data after recovery, and * is a convolution integral. Step S504 is a processing example of the recovery means of the present invention.

  In step S505, the development processing unit 206 performs noise reduction on the image data after the demosaicing process in step S502 or the restored image data. In step S506, the development processing unit 206 performs sharpness processing on the image data after noise reduction. In step S507, the development processing unit 206 converts the image data after the sharpness processing into RGB image data such as sRGB and AdobeRGB. In step S508, the development processing unit 206 performs gamma processing on the RGB image data.

  Next, the recovery item selected in step S405 will be described in detail with reference to FIG. FIG. 6 is a diagram showing a table in which recovery items to be selected, recovery methods, and adverse effects due to manufacturing variations are associated with each other. In FIG. 6, “resolution feeling”, “missing”, “color blur”, and “asymmetrical aberration” are illustrated as recovery items to be selected.

  The “resolution” is mainly due to the high-frequency component of the subject. The recovery of the resolution in the recovery process is a process for recovering the one in which the high frequency component has decreased when light passes through the lens. At this time, if the deterioration is larger than expected due to manufacturing variations, the recovery will be insufficient. On the other hand, when the decrease is small, over-recovery occurs and image quality degradation such as undershoot and overshoot occurs.

  The “missing” mainly adjusts the low to medium frequency components of the subject. In this case as well, if manufacturing variations occur as in the above case, insufficient recovery and excessive recovery occur. “Color blur” is caused by a phenomenon in which the blur spreads differently in R, G, and B colors (axial chromatic aberration) or in the center of the blur (magnification chromatic aberration). In this case, blurring can be eliminated by making the spread, center of blurring of R, G, B the same. Here, even if the manufacturing variation is recovered, the bleeding cannot be removed.

  “Asymmetrical aberration” is a phenomenon in which when a point is input on the high image height side, an image is not focused on the point due to phase fluctuations, and an asymmetric blur called coma aberration or astigmatism is generated. On the other hand, in the recovery process, the phase component is removed, resulting in a symmetric blur. However, when manufacturing variations occur, the phase component remains and cannot be symmetric.

  Next, the adjustment image region extraction process suitable for the recovery item in step S406 will be described in detail with reference to FIGS. FIG. 7 is a flowchart showing details of the adjustment image region extraction process suitable for the recovery item. FIG. 8 is a diagram showing a table in which recovery items are associated with search ranges of image data. FIG. 9 is a diagram for explaining a search range of image data. In FIG. 9, reference numeral 901 denotes all image data. The search range 902 is a low image height region of the entire image data 901, the search range 903 is a medium image height region of the entire image data 901, and the search range 904 is a high image height of the entire image data 901. It is an area. Reference numeral 905 denotes a search area for searching these search ranges.

  First, in step S701, the adjusted image area extraction unit 208 sets a search range corresponding to the recovery item selected by the user in step S405. At that time, the adjustment image region extraction unit 208 selects a search range corresponding to the recovery item selected by the user by referring to a table of contents in which the recovery item and the search range are associated as shown in FIG. is doing. That is, when the recovery item selected by the user is “resolution”, “low image height region to medium image height region” is selected as the search range. When the recovery item selected by the user is “missing”, “medium image height region” is selected as the search range. When the recovery item selected by the user is “color blur”, “image range in general” is selected as the search range. When the recovery item selected by the user is “asymmetrical aberration”, “high image height region” is selected as the search range.

  In step S702, the adjusted image area extraction unit 208 sets an initial search area for the search range set in step S701. In step S703, the adjusted image area extracting unit 208 reads image data of the search area. In step S704, the adjusted image area extraction unit 208 calculates an evaluation value of the search area. In step S705, the adjusted image region extraction unit 208 determines whether or not evaluation values have been calculated for all search regions included in the search range set in step S701. When evaluation values are calculated in all search areas, the process proceeds to step S707. On the other hand, if evaluation values have not been calculated for all search areas, the process proceeds to step S706. In step S706, the adjusted image area extraction unit 208 updates the search area. Until the evaluation values are calculated in all the search areas, the processes in steps S703 to S706 are repeated. In step S707, the adjustment image area extraction unit 208 extracts a search area indicating the maximum evaluation value among the evaluation values calculated in steps S703 to S706 as the adjustment image area.

  Next, the evaluation value calculation process in step S704 will be described in detail with reference to FIGS. FIG. 10 is a flowchart showing details of the evaluation value calculation processing. FIG. 11 is a diagram illustrating a table in which recovery items are associated with extraction frequencies.

  First, in step S1001, the adjusted image area extraction unit 208 performs development processing that does not include recovery processing on the image data in the search area read in step S703. In step S1002, the adjusted image region extraction unit 208 performs development processing including recovery processing on the image data. In step S1003, the adjusted image region extraction unit 208 performs a Fourier transform on each of the image data before recovery and the image data after recovery obtained in steps S1001 and S1002. In step S1004, the adjusted image region extraction unit 208 extracts a frequency component corresponding to the recovery item selected by the user from the image data after the Fourier transform. At that time, the adjustment image region extraction unit 208 selects the extraction frequency corresponding to the recovery item selected by the user by referring to the table of the contents in which the recovery item and the extraction frequency are associated as shown in FIG. is doing. That is, when the recovery item selected by the user is “resolution”, “high frequency component” is selected as the extraction frequency. When the recovery item selected by the user is “missing”, “low frequency component” is selected as the extraction frequency. When the recovery item selected by the user is “color blur”, “low frequency component” is selected as the extraction frequency. When the recovery item selected by the user is “asymmetrical aberration”, “phase component” is selected as the extraction frequency.

  In step S1005, the adjusted image region extraction unit 208 calculates a square error (evaluation value) for the frequency component extracted in step S1004. That is, in the present embodiment, the search area where the error of the image data before and after the recovery process is maximized is set as the adjusted image area.

  Next, the recovery filter adjustment processing in step S407 will be described in detail with reference to FIGS. FIG. 12 is a flowchart showing details of the adjustment process of the recovery filter. FIG. 13 is a diagram showing a table in which recovery items are associated with adjustment parameters.

  First, in step S1201, the recovery filter reading unit 204 reads a recovery filter corresponding to the adjusted image area extracted in step S406. In step S1202, the recovery filter adjustment unit 207 performs Fourier transform on the recovery filter read in step S1201. In step S1203, the recovery filter adjustment unit 207 adjusts the recovery filter after the Fourier transform in step S1202. Here, the recovery filter is adjusted with the parameter corresponding to the recovery item selected by the user. At that time, the recovery filter adjustment unit 207 selects a parameter corresponding to the recovery item selected by the user by referring to the table of the content in which the recovery item and the parameter are associated with each other as shown in FIG. That is, when the recovery item selected by the user is “resolution”, “amplitude characteristics” is selected as a parameter. When the recovery item selected by the user is “missing”, “amplitude characteristics” is selected as a parameter. When the recovery item selected by the user is “color blur”, “balance of RGB amplitude characteristics” is selected as a parameter. When the recovery item selected by the user is “asymmetrical aberration”, “phase characteristics” is selected as a parameter.

  FIG. 14 is a diagram for explaining a recovery filter adjustment method when “amplitude characteristics” is selected as a parameter and when “phase characteristics” is selected. That is, FIG. 14A is a diagram illustrating an adjustment method of the recovery filter when the “amplitude characteristic” parameter is selected, and FIG. 14B is the case where the “phase identification” parameter is selected. It is a figure which shows the adjustment method of this recovery filter. As described above, when the recovery item selected by the user is “resolution” or “missing”, “amplitude characteristics” is selected as a parameter. At this time, as shown in FIG. 14A, the recovery filter adjustment unit 207 changes the gain of the recovery filter according to the amount adjusted by the user with the adjustment bar 305. When the recovery item is “asymmetrical aberration”, “phase characteristics” is selected as the adjustment parameter. At this time, as illustrated in FIG. 14B, the recovery filter adjustment unit 207 changes the phase angle of the recovery filter according to the amount adjusted by the user with the adjustment bar 305. In step S1204, the recovery filter adjustment unit 207 performs inverse Fourier transform on the recovery filter adjusted in step S1203.

  Next, the recovery filter calculation process of the all-image display unit 302 in step S411 will be described. By performing the processing of steps S405 to S410, the restoration filter adjustment amount in the specific area (adjusted image area) can be calculated. By applying this to the recovery filter for the entire screen area, the recovery filter for the entire screen area can be adjusted. For example, if the amplitude characteristic of the recovery filter is increased by 1.5 times in a specific area, the recovery filter in the entire screen area is also increased by 1.5 times.

  In the present embodiment, since the user can operate the parameters for recovering the deterioration while confirming the image data, the deterioration of the image data can be recovered even if there is a difference in lens characteristics due to manufacturing variations. It becomes possible. In addition, since the effective adjustment image area is automatically presented when the user performs the recovery process, it is possible to reduce the load on the user during parameter adjustment.

  Next, a second embodiment of the present invention will be described. In the above-described first embodiment, the adjustment method in the case where the lens characteristics are different from the characteristics assumed due to manufacturing variations has been described. On the other hand, in the second embodiment, an adjustment method when the lens characteristic is ideally point-symmetric with respect to the center of the optical axis but the point-symmetry is impaired due to manufacturing variations will be described. To do.

  Since the hardware configuration and functional configuration of the image processing apparatus according to the second embodiment are the same as those of the first embodiment, the description thereof is omitted. This embodiment is different from the first embodiment in the user interface, the adjustment image region extraction method, and the restoration filter adjustment method. Hereinafter, it demonstrates in detail using FIGS. 15-18.

  FIG. 15 is a diagram illustrating an example of a user interface according to the second embodiment. Reference numeral 1501 denotes a user interface in the present embodiment. Reference numeral 1502 denotes an entire image display unit for displaying the entire image. An adjustment image display unit 1503 displays an adjustment image area. Reference numeral 1504 denotes a recovery item selection button. Reference numeral 1505 denotes an adjustment bar. Reference numeral 1506 denotes an apply button for applying a process. Reference numeral 1507 denotes a cancel button.

  FIG. 16 is a flowchart showing details of the adjustment image region extraction processing in step S406 in the second embodiment. FIG. 17 is a diagram for explaining a region belonging to image data that is a target of adjustment image region extraction processing. Reference numeral 1701 denotes all image data. Reference numeral 1702 denotes a low image height region. Reference numeral 1703 denotes a medium image height region. Reference numeral 1704 denotes a high image height region. Reference numeral 1705 denotes a first quadrant area. Reference numeral 1706 denotes a second quadrant area. Reference numeral 1707 denotes a third quadrant area. Reference numeral 1708 denotes a fourth quadrant region. The first quadrant region 1705 to the fourth quadrant region 1708 are application examples of the divided regions of the present invention.

  First, in step S1601, the adjusted image region extraction unit 208 sets an initial search range. More specifically, the adjusted image area extraction unit 208 sets the first quadrant area 1705. In step S1602, the adjusted image area extraction unit 208 sets an initial search area. In step S1603, the adjusted image area extraction unit 208 reads image data of the search area. In step S1604, the adjusted image area extraction unit 208 calculates an evaluation value. In step S1605, the adjusted image area extraction unit 208 determines whether or not evaluation values have been calculated for all search areas included in the search range. If evaluation values have been calculated for all search regions, the process proceeds to step S1607. On the other hand, if evaluation values have not been calculated for all search regions, the process proceeds to step S1606. In step S1606, the adjusted image area extraction unit 208 updates the search area. In step S1607, the adjusted image area extraction unit 208 determines whether or not the maximum evaluation value in the processes in steps S1602 to S1606 is equal to or greater than a threshold value. If the maximum evaluation value is equal to or greater than the threshold, the process proceeds to S1608. On the other hand, if the maximum evaluation value is smaller than the threshold, the process proceeds to step S1609. In step S1608, the adjusted image area extracting unit 208 displays the search area having the maximum evaluation value on the adjusted image display unit 1503 as the adjusted image area. In step S1609, the adjusted image region extraction unit 208 determines whether or not the processing of S1602 to S1608 has been performed for all search ranges (first quadrant region to fourth quadrant region). If the processes of S1602 to S1608 have been performed for all search ranges, the process ends. On the other hand, if the processes of S1602 to S1608 have not been performed for all search ranges, the process proceeds to step S1610. In step S1610, the adjusted image region extraction unit 208 updates the search range.

  In the second embodiment, adjustment image areas corresponding to four search ranges can be displayed, and parameter adjustment can be performed on each of the adjustment image areas. However, when the user performs parameter adjustment, the items to be adjusted become enormous. Therefore, as shown in FIG. 18, a plurality of sets for adjusting parameters in advance for the four search ranges are prepared, and the adjustment is performed only by the user selecting a desired set from the plurality of sets. Is possible.

  As described above, by using this embodiment, it is possible to perform parameter adjustment while reducing the user load even when the point symmetry in the screen is lost.

  The present invention can also be realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

  201: Image processing unit, 202: User interface unit, 203: Adjustment parameter reading unit, 204: Recovery filter reading unit, 205: Raw image reading unit, 206: Development processing unit, 207: Recovery filter adjustment unit, 208: Adjustment image Area extraction unit, 209: recovery processing unit, 210: image display unit, 211: recovery filter output unit

Claims (8)

Extraction means for extracting an image area corresponding to a recovery item of image data from the image data;
Adjusting means for adjusting a recovery filter according to the adjustment operation of the recovery item;
An image processing apparatus comprising: recovery means for performing recovery processing on the image area extracted by the extraction means by the recovery filter adjusted by the adjustment means.   The image processing apparatus according to claim 1, further comprising a presentation unit that presents the image area recovered by the recovery unit. A selection means for selecting the recovery item;
The image processing apparatus according to claim 1, wherein the extraction unit changes the image area to be extracted according to the recovery item selected by the selection unit.   The image processing apparatus according to any one of claims 1 to 3, wherein the extraction unit extracts, as the image area, an area in which an error of the image data before and after the recovery process is maximized.   5. The adjustment unit according to claim 1, wherein the adjustment unit performs a Fourier transform on the recovery filter and adjusts the recovery filter after the Fourier transform with an amplitude characteristic or a phase characteristic corresponding to the recovery item. The image processing apparatus according to item 1.   The extraction unit extracts the image region for each of a plurality of divided regions in the image data, and the recovery unit performs a recovery process on each image region extracted by the extraction unit. The image processing apparatus according to any one of claims 1 to 5. An image processing method executed by an image processing apparatus,
An extraction step of extracting from the image data an image region corresponding to a recovery item of the image data;
An adjustment step of adjusting a recovery filter according to the adjustment operation of the recovery item;
And a recovery step of performing a recovery process on the image area extracted in the extraction step by the recovery filter adjusted in the adjustment step. An extraction step of extracting from the image data an image region corresponding to a recovery item of the image data;
An adjustment step of adjusting a recovery filter according to the adjustment operation of the recovery item;
A program for causing a computer to execute a recovery step of performing a recovery process on the image area extracted in the extraction step by the recovery filter adjusted in the adjustment step.

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