Image capture device, image capture device control method, and program

Abstract

To provide an imaging apparatus that is capable of easily taking an image that effectively blurs a background.SOLUTION: A digital camera 100 generates a plurality of background-blurred images simulating a blurring degree of a background in a case of taking an image of a subject at different imaging distances d, on the basis of a preliminary taken image. The digital camera 100 sets an evaluation frame A to each of the background-blurred images, calculates a background blurring evaluation value E of each evaluation frame A, and reports information on an optimal subject position based on the background blurring evaluation value E.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to an imaging device, a control method for an imaging device, and a program. [Background technology]

[0002] An assist function has been proposed in which an imaging device such as a digital camera suggests to the photographer the optimal composition, including the position of the subject, when photographing a subject such as a person. A related technique is proposed in Patent Document 1. In Patent Document 1, the position of the subject area in a previously photographed image is moved, and the position of the subject area where the positional relationship between the subject area and background objects is on the golden division line is detected, and the subject position that will result in the optimal composition is notified to the photographer based on the position of the detected subject area.

[0003] Furthermore, when photographing subjects such as people, there is a need to capture portraits with effectively blurred backgrounds in addition to the composition. Photographing portraits with effectively blurred backgrounds requires consideration of not only the aperture value but also the combination of the distance from the photographer to the subject, the distance to the background, and the focal length. For this reason, photographing portraits with effectively blurred backgrounds is extremely difficult for beginners with little knowledge or experience in photography, and there is a demand for a system that allows even beginners to easily perform such photography. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-244249 Summary of the Invention [Problem to be solved by the invention]

[0005] In the technology of Patent Document 1 described above, the optimum subject position is detected only from the positional relationship between the subject region and the background region, and therefore it is not possible to detect the subject position taking into consideration the degree of blurring of the background.

[0006] An object of the present invention is to provide an imaging device, an imaging device control method, and a program that can easily capture an image with an effectively blurred background. [Means for solving the problem]

[0007] In order to achieve the above object, the imaging device of the present invention is characterized by comprising: a generation means for generating a plurality of simulation images that simulate the degree of background blur when a subject is photographed at different shooting distances, based on a preliminary photographed image generated by photographing the background without including the subject; a setting means for setting an evaluation frame for each of the plurality of simulation images; a calculation means for calculating an evaluation value of the degree of blur of the evaluation frame; and a notification means for notifying information regarding the subject position at which the degree of blur is optimal, based on the evaluation value of the degree of blur. [Effects of the Invention]

[0008] According to the present invention, it is possible to easily take a photograph with an effectively blurred background. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a diagram illustrating a configuration of a digital camera as an imaging apparatus according to an embodiment of the present invention. [Figure 2] 2 is a flowchart for explaining a series of steps when a photographer takes a picture of a subject using the digital camera of FIG. 1. [Figure 3] FIG. 2 is a diagram showing an example of a pre-captured image generated by the digital camera of FIG. [Figure 4] 2 is a diagram showing an example of an image displayed on the display unit of FIG. 1. FIG. [Figure 5] 2 is a diagram showing an example of a photographed image generated by the digital camera of FIG. 1. FIG. [Figure 6] 10 is a flowchart showing the procedure of an optimum subject position detection process executed by an optimum subject position detection unit in FIG. [Figure 7] FIG. 7 is a diagram showing an example of filter coefficients of a blur function used in the processing of step S601 in FIG. [Figure 8] FIG. 10 is a diagram illustrating an outline of distance information when photographing a person according to the present embodiment. [Figure 9] FIG. 7 is a diagram showing an example of a background blur image generated in step S601 of FIG. [Figure 10] FIG. 7 is a diagram for explaining the setting of the evaluation frame in step S602 of FIG. [Figure 11] FIG. 7 is a diagram for explaining calculation of a background blur evaluation value in step S603 of FIG. [Figure 12] FIG. 2 is a diagram for explaining the configuration of an evaluation framework in the present embodiment. [Figure 13] 10 is a flowchart showing the procedure of a blur amount evaluation value calculation process executed by an optimum subject position detection unit in FIG. [Figure 14] FIG. 14 is a diagram illustrating an example of a high-frequency component extraction filter used in step S1301 of FIG. [Figure 15] 10 is a flowchart showing the procedure of a color luminance evaluation value calculation process executed by the optimum subject position detection unit of FIG. [Figure 16] 10A and 10B are diagrams for explaining the setting of an evaluation frame based on a shooting distance and a focal length in the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0011] Fig. 1 is a diagram schematically illustrating the configuration of a digital camera 100 as an imaging apparatus according to an embodiment of the present invention. In Fig. 1, the digital camera 100 includes an imaging lens 101, an aperture 102, an imaging unit 103, an internal memory 104, a development processing unit 105, an optimum subject position detection unit 106, an optical information storage unit 107, a display unit 108, an external memory control unit 109, and an operation input unit 111. The imaging unit 103, the internal memory 104, the development processing unit 105, the optimum subject position detection unit 106, the optical information storage unit 107, the display unit 108, the external memory control unit 109, and the operation input unit 111 are connected to one another via a system bus 112.

[0012] The imaging lens 101 is a group of lenses including a zoom lens and a focus lens. The aperture 102 is used to adjust the amount of light incident through the imaging lens 101. The imaging unit 103 is composed of an imaging element such as a CMOS sensor that converts the light incident through the imaging lens 101 into an electrical signal, and an A / D converter that converts the analog signal output from the imaging element into a digital signal. The internal memory 104 is a storage device that temporarily stores the digital signal output from the imaging unit 103 (hereinafter referred to as "RAW image data") and post-development image data generated by the development processing unit 105. The internal memory 104 is composed of a volatile memory such as a DRAM.

[0013] The development processing unit 105 performs various image processing such as WB processing, noise reduction processing, and sharpness on the RAW image data stored in the internal memory 104 to generate developed image data. The generated developed image data is stored in the internal memory 104. The optimum subject position detection unit 106 uses the developed image data to calculate an optimum subject position that will provide effective background blur. Details of the processing by the optimum subject position detection unit 106 will be described later. The optical information storage unit 107 is a storage device that stores a blur function (PSF: Position Spread Function) that will be described later and is used by the optimum subject position detection unit 106. The optical information storage unit 107 is configured with a non-volatile memory such as a flash ROM.

[0014] The display unit 108 is a display device that displays developed image data and notifies the photographer of the detection results of the optimal subject position detection unit 106. The display unit 108 is composed of a display device such as an LCD. The external memory control unit 109 controls writing of RAW image data and developed image data held in the internal memory 104 to the external memory 110, and controls reading of data stored in the external memory 110 into the internal memory 104. The external memory 110 is a storage device that is detachable from the digital camera 100. For example, the external memory 110 is an SD card composed of non-volatile memory such as Flash memory. The operation input unit 111 is input means that the photographer uses to give various operation instructions to the digital camera 100, such as setting shooting conditions and displaying developed image data, and is composed of buttons, an electronic dial, a touch panel, etc.

[0015] Fig. 2 is a flowchart for explaining a series of steps that are taken when a photographer photographs a subject using digital camera 100 of Fig. 1. In the following, a case where a person is photographed as an example of the subject will be described.

[0016] In FIG. 2, first, in step S201, the photographer uses digital camera 100 to take a preliminary image at a location where he or she wishes to photograph a person. This causes digital camera 100 to generate a preliminary image. A preliminary image is an image generated by capturing an image of the surroundings of the shooting location without the presence of a person to be photographed. FIG. 3 shows an example of a preliminary image. The preliminary image is preferably captured using the wide-angle side of a zoom lens with a large aperture value so that a wide range and all areas of the image are in focus (deep focus). Using the generated preliminary image, optimal subject position detection unit 106 of digital camera 100 executes the optimal subject position detection process shown in FIG. 6, which will be described later, to calculate the optimal subject position, which is the subject position that will produce the optimal degree of blur.

[0017] Next, in step S202, the photographer checks information related to the optimum subject position displayed on display unit 108. For example, as information related to the optimum subject position, as shown in FIG. 4(a), display unit 108 displays, superimposed on the preliminary captured image, subject model 401 indicating the subject's position at which the degree of blur is optimum, shooting distance information 402 indicating the distance from the photographer to the subject position, and shooting angle of view 403. Furthermore, as information related to the optimum subject position, display unit 108 displays assumed shooting image 404 assuming shooting at the optimum subject position, as shown in FIG. 4(b).

[0018] Next, the photographer guides the person to be photographed to the position indicated by the subject model 401. Next, in step S203, the photographer sets the focal length of the zoom lens to the telephoto end and performs the actual photograph, that is, photographs the actual person. As a result, effective background blur equivalent to that of the intended photograph image 404 can be obtained, as shown in FIG. 5(a), for example. On the other hand, an example of a failed scene in which the present invention is not used is shown in FIG. 5(b). In FIG. 5(b), the background is not blurred, and high-resolution background such as branches and leaves are present around the person, which makes the photograph look bad.

[0019] FIG. 6 is a flowchart showing the procedure of the optimum subject position detection process executed by the optimum subject position detection unit 106 in FIG.

[0020] 6, first, in step S601, the optimum subject position detection unit 106 generates a plurality of background blur images (simulation images) based on the pre-captured images. The background blur images are images that simulate the degree of background blur when a subject such as a person is photographed at different shooting distances, for example, 1 m, 5 m, and 10 m, at the telephoto end of the zoom lens with the minimum aperture value. If the pre-captured image is Iin, the background blur image Iout is calculated using the following equation (1). Iout(x,y)=Iin(x,y)×PSF(x,y) …(1)

[0021] Here, PSF denotes a blurring function. x and y respectively denote the horizontal and vertical pixel positions in the image. The blurring function PSF is expressed by a two-dimensional filter kernel as shown in FIG. 7. The blurred image Iout is calculated as a result of convolution integral of the preliminary captured image Iin and the blurring function PSF at each pixel position (x, y). Note that, hereinafter, as shown in FIG. 8, the distance from the photographer to the subject (person) is defined as the shooting distance d, and the distance from the photographer to the background is defined as the background distance D. In this embodiment, a blurring function PSF with different coefficients is used for each pixel position of the preliminary captured image based on the shooting distance d and the background distance D.

[0022] Fig. 9 is a diagram showing an example of a background blur image generated in step S601 of Fig. 6. Generally, the closer the shooting distance d, that is, the greater the distance between the subject and the background, the greater the degree of background blur. The coefficients of the blur function PSF are stored in optical information storage unit 107 for a finite number of combinations (discrete points) of shooting distance d and background distance D, and in step S601, the coefficients of the blur function PSF for conditions closest to the actual shooting conditions are used.

[0023] The background distance D is calculated for each pixel based on the amount of defocus detected using an image sensor with a structure in which the unit pixel is divided. For example, the unit pixel of the image sensor is divided into two sub-pixels, and the amount of defocus is detected based on the correlation between the image signal waveforms obtained from both sub-pixels, and the distance to the subject is calculated based on the detection result.

[0024] Next, in step S602, the optimum subject position detection unit 106 sets an evaluation frame for each of the plurality of background blur images generated in step S601, based on the photographing angle of view on the telephoto side of the zoom lens.

[0025] FIG. 10 is a diagram illustrating the setting of the evaluation frame in step S602 of FIG. 6. FIG. 10(a) is an example of the setting of the evaluation frame when the shooting distance d is 1 m. The frame A in the figure is the evaluation frame, and indicates the range (shooting angle of view) captured when the shooting distance d is 1 m at the telephoto end of the zoom lens. The black portion B in the frame indicates the person area representing a person whose shooting distance d is 1 m. When the shooting distance d is 1 m, as shown in FIG. 10(a), the evaluation frame A is almost entirely occupied by the person's face area. Thus, in this embodiment, when the evaluation frame A is set, the person area is set within the evaluation frame A based on the shooting distance d. FIG. 10(b) is an example of the setting of the evaluation frame when the shooting distance d is 5 m. Compared to when the shooting distance d is 1 m, the shooting angle of view is smaller, and the proportion of the face in the person area B within the evaluation frame A is smaller, so that the upper half of the person's body is included. FIG. 10(c) is an example of the setting of the evaluation frame when the shooting distance d is 10 m. When the shooting distance d is 10 m, the size of the evaluation frame A becomes even smaller than when the shooting distance d is 5 m, and the entire body of the person comes to be included within the evaluation frame A.

[0026] In this embodiment, the size of the evaluation frame A and information on the person area are also stored in the optical information storage unit 107 at discrete points relative to the shooting conditions, similar to the blur function PSF, and the conditions that are closest to the actual shooting conditions are referenced.

[0027] Next, in step S603, the optimum subject position detection unit 106 calculates the background blur evaluation value E (evaluation value of the degree of blur) of the evaluation frame A for each of the multiple background blur images corresponding to each shooting distance d. In calculating the background blur evaluation value E, as shown in FIGS. 11(a) to 11(c), the evaluation frame A is shifted horizontally in the background blur image at each shooting distance d, and the background blur evaluation value E is calculated for each position of the evaluation frame A. The position of the evaluation frame A with the highest background blur evaluation value E and the shooting distance d of the background blur image at which the evaluation frame A is set are determined as the optimum subject position. In addition, the background blur evaluation value E is calculated by multiplying the blur amount evaluation value E by the blur amount evaluation value E. BOKE and color luminance evaluation value E CY This is the sum of the above values.

[0028] Blur evaluation value E BOKE is calculated based on the high-frequency components of the luminance of blocks belonging to either the background region or the boundary region of the evaluation frame A, that is, the edge and noise components. The boundary region is the region that forms the boundary between the background region and the person region. The blur amount evaluation value E BOKE In the example, the fewer high-frequency components there are in the entire background region, the more smoothly the background is blurred, and a higher evaluation value is set.

[0029] Color brightness evaluation value E CY is calculated based on the variance of the color components and the variance of the luminance components in the entire background region, which are calculated from the average values ​​of the color components and the average values ​​of the luminance components of the blocks belonging to the background region of the evaluation frame A. CY In the example, the smaller the variance values ​​of the color components and the luminance components, the more uniform the background color and luminance are, and the more smoothly blurred the image is overall, and a higher evaluation value is set. The optimum subject position detection unit 106 executes the blur amount evaluation value calculation process shown in FIG. 13 to calculate the blur amount evaluation value E BOKE and executes the color luminance evaluation value calculation process shown in FIG. 15 to obtain the color luminance evaluation value E CY In the blur amount evaluation value calculation process and the color luminance evaluation value calculation process, the evaluation frame A is divided into a plurality of blocks as shown in FIG.

[0030] FIG. 13 is a flowchart showing the procedure of the blur amount evaluation value calculation process executed by the optimum subject position detection unit 106 in FIG.

[0031] In the blur evaluation value calculation process, first, the optimum subject position detection unit 106 calculates the blur evaluation value E BOKE Variable E for calculating BOKE_TEMP is cleared to 0. Next, the optimum subject position detection unit 106 identifies one block from among the multiple blocks included in the evaluation frame A. In step S1301, the optimum subject position detection unit 106 applies an edge extraction filter as shown in FIG. 14 to the luminance components of all pixel values ​​in the identified block, and extracts the high-frequency component E HNext, in step S1302, the optimum subject position detection unit 106 extracts the extracted high frequency component E H The block blur evaluation value E BOKE_1BLK is calculated using the following formula (2). E BOKE_1BLK =K×(P _NUM / ΣE H ) …(2)

[0032] Here, K is a blur amount conversion coefficient. In this embodiment, a fixed value is set as the blur amount conversion coefficient, regardless of the shooting distance d or the position of the evaluation frame A. P _NUM is the number of pixels in a specified block. H is the integration result of the high frequency components in one identified block. Next, in step S1303, the optimum subject position detection unit 106 determines whether or not the identified block belongs to the background region.

[0033] In step S1303, if it is determined that the identified block belongs to the background region, the optimum subject position detection unit 106 proceeds to step S1304. In step S1304, the optimum subject position detection unit 106 calculates the block blur amount evaluation value E BOKE_1BLK to variable E BOKE_TEMP Next, the optimum subject position detecting unit 106 proceeds to step S1307, which will be described later.

[0034] If it is determined in step S1303 that the identified block does not belong to the background area, the optimum subject position detection unit 106 proceeds to step S1305. In step S1305, the optimum subject position detection unit 106 determines whether the identified block belongs to a boundary area.

[0035] If it is determined in step S1305 that the identified block does not belong to the boundary area, the optimum subject position detection unit 106 proceeds to step S1307, which will be described later. In other words, if the identified block does not belong to either the background area or the boundary area, the block blur amount evaluation value E calculated in step S1302 BOKE_1BLK But the variable EBOKE_TEMP is not added to.

[0036] In step S1305, if it is determined that the identified block belongs to a boundary area, the optimum subject position detection unit 106 proceeds to step S1306. BOKE_1BLK Then, the optimum subject position detection unit 106 proceeds to step S1304. In step S1304, the weighted block blur evaluation value E BOKE_1BLK is the variable E BOKE_TEMP In this way, in this embodiment, the variable E BOKE_TEMP The block blur evaluation value E of the block belonging to either the background region or the boundary region among all the blocks constituting the evaluation frame A is BOKE_1BLK Only included.

[0037] Next, in step S1307, the optimum subject position detection unit 106 calculates the block blur evaluation values ​​E BOKE_1BLK It is determined whether the calculation of

[0038] In step S1307, the block blur evaluation value E of any block included in the evaluation frame A is calculated. BOKE_1BLK If it is determined that the calculation of the block blur amount evaluation value E has not been completed, the optimum subject position detection unit 106 identifies another block from among the multiple blocks included in the evaluation frame A. The other block is BOKE_1BLK In step S1307, the block blur evaluation values ​​E of all the blocks included in the evaluation frame A are calculated. BOKE_1BLK If it is determined that the calculation of has been completed, the optimum subject position detecting unit 106 proceeds to step S1308.

[0039] In step S1308, the optimum subject position detection unit 106 performs normalization processing. Specifically, the optimum subject position detection unit 106 calculates E BOKE_TEMPLet N be the total number of blocks in the background and border regions. B Divide by to get the blur evaluation value E BOKE Calculate. E BOKE =E BOKE_TEMP / N B …(3)

[0040] Thereafter, the optimum subject position detection unit 106 ends the blur amount evaluation value calculation process.

[0041] FIG. 15 is a flowchart showing the procedure of the color luminance evaluation value calculation process executed by the optimum subject position detection unit 106 of FIG.

[0042] In the color luminance evaluation value calculation process, the optimum subject position detection unit 106 calculates the average value Y BA (n) and the average value of the luminance component C BA (n) of the blocks belonging to the background region, where n is the block number of the block belonging to the background region. Next, in step S1502, the optimum subject position detection unit 106 calculates the average color value Y AVE and the average brightness value C AVE where N is the number of blocks that belong to the background region.

[0043]

number

[0044] Next, in step S1503, the optimum subject position detection unit 106 calculates the variance Y D and the variance value of the luminance component C D are calculated respectively.

[0045]

number

[0046] Next, in step S1504, the optimum subject position detection unit 106 calculates the color luminance evaluation value E CY Calculate. E CY =K Y / Y D +K C / C D …(8)

[0047] Here, the weighting factor K Y , K. C are conversion coefficients for adjusting the weights of the evaluation values ​​of the color components and luminance components, respectively. In this embodiment, the weighting coefficients K Y , K. C A fixed value is set as the color luminance evaluation value E, regardless of the shooting distance d or the position of the evaluation frame A. CY After calculating the blur evaluation value E, the optimum subject position detection unit 106 ends the color luminance evaluation value calculation process. Next, the optimum subject position detection unit 106 calculates the blur evaluation value E using the following equation (9): BOKE and color luminance evaluation value E CY are added together to calculate the background blur evaluation value E. E=E BOKE +E CY …(9)

[0048] The optimum subject position detection unit 106 calculates a background blur evaluation value E of the evaluation frame A for each of a plurality of background blur images corresponding to each shooting distance d. Furthermore, the optimum subject position detection unit 106 calculates a background blur evaluation value E for each position of the evaluation frame A while shifting the evaluation frame A horizontally for the background blur images at each shooting distance d. In this manner, in this embodiment, a plurality of background blur evaluation values ​​E are calculated for different shooting distances d and different positions of the evaluation frame A. The optimum subject position detection unit 106 determines the combination of the shooting distance d and the position of the evaluation frame that has the largest evaluation value among the plurality of calculated background blur evaluation values ​​E as the optimum subject position.

[0049] 6, in step S604, optimum subject position detection unit 106 notifies information related to the optimum subject position. Specifically, optimum subject position detection unit 106 causes display unit 108 to display a superimposed image in which subject model 401, shooting distance information 402, and shooting angle of view 403 are superimposed on the preliminary captured image, as shown in FIG. 4(a), based on the shooting distance d and the position of evaluation frame A determined to be the optimum subject position. Furthermore, optimum subject position detection unit 106 generates assumed photographing image 404 by superimposing a person area corresponding to subject model 401 on the image of evaluation frame A at the position determined to be the optimum subject position, and causes display unit 108 to display assumed photographing image 404.

[0050] In this case, for example, the screen of the display unit 108 may be divided into two and the superimposed image and the assumed photographing image 404 may be displayed, or the superimposed image may be further superimposed on the assumed photographing image 404 and displayed. Furthermore, the superimposed image and the assumed photographing image 404 may be switched between and displayed by a predetermined user operation. Furthermore, the superimposed image or the preliminary photographing image may be displayed together with a so-called live view image photographed in real time. In this case, too, the display unit may be divided and displayed together, one may be superimposed on the other, or the two may be switched between and displayed by a predetermined user operation.

[0051] Furthermore, the subject model 401, shooting distance information 402, and shooting angle of view 403 may be superimposed on the live view image. In this case, the subject model 401, shooting distance information 402, and shooting angle of view 403 are superimposed on the live view image according to the coordinates at which the subject model 401, shooting distance information 402, and shooting angle of view 403 are superimposed in the preliminary captured image. This display process enables the photographer to more easily guide the person who will be the subject to an appropriate position. Thereafter, the optimum subject position detection process ends.

[0052] After the optimal subject position detection unit 106 notifies the user of information about the optimal subject position, the image currently being captured and the preliminary captured image may differ significantly due to a significant change in the subject or angle of view. In this case, a warning may be issued to the user, or guidance may be displayed recommending that the user retake the preliminary capture. The change in the image may be identified based on, for example, the difference in histogram between the image currently being captured and the preliminary captured image.

[0053] According to the above-described embodiment, a plurality of background blur images are generated based on the preliminary captured images, simulating the degree of background blur when a subject is photographed at different shooting distances d. An evaluation frame A is set for each of the plurality of background blur images, a background blur evaluation value E for each evaluation frame A is calculated, and information regarding the optimal subject position is notified based on the background blur evaluation value E. This allows even a beginner with little knowledge or experience in photography to easily photograph an image with an effectively blurred background.

[0054] Furthermore, in the above-described embodiment, in generating a background blur image, a blur function PSF is used whose coefficient varies for each pixel position constituting the preliminary captured image based on the shooting distance d and the background distance D. This makes it possible to generate a background blur image that corresponds to the shooting distance d and the background distance D.

[0055] In the above-described embodiment, the subject is a person, so that it is easy to photograph the person with the background effectively blurred.

[0056] In the above-described embodiment, when the shooting distance d is a first distance (e.g., 1 m), a person area where the proportion of the person's face is dominant is set in evaluation frame A. When the shooting distance d is a second distance (e.g., 5 m) that is longer than the first distance, a person area that includes the person's upper body is set in evaluation frame A. When the shooting distance d is a third distance (e.g., 10 m) that is longer than the second distance, a person area that includes the person's entire body is set in evaluation frame A. This allows processing of the boundary between the background area and the person area to be performed, simulating actual shooting.

[0057] In the above-described embodiment, the blur evaluation value E BOKE is calculated based on the high-frequency components of luminance extracted from the blocks belonging to the background region in the evaluation frame A and the high-frequency components of luminance extracted from the blocks belonging to the boundary region. As a result, the evaluation result of whether the background is smoothly blurred in the background region and boundary region of the evaluation frame A is calculated as the blur amount evaluation value E BOKE can be reflected in.

[0058] In the above-described embodiment, a larger weight is assigned to the boundary region in the evaluation frame A than to the background region, and the blur evaluation value E BOKE This allows the evaluation value to be set lower for high-frequency components around the person, that is, when there is an object that gets in the way of the person, and thus makes it possible to avoid failure cases such as those shown in Figure 5(b).

[0059] In the above-described embodiment, the color luminance evaluation value E CY is calculated based on the variance values ​​of the color components and the variance values ​​of the luminance components in the background region of the evaluation frame A. As a result, the evaluation result of whether the background region of the evaluation frame A is smooth and blurred overall without unevenness in color or luminance is expressed as the color luminance evaluation value E CY can be reflected in.

[0060] In the above-described embodiment, in a background blur image at each shooting distance d, the evaluation frame A is shifted horizontally and a background blur evaluation value E is calculated for each position of the evaluation frame A. This makes it possible to detect a subject position that does not obstruct people within the same shooting distance d and that improves the impression of the photograph.

[0061] In the above-described embodiment, subject model 401 and shooting distance information 402 are displayed superimposed on the preparatory image based on information about evaluation frame A with the highest background blur evaluation value E. This allows even a beginner with little knowledge or experience in photography to easily guide the person who will be the subject to a subject position that will provide the optimum degree of blur.

[0062] In the embodiment described above, the assumed image 404, which is assumed to be taken when photographing at the optimum subject position, is displayed. This allows the photographer to know the composition and the degree of background blur when photographing at the optimum subject position before actually photographing.

[0063] In the above-described embodiment, the preliminary image is an image generated by capturing the surroundings of the shooting location using the wide-angle side of the zoom lens. The size of the evaluation frame is set based on the shooting angle of view at the focal length of the zoom lens. In other words, the image is captured using optical information to maximize the lens performance. This allows for the generation of a high-quality image without the degradation of image quality near the boundary between the person area and the background area that occurs when blurring the background using an image processing application after capture.

[0064] Although the present invention has been described using the above-mentioned embodiment, the present invention is not limited to the above-mentioned embodiment. For example, the present invention may be applied to photographing subjects other than people.

[0065] Furthermore, in the above-described embodiment, by considering multiple focal lengths in addition to the telephoto end of the lens when setting the evaluation frame, the photographer may be notified of more optimal subject position candidates. For example, in step S602 of FIG. 6 described above, the focal length is fixed to the telephoto end of the zoom lens, so the size of the evaluation frame is uniquely determined for each shooting distance. In contrast, the background blur image is evaluated using multiple sizes of evaluation frame A for each shooting distance.

[0066] Figure 16 shows an example of evaluation frame A and person area B when the focal length is changed to 70 mm (telephoto end), 50 mm, and 24 mm (wide-angle end) when the shooting distance d is 1 m, 5 m, and 10 m. As the focal length becomes shorter, the shooting angle of view becomes larger, and so the size of the evaluation frame becomes larger. At the wide-angle end, evaluation frame A matches the shooting angle of view of the preliminary shot, so only one pattern of evaluation value is calculated.

[0067] In this way, by considering multiple focal lengths rather than just the telephoto end of the lens when evaluating the optimal subject position, it becomes possible to evaluate a larger number of optimal subject positions. By displaying multiple optimal subject position candidates and allowing the photographer to select their preferred subject position, particularly when there is a restricted area such as a road around the shooting position, the photographer can avoid that candidate and select an effective shooting position from multiple candidates.

[0068] In this embodiment, the present invention is applied to a digital camera having a lens with a zoom function, but the present invention is not limited to this configuration and may also be applied to a digital camera having a lens without a zoom function. In a digital camera having a lens without a zoom function, a preliminary shot image is acquired using the panoramic shooting mode in step S201 described above.

[0069] When shooting using the panoramic shooting mode, a single preliminary image is generated by combining multiple images taken by the photographer moving the camera up, down, left, and right, similar to the function installed in a typical digital camera. The preliminary image is used to execute the optimal subject position detection process shown in FIG. 6. In this case, the evaluation frame is set in step S602 based on the shooting angle of view when the panoramic shooting mode is not used, and the background blur image is evaluated. By using the panoramic shooting mode in this way, the same effects as those of the above-described embodiment can be achieved even with a digital camera having a lens without a zoom function.

[0070] In this embodiment, the configuration may be such that the user can set the calculation of the optimum subject position to ON / OFF.

[0071] The present invention can also be realized by supplying a program that realizes one or more functions of the above-described embodiments to a system or device via a network or a storage medium, and having one or more processors in the computer of the system or device read and execute the program.The present invention can also be realized by a circuit (e.g., ASIC) that realizes one or more functions.

[0072] Furthermore, the above-described embodiments are merely specific examples intended to aid in understanding the present invention, and are not intended to limit the present invention in any way. All embodiments falling within the scope defined by the claims are encompassed by the present invention. [Explanation of symbols]

[0073] 100 digital cameras 106 Optimal subject position detection unit 108 Display section 401 Subject Model 402 Shooting distance information 404 Expected image A rating category D Background distance d Shooting distance E Background blur evaluation value E BOKE Blur evaluation value E CY Color luminance evaluation value

Claims

1. a generating means for generating a plurality of simulation images that simulate the degree of background blur when the subject is photographed at different shooting distances, based on a preliminary photographed image that is generated by photographing the background without including the subject; a setting means for setting an evaluation frame for each of the plurality of simulation images; a calculation means for calculating an evaluation value of the blurriness of the evaluation frame; and notifying means for notifying information regarding a subject position at which the degree of blur is optimal based on the evaluation value of the degree of blur.

2. 2. The imaging device according to claim 1, wherein the generating means generates the plurality of simulation images using a blur function having a different coefficient based on a shooting distance and a background distance for each pixel position constituting the preliminary captured image.

3. 3. The imaging device according to claim 1, wherein the calculation means divides the evaluation frame into a plurality of blocks, and calculates the evaluation value of the degree of blur based on the blur amount evaluation value and the color luminance evaluation value calculated for each of the plurality of blocks.

4. 4. The imaging device according to claim 3, wherein the subject is a person.

5. a person area indicating a person that is distant from the photographer by the shooting distance used to generate the simulation image in which the evaluation frame is set is set in the evaluation frame; The imaging device according to claim 4 , wherein the plurality of simulation images include different portions of the person area included in the evaluation frame depending on the shooting distance.

6. 6. The imaging device according to claim 5, wherein the calculation means calculates the blur evaluation value based on high-frequency components of luminance extracted from blocks belonging to a background region in the evaluation frame and high-frequency components of luminance extracted from blocks belonging to a boundary region that is a boundary between the background region and the person region.

7. 7. The imaging device according to claim 6, wherein the calculation means calculates the blur evaluation value by weighting the boundary region more heavily than the background region in the evaluation frame.

8. 8. The imaging device according to claim 3, wherein the calculation means calculates the color luminance evaluation value based on a variance value of a color component and a variance value of a luminance component in a background region of the evaluation frame.

9. The imaging device according to any one of claims 1 to 8, characterized in that the calculation means calculates an evaluation value of the degree of blur of the evaluation frame for each position of the evaluation frame while shifting the evaluation frame horizontally in a simulation image for each shooting distance.

10. The imaging device according to any one of claims 1 to 9, characterized in that the notification means displays a subject model indicating the position of the subject and a distance from the photographer to the subject, superimposed on the preliminary captured image, based on information about the evaluation frame with the highest evaluation value of the degree of blur.

11. 11. The imaging device according to claim 10, wherein the notification means further displays an assumed image that is assumed to be taken when the image is taken at a subject position that provides the optimum degree of blur.

12. 10. The imaging apparatus according to claim 1, wherein the notification unit notifies the user of information regarding a plurality of subject positions that are candidates for selection by the user.

13. 13. The imaging device according to claim 1, wherein the preliminary captured image is an image generated by capturing an image of the surroundings of a shooting location with a wide-angle side of a zoom lens.

14. 14. The imaging device according to claim 13, wherein the size of the evaluation frame is set based on a photographing angle of view at a focal length of the zoom lens.

15. 13. The imaging device according to claim 1, wherein the preliminary captured image is an image generated by capturing an image of the surroundings of a shooting location using a panoramic shooting mode.

16. A control method for an imaging device, comprising: a generating step of generating a preliminary captured image by capturing a background without including the subject, and generating a plurality of simulation images based on the preliminary captured image, which simulate the degree of background blur when the subject is captured at different shooting distances; a setting step of setting an evaluation frame for each of the plurality of simulation images; a calculation step of calculating an evaluation value of the blurriness of the evaluation frame; and notifying information relating to a subject position at which the degree of blur is optimal, based on the evaluation value of the degree of blur.

17. A program for causing a computer to execute a control method for an imaging device, The method for controlling the imaging device includes: a generating step of generating a preliminary captured image by capturing a background without including the subject, and generating a plurality of simulation images based on the preliminary captured image, which simulate the degree of background blur when the subject is captured at different shooting distances; a setting step of setting an evaluation frame for each of the plurality of simulation images; a calculation step of calculating an evaluation value of the blurriness of the evaluation frame; and notifying information regarding a subject position at which the degree of blur is optimal, based on the evaluation value of the degree of blur.

Images