JP4400481B2 - Image processing device - Google Patents

Description

  The present invention relates to an image processing apparatus that detects and corrects a defective area included in an image displayed based on acquired image data.

  When printing an image taken by a digital camera or the like, image data stored in a recording medium such as an FD, a media card, or a CD-R is read and displayed on a monitor screen every predetermined number. In addition, an image photographed on a film is read as digital data by a film scanner, and is similarly displayed on a monitor screen every predetermined number. For each image displayed on the monitor screen, after performing various corrections such as color, density, red eye, and backlight so as to be an appropriate image, the number of prints is designated and print processing is performed (Patent Document 1, Patent Document 1). 2).

When setting the above correction processing, it is necessary to correct defective parts such as black spots that appear on the image due to dust or dirt adhering to the surface of the image sensor when replacing a pixel abnormality in a digital camera or a telephoto lens. There may be. For this reason, when such a defective part is included in the image, an operator can correct an image one by one while specifying the defective part displayed on the monitor screen, thereby obtaining an appropriate image. .
JP-A-9-281613 (released on October 31, 1997) JP 2004-038728 A (published February 5, 2004)

  However, the conventional image processing apparatus has the following problems.

  That is, the defect portion specified by the operator is likely to appear as the same shape in the same place in each image because the positions of abnormal pixels and dust that are the cause of occurrence are constant. However, the conventional image processing apparatus has a problem in that work efficiency is poor because a defect portion appearing at the same position over a plurality of images is specified one by one and the operator corrects the defect.

  An object of the present invention is to automatically detect a defective area appearing in an image due to pixel abnormality in a digital camera, dust attached to the surface of an image sensor, or the like, and an image that can be efficiently corrected to an appropriate image. It is to provide a processing apparatus.

  An image processing apparatus according to a first invention includes an image data acquisition unit, a pixel value extraction unit, a defect area determination unit, and a defect correction unit. The image data acquisition unit acquires a plurality of image data corresponding to a plurality of images. The pixel value extraction unit divides each image corresponding to the plurality of image data acquired by the image data acquisition unit into regions of a predetermined size, and the pixels of each pixel included in each region for each divided region Extract the value. The defective area determination unit determines that the area is a defective area when the areas having specific pixel values extracted by the pixel value extraction section are in the same place in a plurality of images. The defect correcting unit corrects all or part of the pixels included in the area determined as the defective area.

  Here, one image is divided into a plurality of regions of a predetermined size, and pixel values are extracted for each region. If an area having a certain pixel value has an area having the same pixel value at the same place over a plurality of images as compared with another image, this area is determined as a defective area.

  Normally, in a plurality of images taken using a digital camera or the like, dust or dirt is attached to the surface of the image sensor, or pixels are abnormal in a digital camera or scanner that acquires image data. In some cases, a defect area having the same shape appears at the same position over a plurality of images. At this time, in the method in which the operator designates the defect area one by one for each image and corrects it, there is a problem that the same work needs to be repeated many times and the work efficiency is very poor.

  Therefore, in the image processing apparatus of the present invention, a defect area that appears in an image due to dust adhering to the surface of an image sensor or pixel abnormality of a digital camera or the like appears in the same place in a plurality of (for example, one order) images. Paying attention to this, the defect area is automatically determined and corrected without any operator operation. Specifically, each pixel value is extracted in each region obtained by dividing each image into regions of a predetermined size. Then, for an area having a certain pixel value extracted, for example, when an area having the same pixel value exists in the same place as compared with another image within one order, this area is determined as a defective image.

  As a result, it is possible to automatically detect and correct a defective area that appears in the same place over a plurality of images due to dust adhering to the surface of the image sensor or pixel abnormality of a digital camera or the like. As a result, it is possible to significantly improve the working efficiency as compared with the conventional case and correct an image including a defective area to an appropriate image.

  An image processing device according to a second invention is the image processing device according to the first invention, and further includes a pixel value frequency calculation unit and a defect candidate region determination unit. The pixel value frequency calculation unit calculates the frequency of the pixel value in each region extracted by the pixel value extraction unit. The defect candidate area determination unit determines that this is a defect candidate area when the frequency of the pixel value calculated by the pixel value frequency calculation unit is equal to or greater than a predetermined threshold. The defect area determination unit compares the area determined as the defect candidate area by the defect candidate area determination unit with another image, and the area determined as the defect candidate area exists at the same position in the other image. Is determined as a defective area.

  Here, the defect area is determined based on the frequency of the pixel values extracted in the area of the image divided into a plurality of parts.

  Here, such a defective region has a characteristic that the frequency of a specific pixel value increases among pixel values indicating the color, luminance, shading, and the like of the pixels included therein.

  Therefore, in the image processing apparatus of the present invention, paying attention to the fact that the frequency of a specific pixel value is high in the defective area, the pixel value frequency of the pixel value extracted in the divided image area is set. A region that is calculated and whose frequency exceeds a predetermined threshold is determined as a defect candidate region. When the region determined as the defect candidate region is compared with another image (for example, a plurality of images included in one order) identified as a target for performing the defect region determination, the positions in the image match. Determines this area as a defective area.

  As a result, the determination, detection, and correction of the defective area can be performed automatically and with high accuracy.

  An image processing apparatus according to a third aspect is the image processing apparatus according to the first or second aspect, wherein the region having a predetermined size is one pixel.

  Here, the determination of the defective area for the acquired image is performed in units of one pixel.

  As a result, since the detailed defect area can be determined in units of one pixel, the defect area can be detected with higher accuracy. As a result, even when the defect area included in the image appears as a fine flaw, it can be reliably detected.

  An image processing apparatus according to a fourth aspect of the present invention is the image processing apparatus according to any one of the first to third aspects of the present invention, wherein if the image data is attached with additional information related to the shooting date and time, The region determination unit determines the defective region with reference to the additional information.

  Here, with reference to additional information related to the shooting date and time attached to the image data, a plurality of images whose shooting date and time intervals are equal to or smaller than a predetermined interval are determined as defective areas. That is, a short imaging interval means that when one image includes a defective area, there is a high possibility that the other image includes the same defective area.

  For this reason, it is possible to detect the defect area more efficiently and obtain an image in which the defect is appropriately corrected by determining the defect area for an image with a particularly short interval in one order.

  An image processing apparatus according to a fifth invention is the image processing apparatus according to any one of the first to fourth inventions, wherein the defect area determination unit is arranged between the defect candidate area and the surrounding area. The pixel values are compared to determine whether the area is a defective area.

  Here, when determining the defective area, the pixel value in the area is compared with the pixel value in the peripheral area, and a criterion for determining whether the frequency of the specific pixel value is higher than that in the peripheral area is also added. Determine the area. That is, it is an area where the frequency of specific pixel values tends to be higher in the defective area than in the peripheral area, and the frequency of specific pixel values is prominent compared with the pixel value in the peripheral area. Whether or not it is a criterion.

  Thereby, it is possible to detect a defect area appearing as a foreign substance in an image including a peripheral area with higher accuracy.

  Furthermore, in the image processing apparatus according to the present invention, the defective area determination unit may determine a defective area for a plurality of images included in one order.

  In this case, the defect area is determined for each order for which an image processing order has been received. Normally, defects that appear in an image due to pixel abnormalities in a digital camera or dust adhering to the surface of an image sensor appear continuously in the same place in images taken continuously for a relatively short time. Cheap.

  For this reason, it is possible to effectively correct a defect appearing at a common position in a plurality of images included in one order by determining a defect area with one order having a high possibility of being photographed as one unit. Can do.

  Note that the image of one order unit means a plurality of images included in one order when the print processing is requested.

  Furthermore, in the image processing apparatus according to the present invention, the defective area determination unit may determine a defective area for a plurality of designated images.

  Here, the above-described defect area determination is performed for a plurality of images designated by the operator.

  Thereby, for example, in the pre-judge screen where a plurality of images are displayed on the display screen, it is possible to automatically determine the defective area by designating only an image whose defect is clearly included in the image. . As a result, it is possible to obtain an image in which the defect area is detected more efficiently and the defect is corrected appropriately.

  Note that the designation of a plurality of images by the operator may be performed by designating the number of defective areas to be determined or by designating a specific image.

  Furthermore, the image processing apparatus according to the present invention may further include an image display unit that displays an image based on the image data.

  In this case, the image display unit displays an image based on the acquired image data. Thereby, for example, the operator can automatically specify a defect area by directly specifying an image including a defect such as a scratch for a plurality of images displayed on the display screen of the image display unit. .

  Therefore, compared to the conventional method in which the operator specifies and corrects the defect area for each image, the defect area is automatically detected and corrected only by specifying the image for determining the defect area. Therefore, workability can be greatly improved. In addition, since an image including a defect can be directly specified on the display screen, the defect area can be determined with higher accuracy.

  According to the image processing apparatus according to the first aspect of the present invention, it is possible to significantly improve the working efficiency as compared with the prior art and correct an image including a defective area to an appropriate image.

  According to the image processing apparatus according to the second aspect of the present invention, it is possible to automatically and accurately perform the defect area determination, detection and correction.

  According to the image processing apparatus of the third aspect of the present invention, even when a defective area included in the image appears as a fine scratch, it can be reliably detected.

  According to the image processing apparatus of the fourth aspect of the invention, it is possible to detect the defect area more efficiently and obtain an image in which the defect is appropriately corrected.

  With the image processing apparatus according to the fifth aspect of the present invention, it is possible to detect a defective area that appears as a foreign substance in an image including a peripheral area with higher accuracy.

  An image processing apparatus according to an embodiment of the present invention will be described below with reference to FIGS.

[Configuration of Entire Image Processing Apparatus 100]
An image processing apparatus 100 according to an embodiment of the present invention is an apparatus that performs photographic printing based on image data acquired from photographic film or storage media. As shown in FIG. 1, the image processing apparatus 100 includes a film scanner 1, an image data acquisition unit 2, an image data storage unit 3, an image processing unit 4, a defect candidate area position storage unit 5, a correction data storage unit 6, An imaging time information storage unit 7, an input operation unit 8, a display control unit 9 (monitor 9a), a print image data generation unit 10, an exposure unit 11, a paper magazine 12, a cutter 13, a development processing unit 14, and a drying processing unit 15 are provided. I have.

  The film scanner 1 scans a frame image formed on the developed photographic film F, and acquires digitized image data.

  The image data acquisition unit 2 acquires image data stored in a digital camera or other storage medium M.

  The image data storage unit 3 is a hard disk, a semiconductor memory, or the like, and stores the captured image data in units of orders.

  The image processing unit 4 includes various control blocks 41 to 46 formed by the CPU reading various programs stored in a storage unit such as a RAM (not shown), and performs various image processing on the image data. The functional blocks formed in the image processing unit 4 will be described in detail later.

  The defect candidate area position storage unit 5 stores the position in the image of the area determined as the defect candidate area by the defect candidate area determination unit 43 described later. Note that the position of the defect candidate area stored here serves as a determination reference when performing defect area determination described later.

  The correction data storage unit 6 stores the correction content set in the defect correction unit 45 described later, trimming, and special correction such as correction of color and density of the image, red-eye correction and backlight correction set in the image correction unit 46 described later. The reflected correction data is stored.

  The shooting time information storage unit 7 stores information related to the shooting time attached to each acquired image data in a state associated with each image data.

  The input operation unit 8 includes a keyboard, a mouse, and the like, and various operations, data input, commands, and the like are input while the operator confirms the monitor screen.

  The display control unit 9 controls the monitor 9a that displays an image based on the image data.

  The print image data generation unit 10 generates print image data to be transferred to the exposure unit 11. The print image data is subjected to image processing on the image data based on the image data stored in the image data storage unit 3 and the correction data stored in the correction data storage unit 6, and the print image Generate data.

  The exposure unit 11 prints and exposes an image on the surface of the photographic paper (photosensitive material) based on the print image data (corrected image data). The exposure unit 11 is a laser engine, and forms an image on the surface of the photographic paper by scanning and exposing a light-modulated laser beam.

  The paper magazine 12 accommodates long photographic paper wound in a roll shape. The long photographic paper drawn from the paper magazine 12 is cut into a print size by the cutter 13. The cut photographic paper is conveyed to an exposure position formed on the photographic paper conveyance path close to the exposure unit 11, and an image (latent image) is formed on the surface thereof. Thereafter, the photographic paper passes through the development processing unit 14 and the drying processing unit 15 and is subjected to predetermined processing, and then is discharged as a photographic print.

  The development processing unit 14 is disposed on the downstream side of the exposure unit 11 in the conveyance direction of the photographic paper, and includes processing layers storing a color development processing solution, a bleach-fixing processing solution, and a stable processing solution. Then, the exposed photographic paper is conveyed through these processing tanks in this order, whereby a desired photographic print image is formed on the surface of the photographic paper.

  The drying processing unit 15 dries the photographic paper that has passed through various processing solutions and has been subjected to the development processing in the development processing unit 14.

[Configuration of Image Processing Unit 4]
As shown in FIG. 1, the image processing unit 4 includes an image display unit 41, a histogram creation unit (pixel value extraction unit, pixel value frequency calculation unit) 42, a defect candidate region determination unit 43, a defect region determination unit 44, and defect correction. A unit 45 and an image correction unit 46 are provided. The image processing unit 4 performs the above-described color correction and the like and is included in the image when dust or the like adheres to the surface of the image sensor of the digital camera and a defective area such as a black spot is included in the image. The defect area is automatically detected and corrected.

  The image display unit 41 displays the acquired image data on the screen of the monitor 9a. When displaying each image based on the image data, thumbnail image data is generated and displayed in a predetermined display format. Thus, by generating thumbnail image data and displaying the thumbnail images on the monitor 9a, a plurality (six) images can be displayed as shown in FIG.

  The histogram creation unit 42 divides a plurality of images displayed on the screen of the monitor 9a into pixels, and creates a histogram indicating the frequency of pixel values at each pixel for each pixel. Specifically, as shown in FIG. 3, a frequency is created for each pixel value 0 to 250 in each pixel A (x1, y1) to create a histogram. In the graph shown in FIG. 3, the pixel value 0 side corresponds to black, and the pixel value 250 side corresponds to white. That is, the pixel A (x1, y1) shown in FIG. 3 is a pixel in which a black point corresponding to the defective area appears because the frequency on the black side close to the pixel value 0 protrudes. The pixel value for calculating the frequency for each pixel is, for example, a pixel value corresponding to any one of R, G, B data, a pixel value corresponding to an average value of R, G, B data, RGB3 Pixel values corresponding to the respective colors can also be used.

  The defect candidate area determination unit 43 determines whether any pixel value exceeds a predetermined threshold based on the histogram created by the histogram creation unit 42. Here, with reference to a large number of histograms formed for each pixel, if any pixel value exceeds a predetermined threshold in each histogram, the pixel corresponding to this histogram is detected as a defect candidate region. In the histogram shown in FIG. 3, pixel values exceeding the threshold value shown in the figure are present near the pixel value 0. For this reason, the pixel corresponding to this histogram is detected as a defect candidate area.

  The defect area determination unit 44 determines the position in the image of the area (pixel) detected as the defect candidate area in the defect candidate area determination unit 43 stored in the defect candidate area position storage unit 5 in other images. Is compared with the position of the detected pixel. In other images, if the positions of the defect candidate areas (pixels) match in each image, this is determined as a defective area. For example, when a defect candidate area is detected in the first image, it is compared with a defect candidate area detected in a plurality of images including the second image. Here, when the defect candidate region appearing in the first image appears in a common position (common pixel) in another image such as the second image, the defect from the first image to another A pixel in which a defect such as a black dot appears over a plurality of images is detected as a defect area.

  The defect correcting unit 45 causes the pixel determined as the defective region by the defective region determining unit 44 to have a normal pixel value by a technique such as interpolation processing based on image information of the peripheral region (peripheral pixel). The image data corresponding to the area is corrected. Here, the defect area is determined in units of one pixel. However, for example, when the defect area is determined in units of areas in which the defect candidate area includes a plurality of pixels of 3 × 3, The correction unit 45 only needs to make corrections so that only a pixel having a defect has an appropriate image.

  The image correction unit 46 corrects image data corresponding to each image by reflecting correction contents such as color correction set for each image stored in the correction data storage unit 6.

<Operations on the pre-judge screen>
Next, a description will be given of a procedure when the operator makes various settings on the pre-judge screen using each functional block included in the image processing unit 4 shown in FIG.

  In the image processing apparatus 100 of the present embodiment, when image data is acquired from the film scanner 1 or the image data acquisition unit 2, the image display unit 41 displays images corresponding to these on the monitor 9a in six sheets (see FIG. 2). . As a result, it is possible to determine in advance whether or not an appropriate photo print can be obtained by displaying an image on the monitor screen before shifting to the photo print creation process. Here, when it is necessary to correct an image or to correct a defective area, predetermined correction and setting input related to correction are performed.

  A print frame 22 representing a print area is displayed on the inner side of the image area 20 that is a setting input target among the six frames displayed on the monitor 9a. In the print size display area 23, the print size corresponding to the print frame 22 displayed on the image is displayed. Here, “C” (classical size) is displayed as the print size, but the print size setting can also be changed. The file name display area 25 displays an image file name. For example, when a frame image of a photographic film is read via the film scanner 1, the file name is automatically given.

  The color / density correction area 24 includes an area for inputting correction data for three colors Y, M, and C and an area for inputting density correction data. The operator can perform correction while viewing the image displayed on the display screen of the monitor 9a. The button 26 is used to activate a setting screen when performing special correction. For example, in the case where defect correction by the function of the image correction unit 46 or special correction such as red-eye correction is performed in addition to color / density correction, clicking this button 26 shifts to a one-frame enlarged screen. The number of prints display area 27 displays the number of images to be printed, and “1” is displayed as a default.

  Further, as described above, the presence / absence of a defect region such as a black spot appearing at the same position over a plurality of images can be confirmed on the pre-judge screen of the monitor 9a shown in FIG. In the pre-judge screen shown in FIG. 2, black spots (defect areas) A having almost the same shape appear as scratches at the same position in each image.

  In the image processing apparatus 100 of the present embodiment, black dots appearing at the same position over a plurality of images acquired (captured) by a digital camera in which dust or the like has adhered to the surface of the image sensor in this way are displayed as appropriate images (color, The above-described image processing unit 4 automatically performs an operation for correcting the image to a density or the like. Therefore, the operator only needs to set an image to be subjected to defect area determination.

  For example, the number of images to be subjected to defect area determination can be set in advance, and the defect area can be sequentially determined for the number of images when the image data is acquired. In this case, it is not necessary for the operator to determine on the pre-judge screen which image the defect area should be determined, so that the operator's work efficiency can be further improved.

  As shown in FIG. 4, it is also possible to set up an image to be a target for determining a defective area on the window by starting up a window from the pre-judge screen. Specifically, as shown in FIG. 4, the operator can select a desired one from four options. In FIG. 4, as options, first, all acquired images (that is, all images in one order), and second, a predetermined number of images from the one with the smallest frame number input in the number input box 31 are displayed. Third, an image designated by inputting a specific frame number in the text input box 32, and fourth, a photographing time attached to the image data stored in the photographing time information storage unit 7 is a time interval input box. The defect area can be determined for the image of the group that is equal to or less than the predetermined time interval input in 33.

  In this way, by determining the defect area as appropriate for the image specified by the operator, if it is known that all images are included in the pre-judge screen, or if only a specific image is defective. Even when a region is included, an accurate defect region can be determined.

  Finally, when the Yes button 34 is clicked, an image corresponding to the selected item is set as a target for determining a defective area. On the other hand, when the No button 35 is clicked here, the setting of the image to be subjected to the determination of the defective area is stopped.

<Defect area determination to correction process>
Here, steps from determination to correction of a defect area by the image processing apparatus 100 according to the present embodiment will be described with reference to FIG.

  First, in step S1, image data is acquired via the film scanner 1 and the image data acquisition unit 2. In step S <b> 2, the acquired image data is stored in the image data storage unit 3. When the pre-judge screen is displayed in step S3, it is confirmed in step S4 whether or not an image to be subjected to defect area determination is specified. Here, if an image to be determined is specified, the process proceeds to step S5. On the other hand, if not specified, the process proceeds to step S12, and the window shown in FIG. 4 is launched to specify the image to be determined. It should be noted that the image to be determined may be specified as a determination target for all images in one order unit, or the operator can select and specify a specific image. Furthermore, when the specification based on the shooting time information attached to each image data stored in the shooting time information storage unit 7 is selected, the shooting interval of each image is calculated based on the shooting time information, and the shooting interval is calculated. A group of images having a predetermined time interval or less is specified as a determination target.

  In step S5, a histogram is created by calculating the frequency of pixel values 0 to 250 for each pixel included in the image identified as a target for defect area determination. In step S6, based on the histogram created in step S5, it is determined whether there is a pixel whose frequency of a certain pixel value exceeds a predetermined threshold value. Here, when the frequency of a certain pixel value exceeds a threshold value, the pixel is determined as a defect candidate region. In step S7, the position of the pixel determined as the defect candidate area in the image is stored in the defect candidate area position storage unit 5, and the process proceeds to step S8. On the other hand, when the pixel value having a frequency exceeding the threshold is not included, it is determined that the defective area is not included in the image, and the process is ended.

  Next, in step S8, the position in the image of the defect candidate area similarly detected about the other image specified as determination object is compared. In step S9, as a result of the comparison, it is determined whether or not the defect candidate region is at the same position. Here, if a defect candidate area included in a certain image appears at the same position over a plurality of other images, it is determined as a defective area in step S10. On the other hand, if the defect candidate area appears at a different position compared to the plurality of other images, this is not determined as the defect area, and the process is terminated assuming that there is no defect area.

  In step S11, for the pixel determined to be a defective area in step S10, the defective area is corrected to an appropriate image with reference to the pixel value information in the peripheral pixels, and the process ends.

[Features of the image processing apparatus 100]
(1)
As shown in FIG. 1, the image processing apparatus 100 according to the present embodiment automatically detects defective areas that may be included in the corresponding images of image data acquired via the film scanner 1 and the image data acquisition unit 2. In order to detect and correct automatically, a histogram creation unit 42, a defect candidate region determination unit 43, a defect region determination unit 44, and a defect correction unit 45 are provided. Specifically, the histogram creation unit 42 divides the image displayed on the basis of the acquired image data for each pixel, and creates a histogram indicating the frequency of the pixel value in each pixel. Then, if there is a pixel having a pixel value equal to or greater than a predetermined threshold based on the created histogram, the defect candidate area determination unit 43 determines this as a defect candidate area. Subsequently, the defect area determination unit 44 compares the pixel determined as the defect candidate area with another plurality of images, and if the position of the defect candidate area in the image matches the other plurality of images, Are determined as defective areas. Finally, the defect correction unit 45 corrects the pixel (area) determined to be a defective area into an appropriate image with reference to the color, density, and the like of surrounding pixels.

  Here, in the case where dust adhered to the surface of the image sensor of the digital camera or a part of the pixels included in the film scanner 1 is abnormal, an image displayed based on the acquired image data includes black dots. Such a defect area may appear. Such a defective region often appears in a similar shape at the same position in a plurality of images taken during a comparative short time included in one order, for example. In particular, in an interchangeable lens digital camera, dust or the like adheres to the image sensor when the lens is replaced, and a plurality of images during photographing with the lens, that is, a plurality of images requested to be printed as one order. In an image, defective areas tend to occur continuously.

  In view of this, the image processing apparatus 100 according to the present embodiment detects a pixel with a prominent frequency of pixel values as a defect candidate region, and compares this defect candidate region with other images taken at close intervals. If a defect candidate area appears at the same position in the image of, this is detected as a defective area and corrected to an appropriate image.

  As a result, since the defect area can be automatically determined and corrected, it is compared with the conventional image processing apparatus in which the defect area included in each image is manually specified and corrected one by one by the operator. Thus, the operator can eliminate the defect area identification work and correction work, and the workability can be greatly improved.

(2)
In the image processing apparatus 100 of the present embodiment, a histogram that is referred to when determining a defective area is created for each pixel.

  As a result, even when a fine defect area in units of one pixel is included in the image, it can be detected with high accuracy by making a determination with reference to a histogram indicating the frequency of pixel values created for each pixel. Is possible.

(3)
In the image processing apparatus 100 according to the present embodiment, when a defect area is determined for a plurality of acquired images, the determination can be performed in units of one order.

  As a result, the defect area can be determined with high accuracy by determining the defect area in units of one order that are likely to be continuously photographed in a relatively short time.

(4)
In the image processing apparatus 100 according to the present embodiment, it is possible to determine a defect area for a specific image designated by the operator in the window 30 shown in FIG.

  Thereby, the defect area can be detected with high accuracy by determining the defect area only for the image including the defect area that can be visually confirmed on the pre-judge screen shown in FIG.

(5)
In the image processing apparatus 100 according to the present embodiment, when information on shooting time is attached to the acquired image data, the defect region is targeted for an image group in which the interval between these shooting times is shorter than a predetermined time interval. Judgment can be made.

  Here, for a plurality of image groups with short shooting intervals, if dust or the like has adhered to the surface of the image sensor of the digital camera that shot these images, a defective area may appear at the same position in the image High nature.

  For this reason, in the image processing apparatus 100 of the present embodiment, the shooting interval is calculated based on the shooting time information attached to the image data stored in the shooting time information storage unit 7 shown in FIG. The defect area is determined using a short image as a group of images. Thereby, a defective area can be detected with higher accuracy.

(6)
The image processing apparatus 100 according to the present embodiment includes a monitor 9a that displays an image to be displayed based on acquired image data.

  As a result, the operator can specify an image for which a defect area is to be determined while viewing a thumbnail image displayed on the monitor 9a.

  Although it seems that it is inferior in terms of improving workability at first glance that the operator identifies the image for determining the defective area while looking at the monitor 9a, the operator also identifies the location of the defective area. Compared with the conventional image processing apparatus, it is more preferable in that the workability can be improved and the detection accuracy of the defective area can be improved.

[Other Embodiments]
As mentioned above, although one Embodiment of this invention was described, this invention is not limited to the said embodiment, A various change is possible in the range which does not deviate from the summary of invention.

(A)
In the above-described embodiment, the position of the defect candidate area has been described by taking an example in which the defect area is determined by comparing over a plurality of images such as one order unit. However, the present invention is not limited to this.

  For example, in addition to the determination criteria in the above embodiment, when a region (pixel) determined to be a defective region is compared with a peripheral region (pixel) and the frequency of a specific pixel value is prominent, this is determined as a defect. The image processing apparatus may be determined as a region.

  In this case, even when the pixel value of the defective area approximates the background portion, the defective area can be determined and detected with high accuracy.

(B)
In the above embodiment, an example has been described in which a black spot that appears in an image due to dust or the like attached to the surface of the image sensor is determined and corrected as a defective area. However, the present invention is not limited to this.

  For example, a defective region appearing in an image when a pixel defect occurs in an image data acquisition unit such as a digital camera or a film scanner can be similarly performed by detecting a protrusion of a specific pixel value frequency.

(C)
In the above-described embodiment, the example in which the defect area is determined based on the presence or absence of the protruding pixel value frequency has been described. However, the present invention is not limited to this.

  For example, a binary image is created for a specific pixel value that is determined to be a defective area that appears due to dust or the like adhering to the image sensor, and the binary images are compared with each other to determine a portion where the images match. It can also be determined as a region.

(D)
In the above-described embodiment, an example has been described in which a defect candidate region is determined by creating a histogram of pixel values in each pixel. However, the present invention is not limited to this.

  For example, a pixel value (at least one of R, G, and B data or an average value of R, G, and B data) with respect to the position of pixel A (x1, y1) is the same over a plurality of image data You may determine with a defect area | region. That is, a method for directly determining a defect area without providing a step for determining a defect candidate area may be used.

(E)
In the above-described embodiment, an example has been described in which, when determining a defective area, an area (pixel) in which the frequency of any pixel value is higher than a predetermined threshold is determined as a defect candidate area. However, the present invention is not limited to this.

  For example, any one of R, G, and B data, or an area (pixel) in which the frequency of a specific pixel value corresponding to the average value of R, G, and B is higher than a predetermined threshold is determined as a defect candidate area. An image processing apparatus that performs defective area determination may be used.

  In this case, the final defective area is determined by comparing with the peripheral area described above, so that even when the background portion and the specific pixel value are approximated, the defective area is accurately determined and detected. It can be performed.

(F)
In the embodiment described above, the example of determining whether or not the region is a defective region has been described. However, the present invention is not limited to this.

  For example, instead of performing one pixel at a time, a defect region may be determined by creating a histogram relating to pixel values for each region in which nine pixels of 3 × 3 are taken as one unit. Even in this case, the same effect as described above can be obtained.

  In this case, when correcting the area determined to be a defective area, not all the pixels are corrected, but the defective area included in this area is further specified, and only the pixel including the defect is determined. You just have to fix it.

(G)
In the embodiment described above, an example in which an image to be a defect area determination target is specified by starting up the window 30 shown in FIG. 4 has been described. However, the present invention is not limited to this.

  For example, the image processing apparatus 100 may directly specify an image to be subjected to defect area determination on the pre-judge screen shown in FIG. In addition, an image processing apparatus that automatically determines a defective image region for all images corresponding to acquired image data without providing such a setting screen may be used.

(H)
In the above-described embodiment, an example has been described in which an image for determining a defect area can be specified on a pre-judge screen on which six thumbnail images are displayed. However, the present invention is not limited to this.

  For example, an image to be determined may be specified by selecting one image from six thumbnail images displayed on the pre-judge screen and confirming the presence or absence of a defective area on an enlarged screen obtained by enlarging one image. In this case, a fine defect region that is difficult to see on the pre-judge screen can be easily found and specified as a defect region determination target. Since the defect area is determined after the image having a high possibility of including the defect area is accurately identified, it is possible to perform the determination of the more accurate name defect area.

  However, as in the above-described embodiment, it is more preferable to automatically determine the defective area on the pre-judge screen or without using the pre-judge screen in terms of improving work efficiency.

(I)
In the embodiment described above, an example in which the histogram shown in FIG. 3 is created when calculating the frequency of pixel values included in an image in order to determine a defective area has been described. However, the present invention is not limited to the method of creating a histogram.

  For example, an image processing apparatus that can have the frequency of pixel values in each pixel as a data table without creating a histogram may be used.

(J)
In the above-described embodiment, an example has been described in which the position of a defect candidate area in an image is compared across a plurality of images when determining a defect area. However, the present invention is not limited to this.

  For example, by determining not only the position of the defect candidate area but also the shape of the defect area, it is possible to determine the defect area with higher accuracy.

  The addition of the shape of the defect area as a determination element is particularly effective when the unit for calculating the pixel value frequency is an area composed of a plurality of pixels, and the unit of the area for calculating the pixel value frequency is A decrease in determination accuracy in the case of a large value can be suppressed.

(K)
In the above embodiment, the case of creating a photographic print has been described, but the present invention is not limited to this.

  For example, the present invention can also be applied when performing a process of writing image data to a storage medium after correcting a defective area.

  The image processing apparatus of the present invention has an effect that it can accurately detect and automatically correct a defect area appearing in an image taken due to dust attached to the surface of an image sensor of a digital camera. Therefore, it can be widely applied to various image processing apparatuses that handle digital image data.

1 is a schematic diagram illustrating a configuration of an image processing apparatus according to an embodiment of the present invention. The figure which shows the pre-judge screen displayed on the monitor of the image processing apparatus of FIG. The figure which shows the histogram produced for every pixel in the image processing apparatus of FIG. The figure which shows the window screen for setting the target image which performs a defect area | region determination. The flowchart which shows the flow of a process from determination of a defect area | region to correction.

Explanation of symbols

1 Film scanner (image data acquisition unit)
2 Media reader (image data acquisition unit)
3 Image data storage unit 4 Image processing unit 5 Defect candidate area position storage unit 6 Correction data storage unit 7 Shooting time information storage unit 8 Input operation unit 9 Display control unit 9a Monitor (image display unit)
10 Print image data generation unit 11 Exposure unit 12 Paper magazine 13 Cutter 14 Development processing unit 15 Drying processing unit 20 Image area 22 Print frame 23 Print size display area 24 Color / density correction area 25 File name display area 27 Print number display area 30 Window 31 Number input box 32 Text input box 33 Time interval input box 41 Image display unit 42 Histogram creation unit (pixel value extraction unit, pixel value frequency calculation unit)
43 Defect candidate region determination unit 44 Defect region determination unit 45 Defect correction unit 100 Image processing apparatus

Claims (4)

An image data acquisition unit for acquiring a plurality of image data corresponding to a plurality of images;
Each image corresponding to the plurality of image data acquired by the image data acquisition unit is divided into regions of a predetermined size, and pixel values of each pixel included in each region are extracted for each of the divided regions. A pixel value extraction unit to
A defective region determination unit that determines the region as a defective region when the region having the specific pixel value extracted in the pixel value extraction unit is in the same place in the plurality of images;
A defect correcting unit that corrects all or part of the pixels included in the area determined to be the defective area;
Equipped with a,
When additional information regarding the shooting date and time is attached to the image data,
The defective area determination unit determines the defective area with reference to the additional information;
Image processing device. A pixel value frequency calculation unit that calculates the frequency of the pixel value in each region extracted by the pixel value extraction unit;
A defect candidate region determination unit that determines that the region having the pixel value frequency is a defect candidate region when the pixel value frequency calculated by the pixel value frequency calculation unit is equal to or greater than a predetermined threshold; Has
The defect region determination unit compares the region determined as the defect candidate region by the defect candidate region determination unit with the other image, and the region determined as the defect candidate region is the same in the other image If present at a position, determine the area determined as the defect candidate area as a defective area,
The image processing apparatus according to claim 1. The region of the predetermined size is one pixel;
The image processing apparatus according to claim 1. The defect area determination unit determines whether the defect area is a defect area by comparing pixel values between the defect candidate area and the surrounding area.
The image processing apparatus according to any one of claims 1 to 3.

Images