JP4168229B2 - Edge enhancement processing device - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
  The present invention provides an edge enhancement processing device.In placeRelated.
[0002]
[Prior art]
Conventionally, as this type of edge enhancement processing device, calculation is performed on image data of each pixel generated by an imaging device (for example, a digital still camera) that captures a subject image as image information by an imaging device via a mosaic filter. Some edge enhancement is performed based on the edge enhancement degree. At this time, the degree of edge enhancement is defined on the basis of edge enhancement luminance that is uniquely calculated from the calculation by performing a predetermined calculation method on the image data.
[0003]
[Problems to be solved by the invention]
In the above-described conventional edge enhancement processing apparatus, there is a problem that the characteristics of image data cannot be reflected in edge enhancement because edge enhancement luminance calculated based on one calculation method is used.
[0004]
  The present invention has been made in view of the above problems, and by using luminance based on mutually different calculation methods for edge enhancement, an edge enhancement processing apparatus capable of reflecting the characteristics of image data by the edge enhancement.SetFor the purpose of provision.
[0005]
[Means for Solving the Problems]
  To achieve the above objective,Edge enhancement device of the present inventionIsFirst calculation means for calculating the luminance of each pixel of image data composed of dot matrix pixels in which each element color is arranged in a mosaic pattern based on a predetermined calculation method in which the luminance is not a negative number; and Second computing means for calculating the brightness of each pixel by image processing tuned so that the brightness can be a negative number, and calculating the edge amount of each pixel based on the brightness calculated by the first computing means, Edge enhancement means for enhancing the edge degree of each pixel calculated by the second calculation means based on an edge amount;It is set as the structure which comprises.
[0006]
  the aboveIn the configurationIn the first calculation meansThe luminance of each pixel of image data composed of dot matrix pixels in which each element color is arranged in a mosaic pattern is calculated based on a predetermined calculation method in which the luminance is not a negative number.. In the second calculation meansThe luminance of each pixel is calculated by image processing tuned so that the luminance can be a negative number.. And with edge enhancement meansThe edge amount of each pixel is calculated based on the luminance calculated by the first calculation means, and the edge degree of each pixel calculated by the second calculation means is emphasized based on the edge amount.. Usually, the edge degree is emphasized using luminance calculated based on one calculation method. However, in the present invention, since two luminances having different properties calculated based on different calculation methods are used for edge enhancement, the essential characteristics of image data can be reflected in the degree of edge enhancement. Become.
[0007]
  As an example of calculation method in the first calculation means,UpThe first calculation means is configured to calculate the luminance of each pixel based on a calculation method that averages each element color of image data captured by the image sensor via a predetermined mosaic filter.Good.
  According to the configurationThe first calculation means calculates the luminance of each pixel based on a calculation method that averages the element colors of the image data captured by the image sensor via a predetermined mosaic filter. This makes it possible to calculate the luminance based on raw data that is not subjected to processing such as image data processing.
[0008]
  The first calculation means described above can calculate the luminance based on the raw data. On the other hand, as an example of the calculation method in the second calculation means for this,UpThe second calculating means is configured to calculate the luminance of each pixel based on a calculation method in which the luminance can be a negative number by image processing that performs pixel interpolation and color conversion to a different color space for the image data.Good.
  According to the configurationThe luminance of each pixel is calculated based on a calculation method in which the luminance can be a negative number in image processing in which pixel interpolation and color conversion to a different color space are performed on the image data by the second calculation means. In other words, the calculation method using the first calculation means calculates the luminance based on raw data that is not subjected to image processing, and the calculation method using the second calculation means calculates the luminance based on data subjected to various image processing. . At this time, in the calculation method using the second calculation means, calculation is performed such that the luminance can take a negative number for tuning the image data. In this way, the first calculation means calculates a positive luminance based on the raw data, and the second calculation means calculates the luminance reflecting the tuning state of the image data after image processing. Then, by performing edge enhancement based on both luminances, it becomes possible to reflect the characteristics of the image data by edge enhancement.
[0009]
  In order to adjust the level of the degree of conversion between the luminance calculated by the first calculation means and the luminance calculated by the second calculation means,UpThe first calculating means executes a γ correction process included in the image processing executed by the second calculating means for the calculated luminance of each pixel.Good.
  According to the configurationThe γ correction processing included in the image processing executed by the second calculation means is executed by the first calculation means for the calculated luminance of each pixel.
[0010]
  When edge enhancement is performed on all pixels, the processing load increases and throughput decreases. Therefore,UpThe edge enhancement means calculates the edge amount of each pixel based on the luminance of each pixel calculated by the first calculation means, and emphasizes the edge degree of each pixel corresponding to the calculated edge amount. As a configuration toGood.
  According to the configurationThen, the edge amount of each pixel is calculated based on the luminance of each pixel calculated by the first calculation means by the edge enhancement means. Then, the edge degree of each pixel is emphasized corresponding to the calculated edge amount. In other words, the pixels constituting the contour are targeted for edge enhancement, thereby limiting the pixels on which the edge enhancement processing is performed, thereby improving the processing efficiency.
[0011]
  As an example of a technique to prevent the brightness of pixels with low edge amount from being reflected in the degree of edge enhancement,UpA non-linear function value (for example, a coring function value) is calculated based on the calculated edge amount, and the calculated non-linear function value is added to the luminance calculated by the second calculating means to thereby obtain an edge of each pixel. As composition to emphasize degreeGood.
  According to the configurationThen, a nonlinear function value is calculated based on the edge amount calculated by the edge enhancement means. Thereby, pixels with a small edge amount are filtered. Then, the edge degree of each pixel is emphasized by adding the calculated nonlinear function value to the luminance calculated by the second calculating means.
[0012]
  As an example of a mosaic filter,UpNote that the mosaic filter is formed with each element color of CMYG.Good.
  According to the configurationThe mosaic filter is formed with each element color of CMYG.
[0013]
  As another example of mosaic filter,UpNote that the mosaic filter is composed of RGB element colors.Good.
  According to the configurationThe mosaic filter is formed with RGB element colors.
[0014]
  In addition, the method of enhancing the edge degree of each pixel of image data composed of dot matrix pixels in which each element color is arranged in a mosaic pattern is not necessarily limited to a substantial device. Can also be easily understood.
  For this reason,eachAn edge emphasis processing method for emphasizing the edge degree of each pixel of image data composed of pixels in a dot matrix in which element colors are arranged in a mosaic pattern,A first calculation step of calculating the luminance of each pixel based on a predetermined calculation method in which the luminance is not negative, and a first calculation step of calculating the luminance of each pixel by image processing tuned so that the luminance can be negative. The edge amount of each pixel is calculated based on the two calculation steps and the luminance calculated in the first calculation step, and the edge degree of each pixel calculated in the second calculation step is emphasized based on the edge amount. An edge emphasizing step is also possible..
  That is, it is not necessarily limited to a substantial apparatus, and there is no difference that the method is also effective.
[0015]
By the way, such an edge emphasis processing apparatus may exist alone or may be used in a state where it is incorporated in a certain device. However, the idea of the invention is not limited to this and includes various aspects. It is a waste. Therefore, it can be changed as appropriate, such as software or hardware. When the software of the edge emphasis processing apparatus is implemented as an embodiment of the idea of the invention, it naturally exists on a recording medium on which such software is recorded, and it must be used.
[0016]
  As an example,eachRecorded an edge enhancement processing program that enhances the edge degree of each pixel of image data composed of dot matrix pixels with element colors arranged in a mosaic patternRecordA medium,A first calculation function for calculating the luminance of each pixel based on a predetermined calculation method in which the luminance is not a negative number, and a first calculation function for calculating the luminance of each pixel by image processing tuned so that the luminance can be a negative number. The edge amount of each pixel is calculated based on the two calculation function and the luminance calculated by the first calculation function, and the edge degree of each pixel calculated by the second calculation function is emphasized based on the edge amount. A computer-readable recording medium that causes the computer to execute the edge emphasizing step..
[0017]
Of course, the recording medium may be a magnetic recording medium, a magneto-optical recording medium, or any recording medium that will be developed in the future. In addition, the duplication stages such as the primary duplication product and the secondary duplication product are equivalent without any question. In addition, even when a part is software and a part is realized by hardware, the idea of the invention is not completely different, and a part is stored on a recording medium and is appropriately changed as necessary. It may be in the form of being read.
[0018]
【The invention's effect】
  As described above, the present invention calculates the luminance of each pixel based on two different calculation methods, and uses these two luminances when emphasizing the edge of each pixel. It is possible to provide an edge enhancement processing apparatus capable of realizing edge enhancement capable of reflecting the characteristics in the edge enhancement degree.
  Furthermore, it is possible to improve processing efficiency by limiting the pixels on which edge enhancement processing is performed.
  further, DIt is possible to reflect the characteristics of the image data by enhancing the wedge.
  And claims2According to the invention, the luminance calculated by the first calculating means is subjected to γ correction similar to the luminance calculated by the second calculating means, so that the level of γ conversion can be made equivalent. become.
[0019]
  And claims3According to the invention, it is possible to prevent the luminance of a pixel having a small edge amount from being reflected in the edge enhancement degree..
[0020]
DETAILED DESCRIPTION OF THE INVENTION
Here, embodiments of the present invention will be described in the following order.
(1) Configuration of digital still camera:
(2) Outline of image processing:
(3) About edge enhancement processing:
(4) Modified example of edge enhancement processing:
(5) Summary:
[0021]
(1) Schematic configuration of digital still camera:
FIG. 1 is a block diagram showing a schematic configuration of a digital still camera to which an edge enhancement processing device of the present invention is applied. In the figure, the digital still camera 10 includes an optical unit 20 and a control unit 30 having a CPU 32 as a core. The optical unit 20 includes an optical lens system 21, an autofocus mechanism 22, a distance measuring unit 23, and an autofocus controller 24, and the autofocus controller 24 controls the distance measuring unit 23 based on a control signal from the controller 25. The optical lens system 21 is driven by the autofocus mechanism 22 while the distance to the subject is measured. A subject image is formed by the optical lens system 21 on the image pickup surface of a CCD 26 as an image pickup element, and the CCD 26 is constituted by a single plate having 1800 × 1200 pixels. Since it is composed of a single plate, green (G), magenta (M), yellow (Y), and cyan (C) color filters are sequentially formed for 2 × 2 pixels. In addition, although the shutter is provided with the mechanical shutter with the electronic shutter, illustration is abbreviate | omitted about the mechanical shutter.
[0022]
In addition, the optical unit 20 is also provided with a strobe 27, which emits a predetermined amount of light and a predetermined number of times according to a drive signal from the controller 25. This realizes shooting such as red-eye prevention or slow sync. Note that an auto gain controller (AGC) 28 for amplifying an analog electric signal output from the CCD 26 is provided, and an A / D converter 29 for converting the amplified analog electric signal into a digital value and outputting the digital value. . Of course, the optical unit 20 described above is merely an example of a general configuration as the digital still camera 10, and it is needless to say that various changes can be made. For example, the optical lens system 21 may include a zoom lens, or may be an inexpensive one that does not have an autofocus function as a fixed focus.
[0023]
The control unit 30 includes a bus 31, and the CPU 32, the ROM 33, the RAM 34, and the A / D converter 29 are connected to the bus 31. The CPU 32 executes firmware written in the ROM 33 to execute control of the optical unit 20 and calculation of image processing. At this time, the RAM 34 functions as an image area 34a for storing image data or performs calculation processing. Function as a work area 34b. When the CPU 32 controls the optical unit 20, it outputs a control signal to the controller 25, and the controller 25 generates and outputs an appropriate control signal for each component circuit.
[0024]
The control unit 30 also has a function as a man-machine interface, and includes an operation panel 35 on which operation buttons and the like are arranged, and an LCD panel 36 for displaying captured images and operation instructions. The operation is monitored, and the corresponding control is executed while receiving the operation as appropriate. Further, the display on the LCD panel 36 is performed by the CPU 32 writing predetermined data in the video RAM area 34c allocated to the RAM 34, so that the display controller provided in the LCD panel 36 appropriately reads the data and displays it. . Then, image data that has been shot and generated through predetermined image processing is written to the flash memory card 37b, which is an external memory, via the I / O 37a, and is read out from the flash memory card 37b as necessary.
[0025]
The configuration of the control unit 30 is also a typical example of this type of digital still camera 10, and various changes can be made. For example, the type of external memory can be easily replaced with another type as appropriate, and image data can be output to a computer via a USB interface even without an interface with a removable memory. It may be. An LCD for information display may be provided along with the LCD panel as a display unit, and the CPU 32 may be provided with a plurality of CPUs having different control targets.
[0026]
The image picked up by the optical unit 20 is output from the CCD 26 as an analog electric signal, then converted into digital data by the A / D converter 29 via the AGC 28, and further recorded in the image area 34 a of the RAM 34 via the bus 31. The Then, the CPU 32 executes predetermined image processing to convert it into JPEG image data and write it into the above-described flash memory card 37b.
[0027]
(2) Outline of image processing:
FIG. 2 shows a main flow of image processing executed by the CPU 32. Although detailed processing as described below is executed in detail, the processing is generally proceeded according to this flow. First, this outline will be described. In the figure, in step S102, defective pixel interpolation is executed. A defective pixel is inevitable in the CCD 26 having about 2 million pixels, and if it is below a predetermined reference value, it is supplied as a non-defective product. For this reason, defective pixels within a non-defective range are compensated by using a 5 × 5 pixel median filter based on only the same color pixels. That is, if the defective pixel is a cyan pixel, the output values of 5 × 5 cyan pixels located around the defective pixel are arranged in order, and the median value is set as the value of the defective pixel. The defective pixel itself has already been detected by the optical unit 20.
[0028]
In the next step S104, white balance is measured. Depending on the type of light source at the time of shooting and the combination of the CCD 26 and the color filter, the white balance may be shifted. In this embodiment, the white balance is measured at step S104 for each shooting, and the result is reflected. In step S110, the white balance is controlled so as to reduce the deviation. When measuring the white balance, 113 × 75 pixel image data selected in the thinning process is used to measure the bias of the R component and the bias of the B component in the RGB color system based on the G component. The CCD 26 includes a complementary color filter, and performs control based on the fact that it is a complementary color system.
[0029]
In this embodiment, three types of images are generated. The first is a confirmation image, the second is a thumbnail image, and the third is a main image. The confirmation image is an image to be displayed on the LCD panel 36 immediately after shooting, and is composed of image data of 720 × 240 pixels. The thumbnail image is recorded as image data together with the main image, and is composed of image data of 160 × 120 pixels. The main image can be selected in three sizes according to the selection of the operator, and is either 720 × 480 pixels as an E-mail image, 1800 × 1200 pixels as a Print image, or 2160 × 1440 pixels with high resolution as Hypic2 It is.
[0030]
In FIG. 2, Steps S106 to S114 are displayed surrounded by broken lines, and at least these processes are performed for each of the three types of generated images. In step S106, data interpolation is performed. Although the CCD 26 is composed of a single plate and has 2 million pixels, the color information is not completely completed for all the pixels. That is, there is only cyan information for some pixels, only magenta information for some pixels, only yellow information for some pixels, and only green information for some pixels. This data is called mosaic color data. Data interpolation is a process for completing the color information for each pixel by supplementing the information of other colors that are insufficient for each pixel. The lacking information is the average value of the color information included in the eight pixels surrounding the target pixel. For example, there are two yellow pixels (Y1, Y2), two magenta pixels (M1, M2), and four green pixels (G1-G4) around the cyan pixel (C1).
[0031]
Therefore, for the color information (C, M, Y, G) of this cyan pixel,
C = C1
M = (M1 + M2) / 2
Y = (Y1 + Y2) / 2
G = (G1 + G2 + G3 + G4) / 4
Calculate as
[0032]
In step S108, the color system is changed and converted to RGB image data. There are general formulas for conversion, but actually, a simple general formula is not used, but conversion is performed using a tuned lookup table or a determinant. After conversion into RGB image data, in step S110, as described above, control is performed to reduce the bias of the R component and the bias of the B component in the RGB color system. In the next step S112, tone curve correction is performed. Tone curve correction is also referred to as so-called γ correction. At this time, 10-bit image data is converted into 8-bit image data for each component, and further noise reduction and gradation characteristics in the white side region and the black side region are performed. The γ curve itself is also adjusted to maintain The tone curve correction itself uses a look-up table, and is converted with reference to a 10-bit → 8-bit look-up table created by tuning in advance.
[0033]
Thereafter, color conversion is performed from the RGB color system to the YUV color system in order to use the JPEG image compression technique. In order to distinguish between brightness and yellow, the brightness is hereinafter displayed as Ym, and the brightness directly derived from the mosaic color data is displayed as simple brightness Ys as described later. The color conversion from the RGB color system to the YUV color system is performed using a general formula or a determinant.
[0034]
The general formula for conversion from mosaic color data to YUV color system is:
Ys = 0.25 × (C + M + Y + G)
U = C + M- (Y + G)
V = -C + M + Y-G
However, in practice, the tuning and white balance control as described above are performed, and this correspondence is not adopted.
[0035]
Steps S116 and S118 are processes performed only when the main image is created. Noise removal is performed by applying a so-called low-pass filter only for the UV component as the color component. In other words, the color change that is too steep acts on the pressing feeling. In the edge enhancement, a non-linear function value (for example, a coring function value) is calculated from an edge amount based on the luminance component only for the luminance component, and the non-linear function value is weighted to the original luminance component. Therefore, when the luminance value changes between adjacent pixels, the edge amount is calculated, and if the absolute value of the edge amount is large, the amount of change is reflected in the luminance value. If the absolute value is small, the original luminance is calculated. The value is almost unchanged.
[0036]
The above is the outline of the image processing. However, the above procedure also shortens the calculation processing time by simultaneously performing a plurality of processes in the actual calculation processing. The shooting is completed by executing the above-described image processing for each of the three types of images described above, and finally writing the JPEG compressed image of the main image including the thumbnail image in the flash memory card 37b. In addition, this digital still camera can read image data from the flash memory card 37b and display it on the LCD panel 36, or can delete data and perform various settings. The description is omitted because it is applicable.
[0037]
(3) About edge enhancement processing:
Note that the edge enhancement processing in step S118 described above includes YmUV generated by executing image processing such as data interpolation processing in step S106, color conversion processing in steps S108 and S114, and step white balance control processing in step S110. It is also possible to emphasize the edge degree of each pixel by using the luminance Ym of the image data. However, when each process is performed as described above and the tuning is performed, the luminance Ym may become a negative number. Here, when edge enhancement processing is executed using such a negative luminance Ym, edge enhancement may be hindered. Therefore, the edge enhancement processing device according to the present invention uses the simple luminance Ys that is directly derived from the mosaic color data, thereby preventing the luminance used for edge enhancement from becoming a negative number and further improving the characteristics of the image data to the edge. It is possible to reflect in the emphasis.
[0038]
Here, as described above, the CCD 26 that is an image pickup device picks up the subject image formed by the optical system lens 21. The image signals picked up by the CCD 26 are sequentially converted into digital image signals by the A / D converter 29 based on a predetermined timing signal, and sent to a YUV conversion module (not shown). This YUV conversion module generates a luminance Ym and two color signals (U, V) from an input signal. The generated luminance Ym is sent to the edge enhancement processing module, and is used for edge enhancement of the subject based on the edge enhancement amount combined with the simple luminance Ys by the edge enhancement processing module.
[0039]
FIG. 3 is a block diagram showing the configuration of this edge enhancement processing module. In the figure, the edge enhancement processing module 40 includes a simple luminance calculation module 41, an edge amount calculation module 42, a non-linear function module 43, and an addition module 44. FIG. 4 is a diagram showing signal waveforms in the modules 41 to 44 built in the edge enhancement processing module 40. In the figure, the luminance Ym is input from the YUV conversion module described above. The simple luminance Ys is directly derived from the mosaic color data as described above. The edge amount E is calculated from the simple luminance Ys. The nonlinear function value f (E) is calculated based on the edge amount E. The edge enhancement luminance Y ′ is calculated by adding the luminance Ym and the nonlinear function value f (E).
[0040]
The edge amount calculation module 42 includes a 3 × 3 pixel unit Laplacian filter 50 shown in FIG. The Laplacian filter 50, when calculating the edge amount E of the center pixel, quadruples the image data of the center pixel and also doubles the image data of the adjacent pixels in the vertical and horizontal directions, The image data of pixels adjacent in the vertical and horizontal directions is subtracted from the image data of the pixels. That is, the amplitude of the simple luminance Ys of the central pixel is subtracted by the vertical, horizontal, and horizontal pixel widths according to the luminance of the central pixel and surrounding pixels adjacent thereto. When the filter operation is executed by such a Laplacian filter 50, the edge amount E of the center pixel is calculated as shown in FIG.
[0041]
The nonlinear function module 43 includes the nonlinear function shown in FIG. 7 as a table. The nonlinear function module 43 inputs the edge amount E calculated by the edge amount calculating module 42 and also uses a nonlinear function value f corresponding to the edge amount E. (E) can be calculated. In this non-linear function, as shown in FIG. 4, the amplitude can be cut to a certain non-linear function level L to remove noise. When the nonlinear function value f (E) is calculated from the edge amount E of the simple luminance Ys, this nonlinear function value f (E) is output to the addition module 44. The addition module 44 adds the nonlinear function value f (E) input from the nonlinear function module 43 and the luminance Ym output from the YUV conversion module. Thereby, an edge enhancement luminance Y ′ for enhancing the edge of the subject is calculated.
[0042]
FIG. 8 is a flowchart showing the processing contents of the edge enhancement processing executed by the edge enhancement processing module 40 using the modules 41 to 44.
In the figure, a dot matrix in which C, M, Y, and G are arranged in a mosaic pattern
The simple luminance Ys is calculated based on the mosaic color data configured in the shape (step S118a). Here, calculation of the simple luminance Ys will be described. Mosaic color data taken in via the CCD 26 is formed by pixels in a dot matrix form shown in FIG. Here, the horizontal axis (a1, a2,...) Indicates the pixel position in the horizontal axis direction, and the vertical axis (b1, b2,...) Indicates the pixel position in the vertical axis direction. For example, the pixel (a1, b1) indicates that it has G11 mosaic color data, and the pixel (a2, b1) indicates that it has M21 mosaic color data. Then, when calculating the simple luminance Ys of the predetermined pixel, it is calculated based on the mosaic color data of four pixels adjacent to each other including the pixel.
[0043]
For example, the simple luminance Ys (a1, b1) of the pixel (a1, b1) is G11 which is mosaic color data of the pixel (a1, b1), Y12 which is mosaic color data of the pixel (a1, b2), The calculation is based on M21 which is the mosaic color data of the pixel (a2, b1) and C22 which is the mosaic color data of the pixel (a2, b2). If the calculation method in such a case is expressed in a mathematical formula,
Ys (a1, b1) = (G11 + M21 + Y12 + C22) / 4
It becomes.
[0044]
The simple luminance Ys (a2, b1) of the pixel (a2, b1) is M21 which is mosaic color data of the pixel (a2, b1), C22 which is mosaic color data of the pixel (a2, b2), It is calculated based on G31 which is the mosaic color data of the pixel (a3, b1) and Y32 which is the mosaic color data of the pixel (a3, b2). If the calculation method in such a case is expressed in a mathematical formula,
Ys (a2, b1) = (M21 + G31 + C22 + Y32) / 4
It becomes.
[0045]
That is, when calculating the simple luminance Ys of a predetermined pixel, the average value of the mosaic color data of the pixel and the mosaic color data of the adjacent pixels on the right, bottom, and diagonally lower right of the pixel is calculated. Become. The calculation of the simple luminance Ys is sequentially performed on all pixels of the dot matrix-like mosaic color data from the pixel (a1, b1). When the simple luminance Ys of each pixel is calculated as described above, tone curve correction is performed on the calculated simple luminance Ys. This tone curve correction is so-called γ correction.
[0046]
This tone curve correction itself uses a look-up table, and in order to adjust the level with the luminance Ym, the γ curve is prepared by tuning in advance so as to have a curve equivalent to that used in step S112. Yes. In this tone curve correction, conversion is performed with reference to a lookup table of 10 bits → 8 bits. Then, simple luminance data holding the simple luminance Ys of each pixel (a1, b1)... Shown in FIG. Thus, when the calculation of the simple luminance Ys for each pixel is completed, the edge amount E of each pixel is then calculated based on the simple luminance Ys (step S118b). The edge amount E is calculated using the Laplacian filter 50 as described above. For example, the edge amount E (a2, b2) of the simple luminance Ys (a2, b2) is performed based on the following calculation method.
[0047]
E (a2, b2) = 4 × Ys (a2, b2) −Ys (a2, b1) −Ys (a1, b2) −Ys (a2, b1) −Ys (a3, b2)
In this way, when calculating the edge amount E of a predetermined pixel, the simple luminance Ys of the pixel is quadrupled as described above, and the simple luminance Ys of pixels adjacent vertically and horizontally is subtracted from the quadruple simple luminance Ys. To calculate. Then, this edge amount E is calculated for all pixels. When the edge amount E of all the pixels is calculated, the edge amount E is output to the nonlinear function module 43. The nonlinear function module 43 calculates a nonlinear function value f (E) based on the input edge amount E (step S118c). In calculating the nonlinear function value f (E), the nonlinear function value f (E) corresponding to the predetermined edge amount E may be extracted by using a table, or the nonlinear function value shown in FIG. By substituting the edge amount E into, the nonlinear function value f (E) may be calculated by calculation.
[0048]
When the nonlinear function value f (E) is calculated in step S118c, the luminance Ym for all pixels is acquired from the YUV conversion module (step S118d). The luminance Ym has already been calculated for each pixel as shown in FIG. Then, the edge enhancement brightness Y ′ is sequentially calculated for each pixel (step S118e). The calculation of the edge enhancement luminance Y ′ is executed by the addition module 44. The adding module 44 calculates edge enhancement luminance Y ′ based on the following equation.
Y '= Ym + f (E)
Then, when the edge enhancement luminance Y ′ is calculated, the luminance Ym of each pixel generated by the YUV conversion module is corrected based on the edge enhancement luminance Y ′ as shown in FIG. Emphasis is realized (step S118f).
[0049]
In the edge enhancement processing described above, the simple luminance Ys for all pixels is calculated in step S118a, the edge amount E for all pixels is calculated in step S118b, and the nonlinear function value f (for all pixels is calculated in step S118c. E) is calculated, the luminance Ym for all the pixels is acquired in step S118d, each edge enhanced luminance Y ′ for all the pixels is calculated in step S118e, and based on this edge enhanced luminance Y ′ in step S118f. In this case, the subject is edge-emphasized. Of course, the present invention is not limited to the configuration for calculating the simple luminance Ys, the edge amount E, the nonlinear function value f (E), the luminance Ym, and the edge enhancement luminance Y ′ for all pixels in each step. Alternatively, the edge enhancement luminance Y ′ may be calculated and the image data corrected based on the simple luminance Ys, the edge amount E, the nonlinear function value f (E), and the luminance Ym, and may be sequentially performed for all the pixels.
[0050]
In the above-described embodiment, an aspect is adopted in which edge enhancement processing is performed on all pixels regardless of the state of each pixel. Of course, the present invention is not limited to the aspect in which edge enhancement is performed on all pixels, and an aspect in which edge enhancement processing is performed only on pixels having a predetermined edge amount E, that is, contour pixels, may be employed. The processing content of the edge enhancement processing in such a case is shown in the flowchart of FIG. In the figure, a mode in which processing is sequentially executed for each pixel is adopted. First, the luminance Ym of the first pixel (a1, b1) in the dot matrix shape is acquired (step S118g). And it is discriminate | determined whether this brightness | luminance Ym is more than predetermined threshold value ST (step S118h).
[0051]
When it is determined that the luminance Ym is equal to or greater than the predetermined threshold ST, the simple luminance calculation module 41 acquires the mosaic data of the pixel (a1, b1) and adjacent pixels, and based on this mosaic data Then, the simple luminance Ys (a1, b1) of the pixel (a1, b1) is calculated using the same calculation as in step S118a described above (step S118i). Next, the edge amount calculation module 42 calculates the edge amount E (a1, b1) of each pixel based on the simple luminance Ys (a1, b1) by using the same operation as in step S118b described above ( Step S118j). When the edge amount E of the pixel (a1, b1) is calculated, the edge amount E (a1, b1) is output to the nonlinear function module 43.
[0052]
The nonlinear function module 43 calculates a nonlinear function value f (E) (a1, b1) based on the input edge amount E (a1, b1) (step S118k). Then, the edge enhancement luminance Y ′ (a1, b1) of the pixel (a1, b1) is calculated by the addition module 44 (step S118l). It is determined whether or not the above calculation has been performed for all pixels (step S118m). If all the pixels have not been completed, the process returns to step S118g and the above steps S118g to S118l are repeated. If it is determined that the processing has been completed for all pixels, the image data is corrected based on the edge enhancement luminance Y ′ of each pixel calculated in step S118l (step S118n).
[0053]
In the above-described embodiment, the threshold value ST to be compared with the luminance Ym is fixed in step S118h. A mode of executing processing was adopted. On the other hand, the threshold value ST is not limited to a fixed mode, and the threshold value ST may be varied based on the distribution of the edge amount E of all pixels. For example, when the edge amount is large as a whole, the threshold pixel ST is set small because the number of contour pixels is large. When the edge amount is small as a whole, the threshold value ST is set large. That is, when the number of sharp pixels is small, by setting the threshold value to a higher ST, it is possible to adjust the number of contour pixels for executing the edge enhancement processing.
[0054]
In the present embodiment, the CCD 26 is formed of a single plate having 1800 × 1200 pixels, and the colors of green (G), magenta (M), yellow (Y), and cyan (C) are used for 2 × 2 pixels. A configuration in which filters are sequentially formed is employed. The calculation of the simple luminance Ys is the average value of the mosaic data of G, M, Y, and C. Of course, the CCD 26 is composed of a single plate having 1800 × 1200 pixels, and red (R), green ( G) and blue (B) color filters may be sequentially formed. In such a case, the simple luminance Ys may be calculated as the average value of the R, G, B color data.
[0055]
(4) Summary:
As described above, the second calculation method for calculating the simple luminance Ys by the first calculation method for averaging the mosaic color data of C, M, Y, G captured via the CCD 26 and executing the data interpolation process or the like. The brightness Ym is calculated by calculating the edge emphasizing brightness Y ′ based on the simple brightness Ys and the brightness Ym calculated by different calculation methods, and correcting the image data. It is possible to reflect the characteristics in edge enhancement.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a schematic configuration of a digital still camera to which an edge enhancement processing apparatus according to the present invention is applied.
FIG. 2 is a flowchart showing a main flow of image processing executed by a digital still camera.
FIG. 3 is a configuration diagram showing a configuration of an edge enhancement module.
FIG. 4 is a diagram showing signal changes inside the edge enhancement module.
FIG. 5 is a diagram illustrating a configuration of a Laplacian filter.
FIG. 6 is a diagram showing an aspect of an edge.
FIG. 7 is a diagram illustrating an example of a nonlinear function.
FIG. 8 is a flowchart showing processing details of edge enhancement processing;
FIG. 9 is a diagram showing image data of mosaic data.
FIG. 10 is a diagram illustrating a simple luminance component.
FIG. 11 is a diagram showing luminance components of image data generated by a YUV conversion module.
FIG. 12 is a diagram showing edge-enhanced luminance components.
FIG. 13 is a flowchart showing other processing details of edge enhancement processing;
[Explanation of symbols]
10. Digital still camera
20 ... Optical part
21 ... Optical lens system
22 ... Autofocus mechanism
23. Ranging section
24 ... Autofocus controller
25 ... Controller
26 ... CCD
27 Strobe
28 ... Auto gain controller (AGC)
29 ... A / D converter
30 ... Control unit
31 ... Bus
32 ... CPU
33 ... ROM
34 ... RAM
34a ... Image area
34b ... Work area
34c ... Video RAM area
35 ... Control panel
36 ... LCD panel
37a ... I / O
37b ... Flash memory card

Claims (3)

First calculation means for calculating the luminance of each pixel of image data composed of dot matrix pixels in which each element color is arranged in a mosaic pattern based on a predetermined calculation method in which the luminance is not a negative number ;
On SL luminance of each pixel, a second calculating means for calculating the tuned image processing so that the luminance can be a negative number,
Edge enhancement means for calculating an edge amount of each pixel based on the luminance calculated by the first calculation means, and enhancing an edge degree of each pixel calculated by the second calculation means based on the edge amount ; ,
An edge emphasis processing apparatus comprising: 2. The edge enhancement according to claim 1 , wherein the first calculation means executes γ correction processing included in the image processing executed by the second calculation means for the calculated luminance of each pixel. Processing equipment. The edge enhancement means calculates a nonlinear function value based on the calculated edge amount, and adds the calculated nonlinear function value to the luminance calculated by the second calculation means, thereby increasing the edge degree of each pixel. The edge emphasis processing apparatus according to claim 1 or 2 , wherein emphasis is performed.

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