KR101299250B1 - Apparatus and method for digital picturing image - Google Patents

Abstract

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a digital image processing apparatus and a control method thereof, and more particularly, to a digital image processing apparatus and a control method thereof having improved contrast through three-dimensional gamma correction.

The present invention provides a gamma table generator for generating a three-dimensional gamma correction table; And a contrast correction unit configured to correct an input luminance component (Y _in ) of an image file to an output luminance component (Y _out ) by the three-dimensional gamma correction table generated by the gamma table generator. do.

Description

Digital image processing apparatus and control method thereof {Apparatus and method for digital picturing image}

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a digital image processing apparatus and a control method thereof, and more particularly, to a digital image processing apparatus and a control method thereof having improved contrast through three-dimensional gamma correction.

Typically, the digital image processing apparatus includes all devices that process images of a digital camera, a PDA (personal digital assistant), a phone camera, a PC camera, or the like, or use motion recognition sensors. Such a digital image processing apparatus receives a desired image through an image pickup device, displays the input image on an image display device, displays the image on an image display device, stores the image as an image file by user's selection, and prints the stored image file.

The imaging device used in such a digital image processing device has a limited amount of light sources that can be received at one time, unlike the human eye, even if the exposure time or aperture is perfectly adjusted. If you take a lot of images, you will get a low contrast image, which means that the details of one region are not well represented. In this case, the task of improving the contrast in areas where details are hardly represented is called contrast enhancement / enhancement, which is also used to improve the image quality of images shot with backlighting. Also called compensation.

As a method of improving the contrast, a method of separating the luminance component and the remaining components of the input image, gamma correction of the luminance component, and applying a histogram equalization method are used.

1 is a diagram illustrating a conventional gamma correction transfer function.

Referring to FIG. 1, gamma correction is a method of improving contrast by adjusting a brightness of an image by adjusting a gamma value based on Equation 1 below.

Here, Y _in is a luminance value of the input image, and Y _out is a luminance value of the output image. However, when performing gamma correction using such a transfer function, if the gamma (Γ) value is smaller than 1 in order to make the details of the dark part visible, the details of the list are lost. In order to make the gamma (Γ) value larger than 1, there was a problem in that the details of the dark part were lost.

That is, when gamma correction is performed with a gamma (Γ) value greater than 1 in order to make the detailed information of the roster 10a visible in the original image as shown in FIG. 2A, the list 10b becomes more clearly as shown in FIG. 2B. Although visible, the darker portion 20b becomes darker so that it is difficult to identify the image. On the contrary, when gamma correction is performed by making the gamma (Γ) value smaller than 1 in order to make the detailed information of the dark portion 20a visible in the original image as shown in FIG. 2A, the dark portion 20c becomes brighter than the original as shown in FIG. Although identification of the image becomes easy, the roster 10c becomes dark so that identification of the image becomes difficult.

In order to make up for the shortcomings of gamma correction, a "multiple correction" method is proposed in which luminance components of an input image are divided into various ranges and different gamma (Γ) values are applied to each range. In this method, there is a problem that the contrast is reduced because the luminance range near the inflection point is reduced due to the linearity of the curve.

In addition, a method such as "non-linear mapping" based on Equation 2 below has also been proposed as another method to compensate for the disadvantage of gamma correction.

Here, T is called the transfer function, which is a nonlinear curve. In this method, if a few inflection points are set, a nonlinear transfer function is generated under the constraint that the high luminance component of the input image has a high luminance value in the resultant image, and then the contrast is adjusted by adjusting the luminance component. do. However, even in this method, there is still a problem that the contrast is reduced because the expression range near the inflection point is reduced.

It is an object of the present invention to provide a digital image processing apparatus and a control method thereof in which the contrast is improved and the reduction of the expression range near the inflection point is improved.

The present invention provides a gamma table generator for generating a three-dimensional gamma correction table; And a contrast correction unit configured to correct an input luminance component (Y _in ) of an image file to an output luminance component (Y _out ) by the three-dimensional gamma correction table generated by the gamma table generator. do.

The gamma table generator may generate the three-dimensional gamma correction table according to a correlation between each pixel of the digital image processing apparatus and neighboring pixels.

In the present invention, the three axes of the three-dimensional gamma correction table are the input luminance component (Y _in ), the correlation (Y _relation ) between the input luminance component and its surrounding pixels, and the output luminance component (Y _out ), respectively. Can be represented.

In the present invention, the input luminance component and the output luminance component may have a 1: 1 correspondence relationship.

The gamma table generator may include: a luminance component extractor configured to extract the input luminance component from the image file; A peripheral relationship definition unit defining a correlation (Y _relation ) between an input luminance component of each pixel and input luminance components of peripheral pixels of each pixel; And a transfer function generator for generating a transfer function for the 3D gamma correction using the correlation.

Here, the Y _relation between the input luminance component of each pixel and the input luminance components of the peripheral pixels of each pixel may include an input luminance component of each pixel and an input luminance component of the peripheral pixels of each pixel. Can be defined by calculating a predetermined weight.

Here, the transfer function may calculate an output luminance component in consideration of the input luminance component of each pixel and the correlation.

The gamma table generator may further include a high frequency component recovery coefficient determiner configured to determine a high frequency component recovery coefficient for restoring a high frequency component such as an edge in the input image.

Here, the high frequency component recovery function generated by the high frequency component recovery coefficient determiner may be added to the transfer function.

The contrast corrector may include a brightness corrector that adjusts brightness of an output image by correcting a luminance component of an input image through the transfer function.

The contrast correction unit may further include a high frequency component restoration unit for restoring a high frequency component such as an edge in the input image by using the high frequency component restoration function generated by the high frequency component restoration coefficient determiner.

The digital image processing apparatus may further include a saturation correction unit configured to correct saturation of the color of the reduced input image according to a difference between the input luminance component and the output luminance component.

According to another aspect of the present invention, there is provided a method including generating a three-dimensional gamma correction table; And correcting the input luminance component (Y _in ) of the image file with the output luminance component (Y _out ) by using the generated three-dimensional gamma correction table.

In the present invention, generating the three-dimensional gamma correction table may generate the three-dimensional gamma correction table according to a correlation between each pixel of the digital image processing apparatus and its neighboring pixels.

In the present invention, the three axes of the generated three-dimensional gamma correction table are respectively the input luminance component (Y _in ), the correlation (Y _relation ) between the input luminance component and its surrounding pixels, and the output luminance component (Y). _out )

In the present invention, the input luminance component and the output luminance component may have a 1: 1 correspondence relationship.

In the present invention, the generating of the 3D gamma correction table may include: extracting the input luminance component from the image file; Defining a Y _relation between an input luminance component of each pixel and input luminance components of peripheral pixels of each pixel; And generating a transfer function for the 3D gamma correction using the correlation.

The defining of the Y _relation may be defined by calculating a predetermined weight on an input luminance component of each pixel and input luminance components of peripheral pixels of each pixel.

In the generating of the transfer function, the output luminance component may be calculated in consideration of the input luminance component of each pixel and the correlation.

The method may further include determining a high frequency component reconstruction coefficient for reconstructing a high frequency component such as an edge in the input image, wherein a high frequency component reconstruction function generated by the high frequency component reconstruction coefficient is added to the transfer function. Can be.

Here, the step of correcting the input luminance component (Y _in ) of the image file by using the generated three-dimensional gamma correction table and converting the output luminance component (Y _out ) into the output luminance component (Y _out ) may be performed by the transfer function. The method may include adjusting the brightness of the output image by correcting the luminance component.

Here, the step of correcting the input luminance component (Y _in ) of the image file by using the generated three-dimensional gamma correction table and converting the input luminance component (Y _out ) into the output luminance component (Y _out ) may be performed by using the generated high frequency component reconstruction function. The method may include restoring a high frequency component such as an edge in the image.

The method may further include correcting the saturation of the color of the reduced input image according to the difference between the input luminance component and the output luminance component.

According to the present invention as described above, the contrast can be improved and the reduction of the expression range near the inflection point can be obtained.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

3 is a perspective view showing the front and top contours of the digital image processing apparatus according to the present invention.

The shutter release button 101 is opened and closed to expose the image pickup device or the film to light for a predetermined time, and records an image on the image pickup device by properly exposing the subject in conjunction with an aperture (not shown).

The shutter release button 101 generates the first and second image capturing signals by a photographer input. When the first shutter-release signal as the half-shutter signal is input, the digital image processing apparatus focuses and adjusts the amount of light, and when the focus is achieved, the green light is turned on in the display 113. When the focus is achieved by the input of the first shutter release signal and the amount of light is adjusted, the second shutter release signal as a full shutter signal is input to capture an image.

The power button 103 is input to operate by supplying power to the digital image processing apparatus.

The flash 105 brightens the bright light instantly when shooting in a dark place, and flash modes include auto flash, forced flash, flash off, red eye reduction, and slow synchro.

The auxiliary light 107 supplies light to the subject so that the digital image processing apparatus automatically focuses quickly and accurately when the amount of light is insufficient or at night.

The lens unit 109 receives light from an external light source and processes an image.

FIG. 4 is a rear view illustrating a rear shape of the digital image processing apparatus illustrated in FIG. 3, wherein the wide-angle zoom button 111w, the telephoto-zoom button 111t, the display unit 113, and the touch sensor or the contact switch are connected. The provided input buttons B1 to B14 (hereinafter referred to as buttons B1 to B14) are provided.

The wide-angle zoom button 111w or the tele-zoom button 111t increases the angle of view or narrows the angle of view according to an input, particularly when the size of the selected exposure area is to be changed. When the wide-zoom button 111w is input, the size of the selected exposure area is reduced, and when the tele-zoom button 111t is input, the size of the selected exposure area is increased.

The buttons B1 to B14 are provided in the horizontal column and the vertical column of the display unit 113. The buttons B1 to B14 provided in the horizontal and vertical columns of the display 113 are provided with a touch sensor (not shown) or a contact switch (not shown).

That is, the buttons B1 to B14 are provided with a touch sensor and move up / down / left / right in a state where the buttons B1 to B7 in the horizontal row or the buttons B8 to B14 in the vertical row are touched. Any value of the item (eg, color or brightness) may be selected or a submenu icon included in the main menu icon may be activated.

In addition, the buttons B1 to B14 are provided with contact switches so that the corresponding function can be executed by directly selecting the main menu icon and the submenu icon. The touch sensor requires only a weak touch relative to the contact switch input, but the contact switch input requires a relatively strong touch compared to the touch sensor input.

FIG. 5 is a block diagram illustrating the configuration of the digital image processing apparatus illustrated in FIGS. 3 and 4. The display unit 113, the user input unit 121, the image capturing unit 123, the image processing unit 125, and the storage unit ( 127 and the digital signal processor 130.

The user input unit 121 may open and close the shutter-release button 101 to expose the imaging device or the film to light for a predetermined time, the power button 103 to input power, and widen the angle of view according to the input. , A wide-angle zoom button 111w and a tele-zoom button 111t for narrowing the angle of view, and a touch sensor or a contact switch provided in horizontal and vertical columns around the display 113 for text or menu setting. There are buttons B1 to B14.

The image pickup section 123 includes a shutter, a lens section, a diaphragm, a charge coupled device (CCD), and an analog-to-digital converter (ADC), not shown. The shutter is a mechanism that adjusts the amount of light that is exposed with the iris. The lens unit receives light from an external light source and processes the image. At this time, the diaphragm adjusts the amount (amount of light) of the incident light according to the degree of opening and closing. The opening and closing degree of the iris is controlled by the digital signal processor 130.

The CCD accumulates the amount of light input through the lens unit and outputs an image captured by the lens unit in accordance with the accumulated light amount in accordance with the vertical synchronization signal. Image acquisition of the digital image processing apparatus is performed by a CCD that converts light reflected from a subject into an electrical signal. In order to obtain a color image using a CCD, a color filter is required, and most of them employ a filter (not shown) called a color filter array (CFA). CFA has a regularly arranged structure that passes only light that represents one color per pixel, and it has various forms according to the arrangement structure. The ADC converts an analog video signal output from the CCD into a digital signal.

The image processor 125 performs signal processing to display the digitally converted RAW data. The image processing unit 125 removes a black level due to the dark current generated in the CCD and the CFA filter which are sensitive to the temperature change. The image processor 125 performs gamma correction for encoding information according to nonlinearity of human vision under the control of the digital signal processor 130. The gamma correction will be described later in detail. In addition, the image processor 125 performs CFA interpolation to interpolate the Bayer pattern implemented by the RGRG line and the GBGB line of the gamma corrected predetermined data to the RGB line. In addition, the image processing unit 125 converts the interpolated RGB signal into a YUV signal, sharpens the image by filtering the Y signal by a high band filter, and uses the standard color coordinate system to color the U and V signals. Perform color correction to correct values, and remove their noise. In addition, the image processing unit 125 compresses and signals the Y, U, and V signals from which the noise is removed to generate a JPEG file, and the generated JPEG file is displayed on the display unit 113 and stored in the storage unit 127. Stored. All of the operations of the image processor 125 operate under the control of the digital signal processor 130.

FIG. 6 is a detailed block diagram of the digital signal processor of FIG. 5.

Referring to FIG. 6, the digital signal processor 130 generates a 3D gamma correction table, and controls to generate and output an input luminance level of an image file by using the generated 3D gamma correction table.

In detail, human vision responds nonlinearly to brightness in accordance with Weber's law, so given a limited bit depth, linearly recording the brightness of light results in posterization ( Posterization) occurs. Therefore, in order to show the maximum image quality under a given bit depth, it is necessary to encode using a nonlinear function. Thus, encoding information according to nonlinearity of human vision is called gamma correction.

Conventionally, in order to perform such gamma correction, a general two-dimensional transfer function, a "multiple correction" method, or a "non-linear mapping" method as described above are used. It has been proposed to use a. However, in the case of performing gamma correction using the transfer function in this way, if the gamma (Γ) value is larger than 1 in order to make the details of the list visible, the details of the dark parts are lost, and conversely, the details of the dark parts are well known. To make it visible, if the gamma (Γ) value is smaller than 1, there is a problem that the details of the list are lost. In addition, other methods to compensate for this are to set an inflection point and then use it to generate a transfer function, but even in this case, the luminance component near the inflection point decreases the representation range due to the linearity of the curve. There was a problem.

That is, the conventional gamma correction method forms a 1: 1 correspondence between the input luminance and the output luminance, so that increasing the expression range of the portion to increase the contrast decreases the expression range of the other portion, thus inevitably a specific portion. There was a structural problem that the loss of contrast must occur.

In addition, all of the conventional gamma correction methods adjust only the luminance component of the output image by considering only the luminance component of the input image of each pixel, and do not consider the correlation with neighboring pixels, thereby reducing local contrast. There was a problem. That is, even though the luminance is controlled compared with the conventional art, there is a problem in that an output image having a lowered sharpness is generated because a portion such as an edge is not clear.

In order to solve such a problem, the digital image processing apparatus 100 according to the exemplary embodiment of the present invention creates a 1: multi-corresponding function in consideration of the correlation with the peripheral pixels when generating the nonlinear transfer function, thereby generating the peripheral pixel. By performing different gamma correction in accordance with the correlation with each other, it is characterized by improving the local contrast and reducing the decrease in the expression range around the inflection point.

That is, as shown in FIG. 1, if the existing transfer function can be expressed in a two-dimensional space, as shown in FIG. 7, the digital image processing apparatus 100 according to the exemplary embodiment of the present invention may input an input luminance component and a peripheral area. The three-dimensional gamma correction extended to the three-dimensional space is performed by adding correlation with the pixels as one axis. That is, in the two-dimensional space of FIG. 1, the x axis represents the input luminance component Y _in , and the y axis represents the output luminance component Y _out . In contrast, in the three-dimensional space of FIG. 7, the x-axis represents the input luminance component Y _in , the y-axis represents the correlation (Y _relation ) between the input luminance component and peripheral pixels, and the z-axis represents the output luminance component ( Y _out ) so that different gamma corrections can be performed according to correlations with neighboring pixels.

To this end, the digital signal processor 130 of the digital image processing apparatus 100 of the present invention includes a gamma table generator 131, a contrast corrector 132, a saturation corrector 133, and a controller 134. It includes.

The gamma table generator 131 generates a table for three-dimensional gamma correction under the control of the controller 134. The gamma table generator 131 includes a luminance component extractor 131a, a peripheral relation definition unit 131b, a transfer function generator 131c, and a high frequency component reconstruction coefficient determiner 131d.

In more detail, the luminance component extractor 131a extracts the luminance component from the input image under the control of the controller 134. In detail, the luminance component is a component related to brightness, and the color does not change even if it is changed. If you want to improve the contrast of the image, rather than directly adjust the R, G, and B components in the RGB color space, consider the characteristic that the human eye is particularly sensitive to changes in brightness. After the improvement, a method of adjusting the R, G, and B components in consideration of the change amount of the luminance component is mainly used. Since a process of converting an RGB image into a YCbCr component is conventionally known, its detailed description will be omitted.

The peripheral relation definition unit 131b defines the Y _relation under the control of the controller 134. Here, Y _relation is a function considering a _relationship with neighboring pixels and is a function used to generate a transfer function for 3D gamma correction which will be described later. Such a Y _relation can be obtained by Equation 3 below.

Here, Y _neighborhood represents the luminance value of the neighboring pixels, and R is a function representing the relationship between the pixel of the current position and the neighboring pixel. For example, the function R in consideration of pixels immediately adjacent in the up, down, left, right, and diagonal directions can be obtained by Equation 4 below.

Here, Y (i, j) represents the luminance value of the current pixel, Y (i ± 1, j ± 1) represents the luminance value of the peripheral pixels of the current pixel. On the other hand, the α values represent weighting coefficients for the influence of the surrounding pixels, and in general, Gaussian mean filters or geometric mean filter coefficients are mainly used. That is, the Y _relation function representing the relationship between the current pixel and the neighboring pixel is defined by calculating the input luminance value and the weighting coefficient of the current pixel and the neighboring pixels. Here, the α values are values that can be obtained empirically by experimental data.

Here, in Equation 4, the Y _relation function is illustrated as being defined from the relationship between the current pixel and eight pixels surrounding the current pixel, but the inventive concept is not limited thereto. That is, the Y _relation function may be defined as a relationship between the current pixel and four pixels in the top, bottom, left, and right sides of the current pixel. Further, the Y _relation function may be further added using a matrix such as 5 * 5 or 7 * 7. It is also possible to define the relationship with many surrounding pixels.

The transfer function generator 131c generates a transfer function T for three-dimensional gamma correction under the control of the controller 134. That is, in the digital image processing apparatus 100 according to an embodiment of the present invention, the luminance value of the output image is calculated by considering the correlation between the luminance of the input image and the neighboring pixels. The transfer function T can be expressed as Equation 5 below.

Herein, Y _in is a luminance value of the input image, and Y _out is a luminance value of the output image. In addition, T is a transfer function, which is a nonlinear curve, and Y _relation is a function in consideration of the relationship with the peripheral pixel defined by Equation 3 and Equation 4 above. That is, a gamma table for three-dimensional gamma correction is generated by generating a transfer function considering a relationship between luminance values of an input image and surrounding pixels. Here, the function T can be obtained by Equation 6 below.

Here, n is a normalized constant for converting Y _{in to} have a value between 0 and 1, Γ is a gamma correction coefficient, and ω is a coefficient for adjusting the degree of correction using the relationship with surrounding pixels. Therefore, even if the luminance value Y _in of the input image is constant, the luminance value Y _out of the output image has various different results according to the relation value (Y _relation ) with the surrounding pixels, thereby providing a clearer correction result. Can be obtained. In other words, by generating the transfer function T constituting the nonlinear curve in this way, it is possible to perform brightness adjustment to increase the contrast of the dark part without losing the contrast of the light. Herein, the n, Γ, and ω values are values that can be obtained empirically by experimental data.

The gamma table generator 131 may further include a high frequency component recovery coefficient determiner 131d. The high frequency component recovery coefficient determiner 131d determines the high frequency component recovery coefficient under the control of the controller 134. In detail, the high frequency component recovery coefficient determiner 131d determines a recovery coefficient for additionally restoring a high frequency component such as an edge. In other words, it serves as a kind of high pass filter for restoring high frequency components. By restoring the high frequency component as described above, the detailed information of the output image reduced compared to the input image can be restored, and thus an output image with improved clarity can be obtained. Here, the high frequency component function S can be obtained by the following equation.

Here, κ is a coefficient that determines the degree of restoration of the high frequency component, and is a value that can be obtained empirically by experimental data.

In addition to the high frequency component recovery function S, the function T defined in Equation 6 may be redefined as follows.

As described above, the luminance component extracting unit 131a, the peripheral relation defining unit 131b, the transfer function generating unit 131c, and the high frequency component reconstruction coefficient determining unit 131d of the gamma table generating unit 131 are provided. As a result, a table for three-dimensional gamma correction as shown in FIG. 7 is generated.

Meanwhile, the contrast corrector 132 includes a brightness corrector 132a and a high frequency component restorer 132b. The contrast correction unit 132 corrects and outputs an input luminance level of an image file based on the table for three-dimensional gamma correction generated by the gamma table generator 131 described above under the control of the controller 134. .

The brightness correcting unit 132a performs brightness adjustment by correcting the luminance component under the control of the controller 134. In detail, the brightness corrector 132a adjusts the brightness of the output image by correcting the luminance component of the input image through a transfer function T for 3D gamma correction defined by Equation 6 described above.

The high frequency component corrector 132b restores the high frequency component under the control of the controller 134 to perform contrast adjustment. In detail, the high frequency component correcting unit 132b adds the high frequency component function S defined by the high frequency component reconstruction coefficient determining unit 131d to Equation 6 and redefined in Equation 8 for the 3D gamma correction. Through the transfer function T, the brightness component of the input image is corrected to adjust the brightness of the output image.

On the other hand, when the brightness adjustment through the correction of the luminance component is completed to improve the contrast, the saturation correction unit 133, under the control of the control unit 134, corrects the saturation of the reduced color according to the change amount of the luminance component. In detail, in the YCbCr data, when only the luminance component, that is, the Y component, is corrected while the color component, that is, the Cb and Cr components are left as it is, an image with reduced saturation is output as if the water is dropped by adding a lot of water to the paint. In this case, the user may observe the disadvantage that the saturation is reduced rather than the advantage that the contrast is improved to the naked eye. In order to solve this problem, the present invention may further include a saturation correction unit 133 for correcting saturation after the correction of the luminance component.

When the saturation correction unit 133 outputs the image in the RGB format, the saturation of the output image is corrected according to Equation 8 below, and when the saturation correction unit 133 outputs the image in the YCbCr format, Equation 9 corrects the saturation of the output image.

Where C _in and C _out are the color component values of the input and output, respectively, and C _mid is the median value of the color range (eg, 0 to 255) that can be expressed by the digital image processing apparatus (eg, 128). Indicates. Meanwhile, rgb _p and c _p are parameters of Equations 8 and 9, respectively, and are values that can be obtained empirically by experimental data.

According to the present invention, when the nonlinear transfer function is generated, a 1: multi correspondence function is created in consideration of correlations with neighboring pixels, and different gamma corrections are performed according to correlations with neighboring pixels. It is possible to obtain the effect of improving the contrast and reducing the reduction of the expression range near the inflection point.

Hereinafter, the resultant image of applying the conventional gamma correction and the resultant image of applying the gamma correction according to the present invention will be compared in detail.

The result of performing gamma correction on the original image as shown in FIG. 8A using the conventional two-dimensional gamma correction transfer function as shown in FIG. 9A is shown in FIG. 8B. That is, when gamma correction is performed by making the gamma (Γ) value smaller than 1 in order to make the detailed information of the arm unit 160a visible in the original image as shown in FIG. 8A, the arm unit 160b becomes brighter than the original as shown in FIG. 8B. Although the identification of the image becomes easy, the list 150b becomes darker so that the identification of the image becomes difficult.

On the other hand, the result of performing gamma correction on the original image as shown in FIG. 8A using the 3D gamma correction transfer function generated by the digital image processing apparatus according to the embodiment as shown in FIG. 9B is shown in FIG. 8C. That is, in the original image as shown in FIG. 8A, the dark portion 160c is brighter than the original image to facilitate identification of the image, and the gamma correction is performed so that the roster 150c also appears more clearly than the original image. That is, compared to FIG. 8B, FIG. 8C shows that the bright region is not saturated even though the dark region is brightly corrected, and thus, a more sharp back light correction result can be obtained.

In comparison with FIGS. 9A and 9B, since the luminance component of the input image and the luminance component of the output image are 1: 1 correspondence in FIG. 9A, the luminance component of the input image is determined, regardless of the relationship with the surrounding pixels. The output value is determined. In contrast, in FIG. 9B, the luminance component of the input image and the luminance component of the output image correspond to one-to-one correspondence, so that even when the luminance component of the input image is the same, the luminance component of the output image may have different luminance components according to the relationship with surrounding pixels. As a result, a clearer correction result can be obtained.

Next, a digital image processing method according to the present invention will be described in detail with reference to FIG. 10. The image processing method according to the present invention may be performed in the image processing apparatus as shown in FIG. 5. According to an embodiment, the main algorithm of the operation method may be performed by the digital signal processor 130 with the help of peripheral components in the apparatus. Can be performed internally.

Referring to FIG. 10, the control method of the digital image processing apparatus according to the present invention may include extracting luminance components from an input image (S110), defining a relationship with surrounding pixels (S120), and a nonlinear transfer function. Generating (S130), determining a high frequency component recovery coefficient (S140), correcting image brightness (S150), restoring a high frequency component (S160), and correcting saturation (Step S170).

In detail, the control method of the digital image processing apparatus according to the exemplary embodiment of the present invention creates a 1: multi-corresponding function in consideration of the correlation with the surrounding pixels when generating the nonlinear transfer function, By performing different gamma correction according to the present invention, the local contrast is improved, and the reduction in the expression range near the inflection point is characterized in that the characteristics are reduced.

To this end, first, a table for 3D gamma correction is generated.

In order to generate a table for three-dimensional gamma correction, first, a luminance component is extracted from the input image (step S110). In detail, the luminance component is a component related to brightness, and the color does not change even when it is changed. When the contrast of the image is to be improved, the human eye is not directly controlled by the R, G, and B components in the RGB color space. In consideration of the characteristic of being particularly sensitive to changes in brightness, a method of adjusting the luminance component first to improve contrast and then adjusting the R, G and B components in consideration of the change amount of the luminance component is mainly used. Since a process of converting an RGB image into a YCbCr component is conventionally known, its detailed description will be omitted here.

Next, in order to define the relationship with the surrounding pixels, a Y _relation which is a function considering the relationship with the surrounding pixels is defined (step S120). The Y _relation is a function used to generate a transfer function for three-dimensional gamma correction. Such a Y _relation can be obtained by using Equations 3 and 4 as described above.

Next, the nonlinear transfer function T is generated using the Y _relation function (step S130). T, a nonlinear transfer function, is a transfer function for three-dimensional gamma correction. It is a 1: multi-correspondence function that calculates the luminance value of the output image by considering the luminance value of the input image and the correlation with surrounding pixels. to be. T, which is such a nonlinear transfer function, can be obtained by using Equations 5 and 6 as described above. By generating the transfer function T constituting the nonlinear curve in this way, it is possible to perform brightness adjustment to increase the contrast of the dark portion without losing the contrast of the light.

Next, the high frequency component recovery coefficient is determined (step S140). In detail, by restoring the high frequency component by determining a recovery coefficient for additionally restoring the high frequency component such as an edge, it is possible to restore the detail information of the output image, which is reduced compared to the input image, and thus improves the sharpness of the output. You can get a video. Here, the high frequency component function S can be obtained by Equation 7 as described above. And, by adding the high frequency component recovery function S, the nonlinear transfer function T defined in Equation 6 may be redefined as in Equation 8 described above.

The table for three-dimensional gamma correction is generated through the above-described step S110 to step S140.

Next, the input luminance level of the image file is corrected and output based on the generated 3D gamma correction table.

To this end, first, the brightness of the image is corrected (S150). That is, the brightness component of the output image is adjusted by correcting the luminance component of the input image through a transfer function T for the three-dimensional gamma correction defined by Equation (6).

Next, the high frequency component is restored (step S160). That is, the above-described equation (6), the high-frequency component function S defined in the step S140 is added to the luminance component of the input image through a transfer function T for three-dimensional gamma correction, which is redefined by Equation (8) To adjust the brightness of the output image.

The input luminance level of the image file is corrected and output through the above-described steps S150 and S160.

Finally, the saturation of the reduced color according to the change amount of the luminance component is corrected (step S170). In detail, in the YCbCr data, when only the luminance component, that is, the Y component, is corrected while the color component, that is, the Cb and Cr components are left as it is, an image with reduced saturation is output as if the water is dropped by adding a lot of water to the paint. In this case, the user may observe the disadvantage that the saturation is reduced rather than the advantage that the contrast is improved to the naked eye. In order to solve this problem, in the present invention, the chroma can be corrected after the correction of the luminance component. In this case, when the image is output in the RGB format, the saturation of the output image is corrected according to Equation 8 described above, and when the image is output in the YCbCr format, the saturation of the output image is corrected according to Equation 9 described above.

According to the present invention, when the nonlinear transfer function is generated, a 1: multi correspondence function is created in consideration of correlations with neighboring pixels, and different gamma corrections are performed according to correlations with neighboring pixels. It is possible to obtain the effect of improving the contrast and reducing the reduction of the expression range near the inflection point.

So far I looked at the center of the preferred embodiment for the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

1 is a diagram illustrating a conventional gamma correction transfer function.

FIG. 2 is a diagram illustrating an image in which gamma correction is performed using the gamma correction transfer function of FIG. 1.

3 is a perspective view illustrating a front side and an upper side of a digital image processing apparatus according to an exemplary embodiment of the present invention.

FIG. 4 is a rear view illustrating a rear shape of the digital image processing apparatus of FIG. 3.

FIG. 5 is a block diagram illustrating a configuration of the digital image processing apparatus illustrated in FIGS. 3 and 4.

FIG. 6 is a detailed block diagram of the digital signal processor of FIG. 5.

7 is a diagram illustrating a three-dimensional gamma table according to an embodiment of the present invention.

8A is a diagram illustrating an original image.

FIG. 8B is a diagram illustrating an image in which gamma correction is performed on the original image of FIG. 8A by using a conventional gamma correction transfer function.

FIG. 8C is a diagram illustrating an image in which gamma correction is performed on an original image of FIG. 8A by using a gamma correction transfer function according to an embodiment of the present invention.

FIG. 9A illustrates a conventional gamma correction transfer function used in FIG. 8B.

FIG. 9B is a diagram illustrating a gamma correction transfer function according to one embodiment of the present invention used in FIG. 8C.

10 is a flowchart illustrating a control method of a digital image processing apparatus according to the present invention.

<Explanation of symbols for the main parts of the drawings>

100: digital image processing apparatus 121: user input unit

123: imaging unit 125: image processing unit

127: storage unit 130: digital signal processing unit

131: gamma table generator 132: contrast correction unit

133: saturation correction unit 134: control unit

Claims (23)

delete A gamma table generator for generating a three-dimensional gamma correction table; And A digital image processing apparatus comprising a contrast correction unit for correcting an input luminance component (Yin) of an image file to an output luminance component (Yout) by the three-dimensional gamma correction table generated by the gamma table generator. And the gamma table generator generates the 3D gamma correction table according to a correlation between each pixel of the digital image processing apparatus and neighboring pixels. A gamma table generator for generating a three-dimensional gamma correction table; And A contrast correction unit for correcting an input luminance component (Yin) of an image file to an output luminance component (Yout) by the three-dimensional gamma correction table generated by the gamma table generator, The three axes of the three-dimensional gamma correction table respectively represent the input luminance component (Yin), the correlation between the input luminance component and its surrounding pixels, and the output luminance component (Yout). Processing unit. delete A gamma table generator for generating a three-dimensional gamma correction table; And A contrast correction unit for correcting an input luminance component (Yin) of an image file to an output luminance component (Yout) by the three-dimensional gamma correction table generated by the gamma table generator, The gamma table generator, A luminance component extractor which extracts the input luminance component from the image file; A peripheral relationship defining unit defining a correlation between an input luminance component of each pixel and input luminance components of peripheral pixels of each pixel; And And a transfer function generator for generating a transfer function for correcting the 3D gamma using the correlation. Claim 6 has been abandoned due to the setting registration fee. 6. The method of claim 5, A correlation between an input luminance component of each pixel and input luminance components of peripheral pixels of each pixel is determined by an input luminance component of each pixel and input luminance components of peripheral pixels of each pixel. Digital image processing apparatus characterized in that it is defined by calculating the weight of. Claim 7 has been abandoned due to the setting registration fee. 6. The method of claim 5, And the transfer function calculates an output luminance component in consideration of the input luminance component of each pixel and the correlation. Claim 8 was abandoned when the registration fee was paid. 6. The method of claim 5, The gamma table generator further includes a high frequency component recovery coefficient determiner configured to determine a high frequency component recovery coefficient for restoring a high frequency component such as an edge in the input image. Claim 9 has been abandoned due to the setting registration fee. 9. The method of claim 8, And a high frequency component recovery function generated by the high frequency component recovery coefficient determiner is added to the transfer function. Claim 10 has been abandoned due to the setting registration fee. 6. The method of claim 5, The contrast correction unit may include a brightness correction unit that adjusts the brightness of the output image by correcting the luminance component of the input image through the transfer function. Claim 11 was abandoned when the registration fee was paid. 9. The method of claim 8, The contrast correction unit may further include a high frequency component restoration unit which restores a high frequency component such as an edge in the input image by using a high frequency component restoration function generated by the high frequency component restoration coefficient determiner. Digital image processing device. Claim 12 is abandoned in setting registration fee. The method according to any one of claims 2, 3 and 5 to 11, The digital image processing apparatus may further include a saturation correction unit to correct saturation of the color of the reduced input image according to a difference between the input luminance component and the output luminance component. delete Generating a three-dimensional gamma correction table; And A control method of a digital image processing apparatus comprising correcting an input luminance component Yin of an image file with an output luminance component Yout by using the generated three-dimensional gamma correction table. Generating the three-dimensional gamma correction table, And generating the three-dimensional gamma correction table according to a correlation between each pixel of the digital image processing apparatus and its neighboring pixels. Generating a three-dimensional gamma correction table; And Correcting the input luminance component (Yin) of the image file with the output luminance component (Yout) by the generated three-dimensional gamma correction table, Three axes of the generated three-dimensional gamma correction table represent the input luminance component (Yin), the correlation between the input luminance component and its surrounding pixels, and the output luminance component (Yout), respectively. Control method of digital image processing device. delete Generating a three-dimensional gamma correction table; And Correcting the input luminance component (Yin) of the image file with the output luminance component (Yout) by the generated three-dimensional gamma correction table, Generating the three-dimensional gamma correction table, Extracting the input luminance component from the image file; Defining a correlation between an input luminance component of each pixel and input luminance components of peripheral pixels of each pixel; And And generating a transfer function for the 3D gamma correction using the correlation. Claim 18 has been abandoned due to the setting registration fee. 18. The method of claim 17, Defining the correlation (Yrelation), And a predetermined weight is calculated on the input luminance component of each pixel and the input luminance components of peripheral pixels of each pixel. Claim 19 is abandoned in setting registration fee. 18. The method of claim 17, Generating the transfer function (transfer function), And calculating the output luminance component in consideration of the input luminance component of each pixel and the correlation. Claim 20 has been abandoned due to the setting registration fee. 18. The method of claim 17, Determining a high frequency component reconstruction coefficient for reconstructing a high frequency component such as an edge in the input image, wherein a high frequency component reconstruction function generated by the high frequency component reconstruction coefficient is added to the transfer function. A control method of a digital image processing apparatus. Claim 21 has been abandoned due to the setting registration fee. 18. The method of claim 17, The step of correcting the input luminance component (Yin) of the image file by the generated three-dimensional gamma correction table to convert the output luminance component (Yout), And adjusting the brightness of the output image by correcting the luminance component of the input image through the transfer function. Claim 22 is abandoned in setting registration fee. 21. The method of claim 20, The step of correcting the input luminance component (Yin) of the image file by the generated three-dimensional gamma correction table to convert the output luminance component (Yout), And restoring a high frequency component such as an edge from the input image by using the generated high frequency component restoring function. Claim 23 has been abandoned due to the setting registration fee. The method according to any one of claims 14, 15 and 17-22, And correcting the saturation of the color of the reduced input image according to the difference between the input luminance component and the output luminance component.

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