KR100892078B1 - Image brightness controlling apparatus and method thereof - Google Patents

Abstract

Disclosed is an image brightness adjusting apparatus and method for adjusting brightness sharpness of an output image according to brightness characteristics of an input image. The image brightness adjusting apparatus may include: a preprocessor configured to calculate an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And a tone mapping unit for mapping the offset table to the color data. According to the present invention, it is possible to adjust the dynamic range to be applied to the output image according to the range of pixel values and input variables of the input image.

Picture, brightness, adjustment, dynamic range

Description

Image brightness controlling apparatus and method

1 is a graph of a conversion function between an input image and an output image for applying histogram equalization.

2 is a schematic structural diagram of an imaging apparatus according to an embodiment of the present invention;

3 is a schematic configuration diagram of an image brightness adjusting device according to an embodiment of the present invention;

4 is a schematic configuration diagram of a preprocessor according to an embodiment of the present invention.

5 is a flowchart illustrating a method for adjusting image brightness in a preprocessor according to an embodiment of the present invention.

6A is an exemplary diagram illustrating an original image.

6B is an exemplary diagram illustrating an output image obtained by applying an image brightness adjusting method according to an embodiment of the present invention to an original image of FIG. 6A.

7A is another exemplary diagram illustrating an original image.

FIG. 7B is another exemplary diagram illustrating an output image obtained by applying an image brightness adjusting method according to an embodiment of the present invention to an original image of FIG. 7A; FIG.

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

200: video device

210: RGB-HSV converter

215: RGB-YUV Converter

220: video brightness control device

230: HSV-RGB converter

235: YUV-RGB converter

The present invention relates to an image brightness adjusting device, and more particularly, to an image brightness adjusting device and a method for improving the sharpness of the brightness of the entire image.

Conventional techniques for adjusting the dynamic range of an input image are as follows. Hereinafter, a case of an n-bit image will be described as an example.

(1) Contrast Enhancement

The dynamic range is adjusted to a value between 0 and 2 ⁿ -1 by applying the minimum pixel value and the maximum pixel value in the image to Equation 1 below.

Output = (2 ⁿ -1) × (Input-Min) / (Max-Min)

Here, Output is the pixel value of the output image, Input is the pixel value of the input image, Max is the maximum pixel value of the input image, Min is the minimum pixel value of the input image.

(2) Histogram Equalization

1 is a graph of a conversion function between an input image and an output image for applying histogram equalization.

First, a cumulative density function (CDF) for a pixel value in an image is obtained by using histogram information of the image. The scale of the cumulative density function is adjusted to 0 to 2 ⁿ −1 and used as the conversion function 100 of the input image and the output image.

When the number of specific pixel values is large, since the slope of the conversion function 100 is changed rapidly, there is an effect of increasing the dynamic range for the corresponding pixel value.

The above-described contrast enhancement or histogram equalization method always adjusts the dynamic range to a value between 0 and 2 ⁿ -1 regardless of the range of pixel values of the input image.

However, even though the range of pixel values of the input image is quite narrow, if the dynamic range is forcibly increased to a value between 0 and 2 ⁿ -1, the image quality does not improve, but rather the noise increases and the image looks quite unnatural. There is a problem.

Therefore, in the present invention, when the range of pixel values of the input image is narrow, the contrast enhancement method is effective. However, when the range of pixel values of the input image is wide, the histogram equalization method considering the distribution characteristics of the pixel values is more effective. The present invention provides an image brightness adjusting device and a method for properly combining them according to a range of pixel values of an input image.

In addition, the present invention adjusts the dynamic range to be applied to the output image according to the range of the pixel value of the input image, and the image brightness control device for improving the sharpness of the brightness by automatically considering how much to reflect the distribution characteristics of the image and its method To provide.

Other objects of the present invention will be readily understood through the following description.

According to an aspect of the present invention, there is provided an image brightness adjusting apparatus for adjusting the brightness sharpness of the output image according to the brightness characteristics of the input image.

An image brightness adjusting apparatus according to an embodiment may include: a preprocessor configured to calculate an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And a tone mapping unit for mapping the offset table to the color data.

Here, the color data is HSV data, and the preprocessor may adjust the dynamic range by using a V value of the HSV data.

Alternatively, the color data may be YUV data or YCbCr data, and the preprocessor may adjust the dynamic range by using a Y value of the color data.

The preprocessing unit may further include: a histogram obtaining unit that scales the brightness value to n-bit resolution and indicates a histogram of the number of cases where the brightness values appear for pixels of the input image, wherein n is a natural number. A CDF calculator for calculating a cumulative density function (CDF) by accumulating the histogram with respect to the brightness value, an image range setting unit for setting a predetermined region of the cumulative density function as an image range, and adjusting the image range and brightness. A stretching unit which stretches the brightness value of the input image by combining the intensities, and calculates a ratio of the brightness value to the input image from the cumulative density function, and offsets the brightness value from the ratio It may include an offset calculation unit for calculating a value).

The CDF calculator may normalize the cumulative density function corresponding to the brightness value to calculate a normalized cumulative density function (Normed_CDF) such that the maximum value is 2 ⁿ −1, which is the resolution of the brightness value.

The image range setting unit divides the cumulative density function value of an arbitrary pixel by the size of the input image, and sets the brightness value of the pixel corresponding to a boundary preset by the user or the global minimum value (global_min) and the total maximum value. Can be set to the value (global_max). The stretching unit may determine a dynamic range to be applied to an output image by combining the total minimum value and the total maximum value with the brightness control intensity preset or input from a user.

The offset calculator may calculate a ratio of the current brightness value to the input image from the cumulative density function values of the brightness values of the input image, and calculate the offset value from the ratio. The offset calculator may obtain the offset table by calculating the offset value for all the pixels of the input image.

According to another aspect of the present invention, there is provided an image brightness adjusting method in which the brightness sharpness of the output image is adjusted according to the brightness characteristic of the input image.

According to an embodiment, there is provided a method of controlling an image brightness, the method comprising: calculating an offset table for adjusting a dynamic range corresponding to an image range of an input image by using brightness values of color data of an input image; And mapping the offset table to the color data.

The color data may be HSV data, and the calculating of the offset table may adjust the dynamic range by using a V value of the HSV data.

Alternatively, the color data may be YUV data or YCbCr data, and the calculating of the offset table may adjust the dynamic range by using a Y value of the color data.

The calculating of the offset table may include: obtaining a histogram from a number of cases in which the brightness values appear for pixels of the input image; Calculating a cumulative density function of accumulating the histogram with respect to the brightness value; Setting a predetermined region of the cumulative density function as an image range; Stretching the brightness value of the input image by combining the image range and the brightness control intensity; Calculating a ratio of the brightness value to the input image from the cumulative density function; And calculating an offset value of the brightness value from the ratio.

In the obtaining of the histogram, the step of scaling the brightness value with n-bit resolution is preceded by the step of calculating the cumulative density function. The cumulative density function is normalized corresponding to the brightness value so that the maximum value is the resolution of the brightness value. The cumulative density function normalized to be 2 ^n- 1 can be calculated.

In the image range setting step, a value obtained by dividing a cumulative density function value of an arbitrary pixel by the size of the input image is set in advance or sets a brightness value of a pixel corresponding to a boundary input by a user to a total minimum value and a total maximum value. have. The stretching may determine a dynamic range to be applied to an output image by combining the total minimum value and the maximum maximum value with the brightness control intensity preset or input from a user.

The offset calculation may include calculating a ratio of the current brightness value to the input image from the cumulative density function values of the brightness values of the input image, and calculating the offset value from the ratio. In the offset calculating step, the offset table may be obtained by calculating the offset value for all the pixels of the input image.

According to another aspect of the present invention, a program of instructions that can be executed by a digital processing apparatus that adjusts the brightness sharpness of an output image according to the brightness characteristic of the input image is tangibly implemented and can be read by the digital processing apparatus. In a computer-readable recording medium, there is provided a computer-readable recording medium on which a program for performing the above-described image brightness adjusting method is recorded.

As the invention allows for various changes and numerous embodiments, particular embodiments will be illustrated in the drawings and described in detail in the written description. However, this is not intended to limit the present invention to specific embodiments, it should be understood to include all transformations, equivalents, and substitutes included in the spirit and scope of the present invention. In the following description of the present invention, if it is determined that the detailed description of the related known technology may obscure the gist of the present invention, the detailed description thereof will be omitted.

Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting of the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this application, the terms "comprise" or "have" are intended to indicate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, and one or more other features. It is to be understood that the present invention does not exclude the possibility of the presence or the addition of numbers, steps, operations, components, components, or a combination thereof.

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

2 is a schematic configuration diagram of an imaging apparatus according to an embodiment of the present invention, FIG. 3 is a schematic configuration diagram of an image brightness adjusting apparatus according to an embodiment of the present invention, and FIG. 4 is an embodiment of the present invention. FIG. 5 is a schematic structural diagram of a preprocessor according to an example, and FIG. 5 is a flowchart illustrating a method of controlling image brightness in a preprocessor according to an embodiment of the present invention.

The imaging device 200 includes an RGB-HSV converter 210, an image brightness controller 220, and an HSV-RGB converter 230. Or an RGB-YUV converter 215, an image brightness controller 220, and a YUV-RGB converter 235.

The imaging apparatus 200 according to an embodiment converts RGB data into HSV data among color data to adjust image brightness, and then converts the RGB data into RGB data.

The RGB-HSV converter 210 converts RGB data of the input image into HSV data. In general, the input image has RGB data as image information for each pixel. In order to adjust the brightness of an image according to an embodiment of the present invention, it is necessary to apply image information under an HSV color model.

The RGB color model expresses an arbitrary color by combining components of three colors of red (R), green (G), and blue (B), which are three primary colors of light. Any color is represented by three values of R, G, and B. If the three values of R, G, and B are 0 by applying the principle of additive mixing, the color becomes black.

The CMY color model uses three colors, Cyan, Magenta, and Yellow, which are the three primary colors of the color, as the primary colors, and an arbitrary color is expressed by a combination of these three colors. In this case, if the three values of C, M, and Y are 0 by applying the principle of subtractive mixing, which becomes dark as the color is synthesized, the color becomes white.

The HSV color model is a model that is relatively consistent with the human sense of color. Based on the six colors of RYGCBM, they are arranged at 60-degree intervals on the circumference, and the entire circumference is completed by creating a composite of adjacent primary colors by dividing them at equal intervals. The position on this color wheel is taken as the H value of Hue. The S value of saturation has a larger value toward the edge in the CIE chromaticity diagram, and when this value is 0, it becomes the white of the center. The V value of brightness represents the brightness of the color.

The RGB-HSV converter 210 converts pixel values (R, G, B values) of the input image corresponding to the RGB color model into pixel values (H, S, V values) corresponding to the HSV color model.

The H value represents a color, that is, a color type (a color component such as red, yellow, or blue), and expresses all possible colors in the 0 to 360 range. Normalized to 0-100%. The S value represents the saturation, that is, the sharpness of the color, is expressed in the range of 0 to 100%, and the smaller the value, the closer the achromatic color is. The V value represents the brightness, that is, the brightness of the color, and is expressed in the range of 0 to 100%. A lower value means a darker area and a higher value means a brighter area.

By using Equation 2 below, the RGB-HSV converter 210 performs RGB-HSV conversion.

Here, MAX represents the maximum value among the R, G, and B values of each pixel of the input image, and MIN represents the minimum value among the R, G, and B values of each pixel of the input image. Where H has a value between 0 and 360, and S and V vary between 0 and 1.

If MAX and MIN are equal (MAX = MIN, ie S = 0), H is undefined. This is because if the S value is 0, there is no color component in achromatic color. Also, if MAX is 0, S is undefined. This is because when the value of V is 0, it is pure black and has no color component or saturation component.

H, S, and V values of respective pixels of the input image may be obtained according to the conversion formula of Equation 2.

The image brightness controller 220 adjusts the sharpness of the brightness of the entire image using a V value among H, S, and V values of each pixel of the input image acquired by the RGB-HSV converter 210. The image brightness adjusting apparatus 220 includes a preprocessor 310 and a tone mapping unit 320 (see FIG. 3). The preprocessing part 310 obtains an offset table from the input image, and the tone mapping part 320 maps the obtained offset table to the input image. The image brightness adjusting device 220 will be described in detail later with reference to FIG. 3.

The HSV-RGB converter 230 converts the H, S, and V values for each pixel of the image in which the brightness value (V value) is adjusted by the image brightness controller 220 to R, G, and B values. This corresponds to the inverse of the conversion made in the RGB-HSV converter 210.

An example of the HSV-RGB conversion is as follows.

(1) If S is 0, the color is achromatic series, and R, G, and B follow the V value.

(2) When S is not 0, the following Equation 3 is used.

Here mod N is a function representing the remainder divided by N.

The imaging apparatus 200 converts an input image, which is data about an RGB color model, into an output image, which is also the same color model.

However, the image brightness adjusting apparatus 220 according to an embodiment of the present invention uses a V value which is a brightness value among HSV data regarding the HSV color model when adjusting the image brightness.

Alternatively, when adjusting the image brightness, the image brightness adjusting device 220 according to another embodiment of the present invention uses a Y value which is a brightness value among the YUV data regarding the YUV color model.

The YUV color model is a color model in which the human eye has the most sensitive characteristics to light intensity, and Y represents luminance and luminance, and U and V represent chromaticity.

The imaging apparatus 200 according to another embodiment includes an RGB-YUV converter 215 and a YUV-RGB converter 235.

The RGB-YUV converter 215 performs pixel values (R, G, and B values) of the input image corresponding to the RGB color model according to Equation 4 below. To).

Y = 0.299 × R + 0.587 × G + 0.114 × B

U = -0.1687 × R-0.3313 × G + 0.5 × B + 128

V = 0.5 × R-0.4187 × G-0.0813 × B + 128

Using the Y value obtained by Equation 4, the image brightness adjusting device 220 adjusts the image brightness according to a method described later.

The YUV-RGB converter 235 converts the Y, U, and V values of each pixel of the image in which the brightness value (Y value) is adjusted by the image brightness controller 220 to R, G, and B values. This corresponds to the inverse of the conversion performed by the RGB-YUV conversion unit 215, and is given by Equation 5 below.

R = Y + 1.370705 × (V-128)

G = Y-0.337633 × (U-128) -0.698001 × (V-128)

B = Y + 1.732446 × (U-128)

In addition, the image brightness adjusting apparatus 220 according to another embodiment of the present invention uses the Y value which is the brightness value among the YCbCr data regarding the YCbCr color model when adjusting the image brightness.

That is, in the present invention, the image brightness adjusting device 220 adjusts the image brightness by using the brightness value included in the color data, and those skilled in the art should understand that the present invention is applicable to the color data including the brightness value.

Hereinafter, for convenience of understanding and explanation of the present invention, description will be made based on HSV data among color data. The configuration and function of the image brightness adjusting device 220 that adjusts the image brightness using the brightness value (V value) will be described in detail.

Referring to FIG. 3, the preprocessor 310 includes a histogram acquirer 311, a CDF calculator 313, an image range setter 315, a stretcher 317, and an offset calculator 319. Hereinafter, it will be assumed that the input image has n-bit resolution.

The histogram obtaining unit 311 scales a V value, which is a brightness value, from 0 to 2 ⁿ -1 among H, S, and V values of each pixel of the input image, and displays corresponding V values for each pixel in the input image. The number is represented by a histogram.

The CDF calculator 313 calculates a cumulative density function (hereinafter, referred to as "CDF") that accumulates the histogram obtained by the histogram acquirer 311 when the brightness value is 0. The maximum value of the CDF is the size of the input image, i.e., (number of horizontal pixels) x (number of vertical pixels) when the brightness value is 2 ⁿ -1, which is the total number of pixels in the input image.

Since the maximum value of the above-described CDF is the size of the input image, that is, the total number of pixels in the input image, a normalized CDF (normalized CDF) that is normalized to the brightness value may be further calculated. That is, when the brightness value is 2 ⁿ -1, the normalization is normalized so that the maximum value is 2 ⁿ -1.

The image range setting unit 315 divides the CDF value of an arbitrary pixel by the size of the input image in order to find a distribution range of brightness values of the pixels of the input image. Set the brightness value to the global minimum (global_min) and the global maximum (global_max). The brightness value when the CDF value divided by the size of the input image corresponds to A (for example, 0.001) is the total minimum value, and the brightness value when B (for example, 0.999) is the overall maximum value. Can be set. Where A and B are one of real numbers between 0 and 1, and B is greater than A.

Selecting a range between the total minimum value and the total maximum value of the brightness values of the pixels of the input image is intended to exclude the influence of the splashing noise. In the case of a brightness value (eg, salt and pepper noise) having almost no ratio in the image, the value is ignored and the image processing is performed according to an embodiment of the present invention.

The stretching unit 317 combines the total minimum value and the maximum maximum value set by the image range setting unit 315 with a brightness control intensity which is a preset parameter or an input parameter input from a user, thereby increasing the brightness of the input image. Stretch the value.

That is, a minimum change value (modi_min), which is a change value of the total minimum value, and a maximum change value (modi_max), which is a change value of the total maximum value, are obtained, and the brightness value of each pixel of the input image positioned within the minimum value and the maximum maximum value is changed. And stretching so as to be within the change maximum. The change minimum value and change maximum value acquired here determine the dynamic range to be applied to the output image.

The offset calculator 319 calculates a ratio of the current brightness value from the CDF of the brightness values of the input image to the input image, and calculates an offset value from the ratio. The stretching unit 317 adds an offset value to the brightness value of the stretched image to obtain an offset table for the brightness values 0 to 2 ⁿ −1. In this case, by considering the degree of reflection of the distribution characteristics of the input image obtainable from the CDF, the brightness of the image may be improved according to the characteristics of the input image.

The tone mapping unit 320 performs tone mapping of brightness values of each pixel by applying the offset table calculated by the preprocessor 310 to the input image. The tone-mapped output image has an effect of improving the sharpness of the brightness to match the brightness distribution characteristic of the input image.

Hereinafter, a method of adjusting the image brightness by the image brightness adjusting device 220 will be described in detail with reference to FIG. 5. 5 is a flowchart illustrating a method for adjusting image brightness according to an embodiment of the present invention.

Table 1 above explains the meaning indicated by the terms used below. Referring to Table 1, a method of adjusting image brightness will be described.

The H, S, and V values of the input image are acquired through RGB-HSV conversion. Among these, the V value, that is, the brightness value, is adjusted below. Here, it is assumed that the brightness value of the input image has n-bit resolution.

The brightness value of each pixel of the input image has a value between 0 and 1. The histogram is obtained by scaling it from 0 to 2 ⁿ −1 and expressing the number of cases in which corresponding values appear in the input image (step S510).

A cumulative density function (CDF) obtained by accumulating the obtained histograms in order of brightness values (from 0 to 2 ⁿ −1) is obtained (step S520). Here, the maximum value is the size of the input image, that is, the number of horizontal pixels width × height, and the total number of pixels in the input image when the brightness value is 2 ⁿ −1.

An image range of pixels of the input image is set (step S530). In order to find the distribution range of the brightness value of the input image, the CDF value of an arbitrary pixel is divided by the size of the input image, and the brightness value of the pixel corresponding to the boundary input by the user is preset or global_min Set to the maximum value (global_max).

The brightness value when the CDF value divided by the size of the input image corresponds to A (for example, 0.001) is the total minimum value, and the brightness value when B (for example, 0.999) is the overall maximum value. Can be set. Where A and B are one of real numbers between 0 and 1, and B is greater than A.

In addition, a seven tap method can be used to smooth the CDF curve. The 7-tap method uses an average of brightness values of the left 3 pixels, the right 3 pixels, and the current pixel around the current pixel. This way, the CDF curve can be smoother.

In addition, since the maximum value of the above-described CDF is the size of the input image, that is, the total number of pixels in the input image, a normalized CDF (normed_CDF) that is normalized to the brightness value may be further calculated. That is, when the brightness value is 2 ⁿ -1, the normalization is normalized so that the maximum value is 2 ⁿ -1.

The brightness value of the input image is stretched by combining the total minimum value and the maximum maximum value previously set and the brightness control intensity which is a preset input parameter or an input parameter input from the user (step S540). That is, a minimum change value (modi_min), which is a change value of the total minimum value, and a change maximum value (modi_max), which is a change value of the total maximum value, are acquired, and the brightness value of each pixel of the input image positioned within the minimum value and the maximum maximum value is changed. And stretching so as to be within the change maximum. The change minimum value modi_min and the change maximum value modi_max obtained here determine the dynamic range to be applied to the output image.

For example, the change minimum value modi_min and the change maximum value modi_max may be obtained as in Equation 6 below.

modi_min = global_min-(global_min-0) × strength

modi_max = global_max + ((2 ⁿ -1) -global_max) × strength

Here, the brightness adjustment strength is preset as an input variable or input by a user. This parameter determines the intensity of adjustment of the brightness range and / or brightness value of the image.

After that, an offset table is obtained (step S550).

To this end, first, a first linear curve for stretching the input image is obtained (step S552). Then, a second linear curve is obtained from the normalized CDF within the global minimum value global_min and the global maximum value global_max (step S554).

Examples of the first linear curve and the second linear curve are shown in Equation 7 below.

y = gain1 × x + offset1 (first linear curve)

y = gain2 × x + offset2 (second linear curve)

gain1 = (modi_max-modi_min) / (global_max-global_min)

offset1 = -gain1 × global_min + modi_min

gain2 = (Normed_CDF (1, global_max + 1)-Normed_CDF (1, global_min + 1)) / (global_max-global_min)

offset2 = -gain2 × global_min + Normed_CDF (1, global_min + 1))

Here, x is a brightness value of the input image, y is a stretched brightness value, gain1 and gain2 are the slope of the linear curve, offset1 and offset2 are the y intercept of the linear curve. Normed_CDF (1, a) means a CDF value corresponding to (1, a) in the 1 × 2 ⁿ array.

Using the gain1, gain2, offset1 and offset2 obtained by the equation (7) to generate an offset table for the brightness value of 0 to 2 ⁿ -1 (step S556).

Based on the previously set minimum and maximum maximum values, if the brightness value of any pixel is smaller than the total minimum value, set the brightness value of the pixel to the total minimum value. It is set to the total maximum value (see Equation 8 below).

for i = 0: 2 ⁿ -1

if i <global_min

value = global_min;

else if i> global_max

value = global_max;

else

value = i;

Here, a brightness value stretched_pixel stretched by the first linear curve of Equation 7 is obtained, and an offset table is obtained by Equation 9 below.

offset_table (1, i + 1) = stretched_pixel + (Normed_CDF (1, value + 1)-(gain2 × value + offset2)) × alpha

Here, offset_table (1, i + 1) is an offset value of an offset table corresponding to (1, i + 1) in an 1 × 2 ⁿ array, and alpha is obtained by Equation 10 below.

alpha = strength × 0.4 × (1- (value-30) ² / (2 ⁿ -1) ² )

By considering the degree of reflection of the distribution characteristic of the input image obtainable from the CDF, that is, alpha, it is possible to improve the sharpness of the brightness in accordance with the characteristics of the input image.

The offset table calculated by the above method is applied to the input image to tone mapping the brightness values of the pixels (step S560). The tone-mapped output image has an effect of improving the sharpness of the brightness to match the brightness distribution characteristic of the input image.

FIG. 6A illustrates an original image, and FIG. 6B illustrates an output image obtained by applying an image brightness adjusting method according to an embodiment of the present invention to the original image of FIG. 6A. FIG. 7A illustrates an original image, and FIG. 7B is another exemplary diagram illustrating an output image obtained by applying an image brightness adjusting method according to an embodiment of the present invention to the original image of FIG. 7A. As compared with the original image shown in FIGS. 6A and 7A, it may be confirmed that the brightness of the output image shown in FIGS. 6B and 7B is improved.

On the other hand, the above-described image brightness adjustment method can be created by a computer program. Codes and code segments constituting the program can be easily deduced by computer programmers in the art. In addition, the program is stored in a computer readable media (computer readable media), and is read and executed by a computer to implement the image brightness adjustment method. The information storage medium includes a magnetic recording medium, an optical recording medium and a carrier wave medium.

As described above, the image brightness adjusting apparatus and the method according to the present invention can adjust the dynamic range to be applied to the output image according to the range of pixel values and input variables of the input image.

In addition, it is possible to improve the sharpness of the brightness to match the characteristics of the input image by automatically considering how much to reflect the distribution characteristics of the image.

In addition, much lower noise and natural image quality can be obtained as compared with the conventional method.

Although the above has been described with reference to a preferred embodiment of the present invention, those skilled in the art to which the present invention pertains without departing from the spirit and scope of the present invention as set forth in the claims below It will be appreciated that modifications and variations can be made.

Claims (19)

A preprocessor configured to calculate an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And Tone mapping unit for mapping the offset table to the color data, The preprocessor sets a brightness range between a global minimum value (global_min) and a global maximum value (global_max) corresponding to a boundary set in advance or input by a user among the brightness values of the pixels of the input image as an image range, The preprocessing unit may include: a stretching unit which stretches the brightness value of the input image by combining the image range and the brightness control intensity; and And an offset calculator configured to calculate a ratio of the brightness value to the input image and to calculate an offset value of the brightness value from the ratio. A preprocessor configured to calculate an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And Tone mapping unit for mapping the offset table to the color data, The color data is HSV data, and the preprocessor adjusts the dynamic range using the V value of the HSV data. A preprocessor configured to calculate an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And Tone mapping unit for mapping the offset table to the color data, The color data is YUV data or YCbCr data, and the pre-processing unit adjusts the dynamic range by using the Y value of the color data. The method of claim 1, The preprocessing unit, A histogram obtainer that scales the brightness value to n-bit resolution and represents a histogram of the number of cases where the brightness values appear for pixels of the input image, wherein n is a natural number; A CDF calculator for calculating a cumulative density function (CDF) obtained by accumulating the histogram with respect to the brightness value; And an image range setting unit configured to set, as an image range, a brightness value region between a total minimum value and a total maximum value corresponding to a boundary preset in the cumulative density function or input by a user. The method of claim 4, wherein The CDF calculation unit normalizes the cumulative density function corresponding to the brightness value and calculates a normalized cumulative density function (Normed_CDF) such that the maximum value is 2 ⁿ -1, which is the resolution of the brightness value. Regulator. The method of claim 4, wherein The image range setting unit divides a cumulative density function value of an arbitrary pixel by the size of the input image and sets a brightness value of a pixel corresponding to a boundary preset by a user or a user input to a global minimum value (global_min) and a global maximum value ( global_max). The method of claim 6, And the stretching unit determines a dynamic range to be applied to an output image by combining the total minimum value and the maximum maximum value with the brightness control intensity preset or input from a user. The method of claim 4, wherein And the offset calculator calculates a ratio of a current brightness value to the input image based on cumulative density function values of respective brightness values of the input image, and calculates the offset value from the ratio. The method of claim 8, And the offset calculator calculates the offset values for all the pixels of the input image to obtain the offset table. Calculating an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And Mapping the offset table to the color data; The offset table calculating step, Setting, as an image range, a brightness value region between a global minimum value (global_min) and a global maximum value (global_max) corresponding to a boundary set in advance or input by a user among the brightness values of pixels of the input image; And stretching the brightness value of the input image by combining the image range and the brightness control intensity. Calculating an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And Mapping the offset table to the color data; The color data is HSV data, The calculating of the offset table may include adjusting the dynamic range using a V value of the HSV data. Calculating an offset table for adjusting a dynamic range corresponding to an image range of the input image by using brightness values of color data of an input image; And Mapping the offset table to the color data; The color data is YUV data or YCbCr data, The calculating of the offset table may include adjusting the dynamic range using a Y value of the color data. The method of claim 10, The offset table calculating step, Obtaining a histogram from the number of cases in which the brightness values appear for the pixels of the input image; Calculating a cumulative density function of accumulating the histogram with respect to the brightness value; And setting a brightness value region between an overall minimum value and an overall maximum value corresponding to a boundary set in advance or input by a user among the cumulative density functions as an image range. The method of claim 13, The histogram acquiring step is preceded by scaling the brightness value to n bit resolution. In the calculating of the cumulative density function, the cumulative density function is normalized according to the brightness value and the normalized cumulative density function is calculated so that the maximum value becomes 2 ⁿ -1, which is the resolution of the brightness value. Way. The method of claim 13, In the image range setting step, a value obtained by dividing a cumulative density function value of an arbitrary pixel by the size of the input image is preset or sets a brightness value of a pixel corresponding to a boundary input by a user to an overall minimum value and an overall maximum value. How to adjust the image brightness, characterized in that. The method of claim 15, The stretching may include determining the dynamic range to be applied to an output image by combining the total minimum value and the total maximum value with the brightness control intensity preset or received from a user. The method of claim 13, The calculating of the offset may include calculating a ratio of a current brightness value to the input image based on cumulative density function values of respective brightness values of the input image, and calculating the offset value from the ratio. The method of claim 17, And calculating the offset to obtain the offset table by calculating the offset value for all the pixels of the input image. In the computer-readable recording medium that is tangibly embodied and program of instructions that can be executed by the digital processing device for adjusting the brightness sharpness of the output image according to the brightness characteristics of the input image , A computer-readable recording medium having recorded thereon a program for performing the image brightness adjusting method according to any one of claims 10 to 18.

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