KR100915970B1 - Method and apparatus for compensating color of image obtained from image sensor - Google Patents

Abstract

A method and apparatus for correcting the color of an image obtained by an image sensor is disclosed. The color correction method according to the present invention includes determining whether each pixel in the image is a defective pixel, and weighting a weight corresponding to a homogeneous pixel located in the periphery of the first pixel, which is the pixel determined as the defective pixel, and the first pixel. Computing using the color values of the pixels around the first pixel and the pixels around the same pixel without using the color value of, the same pixel positioned around the second pixel which is a pixel determined to be not a bad pixel Calculating a weight corresponding to the color value of the second pixel by using the color value of the second pixel and the color values of the pixels around the second pixel and the pixels around the same pixel, according to the calculated weight. A weighted average of the color values of the same pixel positioned at, but including the color value of the second pixel except the color value of the first pixel, and the weighted average of the color of the first pixel or the second pixel And correcting the value. According to the present invention, it is possible to effectively correct the color of the image in consideration of the characteristics of the bad pixels and noise included in the image acquired by the image sensor using one filter.

Color correction, image sensor, bad pixels, noise

Description

Method and apparatus for compensating color of image obtained from image sensor

The present invention relates to a method and apparatus for correcting color of an image obtained by an image sensor, and more particularly, to a color correction method and apparatus for effectively correcting color in consideration of characteristics of defective pixels and noise included in an image. .

In an image acquired by a CCD or CMOS sensor mainly used as an image sensor, defective pixels are generated due to manufacturing defects or inadvertent use of the image sensor. In addition to the defective pixels, noises such as photon shot noise, dark-current shot noise, reset noise, and thermal noise are generated due to light quantity or heat due to the characteristics of the image sensor. Bad pixels or noise have a great influence on the color interpolation process, which is a process for obtaining a full color image, and when color interpolation is performed using color information including bad pixels or noise, the resultant image is greatly visually disturbing. Noise or artifacts are caused. In particular, in the case of a low-light image, the influence of bad pixels and noise is large, which greatly degrades the image quality of the image.

Therefore, removing bad pixels and noise is a very important process for obtaining a high quality image. Bad pixels and noise have different statistical characteristics. Bad pixels have the characteristics of Laplacian noise, like salt and pepper noise. The resulting noise is characterized by Gaussian noise. Therefore, a median filter is mainly used to remove bad pixels, and a weighted mean filter is mainly used to remove noise.

However, when the weighted average filter is used, bad pixels cannot be effectively removed, and when the median filter is used, noise due to the characteristics of the image sensor cannot be effectively removed.

The technical problem to be solved by the present invention is to provide a color correction method and apparatus for effectively correcting the color of the image in consideration of the characteristics of the bad pixels and noise included in the image obtained by the image sensor using one filter There is.

According to an aspect of the present invention, there is provided a method of correcting a color of an image obtained by an image sensor, the method including: (a) determining whether a pixel is a bad pixel for each pixel of the image; (b) The weight corresponding to the same pixel located around the first pixel, which is the pixel identified as the bad pixel in step (a), is calculated using the color value of the first pixel, Calculating using color values of pixels and pixels around the same pixel; (c) weights corresponding to homogeneous pixels located in the periphery of the second pixel, which is the pixel determined as not being a bad pixel, in step (a), and the color value of the second pixel and the pixels around the second pixel; And calculating color values of the pixels around the same pixel. And d) weighted average of color values of the same pixel located around the first pixel or the second pixel according to the weight calculated in the step (b) or the step (c). And correcting the color value of the first pixel or the second pixel by weighted averaging including the color value of the second pixel except for the color value.

In addition, in step (b), a weight corresponding to a homogeneous pixel positioned around the first pixel may include a color value of the pixel in the mask formed by excluding the first pixel with respect to the first pixel and the homogeneous pixel. Calculated using the difference of the color values of the pixels in the mask formed by excluding the homogeneous pixels, and the weight corresponding to the homogeneous pixels located in the periphery of the second pixel in the step (c) is The difference between the color value of the pixel in the mask including the second pixel centered on the pixel and the color value of the pixel in the mask including the same pixel centered on the same pixel may be calculated.

In addition, the step (d) may perform the weighted average operation including the color value of the first pixel and the color value of the second pixel, and in step (b), the weight corresponding to the first pixel is 0. And the weight corresponding to the second pixel in step (c) is set to a predetermined value other than 0, so that the color of the second pixel is excluded in step (d) except for the color value of the first pixel. Values can be included and weighted averaged.

In addition, in the step (d), the weighted average operation may be performed by including the color value of the second pixel except for the color value of the first pixel according to the result determined in the step (a).

According to an aspect of the present invention, there is provided an apparatus for correcting color of an image obtained by an image sensor, the apparatus including: a bad pixel discriminating unit configured to determine whether each pixel of the image is a bad pixel; The weights corresponding to homogeneous pixels positioned around the first pixel, which is the pixel determined as the defective pixel, are determined by the defective pixel determination unit, without using the color values of the first pixel and the same pixel, and surrounding the first pixel. A weight value corresponding to a homogeneous pixel positioned around a second pixel, which is a pixel determined as not being a defective pixel, by the pixels of the pixel and the pixels around the homogeneous pixel. A weight calculator configured to calculate color values of the second pixel and the like pixel, pixels around the second pixel, and color values of pixels around the same pixel; And a weighted average of color values of homogeneous pixels positioned around the first pixel or the second pixel according to the weight calculated by the weight calculator, except for the color values of the first pixel. And including a weighted average including a weighted average to correct a color value of the first pixel or the second pixel.

The weight calculator may include a weight corresponding to the same pixel located around the first pixel, and the color value of the pixel in the mask formed by excluding the first pixel with respect to the first pixel, and the same pixel. A first weight calculator configured to calculate a difference based on a color value of a pixel in a mask formed by removing the same pixel as a center; And a weight corresponding to a homogeneous pixel positioned around the second pixel, and a color value of a pixel in a mask formed including the second pixel with respect to the second pixel and the homogeneous pixel with respect to the same pixel. And a second weight calculator configured to calculate using a difference between color values of pixels in the mask.

The weighted average unit may perform the weighted average operation including a color value of the first pixel and a color value of the second pixel, and the first weight calculator sets a weight corresponding to the first pixel to zero. In addition, the second weight calculator sets the weight corresponding to the second pixel to a predetermined value other than 0, thereby including the color value of the second pixel except for the color value of the first pixel in the weighted average unit. To be weighted averaged.

The weighted average unit may perform the weighted average operation including the color value of the second pixel except for the color value of the first pixel according to the result determined by the bad pixel determination unit.

In order to solve the above further technical problem, there is provided a computer-readable recording medium having recorded thereon a program for executing a method for correcting color of an image obtained by an image sensor according to the present invention.

According to the present invention described above, it is possible to effectively correct the color in consideration of the characteristics of the bad pixels and noise included in the image obtained by the image sensor using one filter.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description and the accompanying drawings, the substantially identical components are represented by the same reference numerals, and thus redundant description will be omitted. In addition, in the following description of the present invention, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present invention, a detailed description thereof will be omitted.

1 is a block diagram of an image processing apparatus employing a color correction apparatus according to an embodiment of the present invention. The image processing apparatus includes an image sensor 10, a bad pixel discriminating unit 20, a weight calculating unit 30, a weighted average unit 40, and a color interpolation unit 50.

The image sensor 10 acquires an image by detecting color information by detecting brightness of light introduced through a lens (not shown). The image sensor 10 has a color filter array for passing R (Red), G (Green), and B (Blue) color components for each pixel, and the color filter array is formed by, for example, Bayer ( Bayer) can have an array of patterns.

The bad pixel determination unit 20 determines whether each pixel of the image acquired by the image sensor 10 is a bad pixel. In this case, the bad pixel determination unit 20 may be configured to determine a difference between the color values of pixels of the same channel positioned around the target pixel and the same channel positioned around the target pixel, based on the target pixel to determine whether the defective pixel is a bad pixel. The color value difference between the pixels may be compared with a predetermined threshold value to determine whether the pixel is a bad pixel.

For example, assuming a Bayer pattern image as illustrated in FIG. 2, differences in color values based on the target pixel R of the R channel may be defined by the following equation.

,

,

,

,

,

,

,

,

,

,

,

,

The color value differences calculated according to Equation 1 are compared with a predetermined threshold Th as in the following Equation to determine whether the target pixel is a bad pixel.

According to Equation 1 and Equation 2, the difference between the color value of the target pixel of the R channel and the color value of the pixel of the R channel in the horizontal, vertical, and diagonal positions of the target pixel, and horizontally and vertically When the difference between the color values between the pixels of the located G channel and the difference between the color values between the pixels of the B channel diagonally positioned around the target pixel is larger than a predetermined threshold, the target pixel is determined as a bad pixel. Here, the threshold Th may be appropriately selected through experiments according to the quality of an image to be obtained, and it is preferable to have a small value in a low light environment, and the smaller the value, the more pixels are identified as bad pixels.

According to this embodiment, one filter, that is, the weighted average unit 40 to be described later is used to correct color values for both bad pixels and non-bad pixels. The weight calculator 30 to be described later determines bad pixels. According to the determination result of the unit 20, the weights are calculated in different manners as described below in consideration of noise characteristics of the bad pixels and non-bad pixels.

The weight calculator 30 calculates a weight corresponding to the same pixel located in the periphery of a pixel (hereinafter, referred to as a first pixel) that is determined as a bad pixel by the bad pixel determination unit 20, and determines a color value of the first pixel. Rather than using them, the color values of the pixels around the first pixel and the pixels around the same pixel are calculated. Here, the homogeneous pixel means a pixel having the same channel as a target pixel for correcting a color value. In addition, the weight calculator 30 determines a weight corresponding to the same pixel located in the periphery of the pixel (hereinafter referred to as a second pixel) that is determined as not a bad pixel by the bad pixel determination unit 20. It is calculated using the color value of and the color values of the pixels around the second pixel and the pixels around the same pixel.

The weight calculator 30 calculates weights corresponding to pixels for correcting the shape and color value of a mask used for weight calculation in order to calculate weights in a different manner as described above for the bad pixels and the non-bad pixels. Can be set differently. In addition, the weight calculator 30 may include a first weight calculator 31 and a second weight calculator 32 that calculate weights in different ways as shown in FIG. 2.

The first weight calculator 31 calculates a weight corresponding to a homogeneous pixel positioned around the first pixel, based on the same pixel as the color value of the pixel in the mask formed by excluding the first pixel. It calculates using the difference of the color value of the pixel in the mask formed except the homogeneous pixel. In this case, the weights of each of the pixels of the same type are calculated such that the weight corresponding to the same type of pixel having the color pattern around the first pixel has a larger value. In addition, the first weight calculator 31 sets the weight corresponding to the first pixel to zero.

3 illustrates an embodiment in the form of a mask for weight calculation when the first pixel is a pixel of the R channel. Referring to FIG. 3, a mask formed except for the first pixel is formed of all pixels adjacent to the first pixel, and a mask formed except of the same pixel is formed of all pixels adjacent to the same pixel. The mask of the embodiment may be equally applied to the pixels of the B channel and the pixels of the G channel, and description thereof will be omitted.

Referring to FIG. 3, a first pixel determined as a bad pixel is a pixel of an R channel positioned at the center, and a mask formed by excluding the first pixel around the first pixel is displayed in red. In addition, a mask formed by excluding the pixel of the R channel, centered on the pixel of the R channel located in the northwest, which is one of the same pixels of the first pixel, is displayed in blue.

When using a mask having a shape as shown in FIG. 3, the first weight calculator 31 may calculate weights corresponding to each of the pixels of the same type and the first pixel according to the following equation.

은 제1 화소를 기준으로 동종 화소의 상대적인 위치를 나타내는 좌표 (m, n)에 위치하는 동종 화소에 대응하는 가중치이며,

은 제1 화소 자신에 대응하는 가중치이다. 예를 들면, 도 3에서 푸른색으로 나타난 마스크에 둘러싸인, 북서쪽에 위치한 R 채널의 화소에 대응하는 가중치는

로 표현된다.

(

)는 좌표

에서의 컬러 값을 의미하고,

기호 내부의 컬러 값의 차이는 제1 화소를 둘러싼 마스크 내의 화소들 중 어느 하나의 화소의 컬러 값과 동종 화소를 둘러싼 마스크 내의 화소들 중 이와 대응하는 위치의 화소의 컬러 값의 차이를 나타낸다. 여기서, (i, j)는 제1 화소의 좌표이고, (p, q)는 제1 화소를 기준으로 상기 어느 하나의 화소의 상대적인 위치를 나타내는 좌표이며, H는 도 3에 도시된 형태의 마스크 내부를 의미한다. 도 3에 도시된 형태의 마스크에 포함되는 화소의 수는 총 8개이므로, 상기 수학식에서 합해지는 컬러 값의 차이는 모두 8개가 된다. 수식

은 제1 화소에 대응하는 가중치가 0으로 설정됨을 의미한다. 그리고 상기 수학식에 포함된 문턱값 Th는 가중치의 강약을 조절하기 위한 값으로서, 잡음의 정도에 따라서 적절한 값으로 정의될 수 있다.here,

Is a weight corresponding to a homogeneous pixel located at a coordinate (m, n) indicating a relative position of the homogeneous pixel with respect to the first pixel,

Is a weight corresponding to the first pixel itself. For example, the weight corresponding to the pixel of the R channel located in the northwest, surrounded by the mask shown in blue in FIG.

It is expressed as

(

) Coordinates

Means the color value in

The difference in the color value inside the symbol indicates the difference between the color value of one of the pixels in the mask surrounding the first pixel and the color value of the pixel at the corresponding position among the pixels in the mask surrounding the same pixel. Here, (i, j) is the coordinate of the first pixel, (p, q) is a coordinate indicating the relative position of any one pixel with respect to the first pixel, H is a mask of the form shown in FIG. It means inside. Since the total number of pixels included in the mask of the type shown in FIG. 3 is eight, the difference in color values added in the above equation is eight. Equation

Means that the weight corresponding to the first pixel is set to zero. The threshold Th included in the above equation is a value for adjusting the strength and weakness of the weight, and may be defined as an appropriate value according to the degree of noise.

The second weight calculator 31 calculates a weight corresponding to the same pixel located around the second pixel, which is the pixel determined as not being the bad pixel, by the bad pixel determination unit 20. It calculates using the difference of the color value of the pixel in the mask formed including two pixels, and the color value of the pixel in the mask formed including the same pixel centering on the same pixel. In this case, the weights are calculated for each of the like pixels so that the weight value corresponding to the color value of the second pixel, the color value similar to the surrounding color pattern, and the same pixel having the surrounding color pattern has a larger value. In addition, the weight corresponding to the second pixel is set to a predetermined value other than zero, for example, one.

4 illustrates an embodiment in the form of a mask for weight calculation when the second pixel is a pixel of the R channel. Referring to FIG. 4, the mask including the second pixel is formed of the second pixel and all the pixels adjacent to the second pixel, and the mask including the same pixel is the same pixel and all the pixels adjacent to the same pixel. Is formed. The mask of the embodiment may be equally applied to the pixels of the B channel and the pixels of the G channel, and description thereof will be omitted.

Referring to FIG. 4, the second pixel determined to be not a bad pixel is a pixel of an R channel positioned at the center, and a mask including the second pixel around the second pixel is displayed in red. In addition, a mask formed of the pixels of the R channel located in the northwest, which is one of the same pixels of the second pixel, is displayed in blue.

When using a mask having a shape as shown in FIG. 4, the second weight calculator 32 may calculate weights corresponding to each of the same pixels and the first pixel according to the following equation.

은 제2 화소에 대응하는 가중치가 1로 설정됨을 의미한다. Here, each symbol is the same as that described in Equation 3, except that H 'means the inside of the mask of the form shown in FIG. Since the total number of pixels included in the mask of the type shown in FIG. 4 is nine, the difference in color values is added to all nine. Equation

Means that the weight corresponding to the second pixel is set to one.

Referring back to FIG. 2, the weighted average unit 40 receives the weighted value calculated by the weight calculator 30 and performs a weighted average operation to correct the color value of the first pixel or the second pixel. The weighted average unit 40 may perform a weighted average operation by using the following equation.

는 보정된 컬러 값을 나타내고,

은 가중치 계산부(30)에서 계산된 가중치이며,

은 컬러를 보정할 화소를 기준으로 상대적인 위치를 나타내 는 좌표 (m, n)에 위치하는 화소의 컬러 값을 나타내며, N은 도 3 또는 도 4에 도시된 영역을 나타낸다. here,

Indicates the corrected color value,

Is the weight calculated by the weight calculator 30,

Denotes a color value of a pixel located at coordinates (m, n) indicating a relative position with respect to a pixel to be corrected, and N denotes an area shown in FIG. 3 or 4.

In particular, the weighted average unit 40 weights each color value of the same pixel positioned around the first pixel or the second pixel with respect to each of the first pixel or the second pixel, except for the color value of the first pixel. The weighted average operation is performed, and the weighted average operation is performed by including the color value of the second pixel.

Although already described, the weight corresponding to the first pixel determined as the bad pixel is set to zero. Therefore, even when the weighted average operation according to the above equation includes the color value R _0,0 of the first pixel, the weighted value is 0, and thus the color value of the first pixel is excluded from the weighted average operation. On the other hand, the weight corresponding to the second pixel determined as not being a bad pixel is set to a predetermined value other than zero. Therefore, the color value of the second pixel is included in the weighted average calculation.

As described above, the weight calculation unit 30 selectively uses the color values of the pixels to correct the color according to the determination result of the bad pixel determination unit 20 to perform the weighted average operation according to the weights calculated differently, and the weighted average operation. In addition, by selectively including the color value of the pixel to be corrected color according to the determination result of the bad pixel discrimination unit 20 by using a single filter in consideration of the characteristics of the bad pixels and noise included in the image effectively the color of the image You can correct it.

Meanwhile, according to the above-described embodiment, the first weight calculator 31 sets the weight of the first pixel determined as the bad pixel to 0 so that the color value of the first pixel is excluded from the weighted average calculation. Without the weight calculation unit 31 setting the weight for the first pixel, the weighted average unit 40 selectively selects the bad pixels according to the determination result of the bad pixel determination unit 20. Except for performing a weighted average operation and including a pixel determined to be not a bad pixel, a weighted average operation may be included.

Referring back to FIG. 1, the color interpolator 50 receives an image in which the color of each pixel is corrected by the weighted average unit 40, and outputs a color value of another channel that is not stored in the pixel for each pixel. A full color image is generated by interpolating from color values of neighboring pixels. The color interpolator 50 may use any one of various known color interpolation methods.

Hereinafter, another embodiment in the form of a mask for calculating the weight in the weight calculator 30 will be described.

FIG. 5 illustrates another embodiment in the form of a mask formed to calculate a weight in the first weight calculator 31 when the first pixel is a pixel of the R channel. Referring to FIG. 5, a mask formed by excluding the first pixel around the first pixel is formed of only the pixels of the G channel adjacent to the first pixel in a horizontal or vertical direction. In addition, a mask formed by excluding homogeneous pixels centered on homogeneous pixels positioned around the first pixel may also be formed of pixels of G channels adjacent to the homogeneous pixel in a horizontal or vertical direction. Because of the characteristics of each of the R, G, and B channels, the brightness information of the image acquired by the image sensor has the most color value of the G channel. Accordingly, as shown in FIG. 5, a weight may be calculated using only color values of pixels of adjacent G channels by forming a mask excluding pixels of B channels. In this case, the equation used is the same as Equation 3, except that H denotes the inside of the mask shown in FIG. 5. Since the total number of pixels included in the mask of the type shown in FIG. 5 is four, the difference in color values added in Equation 3 is four.

According to the present embodiment, since the weight is calculated using only the color values of the pixels of the G channel, the computation amount according to the weight calculation can be reduced. The mask of the form according to the present exemplary embodiment may be equally applied to the pixels of the B channel, and description thereof will be omitted.

FIG. 6 illustrates another embodiment in the form of a mask formed to calculate a weight in the second weight calculator 32 when the second pixel is a pixel of the R channel. Referring to FIG. 6, a mask including the second pixel around the second pixel is formed of pixels of a G channel adjacent to the second pixel in a horizontal or vertical direction. In addition, a mask including the same pixel around the same pixel positioned around the second pixel is also formed of pixels of the G channel adjacent to the same pixel in a horizontal or vertical direction. As described above, the brightness information of the image acquired by the image sensor has the most color value of the G channel due to the characteristics of each of the R, G, and B channels. Thus, as shown in FIG. 6, a weight may be calculated using color values of pixels of adjacent G channels by forming a mask except pixels of the B channel. In this case, the equation used is the same as Equation 4, except that H 'means the inside of the mask of the form shown in FIG. Since the total number of pixels included in the mask of the type shown in FIG. 6 is five, the difference in color values added in Equation 4 is five.

According to the present embodiment, since the weight is calculated using the color values of the pixels of the G channel except for the color values of the pixels of the B channel, the amount of calculation according to the weight calculation can be reduced. The mask of the form according to the present exemplary embodiment may be equally applied to the pixels of the B channel, and description thereof will be omitted.

FIG. 7 illustrates another embodiment in the form of a mask formed to calculate a weight in the first weight calculator 31 when the first pixel is a pixel of the G channel. Referring to FIG. 7, a mask formed by excluding the first pixel around the first pixel is formed of only the pixels of the G channel that are diagonally adjacent to the first pixel. In addition, a mask formed by excluding homogeneous pixels centered on homogeneous pixels positioned around the first pixel may also be formed of pixels of G channels adjacent to the same pixel in a diagonal direction. According to the present exemplary embodiment, weights for a larger number of homogeneous pixels may be obtained. That is, weights corresponding to eight G channel pixels at diagonal positions with respect to the first pixel located at the center and four G channel pixels in horizontal and vertical directions may be obtained. Also, since only the color information of the G channel pixel is used, the amount of calculation can be reduced. In this case, the equation used is the same as Equation 3 above, except that H means the inside of the mask of the form shown in FIG. 7. Since the total number of pixels included in the mask of the type shown in FIG. 7 is four, the difference in the color values added in Equation 3 is four.

8 illustrates another embodiment in the form of a mask formed to calculate a weight in the second weight calculator 32 when the second pixel is a pixel of the G channel. Referring to FIG. 8, a mask including the second pixel around the second pixel is formed to include pixels of the G channel adjacent to the second pixel in a diagonal direction. In addition, a mask formed by excluding homogeneous pixels centered on homogeneous pixels positioned around the second pixel may also include pixels of G channels adjacent to the same pixel in a diagonal direction. According to the present exemplary embodiment, similarly to the exemplary embodiment described with reference to FIG. 7, a weight for a larger number of homogeneous pixels can be obtained, and the calculation amount can be reduced by using only the color information of the G channel pixel. In this case, the equation used is the same as Equation 4, except that H 'means the inside of the mask of the form shown in FIG. Since the total number of pixels included in the mask of the type shown in FIG. 8 is five, the difference in color values added in Equation 4 is five.

9 is a flowchart of a color correction method according to an embodiment of the present invention. The color correction method according to the present embodiment is composed of steps processed in the color correction device shown in FIG. Therefore, even if omitted below, the above description of the color correction apparatus shown in FIG. 3 is also applied to the color correction method according to the present embodiment.

In operation 910, it is determined whether each pixel of the image acquired by the image sensor is a bad pixel.

In step 920, if it is determined that the pixel is bad, the process proceeds to step 930. If it is determined that the pixel is not a bad pixel, the process proceeds to step 940.

In operation 930, pixels around the first pixel and pixels around the same pixel may be weighted corresponding to the same pixel located around the first pixel, which is the pixel determined as the bad pixel, without using the color value of the first pixel. Calculate using their color values.

In operation 940, the weight corresponding to the homogeneous pixel positioned around the second pixel, which is the pixel determined to be not the defective pixel, may be determined by comparing the color value of the second pixel and the pixels around the second pixel and the pixels around the same pixel. Calculate using color values.

In step 950, the color value of the first pixel or the second pixel is weighted and averaged to correct the color value of the first pixel or the second pixel according to the weight calculated in step 930 or 940. do. In this case, the weighted average operation is performed except for the color value of the first pixel, and the weighted average operation is performed including the color value of the second pixel.

10 to 12 illustrate an image obtained by performing color interpolation without the color correction process according to the present invention from an image obtained by an image sensor having a Bayer pattern color filter array, and the color correction process according to the present invention. This is a diagram comparing images obtained by performing color interpolation after rough processing. Referring to FIGS. 10 to 12, when the color correction process according to the present invention is not performed, the degree of deterioration of the image due to the bad pixels and noise is very large. However, when the color correction process according to the present invention is performed, You can see that the resolution has been improved by removing the noise.

Meanwhile, the above-described embodiments of the present invention can be written as a program that can be executed in a computer, and can be implemented in a general-purpose digital computer that operates the program using a computer-readable recording medium. The computer-readable recording medium may include a magnetic storage medium (eg, ROM, floppy disk, hard disk, etc.), an optical reading medium (eg, CD-ROM, DVD, etc.) and a carrier wave (eg, internet Storage medium).

So far I looked at the center of the preferred embodiment for the present invention. Those skilled in the art will appreciate that the present invention can be implemented in a modified form without departing from the essential features of the present invention. Therefore, the disclosed embodiments should be considered in descriptive sense only and not for purposes of limitation. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the scope will be construed as being included in the present invention.

1 is a block diagram of an image processing apparatus employing a color correction apparatus according to an embodiment of the present invention.

2 shows an example of an image of a Bayer pattern.

3 illustrates an embodiment in the form of a mask for weight calculation when the first pixel is a pixel of the R channel.

4 illustrates an embodiment in the form of a mask for weight calculation when the second pixel is a pixel of the R channel.

5 illustrates another embodiment in the form of a mask for calculating weights when the first pixel is a pixel of the R channel.

6 shows another embodiment in the form of a mask for calculating weights when the second pixel is a pixel of the R channel.

7 illustrates another embodiment in the form of a mask for calculating a weight when the first pixel is a pixel of the G channel.

8 illustrates another embodiment in the form of a mask for weight calculation when the second pixel is a pixel of the G channel.

9 is a flowchart of a color correction method according to an embodiment of the present invention.

10 to 12 are views illustrating an image obtained by performing color interpolation without the color correction process according to the present invention and an image obtained by performing color interpolation after the color correction process according to the present invention.

Claims (19)

In the method for correcting the color of the image obtained by the image sensor, (a) determining whether each pixel of the image is a bad pixel; (b) The weight corresponding to the same pixel located around the first pixel, which is the pixel identified as the bad pixel in step (a), is calculated using the color value of the first pixel, Calculating using the color values of the pixels and pixels around the homogeneous pixel, where homogeneous pixel means a pixel having the same color channel; (c) weights corresponding to homogeneous pixels located in the periphery of the second pixel, which is the pixel determined as not being a bad pixel, in step (a), and the color value of the second pixel and the pixels around the second pixel; And calculating color values of the pixels around the same pixel. And (d) a weighted average of color values of homogeneous pixels located around the first pixel or the second pixel according to the weight calculated in the step (b) or the step (c), wherein the color of the first pixel And correcting a color value of the first pixel or the second pixel by weighted averaging including a color value of the second pixel without a value. The method of claim 1, In step (b), a weight corresponding to a homogeneous pixel positioned around the first pixel may be a color value of a pixel in a mask formed by excluding the first pixel with respect to the first pixel and the same pixel. Using the difference in the color values of the pixels in the mask formed by excluding the same pixel, In step (c), a weight corresponding to a homogeneous pixel positioned around the second pixel may include a color value of a pixel in a mask including the second pixel and the same pixel. And calculating using a difference of color values of pixels in a mask formed including the same pixel. The method of claim 1, In step (d), the weighted average operation is performed by including the color value of the first pixel and the color value of the second pixel. In step (d), the weight corresponding to the first pixel is set to 0 and the weight corresponding to the second pixel is set to a predetermined value other than 0 in step (c). The color correction method of claim 1, wherein the color value of the second pixel is included in the weighted average except for the color value of the first pixel. The method of claim 1, In the step (d), the weighted average operation is performed by including the color value of the second pixel except for the color value of the first pixel according to the result determined in the step (a). Calibration method. The method of claim 1, In the step (a), the difference between the color values of the pixels and the pixels of the same channel positioned around the pixel or the colors of the pixels of the same channel positioned around the pixel based on the pixel to determine whether the pixel is a bad pixel. And comparing the value difference with a predetermined threshold value to determine whether or not the pixel is a defective pixel. The method of claim 1, And the image sensor comprises a color filter array in a Bayer pattern. The method of claim 2, The mask formed except the first pixel is formed of all pixels adjacent to the first pixel, and the mask formed except the same pixel is formed of all pixels adjacent to the same pixel. The method of claim 2, The mask including the second pixel is formed of the second pixel and all pixels adjacent to the second pixel, and the mask formed of the same pixel is formed of the same pixel and all pixels adjacent to the same pixel. Color correction method characterized in that. The method of claim 2, When the first pixel is a pixel of an R channel or a B channel, a mask formed except the first pixel is formed of pixels of a G channel adjacent to the first pixel in a horizontal or vertical direction, except for the same pixel. And the formed mask is formed of pixels of a G channel adjacent to the same pixel in a horizontal or vertical direction. The method of claim 2, When the second pixel is a pixel of an R channel or a B channel, a mask formed of the second pixel is formed of pixels of a G channel adjacent to the second pixel and the second pixel in a horizontal or vertical direction. The mask formed by excluding the same pixel is formed of the same pixel and pixels of a G channel adjacent to the same pixel in a horizontal or vertical direction. The method of claim 2, When the first pixel is a pixel of a G channel, the mask formed by excluding the first pixel is formed of pixels of a G channel adjacent to the first pixel in a diagonal direction, and the mask formed by excluding the same pixel is the same kind. And a pixel of G channel adjacent to the pixel in a diagonal direction. The method of claim 2, When the second pixel is a pixel of a G channel, the mask including the second pixel is formed of the second pixel and pixels of a G channel adjacent to the second pixel in a diagonal direction, and include the same pixel. The formed mask is formed of the same pixel and the pixel of the G channel adjacent to the same pixel in the diagonal direction. A computer-readable recording medium having recorded thereon a program for executing a method for correcting color of an image obtained by an image sensor according to any one of claims 1 to 12. In the device for correcting the color of the image obtained by the image sensor, A bad pixel discriminating unit for discriminating whether or not each pixel of the image is a bad pixel; The weights corresponding to the same pixels located around the first pixel, which is the pixel identified as the bad pixel, are determined by the bad pixel determination unit, without using the color values of the first pixel and the same pixel, and surrounding the first pixel. A weight value corresponding to a homogeneous pixel positioned around a second pixel, which is a pixel determined as not being a defective pixel, by the pixels of the pixel and the pixels around the homogeneous pixel. A weight calculation unit that calculates the color values of the second pixel and the same pixel by using the color values of the pixels around the second pixel and the pixels around the same pixel. Means a pixel; And The weighted average of color values of the same pixel positioned around the first pixel or the second pixel is weighted according to the weight calculated by the weight calculator, except for the color value of the first pixel. And a weighted average unit for correcting a color value of the first pixel or the second pixel by including a weighted average of the values. The method of claim 14, wherein the weight calculation unit, Weight values corresponding to homogeneous pixels positioned around the first pixel are excluded from color values of pixels in a mask formed by excluding the first pixel with respect to the first pixel and the homogeneous pixel with respect to the same pixel. A first weight calculator configured to calculate the difference between the color values of the pixels in the mask; And A weight value corresponding to a homogeneous pixel positioned around the second pixel includes a color value of a pixel in a mask including the second pixel centered on the second pixel, and the homogeneous pixel centered on the same pixel And a second weight calculator configured to calculate the difference between the color values of the pixels in the mask. The method of claim 15, The weighted average unit performs the weighted average operation including a color value of the first pixel and a color value of the second pixel, The first weight calculator sets the weight corresponding to the first pixel to 0, and the second weight calculator sets the weight corresponding to the second pixel to a predetermined value other than 0, thereby allowing the weighted average unit to set the weight. And a color value of the second pixel to be weighted average except for the color value of the first pixel. The method of claim 14, The weighted average unit performs the weighted average operation including the color value of the second pixel except the color value of the first pixel according to a result determined by the bad pixel determination unit. . The method of claim 14, The bad pixel determination unit may be configured to determine a difference between a color value of the pixel and a pixel of the same channel positioned around the pixel or a color value between pixels of the same channel positioned around the pixel, based on a pixel to determine whether the pixel is a bad pixel. And comparing the difference with a predetermined threshold to determine whether or not the pixel is a defective pixel. The method of claim 14, And the image sensor comprises a color filter array in a Bayer pattern.

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