KR101617553B1 - Method and Apparatus for Minimum shot auto exposure using noise-aware linear model - Google Patents

Abstract

Disclosed are an automatic minimum shot exposure method using a noise-aware linear model, and a device thereof. According to the present invention, the automatic minimum shot exposure method comprises: a step of obtaining a first image captured from a first frame using a first exposure time and a first amplification ratio; a step of updating an exposure time from the first exposure time to a second exposure time; a step of estimating a histogram with respect to the first image when the exposure time is updated to the second exposure time; a step of changing the histogram with respect to the first image based on the saturated pixels; and a step of extracting a target exposure time based on the changed histogram with respect to the first image. As such, the method is able to capture an image having aimed target brightness even in a non-linear section of an over-exposure state by properly adjusting an exposure time, an amplification ratio, or both the exposure time and the amplification ratio.

Description

TECHNICAL FIELD The present invention relates to a minimum exposure automatic exposure method and apparatus using a noise recognition linear model,

The present invention relates to an automatic exposure method and apparatus for reaching a target brightness for an unspecified scene even in a non-linear section in an overexposed state.

In recent years, along with the remarkable development of digital camera technology, digital cameras supporting higher resolution and various functions are being commercialized. Such digital cameras are often used in other portable digital devices such as mobile phones, notebook computers, and PDAs (Personal Digital Assistants). Such a digital camera basically includes an image sensor such as a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS), which captures light of an object and converts the light into an electrical signal. However, in the current technology, it is difficult to completely block the noise generated when a subject is photographed by such an image sensor. Accordingly, most digital cameras have a function of removing or correcting the generated noise, and the importance of such functions is increasing in consideration of the current tendency to pursue high-quality images.

SUMMARY OF THE INVENTION The present invention provides a minimum scene automatic exposure method for photographing an image having a target target brightness in a nonlinear section of an overexposed state by appropriately adjusting both an exposure time, an amplification ratio, an exposure time, and an amplification ratio, Device. In addition, by applying a noise-aware offset considering noise in various illuminance environments such as outdoor backlighting, it is desired to obtain an image of the target brightness with only a minimum of photographing.

In one aspect, the automatic exposure control method proposed by the present invention includes the steps of acquiring a first image photographed in a first frame using a first exposure time and a first amplification ratio, Estimating a histogram for the first image when the exposure time is updated with the second exposure time, calculating a histogram for the first image based on the saturated pixels, And extracting a target exposure time based on the modified histogram for the first image.

The extracting of the target exposure time may include determining whether the brightness of the first image has reached the target brightness when the second exposure time is applied based on the modified histogram.

Wherein the step of estimating the histogram for the first image when the exposure time is updated to the second exposure time comprises the steps of: when the brightness of the image in the overexposed state is smaller than the target brightness, It can be estimated by dividing by the larger case.

If the image brightness in the overexposed state is less than the target brightness, the exposure time can be calculated from the intensity histogram of the initial image.

If the image brightness of the overexposed state is smaller than the target brightness, the following equation is used to estimate L1 by using the histogram of the initial image,

Here, h (x) represents a histogram of the initial image.

If the image brightness in the overexposed state is greater than the target brightness, a saturated pixel may be inferred when the exposure time decreases from the initial exposure time.

If the image brightness in the overexposed state is greater than the target brightness, use the following equation to estimate a saturated pixel that decreases when the exposure time decreases from the initial exposure time,

Here, the x-axis represents the brightness of the initial image, the y-axis represents the ratio of saturated pixels, and the z-axis represents the exact ratio of exposure time.

In another aspect, the automatic exposure control apparatus proposed by the present invention includes a photographing unit that acquires a first image photographed in a first frame using a first exposure time and a first amplification ratio, A histogram lookup section for estimating a histogram for the first image when the exposure time is updated to the second exposure time, a histogram search section for estimating a histogram for the first image based on the saturated pixels, A histogram transforming unit transforming a histogram of the image, and a target exposure time extracting unit extracting a target exposure time based on the transformed histogram for the first image.

The target exposure time extracting unit may determine whether the brightness of the first image has reached the target brightness when the second exposure time is applied based on the modified histogram.

The histogram estimator may be divided into a case in which the image brightness in the overexposed state is smaller than the target brightness and a case in which the image brightness in the overexposed state is larger than the target brightness.

According to embodiments of the present invention, it is possible to appropriately adjust both the exposure time, the amplification ratio, the exposure time, and the amplification ratio, so that an image having a target target brightness can be photographed even in a non-linear section in an overexposed state. In addition, by applying a noise-aware offset in consideration of noise in various illuminance environments such as outdoor backlight, it is possible to obtain an image of the target brightness with a minimum of photographing.

1 is a flowchart for explaining a minimum photographing automatic exposure method using a noise recognition linear model according to an embodiment of the present invention.
2 is a graph illustrating the relationship between exposure time and brightness according to an embodiment of the present invention.
3 is a graph illustrating a relationship between amplification ratio and brightness at zero exposure time according to an embodiment of the present invention.
FIG. 4 is a graph illustrating a relationship between amplification ratio and brightness according to a change in exposure time at a fixed brightness of a scene according to an exemplary embodiment of the present invention. Referring to FIG.
5 is a graph showing the relationship between brightness and exposure time in an overexposed state according to an embodiment of the present invention.
FIG. 6 is a diagram illustrating a brightness histogram of an image in each exposure time according to an embodiment of the present invention.
7 is a diagram illustrating a brightness histogram of an image for each exposure time according to an embodiment of the present invention.
8 is a diagram illustrating an intensity histogram and an expanded histogram of an initial image according to an embodiment of the present invention.
9 is a graph illustrating exposure time and brightness according to an embodiment of the present invention.
10 is a graph showing experimental results in various atmospheres such as plot data and overexposure conditions according to an embodiment of the present invention.
11 is a view illustrating a minimum photographing automatic exposure apparatus using a noise recognition linear model according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a flowchart for explaining a minimum photographing automatic exposure method using a noise recognition linear model according to an embodiment of the present invention.

A minimum photographing auto exposure method using a noise-aware linear model includes the steps of acquiring (110) a first image photographed in a first frame using a first exposure time and a first amplification ratio, Estimating a histogram for the first image if the exposure time has been updated to the second exposure time (130); calculating (130) a histogram for the first image based on the saturated pixels, (140) a histogram for one image, and extracting a target exposure time (150) based on a modified histogram for the first image.

At step 110, a first image taken at a first frame may be obtained using a first exposure time and a first amplification ratio. The first image photographed using the first frame having the predetermined exposure time and amplification ratio can be photographed. For example, in order to apply an automatic exposure algorithm to a video camera, an image can be continuously captured, and the brightness of the image must be calculated for every frame. At this time, the initial brightness of the first frame can be calculated.

In step 120, the exposure time may be updated from the first exposure time to the second exposure time.

In step 130, if the exposure time is updated with the second exposure time, a histogram for the first image may be estimated.

And estimating a histogram for the first image when the exposure time is updated to the second exposure time, if the brightness of the image in the overexposed state is less than the target brightness, It can be estimated by dividing by the case where it is larger than the brightness.

If the overexposed image brightness is less than the target brightness, the exposure time can be calculated from the intensity histogram of the initial image. When the image brightness in the overexposed state is less than the target brightness, we use Equation 12 to infer L1 using the histogram of the initial image, where h (x) may represent the histogram of the initial image. If the image brightness in the overexposed state is greater than the target brightness, a saturated pixel may be inferred when the exposure time decreases from the initial exposure time.

In step 140, the histogram for the first image may be modified based on the saturated pixels.

Equation 17 is used to estimate the saturated pixel, which decreases when the exposure time decreases from the initial exposure time when the image brightness in the overexposed state is greater than the target brightness, where the x axis is the brightness of the initial image, y The axis can represent the percentage of saturated pixels, and the z-axis can represent the exact ratio of exposure time.

In step 150, a target exposure time may be extracted based on a modified histogram for the first image. The extracting of the target exposure time may include determining whether the brightness of the first image has reached the target brightness when the second exposure time is applied based on the modified histogram. Will be described in more detail with reference to Figs. 2 to 10. Fig.

2 is a graph illustrating the relationship between exposure time and brightness according to an embodiment of the present invention.

Since the exposure time determines the amount of light incident on the camera's lens, the brightness of the image can be predicted to be proportional to the exposure time. This relationship can be expressed as Equation (1).

수학식(1)

Equation (1)

Where S is the exposure time, L is the brightness of the image, and i is the frame index of the image to be captured.

For example, in order to show the effectiveness of Equation (1), a color checker is photographed using a PointGrey Flea3 camera as shown in FIG. 2 (a). In a fixed illumination environment, the exposure time is increased from 0 ms to 100 ms and the amplification ratio is increased from 1 to 5 times. To measure the brightness of the photographed image, RGB-YUV conversion is performed on the RGB values of all the pixels of the image, and an average of the Y values of all the pixels is obtained. It can be seen that the linearity between the brightness of the image and the exposure time for the fixed amplification ratios 110, 120, 130, 140, 150 of various values is clearly maintained, as shown in FIG. 2 (b).

Ideally, if the exposure time is 0ms, there is no light coming through the lens, so the brightness value of the image should also be zero. However, as shown in FIG. 2 (b), the brightness value of the image obtained through the exposure time of 0 ms is not zero. In other words, there is something in the camera that keeps the fixed brightness of the image. In particular, when electrons and holes generated irregularly in a depletion region of an element such as an optical element are absent from the optical element, dark current may be generated. This is called dark current noise, which is a relatively small size, but one of the major causes of image sensor noise. The brightness of the image with the exposure time of 0 ms can be attributed mainly to the noise generated regardless of the brightness of the pixel, such as the dark current noise, the read-out noise, and the quantization noise. Since the dark current noise can be expressed by the number of photons, the brightness value due to the dark current noise may be affected by the amplification ratio of the camera.

3 is a graph illustrating a relationship between amplification ratio and brightness at zero exposure time according to an embodiment of the present invention.

In order to confirm the influence of the amplification ratio in the image having the exposure time of 0 ms, the image is photographed while changing the amplification ratio while maintaining the exposure time of 0 ms as shown in FIG. For example, the brightness of an image obtained from various image sensors such as a TOSHIBA CIS sensor 330, three kinds of PointGrey Flea3 cameras 310, 320 and 360 and two kinds of PointGrey Grasshopper cameras 340 and 350, The linear relationship between the amplification ratios of the camera can be confirmed. The offset brightness value at the exposure time of 0 ms can be expressed as Equation (2).

수학식(2)

Equation (2)

Where G is the amplification ratio, N is the offset brightness value at the exposure time of 0 ms, c and a are constant values, which are different for each camera.

As a result, when the illuminance and the amplification ratio of a specific environment are constant, the relationship between the exposure time and the brightness of the image can be expressed by Equation (3).

수학식(3)

Equation (3)

In an ordinary situation, an image having a target brightness value can be obtained by taking an image through an initial exposure time and then adjusting the exposure time again using Equation (3).

The amplification ratio of the camera is always a linear relationship with the brightness of the image because it is a parameter for determining the intensities of the image by multiplying the amount of the photoelectrons stored by the incident light several times. The relationship between the brightness of the image and the amplification ratio can be expressed as shown in Equation (4).

수학식(4)

Equation (4)

Where G _i is the amplification ratio of the i-th captured image. As described above, to verify Equation (4), a color checker is photographed using the same camera in a fixed illumination environment as shown in FIG. 1 (a). At this time, the amplification ratio was increased from 1 to 8 times, and the exposure time was increased from 40 ms to 80 ms. Thereafter, the brightness values of the images photographed as shown in FIG. 3 were measured.

FIG. 4 is a graph illustrating a relationship between amplification ratio and brightness according to a change in exposure time at a fixed brightness of a scene according to an exemplary embodiment of the present invention. Referring to FIG.

Since the camera (Flea3) used in this experiment can not capture images with a 0-fold amplification ratio, it is possible to extend the line connecting the brightness values from 1 to 8 times, I ask. 4, it is confirmed that the linearity between the amplification ratio and the brightness value of the image is maintained. As described above, it can be seen that the brightness value of the image obtained at the amplification ratio of 0 times is not zero. In this case, unlike the case where the fixed amplification ratio is used in Equation (2), it is necessary to reflect the change of the amplification ratio in the equation. Therefore, equation (2) can be modified as shown in equation (5).

수학식(5)

Equation (5)

By considering this offset value N _i , the relationship between the brightness of the image and the amplification ratio can be expressed when the illuminance and the exposure time in a specific environment are fixed. If this offset value is subtracted from the pure video only brightness value, the brightness value of the image can be expressed by Equation (6).

수학식(6)

Equation (6)

Then, since L _i ^net has a linear relationship with the amplification ratio, Equation (4) can be rewritten as Equation (7).

수학식(7)

Equation (7)

In conclusion, the relationship between the amplification ratio and the brightness of the image can be expressed as Equation (8) by taking the offset value N _i into consideration.

수학식(8)

Equation (8)

In an ordinary situation, an image having a target brightness value can be obtained by taking an image through an initial amplification ratio and then adjusting the amplification ratio using Equation (8).

Equations (3) and (8) for adjusting the exposure time and the amplification ratio, respectively, can be integrated into a single equation. Then, for an image given an initial exposure time S _i and an amplification ratio G _i , an appropriate exposure time S _{i + 1} for the target brightness value L _{i + 1} can be determined. Then, the output brightness L _{i + 1} in Equation (9) can be replaced with the initial brightness Li in Equation (8) to determine an appropriate amplification ratio, and can be expressed as Equation (10).

수학식(9)

Equation (9)

By determining the amplification ratio, another integrated formula can be obtained considering the exposure time to follow. By applying the equation (8) to the equation (3), the relationship as shown in the equation (10) can be obtained.

수학식(10)

Equation (10)

Then, the equation representing the linear relationship of the brightness compensated by the offset value considering the noise having the exposure time and the amplification ratio can be rewritten. This can be expressed as Equation (11).

수학식(11)

Equation (11)

Here, L represents brightness, G represents amplification ratio, S represents exposure time, and N represents offset values considering noise. Equation (11) is a special case, and it is possible to explain other relationships in equations (3) and (8). If the exposure time is the same as the S _i unchanged in S _{i + 1,} equation (11) can be expressed by equation (8). In this case, the amplification ratio is fixed similarly to Equation (3). Based on the last relationship of Equation (11), various combinations of exposure time and amplification ratio for target brightness can be expected after one frame image taking some initial exposure time and amplification ratio. A flow chart of such a proposed method is shown in Fig.

5 is a graph showing the relationship between brightness and exposure time in an overexposed state according to an embodiment of the present invention.

The linearity between the brightness of the image and the exposure time or gain can be ensured to have a nearly saturated pixel as shown in Figures 2 and 4. [ If there are many saturated pixels in the image as in Figure 5 (a), the relationship between brightness and exposure time is not linear as in 5 (b).

FIG. 6 is a diagram illustrating a brightness histogram of an image in each exposure time according to an embodiment of the present invention.

Fig. 6 is a diagram showing an intensity histogram having various exposures (40 ms, 60 ms, 120 ms) as shown in Fig. 5 (b). The deviation of the intensity distribution can be increased while the exposure time is increased from 40 ms in FIG. 6 (a) to 60 ms in FIG. 6 (b). As shown in FIG. 6 (c), the intensity histogram for the exposure time of 120 ms can be expected, but the actual histogram of 120 ms is saturated as shown in FIG. 6 (d) due to the limit of the 8-bit image. This can cause non-linearity of brightness and exposure time.

7 is a diagram illustrating a brightness histogram of an image for each exposure time according to an embodiment of the present invention.

To address the nonlinearities of brightness and exposure time, two overexposed conditions can be separated as shown in FIG. Case 1 means that the image brightness is lower than the target brightness when the image is in an overexposed condition. Case 2 is a reverse saturation state in which the image brightness is larger than the target brightness. Before applying the noise-aware linear relationship to equation (9) for these two cases, an additional technique for case 1 and case 2 may be proposed to reduce the mismatch between target L and L 1 caused by non-linearity. Case 1 can be generated when the brightness of the image is smaller than the target brightness. In this case, the appropriate exposure time can be calculated directly from the intensity histogram of the initial image. Based on Equation (12), S1 in Fig. 7 can be inferred.

수학식 12

Equation 12

8 is a diagram illustrating an intensity histogram and an expanded histogram of an initial image according to an embodiment of the present invention.

When S1 is applied to the next frame, the brightness L1 of the image may be smaller than the target brightness. Therefore, before applying S1 to the next frame, L1 can be estimated in advance. The histogram of the image taken at the initial exposure time can be defined as h (x) in Fig. 8 (a).

When increasing the exposure time to S1, the changed histogram bin x0 can be approximated from x.

수학식13

Equation 13

This can be represented by h0 (x0) in Fig. 8 (b). N is the noise model proposed in Equation (2), and S means S1 = Sinit. It can be assumed that these pixels, guessed as X0, can be greater than 255 and are cropped at 255 due to saturation. In Fig. 8 (b), L1 can be estimated from h (0).

수학식14

Equation 14

Equation (14) can be obtained by replacing x0 in Equation (10).

수학식15

Equation 15

By using Equation (15), L1 can be inferred using the histogram of the initial image. k is the maximum value of x that does not exceed 255 when x increases by S1 = Sinit time, and k can be estimated.

9 is a graph illustrating exposure time and brightness according to an embodiment of the present invention.

수학식 16

Equation 16

The experimentally expected L1 shows about 0.5% error compared to the brightness of the image taken with S1. We need more steps to find the correct exposure time, SOPT, to accurately capture the exposure image. As shown in Fig. 9, we can find S2 to reach the target brightness in a straight line that includes both (Sinit, Linit) and (S1, L1).

L2 can also be estimated through Equation (15). By repeating this sequence n times, Sn can be defined as Sopt if the expected Ln is equal to Ltarget, and we can apply Sopt to the next frame.

n generally does not exceed 3. In conclusion, if the brightness of the initial image is excessively exposed and less than the target brightness, then the target brightness can take the correct exposure image immediately after the initial frame using the proposed method.

Case 2, when we take an image with overexposure, the image brightness may be greater than the target brightness. Unlike case 1, it is possible to guess how many saturated pixels decrease when the exposure time decreases from the initial exposure time. As the exposure time decreases, it is difficult to predict the pixel value at which each saturated pixel decreases or maintains its value.

The proposed method for Case 2 estimates the ratio of exposure time to the ratio and brightness of empirically saturated pixels. The database can be obtained from various scenes by estimating the appropriate ratio of the exposure time to the brightness of a given initial image and the ratio of saturated pixels.

10 is a graph showing experimental results in various atmospheres such as plot data and overexposure conditions according to an embodiment of the present invention.

As shown in FIG. 10, about 200 data were collected through experiments in various environments such as three-dimensional plot data and overexposure conditions. The x and y and z axes respectively represent the brightness of the initial image, the ratio of saturated pixels, and the exact ratio of exposure time. You can use the sftool MATLAB function to fit the plotted points on a three-dimensional graph on one side: The result can be expressed as:

수학식 17

Equation 17

The ratio of exposure time can be determined from the equation. An adjusted exposure time, which can be calculated by multiplying the next frame by the initial exposure time by the reduction ratio determined from equation (14), can be applied.

The R-squares in equation (17) for the plotted points are 0: 8217. Equation (17) can not include all conditions including excessive exposure. Case 2 shows that the experiment requires less repetition to capture the image to reach the target brightness than the conventional automatic exposure algorithm.

11 is a view illustrating a minimum photographing automatic exposure apparatus using a noise recognition linear model according to an embodiment of the present invention.

The automatic exposure control apparatus may include a photographing unit 1110, an updating unit 1120, a histogram searching unit 1130, a histogram changing unit 1140, and a target exposure time extracting unit 1150.

The photographing unit 1110 may obtain the first image photographed in the first frame using the first exposure time and the first amplification ratio. The first exposure time and the first amplification ratio may be used to obtain the first image photographed in the first frame. The first image photographed using the first frame having the predetermined exposure time and amplification ratio can be photographed. For example, in order to apply an automatic exposure algorithm to a video camera, an image can be continuously captured, and the brightness of the image must be calculated for every frame. At this time, the initial brightness of the first frame can be calculated.

Updating unit 1120 may update the exposure time from the first exposure time to the second exposure time.

The histogram searching unit 1130 may estimate a histogram of the first image when the exposure time is updated to the second exposure time. When the exposure time is updated to the second exposure time, when the histogram of the first image is estimated, the image brightness of the overexposed state is smaller than the target brightness, and when the brightness of the image in the overexposed state is smaller than the target brightness Can be estimated by dividing by the large case.

If the overexposed image brightness is less than the target brightness, the exposure time can be calculated from the intensity histogram of the initial image. When the image brightness in the overexposed state is less than the target brightness, we use Equation 12 to infer L1 using the histogram of the initial image, where h (x) may represent the histogram of the initial image. If the image brightness in the overexposed state is greater than the target brightness, a saturated pixel may be inferred when the exposure time decreases from the initial exposure time.

The histogram transformer 1140 may transform the histogram for the first image based on the saturated pixels.

Equation 17 is used to estimate the saturated pixel, which decreases when the exposure time decreases from the initial exposure time when the image brightness in the overexposed state is greater than the target brightness, where the x axis is the brightness of the initial image, y The axis can represent the percentage of saturated pixels, and the z-axis can represent the exact ratio of exposure time.

The target exposure time extracting unit 1150 can extract the target exposure time based on the modified histogram for the first image. The target exposure time extracting unit 1150 may determine whether the brightness of the first image has reached the target brightness when the second exposure time is applied based on the modified histogram.

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA) A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (12)

An automatic exposure control method,
Obtaining a first image photographed in a first frame using a first exposure time and a first amplification ratio;
Updating the exposure time from a first exposure time to a second exposure time;
Estimating a histogram for the first image when the exposure time is updated with the second exposure time;
Transforming a histogram for the first image based on saturated pixels; And
Extracting a target exposure time based on a modified histogram for the first image
Wherein the automatic exposure control method comprises: The method according to claim 1,
The step of extracting the target exposure time
Determining whether the brightness for the first image has reached a target brightness when the second exposure time is applied based on the modified histogram
Wherein the automatic exposure control method comprises: The method according to claim 1,
Wherein when the exposure time is updated to the second exposure time, estimating a histogram for the first image comprises:
Wherein when the image brightness of the overexposed state is smaller than the target brightness and when the brightness of the image in the overexposed state is larger than the target brightness, the automatic exposure control method is performed. The method of claim 3,
Wherein the exposure time is calculated from the intensity histogram of the initial image when the brightness of the image in the overexposed state is less than the target brightness. delete The method of claim 3,
Wherein when the image brightness of the overexposed state is greater than the target brightness, the saturated pixel is estimated to decrease when the exposure time decreases from the initial exposure time. The method of claim 3,
If the image brightness in the overexposed state is greater than the target brightness, use the following equation to estimate a saturated pixel that decreases when the exposure time decreases from the initial exposure time,

Wherein the x-axis represents the brightness of the initial image, the y-axis represents the ratio of saturated pixels, and the z-axis represents the exact ratio of exposure time. An automatic exposure control device comprising:
An imaging unit that acquires a first image photographed in a first frame using a first exposure time and a first amplification ratio;
An update unit updating the exposure time from the first exposure time to the second exposure time;
A histogram estimator for estimating a histogram of the first image when the exposure time is updated to the second exposure time;
A histogram transformer for transforming the histogram for the first image based on the saturated pixels; And
A target exposure time extracting unit for extracting a target exposure time based on a modified histogram for the first image,
And an automatic exposure control device. 9. The method of claim 8,
Wherein the target exposure time extracting unit comprises:
And determines whether or not the brightness for the first image has reached the target brightness when the second exposure time is applied based on the modified histogram. 9. The method of claim 8,
The histogram-
And estimates the image by dividing by the case where the image brightness of the overexposed state is smaller than the target brightness, and the case where the image brightness of the overexposed state is larger than the target brightness. 11. The method of claim 10,
Wherein the exposure time is calculated from the intensity histogram of the initial image when the brightness of the image in the overexposed state is smaller than the target brightness. 11. The method of claim 10,
Wherein when the brightness of the image in the overexposed state is greater than the target brightness, the saturated pixel is estimated to decrease when the exposure time decreases from the initial exposure time.

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