KR20110088680A - Image processing apparatus which can compensate a composite image obtained from a plurality of image - Google Patents

Abstract

PURPOSE: An image processing apparatus is provided to correct brightness of synthesis image based on the brightness difference between input images. CONSTITUTION: An image composition unit(13) creates a division area image data and a single image data in order to create single image which is composed of division area images. The image composition unit creates an image data through a data correction of the division area images and the single image. An image output unit(14) creates an output image based on the synthesis image data.

Description

IMAGE PROCESSING APPARATUS WHICH CAN COMPENSATE A COMPOSITE IMAGE OBTAINED FROM A PLURALITY OF IMAGE}

The present invention relates to an image processing apparatus having a correction function for a synthesized image obtained by synthesizing a plurality of images, and more particularly, when synthesizing a plurality of images acquired by a plurality of photographing apparatuses into a single image. The present invention relates to an apparatus having a function of correcting a synthesized image in consideration of brightness between images.

Recently, with the development of IT technology, attempts to apply it to vehicles are increasing. For example, a black box device that mounts a camera in a vehicle to record driving conditions or surrounding conditions, or a parking assistance system that installs a camera in the rear of the vehicle to take a rearward image and output it to a display device inside the vehicle when the vehicle is reversed. This trend is increasing. Meanwhile, among these technologies, wide-angle cameras are installed in front, rear, left, and right sides of the vehicle, and the images captured from these cameras are reconstructed into images of the form directly above the vehicle, that is, viewed from above, and output to the display device of the vehicle. There has also been proposed a system for the driver's convenience. Such a system is called a bird eye vie system or an AVM (around view monitoring) system in that it provides an image as if the bird is looking down from the sky. This technique uses a wide-angle camera with a fish eye lens to secure a wider viewing angle, which includes 1) distortion correction and 2) planarization for a plurality of image signals obtained using such a wide-angle camera. , 3) rearrangement step, and 4) single imaging step to construct and provide a composite image viewed from above the vehicle.

However, such a conventional composite image providing system generates a composite image in such a manner that the separate images obtained from the plurality of wide-angle cameras are connected to one image through the above-described process, so that they are acquired from the plurality of wide-angle cameras. There is a difference in brightness between different images due to various factors such as the exposure level of each camera and the amount of light provided. Such images may provide a very unnatural image between the divided images constituting a single image, especially between adjacent boundary regions, even though the single image is made through the above-described process. In order to solve this problem, a post-processing correction process is required to provide a natural image by performing brightness adjustment on an image after a single imaging, and in a conventional composite image providing system, a brightness adjustment process is provided. There is a problem in that the synthesized image is not natural, and also has to go through a very complex calculation process, which makes it difficult to process in real time and complicated circuit configuration, which increases the manufacturing cost. Therefore, this post-processing correction process is often omitted, thereby providing a very unnatural image.

SUMMARY OF THE INVENTION The present invention has been made in view of the above-described problems. In the case of synthesizing a single image using a plurality of input images obtained from a plurality of wide-angle cameras, the synthesis is performed based on the brightness difference between the respective input images. An object of the present invention is to provide an image processing apparatus capable of increasing user convenience by allowing a final synthesized image to appear natural by correcting an image brightness.

In addition, another object of the present invention is to provide an image processing apparatus that can simplify the circuit configuration by easily and easily adjusting the brightness of the synthesized image without harming the naturalness of the synthesized image, thereby reducing the manufacturing cost. It is done.

SUMMARY OF THE INVENTION In order to solve the above problems, the present invention provides an image processing apparatus having a correction function for a synthesized image obtained by synthesizing a plurality of images, wherein at least two or more images are arranged to partially overlap each other between adjacent wide-angle cameras. A plurality of wide angle cameras; An image receiver configured to receive input image data of at least two input images respectively obtained from the plurality of wide-angle cameras; Receives a plurality of input image data from the image receiver to generate a segment image data and a single image data to generate a single image consisting of a plurality of divided region images, and corrects and synthesizes the segment region image data and a single image data An image synthesizer for generating image data; And an image output unit configured to generate and output an output image based on the synthesized image data generated by the image synthesizer.

Here, the image synthesizing unit may generate composite image data by correcting the plurality of divided region image data and the single image data in consideration of brightness information of the boundary region between the plurality of divided region images constituting the single image. .

The image synthesizing unit may include a distortion correction step of generating a distortion correction image by performing distortion correction on each of at least two input images acquired from the plurality of wide-angle cameras, and distortion correction generated by the distortion correction step. A planarization step of generating a planarized image by performing planarization on each of the images, a rearrangement step of generating a rearrangement image by performing rearrangement on each of the planarized images generated by the planarization step, and in the rearrangement step A single image including a plurality of divided region images may be generated by a single imaging step of generating a single image based on the rearranged images generated by the image.

In addition, the image synthesizing unit, for each of the plurality of divided region images, brightness information of boundary pixels constituting a boundary region with other divided region images and brightness information of boundary pixels of other adjacent region images. Can be configured to correct a plurality of divided region image data and a single image data by making the same to each other.

Further, the brightness information of each boundary pixel may be equalized by the average value of the boundary pixels.

In addition, by calculating scale information with respect to the boundary pixels having the same brightness information, and changing brightness information with respect to pixels included in each divided area image based on the scale information, the brightness information is included in each divided area image. Brightness information of the pixels may be adjusted.

In addition, the scale information may be calculated by a Gaussian fuction.

According to the present invention, in the case of synthesizing a single image using a plurality of input images obtained from a plurality of wide-angle cameras, the final synthesized image is corrected by correcting the brightness of the synthesized image based on the brightness difference between the respective input images. It is possible to provide an image processing apparatus that can make this look natural and can increase user convenience.

In addition, according to the present invention, since the circuit configuration can be simplified by easily and easily adjusting the brightness of the synthesized image without harming the naturalness of the synthesized image, it is possible to provide an image processing apparatus that can reduce manufacturing costs. It works.

1 is a view showing the basic process of the conventional image synthesizing system and the image of each process.
2 is a block diagram illustrating an embodiment of an image processing apparatus having a correction function for a composite image obtained by synthesizing a plurality of images according to the present invention.
FIG. 3 is a diagram illustrating an example of a single image generated through the process described with reference to FIG. 1.
FIG. 4A is an enlarged view of a boundary area between the partition area image 1 and the partition area image 4 shown in FIG. 3, and FIG. 4B shows the boundary pixels included in the border area of FIG. 4A as blue (split area image 4) and red ( The image is divided into divided regions 1).
FIG. 5 illustrates an example of brightness information of a part of each of the boundary pixels shown in blue and red shown in FIG. 4B.
FIG. 6 illustrates an average value and a deceleration request value of brightness information between respective boundary pixels of FIG. 5.
7 illustrates a function value of a Gaussian function.
8 shows a graph of a Gaussian function.
9 is a diagram illustrating an example of an addition / deceleration request value using scale information.
FIG. 10 is a diagram illustrating an example of an image output from the image output unit 14 based on the corrected composite image data.

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

First, prior to explaining the embodiment according to the present invention, the principle of the prior art related to the present invention will be described schematically.

As described above, a wide-angle camera having a plurality of, for example, four fisheye lenses is installed on the front, rear, left, and right sides of the vehicle to take an image in the horizontal direction on the ground, and reconstruct the image into a form looking down from the top of the vehicle (hereinafter, For convenience, such a conventional technique is referred to simply as an "image synthesis system." The basic process of the conventional image synthesizing system and the image for each process are illustrated in FIG. 1.

Referring to FIG. 1, a conventional image synthesizing system is composed of six steps, an image input step S100, a distortion correction step S110, a planarization step S120, a rearrangement step S130, and a single imaging step S140. ) And a single image output step (S150).

The image input step S100 is a process of inputting image data of a plurality of images obtained from a plurality of wide-angle cameras. For example, when a plurality of cameras are mounted on an object that is a vehicle, four wide-angle cameras may be mounted on the front / rear / left side / right side, and the captured image is displayed as shown in FIG. 1. As described above, since the wide-angle camera has a fisheye lens, a wide field of view can be secured. In order to construct a single planarized image as described later by an image signal around a target object, a predetermined area is formed between each camera. This is because there must be overlapping parts and each camera must have a wide viewing angle to reconstruct the image with fewer cameras despite the overlapping areas. Meanwhile, in the present invention, the camera is used as a concept including not only a fisheye lens but also other electrical devices such as an image sensor. That is, it does not mean simply a mechanism for optically acquiring an image, but an apparatus for converting an optical signal into an electrical signal, for example, as shown in FIG. It is used as a concept that means a means to do.

On the other hand, when using a wide-angle camera equipped with a fisheye lens to use as few cameras as possible as described above, a wide viewing angle can be secured, but the image is distorted radially toward the edge of the acquired image. The distortion correction step S110 is a process for correcting such a distorted image. Fisheye lens distortion correction can be largely divided into two methods: "Equi-solid Angle Projection" and "Orthographic Projection", which define how fisheye lens rearranges the light entering the fisheye lens. Lens manufacturers choose one of two methods for manufacturing fisheye lenses. Therefore, if the inverse operation of the distortion operation is obtained according to the distortion method applied to the fisheye lens, and the image converted by the fisheye lens is inversely transformed, a "distortion corrected" image can be obtained, and the converted image is called a "distortion correction image". . The distortion correction image may be displayed as shown in FIG. 1, and an equation for performing distortion correction may use, for example, the following equation.

[Equation 1]

는 카메라의 촛점 거리,

는 카메라의 광중심에서 입력 영상의 (x,y) 좌표 즉,

까지의 거리,

및

은 입력 영상의 (x,y) 좌표값이고,

및

은 왜곡 보정 영상의 (x,y) 좌표값이다.
From here,

The focal length of the camera,

Is the (x, y) coordinate of the input image at the camera's optical center,

Distance to,

And

Is the (x, y) coordinate value of the input image,

And

Is the (x, y) coordinate value of the distortion corrected image.

Next, when the distortion correction image is obtained, a plane (homography) process is performed (S120). The planarization process (S120) is a process of converting an object onto an object, that is, an object on which a camera is mounted, into an image looking downward in a direction toward the ground, that is, vertically. As described above, since the distortion correction image obtained in the distortion correction step S110 corresponds to an image photographed at different viewpoints for each camera, these images are converted into an image of one viewpoint, that is, a vertically viewed viewpoint. The process is a flattening step (S120). An image generated by performing the flattening step S120 is called a flattened image, and an image after performing the flattening step S120 may be displayed as shown in FIG. 1, and the following equation may be used in this flattening step, for example. have.

[Equation 2]

은 상기 수식 1에 의해 획득된 왜곡 보정 영상의 (x,y) 좌표값이고,

은 상기 수식 2에 의해 변환된 평면화영상의 (x,y) 좌표값이며,

은 평면화 변환계수(이를 Perspective Transform이라고 한다)를 의미한다.
here,

Is a (x, y) coordinate value of the distortion correction image obtained by Equation 1,

Is the (x, y) coordinate value of the flattened image converted by Equation 2,

Is the flattening transform coefficient (called Perspective Transform).

Next, when a planarized image is obtained, an rearrangement step (Affine transform) is performed (S130). The rearrangement step (S130) is a step of rearranging the planarized images generated in the planarization step by applying only displacement movement and rotation, wherein the images photographed to surround the target object are reconstructed into surrounding images except for the target object. The rearrangement step S130 may be performed by only moving and rotating the pixel. For this, a method such as an affine transform may be used. An image generated through the rearrangement is called a rearrangement image, and the rearrangement image may be displayed as shown in FIG. 1.

In the rearrangement phase, you can use the following formula:

[Equation 3]

은 수식 2에 의해 변환된 평면화 영상의 (x,y) 좌표값이고,

은 수식 3에 의해 변환될 재배열 영상의 (x,y) 좌표값이고,

는 회전 변환 계수이고,

는 변위 이동 계수(

과

를 합쳐서 affine transform으로 정의한다)를 의미한다.
From here,

Is the (x, y) coordinate value of the flattened image converted by Equation 2,

Is the (x, y) coordinate value of the rearranged image to be converted by Equation 3,

Is the rotation conversion factor,

Is the displacement displacement coefficient (

and

To be defined as an affine transform).

Next, a single imaging step S140 is performed. Since the rearranged images are merely rearranged images, the images photographed around the object have a common area and the common areas are arranged to overlap each other. Therefore, a single imaging step is needed to process overlapping portions of the rearranged image having the common area to obtain one representative image for the common area. Since a single imaging step can use several implementations and can vary depending on the implementation, only the implementation principle is briefly described. When a common area occurs, the single imaging step divides the common area into pixels and analyzes the pixel to form a single image area using only pixels arranged at a more accurate position. The reference for the pixels arranged at the correct position may be various. The simplest reference may be, for example, the distance between the pixel and the optical center of the image to which the pixel belongs. By using this criterion, if the common region is reconstructed using only pixels closer to the optical center among the overlapping pixels of the common region, the rearranged image may be configured as a single image without overlapping regions. An image generated through a single imaging step is called a single image and may be displayed as shown in FIG. 1.

When the single imaging step (S140) is performed as described above, a flattened single image is obtained, and when it is output as a composite image (S150), as shown in FIG. You can see the image of the form.

On the other hand, the above-described steps and formulas 1, 2, and 3 used in each step are used by the prior art, and are not directly related to the present invention, and thus detailed descriptions thereof are omitted. In particular, each of the coefficients in Equations 2 and 3 may be determined differently according to the method or algorithm used, and the present invention is not related to the method of calculating such coefficients, and thus, detailed description thereof is also omitted.

2 is a block diagram illustrating an embodiment of an image processing apparatus 10 (hereinafter, simply referred to as an image processing apparatus) having a correction function for a composite image obtained by synthesizing a plurality of images according to the present invention.

The image processing apparatus 10 according to the present embodiment includes a plurality of wide-angle cameras 11, an image receiving unit 12, an image synthesizing unit 13, and an image signal output unit 14.

The plurality of wide-angle cameras 11 are arranged such that the photographing areas partially overlap between adjacent wide-angle cameras, and are composed of at least two or more pieces, each of which photographs an image, converts the image into an electrical signal, and transmits the image to the image receiving unit 12. As described above, it should be noted that each camera 11 is a concept including not only a simple optical apparatus but also an electrical apparatus such as an image sensor for converting an optical signal into an electrical signal. For example, when the target object is a vehicle, the wide-angle camera 11 may be disposed at the front / rear / left side / right side of the vehicle, and each of these cameras 11 may be located between the cameras 11 whose photographing areas are adjacent to each other. At least a portion is arranged to overlap.

The image receiving unit 12 is a means for receiving input image data of at least two input images respectively obtained from the plurality of wide-angle cameras 11, and transmits the received plurality of input image data to the image synthesizing unit 13. . If necessary, the image receiver 12 may perform an image preprocessing process using a filter.

The image synthesizing unit 13 is a means for generating composite image data by receiving a plurality of input image data from the image receiving unit 12 and performing the process as described in FIG. 1 from the plurality of input image data from the image data receiving unit. Single image data is generated to generate a single image. The single image generated by the image synthesizing unit 13 is composed of a plurality of divided region images, and divided region image data for each of the plurality of divided regions is generated, and based on these, single image data corresponding to the single image is generated. . In addition, the image synthesizing unit 13 generates composite image data of the synthesized image by correcting the divided region image data and the single image data generated as described above based on the brightness information.

Generating a single image in the image synthesizing unit 13 may be performed by the steps as described with reference to FIG. 1. That is, as described with reference to FIG. 1, a distortion correction step of generating distortion correction images by performing distortion correction on each of at least two or more input images acquired from a plurality of wide-angle cameras, and by the distortion correction step A flattening step of generating a planarized image by performing flattening on each of the distortion correction images, a rearrangement step of generating a rearranged image by performing rearrangement on each of the flattened images generated by the flattening step, and A single image is generated by a single imaging step of generating a single image based on the rearranged images generated by the arrangement step. Here, the single image is composed of a plurality of divided region images. In the present invention, the divided region image refers to a separate divided image constituting a single image, which will be described with reference to FIG. 3.

FIG. 3 illustrates an example of a single image generated through the process described with reference to FIG. 1. FIG. 3 illustrates a single image from input images acquired by four wide-angle cameras installed in a vehicle in front, rear, left, and right directions. It shows the created case.

In FIG. 3, the black part in the center represents a vehicle. When viewed from the center, the images are separated by having diagonal brightness between the front, left, right, and rear sides with different brightness. It can be seen that it represents an unnatural single image. As described above, the composite image providing system configures images acquired by different separate wide-angle cameras through distortion correction, planarization, and rearrangement steps, and selects one representative image for the overlapping regions and connects them. Since a single image is created in the form of a paste, each image gives a feeling of being separated from each other. In the present invention, the single image refers to the entire image of the form as shown in FIG. 3, and the divided region image refers to each of four images divided by diagonal lines in FIG. 3, and in front of FIG. 3. The divisional images 1,2,3,4 are shown clockwise from the image.

The image synthesizing unit 13 generates composite image data of the synthesized image by correcting the single image data and the divided region image data corresponding to the single image and the divided region image constituting the single image. At this time, the image synthesizing unit 13 generates composite image data by correcting the plurality of divided region image data and the single image data in consideration of brightness information of the boundary region between the plurality of divided region images constituting a single image. do.

This process will be described in more detail with reference to FIGS. 4A and 4B.

FIG. 4A is an enlarged view of a boundary area between the partition area image 1 and the partition area image 4 shown in FIG. 3, and FIG. 4B shows the boundary pixels included in the border area of FIG. 4A as blue (split area image 4) and red ( The image is divided into divided regions 1).

Brightness information for some of the respective boundary pixels shown in blue and red shown in FIG. 4B may be configured as shown in FIG. 5, for example. As shown in FIG. 5, it can be seen that the brightness information of the boundary pixels of the boundary region is different from each other to some extent to some extent. Therefore, in order to make them the same and make them the same, scale information corresponding to a value added to or subtracted from the brightness information is calculated, and brightness information is applied to the internal pixels included in each of the divided images according to the scale information. When adjusted, the boundary regions of the divided region images may appear naturally.

For example, referring to the divided region image 1 of FIG. 3 as an example, the divided region image 1 is adjacent to the divided region image 4 and the divided region image 2. The boundary pixels of the boundary regions of the divided region image 1 and the divided region image 4 which are in contact with each other may be displayed as shown in FIG. 4, and the boundary pixels of the boundary regions of the divided region image 1 and the divided region image 2 may be displayed similarly. .

Brightness information of the boundary pixels of each of the boundary regions of the divided region image 1 and the divided region image 4 may be configured as shown in FIG. It can be seen in the form similar to 5.

First, equalizing the brightness information of the boundary pixels of the boundary region between the divided region image 1 and the divided region image 4 may be configured by an average value of the brightness information of adjacent boundary pixels. For example, in the case of FIG. 5, the average value as shown in FIG. 6 can be obtained, and the brightness information can be equalized by adding or subtracting the difference from the average value to each of the boundary pixels. Figure 6 also shows these required values.

After the brightness information is the same for the boundary pixels as described above, the brightness information is also adjusted for the internal pixels of the partition image 1. Referring to the partition area image 1, as described above, the boundary pixels of the partition area image 1 may have the same brightness information as the boundary pixels of the partition area image 4. Scale information of a value added to or subtracted from may be obtained, and brightness information may be gradually changed for pixels included in the divided region image 1 from the boundary pixel based on the obtained scale information.

In this case, the scale information may be calculated by, for example, a Gaussian fuction.

Gaussian functions are represented by the following equation, as is well known.

When σ = 1, G (x) may be represented by a graph of the form of FIG. 8 as a value of FIG. 7.

Among these Gaussian functions, only one side based on the axis of symmetry, that is, the side of x> = 0, is used, and the value added or subtracted from the brightness information of the boundary pixels is scaled by the value at the x = 0 position of the Gaussian function, and this scale value By gradually scaling by the Gaussian function toward the inside of the divided region image, the brightness information of the pixels inside the divided region image may be naturally adjusted in the form as shown in the graph of the Gaussian function.

For example, in FIG. 6, the addition / decrease request value of the segmented image 1 is -7, -7, -8, -5, -5, and when the addition / decrease request value is reflected in the Gaussian function values of FIGS. The same deceleration request value can be obtained. That is, since the value of the original Gaussian function when x = 0 is G (0) = 0.383, in order to be G (x) =-7, 0.383 needs to be multiplied by -18.277 to satisfy G (x) =-7. Done. Therefore, -18.277 at this time becomes a scale value. Therefore, multiplying these scale values by the Gaussian function values G (1), G (2), G (3) ... corresponding to x = 1, 2, 3 ... in turn yields x = 1, 2, For the pixels corresponding to 3, the required value of brightness information to be added or subtracted can be obtained in the form of a Gaussian function. As shown in Fig. 9, the scale value at this time is -18.277 since the acceleration / deceleration request value is -7 for the first boundary pixel, and the result is multiplied by a Gaussian function value when x = 1, that is, the first boundary. The brightness adjustment / decrease request value -4.423 for the inner pixel of the adjacent divided region 1 of the pixel can be obtained, and the brightness information is changed for the pixel corresponding to x = 1 by this value. By sequentially performing this for x = 2, 3, 4 ..., all of the brightness information addition / requirement values for the pixels from the first boundary pixel toward the inside of the divided region can be obtained.

Similarly, in the case of G (x) =-8, since the scale value is -20.088, the neighboring pixels for this boundary pixel are multiplied by the Gaussian function value by this value sequentially, so that the brightness adjustment value can be known. 9, it can be seen that the addition / deceleration request value at x = 1 in this case is -5.055.

As described above, all of the boundary pixels of the partition image 1 may be obtained by using a Gaussian function as shown in FIG. 9. Therefore, the brightness information of the pixels in the partition image 1 may be obtained based on each boundary pixel. It is possible to obtain an addition / decrease request value, and by applying the addition / decrease request value, it is possible to perform correction so that the brightness information gradually changes naturally from the boundary area to the inner direction of the divided region image 1.

On the other hand, in the divided region image 1, it may be determined whether the brightness information is adjusted by applying the above acceleration / decrease request value from the boundary pixels to the inside of the divided region image 1 as follows. For example, the process may be performed up to half of the narrowest row or column size, or may be configured to perform the process up to half of the distance between pixels from the midpoint between each boundary region to each boundary region.

In summary, the divided region image 1 equalizes the brightness information between the boundary pixels in consideration of the boundary pixels of the divided region image 4 and the divided region image 2, and then stores the pixels inside the divided region image 1. The brightness information is gradually adjusted using the scale information in the same manner as described above. Similarly, the partition area image 2 performs the above process in consideration of the partition area image 1 and the partition area image 3, the partition area image 3 considers the partition area image 2 and the partition area image 4, and the partition area image 4 is the partition area. By performing the above-described process in consideration of the image 3 and the divided region image 1, the brightness information is corrected by adjusting the brightness information for the entire image.

As described above, when the brightness information is corrected for each divided region image, the divided region image data for each divided region image in which the corrected brightness information is reflected is generated, thereby generating the synthesized image data for the entire synthesized image. This is transmitted to the image output unit 14.

Referring to FIG. 2 again, the image output unit 14 generates an output image based on the synthesized image data generated by the image synthesizer 13 and outputs the image to an external display device such as an LCD monitor as described above. Do this.

FIG. 10 illustrates an image output from the image output unit 14 based on the corrected composite image data as described above. As shown in FIG. 10, the boundary regions between the respective divided region images are naturally connected to form a single screen as a whole. You can see it.

In the above, the present invention has been described with reference to preferred embodiments, but the present invention is not limited to the above embodiments, and those skilled in the art to which the present invention pertains may make various modifications and variations from such descriptions. will be. Therefore, the present invention should be construed with reference to the overall description of the appended claims and drawings, and all equivalent or equivalent modifications thereof will belong to the scope of the present invention.

로 표현되는 시그모이드(sigmoid) 함수나, 1차 또는 2차 함수를 이용할 수도 있다. 또한, 예컨대

등과 같은 함수를 이용할 수도 있다.
For example, in the above embodiment, the scale information is calculated using a Gaussian function, but is not limited thereto.

It is also possible to use a sigmoid (sigmoid) function, or a linear or quadratic function. Also, for example

You can also use functions such as

10 ... image processing unit,
11 camera,
12 ... video receiver,
13, video synthesis unit,
14.Video output.

Claims (7)

An image processing apparatus having a correction function for a composite image obtained by synthesizing a plurality of images,
A plurality of at least two wide-angle cameras arranged to partially overlap the photographing areas between adjacent wide-angle cameras;
An image receiver configured to receive input image data of at least two input images respectively obtained from the plurality of wide-angle cameras;
Receiving a plurality of input image data from the image receiving unit to generate a segment image data and a single image data to generate a single image consisting of a plurality of partition region images, and to correct and synthesize the partition region image data and a single image data An image synthesizer for generating image data; And
An image output unit which generates and outputs an output image based on the synthesized image data generated by the image synthesizer.
Image processing apparatus comprising a.
The method of claim 1,
The image synthesizing unit generates composite image data by correcting the plurality of divided region image data and the single image data in consideration of brightness information of the boundary region between the plurality of divided region images constituting the single image. Processing unit.
The method of claim 1,
The image synthesizing unit includes a distortion correction step of generating a distortion correction image by performing distortion correction on each of at least two input images obtained from the plurality of wide-angle cameras, and each of the distortion correction images generated by the distortion correction step. A planarization step of generating a planarized image by performing a planarization of the imager, a rearrangement step of generating a rearrangement image by rearranging each of the planarized images generated by the planarization step, and generating the rearrangement image And a single image composed of a plurality of divided region images by a single imaging step of generating a single image based on the rearranged images.
The method of claim 2,
The image synthesizing unit, for each of the plurality of divided region images, brightness information of boundary pixels constituting a boundary area with other divided region images and brightness information of boundary pixels of other adjacent region images are mutually different from each other. And correcting the plurality of divided region image data and the single image data by being equal.
The method of claim 4, wherein
And the brightness information of each boundary pixel is equalized by the average value of the boundary pixels.
The method of claim 4, wherein
Pixels included in each divided region image are calculated by calculating scale information with respect to the boundary pixels having the same brightness information, and changing brightness information for pixels included in each divided region image based on the scale information. The image processing apparatus, characterized in that for adjusting the brightness information for the field.
The method of claim 6,
And the scale information is calculated by a Gaussian function.

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