KR20140020464A - Apparatus and method for processing image - Google Patents

Abstract

An image processing device according to an embodiment of the present invention includes a step of receiving images; a step of dividing the received image into a plurality of blocks; a step of obtaining brightness information for the pixels by the divided blocks; a step of detecting a flare area among the divided blocks; a step of determining image restoration conditions applied to the flare area of the image and the rest of the area; and a step of restoring the initial image using the determined image restoration conditions. The image restoration condition applied to the flare area is different from the image restoration condition applied to the rest of the area. [Reference numerals] (AA) Start; (BB) No; (CC) Yes; (DD) End; (S201) Dividing an image into a plurality of blocks; (S202) Checking the brightness information for pixels by divided blocks; (S203) 255 area exists?; (S204) Determining a flare area to adjacent blocks located in an A^th location around the 255 area; (S205) Determining a correction point spread function to be applied to the A^th adjacent block; (S206) Restoring the initial image using the correction point spread function; (S207) Checking a reference point spread function; (S208) Restoring the initial image by applying the reference point spread function to all the blocks

Description

[0001] APPARATUS AND METHOD FOR PROCESSING IMAGE [0002]

An embodiment relates to a camera, and more particularly, to an image processing apparatus and its image processing method capable of removing a flare area included in an image using a point spread function.

Surveillance cameras (CCTV: Closed Circuit Television), which are installed in indoor and outside rooms of department stores, banks, exhibition halls, factories, etc., are used variously to prevent theft and to judge the operating state of the machine,

The surveillance camera has been installed in a specific place and has been used for the purpose of monitoring all the situations occurring in the place remotely, and includes a video transmitter and a display unit for receiving signals transmitted from the video transmitter and providing the signals to the display device .

Generally, a digital camera is similar in that it uses the optics and mechanisms of a general camera in its structure. However, instead of the film, an image is captured by a CCD (Charge Coupled Device), the signal is converted into digital data, The difference is that it takes the approach of storing it in memory as a file.

Such a digital camera can instantly check captured images on a display screen, and can process various data such as editing and output through a computer. If necessary, it can print on a printer without complicated film phenomenon and printing process, Utilization is expanding.

Figs. 1 to 3 are views for explaining flare phenomena occurring according to the prior art.

In the camera according to the related art, when bright light comes from the outside, a sensor saturation state occurs, and a flare phenomenon occurs in which the whole of the photographed image is whitened.

1, the flare phenomenon is generated by a light source such as a zero-order light or a secondary light other than the primary light that the image is accurately formed on the image plane of the image sensor.

That is, as shown in FIG. 2, the secondary light and the zeroth-order light occur in the form of a graph around the primary light, and as the intensity of the primary light increases, the intensity of the zero- .

Accordingly, an image as shown in FIG. 3 is displayed, and a flare is formed around the light source in the displayed image, which causes image quality deterioration.

Such a flare is produced because the 0th order light and the second order light are not accurately formed on the image plane. If the brightness is reduced in order to reduce the flare, the gradation of the dark portion is buried, which causes another image quality deterioration.

Accordingly, there is a need for a technique capable of reducing the image flare phenomenon and preventing deterioration of image quality.

Embodiments provide an image processing apparatus and an image processing method thereof capable of detecting a flare region included in an image and restoring the detected flare region into an original image.

In addition, in the embodiment, a camera and its image processing method capable of dividing an image into a predetermined area and applying different point spread functions to the divided area to restore original images before flare occurs to provide.

It is to be understood that the technical objectives to be achieved by the embodiments are not limited to the technical matters mentioned above and that other technical subjects not mentioned are apparent to those skilled in the art to which the embodiments proposed from the following description belong, It can be understood.

An image processing apparatus according to an embodiment includes: an image; Dividing the received image into a plurality of blocks; Obtaining brightness information of a pixel for each of the divided blocks; Detecting a flare region of the divided blocks using the obtained brightness information; Determining an image restoration condition to be applied to the flare area of the image and other areas; And restoring an original image using the determined image restoration condition, wherein an image restoration condition applied to the flare area and an image restoration condition applied to the other area are different from each other.

The step of detecting the flare region may include the steps of: identifying a first block in which the number of pixels having 255 levels in each of the blocks is equal to or greater than a predetermined reference value using the obtained brightness information; And detecting an adjacent block of one block as the flare area.

The detecting as the flare area may include detecting a neighboring block located from the first block to the Nth flare area.

In addition, the adjacent block includes blocks adjacent to the first, lower, left, and right directions of the first block.

The determining of the image restoration condition may include deriving a reference point spread function from the lens and calculating a correction point spread function to be applied to the flare area using the derived reference point spread function .

The calculated correction point spread function is applied to the flare area, and the derived reference point spread function is applied to the remaining area except for the flare area.

In addition, the step of determining the image restoration condition may include calculating a correction point spread function to be applied to each of the adjacent blocks according to a degree of proximity to the first block.

Also, the adjacent block includes a first adjacent block from the first block to an Nth adjacent Nth adjacent block, and the correction point spread function calculated for the first adjacent block to the Nth adjacent block includes They are different.

In addition, a correction point spread function calculated for the first adjacent block among the correction point spread functions calculated for the first adjacent block to the Nth adjacent block has a largest value.

The correction point spread function calculated for the first adjacent block to the Nth adjacent block decreases in size as the distance from the first block increases.

In addition, the step of reconstructing the image may include performing convolution using the correction point spread function calculated for each adjacent block and the reference point spread function.

Further, the method further comprises refining the flare region, wherein the correction point spread function is calculated for each of the subdivided blocks.

Meanwhile, an image processing apparatus according to an embodiment includes a lens; An image sensor for converting light received through the lens into an electrical image; Wherein the controller is configured to divide the image converted by the image sensor into a plurality of blocks, detect a flare area using the brightness information of each of the divided blocks, An image processor for restoring the original image by applying restoration conditions; And a control unit for setting an image restoration condition to be applied to the flare area and controlling the restoration of the image according to the set image restoration condition, wherein the control unit controls the flare area, the flare area, The image restoration conditions to be applied to the area of the image are different from each other.

The image processing unit may further include an area dividing unit dividing the image into a plurality of blocks, a brightness level determining unit that obtains brightness information of each of the blocks divided through the area dividing unit, A flare region detecting unit for detecting a flare region in which a flare occurs among the plurality of blocks; and an image restoring unit for restoring an original image by applying different image restoring conditions to the detected flare region and other regions .

The flare area detecting unit may identify the first block in which the number of pixels having 255 levels in each of the blocks is equal to or greater than a preset reference value using the obtained brightness information, Is detected as the flare area.

Further, the flare area detecting unit detects the adjacent block located from the first block to the N-th position as a flare area.

In addition, the adjacent block includes blocks adjacent to the first, lower, left, and right directions of the first block.

Also, the control unit derives a reference point spread function from the lens, and calculates a correction point spread function to be applied to the flare area using the derived reference point spread function.

Also, the control unit applies the calculated correction point spread function to the flare area, and applies the derived reference point spread function to the remaining area excluding the flare area so that image restoration is performed.

Also, the control unit calculates a correction point spread function to be applied to each adjacent block specified as the flare area according to the degree of proximity to the first block.

Also, the adjacent block includes a first adjacent block from the first block to an Nth adjacent Nth adjacent block, and the correction point spread function calculated for the first adjacent block to the Nth adjacent block includes They are different.

In addition, a correction point spread function calculated for the first adjacent block among the correction point spread functions calculated for the first adjacent block to the Nth adjacent block has a largest value.

The correction point spread function calculated for the first adjacent block to the Nth adjacent block decreases in size as the distance from the first block increases.

The image restoration unit performs convolution using the correction point spread function calculated for each adjacent block and the reference point spread function.

When the flare region is detected, the region dividing unit re-divides the detected flare region into subdivided blocks, and the control unit calculates a correction point spread function to be applied to each of the subdivided blocks.

According to the embodiment, the original image can be easily restored without deteriorating the image quality by analyzing the image and detecting the area where the flare occurs, and by applying different point spread functions to remove the flare.

Figs. 1 to 3 are views for explaining flare phenomena occurring according to the prior art.
4 is a diagram showing an image processing apparatus according to an embodiment.
5 is a detailed configuration diagram of the image processing unit 130 shown in FIG.
FIG. 6 is a view for explaining the principle of image restoration according to the embodiment.
FIGS. 7 to 12 are views for explaining an image restoration process according to the embodiment.
13 to 15 are flowcharts for explaining the image processing method of the image processing apparatus according to the embodiment step by step.

The following merely illustrates the principles of the invention. Thus, those skilled in the art will be able to devise various apparatuses which, although not explicitly described or shown herein, embody the principles of the invention and are included in the concept and scope of the invention. Furthermore, all of the conditional terms and embodiments listed herein are, in principle, only intended for the purpose of enabling understanding of the concepts of the present invention, and are not to be construed as limited to such specifically recited embodiments and conditions do.

It is also to be understood that the detailed description, as well as the principles, aspects and embodiments of the invention, as well as specific embodiments thereof, are intended to cover structural and functional equivalents thereof. It is also to be understood that such equivalents include all elements contemplated to perform the same function irrespective of the currently known equivalents as well as the equivalents to be developed in the future, i.e., the structure.

Thus, for example, it should be understood that the block diagrams herein illustrate conceptual aspects of exemplary circuits embodying the principles of the invention. Similarly, all flowcharts, state transition diagrams, pseudo code, and the like are representative of various processes that may be substantially represented on a computer-readable medium and executed by a computer or processor, whether or not the computer or processor is explicitly shown .

The functions of the various elements shown in the figures, including the functional blocks depicted in the processor or similar concept, may be provided by use of dedicated hardware as well as hardware capable of executing software in connection with appropriate software. When provided by a processor, the functions may be provided by a single dedicated processor, a single shared processor, or a plurality of individual processors, some of which may be shared.

Also, the explicit use of terms such as processor, control, or similar concepts should not be interpreted exclusively as hardware capable of running software, and may be used without limitation as a digital signal processor (DSP) (ROM), random access memory (RAM), and non-volatile memory. Other hardware may also be included.

4 is a diagram showing an image processing apparatus according to an embodiment.

4, the image processing apparatus includes a lens 110, an image sensor unit 120, an image processing unit 130, a display unit 140, an input unit 150, a storage unit 160, and a control unit 170 do.

The lens 110 allows the optical image of the subject to be formed on the image sensor unit 120. [

The lens 110 may include a zoom lens (not shown) and a focus lens (not shown) movable in the direction of the optical axis to focus an optical image formed on the image sensor unit 120.

Here, the lens 110 may be a lens having a large aperture stop diameter, and thus having an optical characteristic with a short focal length. That is, it may be a lens having a small F number, or may be a general lens without a separate lens design.

At this time, the lens 110 acquires an image of a subject to be photographed by the user.

More specifically, the lens 110 includes a first lens group including at least one surface composed of a diffractive optical element and a second lens group including at least one surface composed of a convex lens composed of a diffractive optical element .

The first lens group is a concave lens having negative power so as to have a wide viewing angle and a sufficient back focal length (BFL), one surface of which is an aspherical surface, and at least one surface of the diffractive optical element Since the dispersion on the surface on which the diffractive optical element is formed has a negative sign, the chromatic aberration on the axis can be corrected easily, but the shape of the lens can be taken to some extent by imposing a part of the power.

The second lens group having a convex lens shape has a positive power, at least one surface is an aspherical surface, and at least one surface is composed of a diffractive optical element, and the first lens group of the concave lens shape Converge the acquired image information.

The image sensor unit 120 may be a Complementary Metal-Oxide Semiconductor (CMOS) or a Charge Coupled Device (CCD).

The image sensor unit 120 is a form in which a plurality of photodetectors are integrated as respective pixels, and converts image information of a subject into electrical data and outputs the electrical data.

That is, the image sensor unit 120 senses an image of a subject passing through the lens 110. The sensed image may be transmitted to a user at a remote location.

The image sensor unit 120 accumulates the amount of light input through the lens 110 and outputs the image photographed by the lens 110 according to the stored amount of light according to the vertical synchronization signal.

Image acquisition is performed by the image sensor unit 120 that converts light reflected from a subject into an electrical signal.

In order to obtain a color image using the image sensor unit 120, a color filter is required, and a filter (not shown) called CFA (Color Filter Array) is employed in most cases. CFA passes only light representing one color per pixel, has a regularly arranged structure, and has various forms according to the arrangement structure.

The image processor 130 receives an electric signal from the image sensor unit 120.

The electric signal includes an image value of an image formed, and the image processor 130 processes the image value.

That is, the image processing unit 130 analyzes the image obtained through the image sensor unit 120 on a frame-by-frame basis, and restores the original image from which the flare area included in the image is removed.

To this end, the image processing unit 130 detects a flare region from the image acquired by the image sensor unit 120, and changes the image processing condition of the flare region, thereby removing the flare region.

Accordingly, the image processor 130 divides the image into a plurality of blocks. In this case, the number of blocks to be divided may vary according to the embodiment. In the embodiment, the number of blocks is divided into 100 blocks.

If the image is divided into a plurality of blocks, the image processing unit 130 determines a luminance level of the pixels for each of the divided blocks. At this time, the brightness level may be a gray level.

In this case, the flare area includes an area where an object such as an incandescent lamp is photographed and an adjacent area adjacent to the area, and an area where a substantial flare occurs in the flare area is a peripheral area of the area where the object is photographed, Corresponds to the edge area of the photographed area.

On the other hand, the flare area is an adjacent area of an area where an object such as an incandescent lamp is photographed as described above, and the luminance level of the area in which the object is photographed has a maximum luminance level of 255 levels.

In other words, the area where the object such as the incandescent lamp is photographed can be referred to as the 255 area, and the flare area is the area adjacent to the 255 area. At this time, the adjacent region may include a left region, a right region, an upper region, and a lower region of the 255 region.

In addition, the adjacent region may include only the block located immediately adjacent to the 255 region, and may be included in the adjacent region from the 255 region to the A-th located block.

The definition of the adjacent region may be changed according to a division condition of the image. If the image is divided into a smaller number of blocks, the adjacent region may be reduced. If the image is divided into many blocks, The area of recognition will also increase.

For example, when the image is divided into 10 blocks, the adjacent region may include only blocks located immediately adjacent to the 255 region. Otherwise, if the image is divided into 100 blocks, May be included up to the fifth block adjacent to the 255 area.

On the other hand, as a criterion for determining the flare area, if the continuity of the object having the 255 level is determined, and the continuity does not have 100 pixels or more, that is, It is possible to judge the adjacent area as the flare area from the center point of the area having the 255 level, if not continuously.

Alternatively, if there is a block in which the number of pixels having 255 levels is equal to or greater than a predetermined number, an adjacent block of the block may be determined as the flare area.

Accordingly, the image processing unit 130 determines the 255 area based on the above-described criteria, and if the 255 area exists, the image processor 130 determines the adjacent block of the 255 area as the flare area.

In addition, assuming that the flare area includes a 255th to a 5th block, the flare area may include a first neighboring block, a second neighboring block, a third neighboring block, An adjacent block, a fourth adjacent block, and a fifth adjacent block.

Hereinafter, the image processing unit 130 receives a point spread function to be applied to adjacent blocks included in the flare area, and performs a restoration process on the adjacent block by applying the received point spread function.

At this time, the point spread functions applied to the first to fifth adjacent blocks are different from each other, and accordingly, the applied point spread function will increase according to the neighboring areas.

For example, assuming that the point spread function according to the optical characteristics of the lens is 1, the point spread function applied to the 255 area may be 1, and the point spread function applied to the first adjacent block may be 5 , The point spread function applied to the second adjacent block may be 4, the point spread function applied to the third adjacent block may be 3, and the point spread function applied to the fourth adjacent block may be 2 , The point spread function applied to the first adjacent block may be one. Also, the point spread function applied to the 255 area and the remaining area excluding the flare area in the image will be 1.

That is, since the degree of saturation of light becomes worse as it gets closer to the 255 area, in the embodiment, the point spread function having a higher multiple adjacent to the 255 area is applied so that the image before saturation can be restored.

In addition, the image processing unit 130 may perform an interpolation process, a gamma correction, an edge enhancement, an auto exposure (AU) control, an auto white balance (AWB) And a digital zoom function.

The display unit 140 displays the photographed image under the control of the control unit 170, which will be described later, and displays a setting screen required for taking a picture or a screen for selecting a user's action.

Also, according to the embodiment, when a preview key is input, a preview screen is displayed, and a pop-up screen popped up at the time of shooting key input, or a predetermined animation or image is displayed.

The input unit 150 receives a user input and transmits the input to the controller 170.

When the display unit 140 is implemented as a touch screen, the display unit 140 may operate as the input unit 150 at the same time.

According to the embodiment, the input unit 150 may further include a photographing key for photographing and a preview key for displaying a preview screen.

The storage unit 160 stores data necessary for the image processing apparatus 100 to operate.

In addition, the storage unit 160 stores a pop-up screen, an animation, or an image to be displayed through the display unit 140 when a shooting key is input.

The storage unit 160 may be a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (for example, SD or XD memory) RAM, ROM (EEPROM, etc.), and the like.

The control unit 170 controls each configuration of the image processing apparatus.

In an embodiment, the control unit 170 causes the image processing unit 130 to output an image in which the flare is removed, so that the image in which the flare is removed is displayed through the display unit 140.

For this purpose, the controller 170 determines an image restoration condition for the flare area confirmed through the image processing unit 130, and restores the image of the flare area using the determined image restoration condition.

Hereinafter, the image restoration process will be described in more detail.

5 is a detailed configuration diagram of the image processing unit 130 shown in FIG.

5, the image processing unit 130 includes an area dividing unit 131, a brightness level determining unit 132, a flare area detecting unit 133, an image restoring unit 134, and an image output unit 135 .

The region dividing unit 131 receives the image output through the image sensor unit 120 and divides the received image according to a predetermined division condition.

The segmentation condition may vary depending on the resolution of the image.

When the number of divided blocks increases, the amount of calculation is increased, but more accurate flare removal can be performed.

The brightness level determining unit 132 receives the divided image through the area dividing unit 131, and confirms the brightness level of the pixel for each of the divided blocks.

At this time, the brightness level can be grasped through histogram analysis.

Here, the histogram includes the frequency number, the number of peaks, the peak distance, and the peak width. Generally, a histogram shows the distribution of brightness values for pixels in an image. When a bright pixel and a dark pixel are distributed, the range and value are expressed. A histogram is called a histogram graph. For example, 256 gray In the level image, the range of brightness values has a value from 0 to 255, and the number of brightness values, that is, the frequency of the level, is represented by the height of the graph. The histogram has a lot of image information and is used for various image processing.

The flare area detecting unit 133 detects the flare area with reference to the brightness level of each block detected through the brightness level determining unit 132. [

For example, if the pixel having the 255 level exceeds the predetermined reference range, the flare area detecting unit 133 can determine the corresponding block as the 255 area and accordingly detect the adjacent area of the 255 area as the flare area have.

When the flare area is detected, the image restoring unit 134 performs image restoration by applying a different point spread function to the detected flare area.

The point spread function to be applied to the flare area is set by the control unit 170, and a detailed description thereof will be described later.

The image output unit 135 outputs the restored image through the image restoration unit 134.

FIG. 6 is a view for explaining the principle of image restoration according to the embodiment.

6, when the original image f [x, y] passes through the lens according to a specific point spread function h [x, y], a captured image g [x, y] is generated.

)를 산출하여, 입력(g[x, y])에 대한 콘볼루션 연산을 취득하면 원 영상을 복원할 수 있다.At this time, the reciprocal of the point spread function (

), And acquires a convolution operation on the input g [x, y], thereby restoring the original image.

At this time, before the camera sensor is saturated, the original image can be accurately reconstructed by performing the convolution as described above.

를 적용한다 하더라도 정확한 원 이미지를 복원할 수 없다. 이는 강한 광원에서 잡음 레벨이 높아지고 화질이 떨어지는 원인으로 작용한다.However, after the camera sensor is saturated, even if the convolution is performed as described above, since the sensor has already saturated, it is as if the point spread function is applied to a value other than h [x, y] , And accordingly,

The correct original image can not be restored. This causes the noise level to rise in a strong light source and cause the image quality to deteriorate.

Accordingly, in the embodiment, if the flare area is generated by saturation, it is confirmed that the flare area is applied to a point spread function different from the original point spread function, and the flare area is applied to the flare area for the original image restoration Correct the point spread function.

Hereinafter, the image restoration process will be described in detail with reference to the accompanying drawings.

FIGS. 7 to 12 are views for explaining an image restoration process according to the embodiment.

First, referring to FIG. 7, the region dividing unit 131 divides the input image into a plurality of blocks according to a predetermined division condition.

That is, the region dividing unit 131 divides the input image 700 into 100 blocks having the same size as the first block 710.

At this time, it is illustrated that the image is divided into 100 blocks in the drawing, but this is only an example, and the number of divided blocks may be further increased or decreased.

Next, referring to FIG. 8, the brightness level determiner 132 determines a brightness level for each of the pixels divided through the area dividing unit 131, for each pixel.

The brightness level can be confirmed according to the analysis of the histogram as described above.

The flare area detecting unit 133 receives the information about the brightness level confirmed by the brightness level determining unit 132 and determines whether the predetermined number of pixels (for example, 100 or more) It is determined whether or not a block exists.

If the block having the 255 level exists, the flare area detecting unit 133 designates the block as the 255 area (center area of the flare area).

In FIG. 8, the number of pixels having the 255 level among the pixels included in the first block 810 on the input image 800 is out of a preset reference value, and accordingly, the first block 810 is designated as the 255 area .

Then, when the 255 area is confirmed, the flare area detector 133 designates the adjacent area 820 of the 255 area as a flare area.

At this time, the adjacent region 820 may include up to the A-th block in the up, down, left, and right directions with respect to the 255 region. In addition, although the adjacent region 820 includes the block located at the second position in the up, down, left, and right directions with respect to the 255 region in the figure, it is only one embodiment, Will increase or decrease further.

Accordingly, the adjacent region 820 includes a first neighboring region 822 including blocks located first in the upper, lower, left, and right directions with respect to the 255 region, and a second adjacent region 822 including blocks located second And may include an adjacent region 824.

FIG. 9 is a graph showing the brightness increasing rate with respect to the adjacent area.

Referring to FIG. 9, it can be seen that the slope increases sharply in the 255 area as shown in the drawing.

It can be seen that the degree of saturation of the image is severe, and the degree of distortion of the point spread function is large.

Accordingly, in the embodiment, the degree of distortion of the point spread function is large according to the degree of saturation of the image, that is, the degree of proximity to the area 255, so that the compensation rate of the point spread function is increased.

For example, since the distortion does not occur in the area 255, the original point spread function is applied as it is, and the correction point spread function that applies a certain multiple to the point spread function is applied to the adjacent area in the area 255. In addition, the correction point spread function increases as the 255 area is further increased, so that the correction point spread function applied to the farthest adjacent area will be substantially the same as the original point spread function.

In other words, referring to FIG. 10, in the embodiment, the original point spread function, that is, the reference point spread function is applied to the 255 area to restore the original image.

In addition, the first neighboring region (A) closest to the 255 region applies a first correction point spread function taking a first multiple to the reference point spread function.

The second neighboring region B, which is adjacent to the 255 region, applies a second correction point spread function that takes a second multiple to the reference point spread function.

The first multiple applied to the first correction point spread function is greater than the second multiple applied to the second correction point spread function. That is, since the degree of distortion of the point spread function is significant according to the degree of proximity to the 255 area, a correction point spread function is calculated by taking a higher multiple.

For example, the reference point spread function may be 1 * PSF, the first correction point spread function may be 5 * PSF, and the second correction point spread function may be 3 * PSF.

When the reference point spread function and the correction point spread function are determined, the image restoration unit 134 performs a convolution by taking the reciprocal of the reference point spread function and the correction point spread function, thereby restoring the original image from which the flare area has been removed do.

Meanwhile, although the correction point spread function may be applied in the same manner as described above, it is possible to further refine the area designated as the flare area for more accurate flare removal.

That is, in the above description, two adjacent blocks around the 255 area are designated as flare areas, and thus two correction point spread functions are applied.

This means that although the flare can be removed, the satisfaction of the flare removal may not be maximized.

Accordingly, in the embodiment, when the flare area is designated as shown in FIG. 11, the area dividing unit 131 performs a more finely divided operation on the flare area.

In other words, although two blocks are conventionally designated as flare areas, the two blocks are subdivided into five blocks so that five adjacent blocks are included in the flare area.

Accordingly, the correction point spread function for the five adjacent blocks is calculated, and the reciprocal of the correction point spread function is calculated so that the original image restoration is performed.

That is, a first correction point spread function is applied to the first adjacent block closest to the 255 region, a second correction point spread function is applied to the second adjacent block adjacent to the second adjacent block, The third correction point spread function is applied to the third adjacent block, the fourth correction point spread function is applied to the fourth adjacent block which is the fourth adjacent block, and the fifth correction is performed to the fifth adjacent block, Apply the point spread function.

In this case, the relationship between the first correction point spread function and the fifth correction point spread function becomes smaller as the distance from the 255 area is increased, and the correction point spread function applied to the block farthest from the 255 area is smaller than the reference point spread function It becomes almost the same.

When the convolution is performed by applying the correction point spread function as described above, the object region such as the actual light source remains as shown in FIG. 12, and only the flare occurring in the vicinity thereof can be effectively removed.

In addition, since the reference point spread function is directly applied to other regions except for the flare region, image quality deterioration occurring in the other region can be prevented.

According to the embodiment, the original image can be easily restored without deteriorating the image quality by analyzing the image to detect the area where the flare occurs, and by applying different point spread functions to remove the flare .

13 to 15 are flowcharts for explaining the image processing method of the image processing apparatus according to the embodiment step by step.

First, referring to FIG. 13, the image processing apparatus receives an image input through the lens 110 (Step 101).

Thereafter, when the image is received, it is determined whether 255 area exists by using the luminance level of the received image. If the 255 area exists, the neighboring area of the 255 area is confirmed as a flare area (step 102) .

The flare area may be an adjacent block spaced by the A th center around the 255 area.

When the flare area is confirmed, the image processing apparatus derives a reference point spread function from the lens 110 (step 103).

Thereafter, a correction point spread function applied to the flare area is determined (step 104).

That is, the correction point spread function is calculated by multiplying the reference point spread function by a multiple of a high constant so as to be adjacent to the 255 area. At this time, the calculated correction point spread function has the largest value to be applied to the closest neighboring block in the 255 area, and thus becomes smaller as it gets further from the 255 area.

Thereafter, the image processing apparatus restores the original image using the reference point spread function and the correction point spread function (step 105).

Referring to FIG. 14, when the image is received, the received image is divided into a plurality of blocks (step 201).

Then, for each of the divided blocks, a brightness level for each pixel is checked (step 202).

If the luminance level for each pixel is confirmed, it is determined whether or not the 255 area of the block is present (step 203).

That is, it is determined whether or not there is a block whose number of pixels having 255 levels is equal to or greater than a preset reference value.

If the 255 area is present, it is determined that the blocks adjacent to the A th to the center of the 255 area are the adjacent area (operation 204).

Thereafter, a correction point spread function to be applied to the Ath neighbor block is determined (step 205). The method of determining the correction point spread function has been described above, and a description thereof will be omitted.

When the correction point spread function is determined, a restoration process for each block of the image is performed using the determined correction point spread function and the reference point spread function (operation 206).

On the other hand, if the 255 area does not exist, it is determined that the sensor saturation has not occurred, and the reference point spread function is checked accordingly (step 207).

Then, the reference point spread function is applied to all blocks of the image to restore the original image (step 208).

Next, referring to FIG. 15, when the flare area is determined, the determined flare area is separated (step 301).

Thereafter, the separated flare area is subdivided into a larger number of blocks than the previous partitioning condition (step 302).

Next, a correction point spread function to be applied to each of the adjacent blocks that have been segmented and divided is determined (step 303)

Thereafter, the original image is restored using the determined correction point spread function (step 304).

According to the embodiment, the original image can be easily restored without deteriorating the image quality by analyzing the image and detecting the area where the flare occurs, and by applying different point spread functions to remove the flare.

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, but, on the contrary, It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention.

110: lens
120: Image sensor unit
130:
140:
150:
160:
170:
131:
132: Brightness level determination unit
133: flare area detecting section
134: image restoration unit
135: image output section

Claims (15)

Receiving an image;
Dividing the received image into a plurality of blocks;
Obtaining brightness information of a pixel for each of the divided blocks;
Detecting a flare region of the divided blocks using the obtained brightness information;
Determining an image restoration condition to be applied to the flare area of the image and other areas; And
And restoring the original image using the determined image restoration condition,
Wherein image restoration conditions applied to the flare area and image restoration conditions applied to the other areas are different from each other. The method according to claim 1,
Wherein the step of detecting the flare region comprises:
Identifying a first block in which the number of pixels having 255 levels in each of the blocks is equal to or greater than a preset reference value using the obtained brightness information,
And detecting the adjacent block of the identified first block as the flare area. The method according to claim 1,
Wherein the step of determining the image restoration condition comprises:
Deriving a reference point spread function from the lens,
And calculating a correction point spread function to be applied to the flare area using the derived reference point spread function. The method of claim 3,
In the flare area,
The calculated correction point spread function is applied,
In the remaining region except for the flare region,
An image processing method to which the derived reference point spread function is applied lens;
An image sensor for converting light received through the lens into an electrical image;
Wherein the controller is configured to divide the image converted by the image sensor into a plurality of blocks, detect a flare area using the brightness information of each of the divided blocks, And an image processing unit for restoring the original image by applying restoration conditions. 6. The method of claim 5,
The image restoration condition includes:
And a point spread function to be used for the image restoration. 6. The method of claim 5,
Wherein the image processing unit comprises:
An area dividing unit dividing the image into a plurality of blocks;
A brightness level determining unit for obtaining brightness information for each block divided through the area dividing unit,
A flare region detecting unit that detects a flare region in which a flare occurs among the plurality of blocks using the determined brightness information;
And an image restoration unit for restoring an original image by applying different image restoration conditions to the detected flare area and other areas. 6. The method of claim 5,
Wherein the image processing unit comprises:
And a controller for checking the first block in which the number of pixels having 255 levels in each of the blocks is equal to or greater than a preset reference value using the obtained brightness information and detecting an adjacent block in the verified first block as the flare area Processing device. 9. The method of claim 8,
Further comprising a controller configured to set an image restoration condition to be applied to the flare area and to control restoration of the image according to the set image restoration condition,
Wherein,
Wherein the image restoration conditions to be applied to the flare area and the other areas except for the flare area are different from each other. 10. The method of claim 9,
Wherein,
Deriving a reference point spread function from the lens, and calculating a correction point spread function to be applied to the flare region using the derived reference point spread function. 11. The method of claim 10,
Wherein,
Applying the calculated correction point spread function to the flare area,
Wherein the derived reference point spread function is applied to the remaining region except for the flare region to perform image restoration. 11. The method of claim 10,
Wherein,
And calculates a correction point spread function to be applied to each adjacent block designated as the flare area according to the degree of proximity to the first block. 13. The method of claim 12,
Wherein the adjacent block comprises:
A first adjacent block from the first block to an Nth adjacent Nth adjacent block,
Wherein the correction point spread functions calculated for the first to Nth adjacent blocks are different from each other. 14. The method of claim 13,
Wherein the image processing unit comprises:
And performs convolution using the correction point spread function calculated for each adjacent block and the reference point spread function. 11. The method of claim 10,
Wherein the image processing unit comprises:
If the flare region is detected, re-segment the detected flare region into subdivided blocks,
Wherein,
And calculates a correction point spread function to be applied to each of the re-divided blocks.

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