KR20210063207A - apparatus and method for image processing - Google Patents

Abstract

The present invention relates to a video processing apparatus to increase a video data transmission compression rate and a video processing method thereof. According to an embodiment of the present invention, the video processing apparatus comprises: an area comparison unit receiving first luminance information corresponding to a first video signal and second luminance information corresponding to a second video signal, and generating third luminance information by using the first luminance information and the second luminance information; an area determination unit calculating a brightness value of the first video signal by using the first luminance information; a reliability determination unit calculating a reliability determination value of the first video signal by using the first luminance information; an extraction unit generating a luminance correction threshold of the first video signal by using the brightness level value of the first video signal output from the area determination unit and the reliability determination value of the first video signal output from the reliability determination unit; and an interpolation unit outputting corrected luminance information for the first luminance information by using the luminance correction threshold and the third luminance information.

Description

Image processing apparatus and method {apparatus and method for image processing}

An embodiment of the present invention relates to a surveillance camera system, and more particularly, to an image processing apparatus and method applied to a surveillance camera system.

In recent years, it is common to install a surveillance camera system inside or outside a building, on the street, etc. Such a surveillance camera system may perform a function as a network camera by connecting a plurality of cameras to each other through a network by wire or wirelessly.

In transmitting the image data captured by the surveillance camera, various compression techniques may be used to reduce the amount of image data transmitted. For example, by dividing transmitted image data into a plurality of blocks, a block including a region with a lot of various motions among the blocks decreases the compression rate, and conversely, by increasing the compression rate for a block including a region with low motion, the transmission compression rate A method of maximizing the

In addition, since most of the surveillance cameras used in the network-based surveillance camera system need to be operated 24 hours a day, it is necessary to generate an image of a higher quality even in a low-light environment such as a dark place or at night, but in a low-light environment, there is noise in the image. likely to occur As a method for improving the quality of the image data, a method of boosting the luminance of a portion (block) with a high amount of change of an image may be used. However, such an image quality improvement method does not take into account the aforementioned transmission compression ratio. have.

Accordingly, when the block including the low illuminance region is boosted, invisible low illuminance noise may also be boosted, which may result in a problem of lowering the compression rate or image quality.

In an image processing apparatus and method applied to a surveillance camera system, an embodiment of the present invention provides image processing capable of increasing image data transmission compression rate by suppressing a boosting phenomenon applicable to low-illuminance noise while reducing loss of original image data It is an object of the present invention to provide an apparatus and method.

In order to achieve the above object, an image processing apparatus according to an embodiment of the present invention receives first luminance information corresponding to a first image signal and second luminance information corresponding to a second image signal, and the first luminance information and a region comparison unit generating third luminance information by using the second luminance information. an area determination unit calculating a brightness level value of the first image signal by using the first brightness information; a reliability determination unit for calculating a reliability determination value for the first image signal by using the first luminance information; an extractor configured to generate a luminance correction threshold value of the first image signal using the brightness level value of the first image signal output from the area determination unit and the reliability determination value of the first image signal output from the reliability determination unit; and an interpolator outputting corrected luminance information for the first luminance information using the luminance correction threshold and the third luminance information.

The first image signal may be an original image signal of a first image block among received image signals of one frame, and the second image signal may be an image signal of the first image block filtered by a filter.

The first image block may be implemented as a single pixel or as a predetermined area including a plurality of pixels.

The filter may be implemented as a bandpass filter.

The region comparator may generate the third luminance information Ic through Equation 1 below.

[Equation 1]

If I _E > Imax Ic = Imax

Elseif I _E < Imin Ic = Imin

Else Ic = I _E

(I _E : second luminance information, Imax: maximum luminance value of image blocks including the first image signal, Imin: minimum luminance value of image blocks including the first image signal, I _C : third luminance information).

The brightness level value calculated by the area determination unit may be an average brightness value of the first image block.

The reliability determination value calculated by the reliability determination unit corresponds to a result of comparing the luminance of the first image block with the luminance of neighboring pixels, and indicates that the difference between the luminance of the first image block and the luminance with the neighboring pixels is small. A lower reliability determination value may be calculated, and a higher reliability determination value may be calculated as the difference between the luminance of the first image block and the luminance of neighboring pixels is greater.

The extractor calculates the luminance correction threshold Th(x) through Equation 4 below,

[Equation 4]

Th(x) = n(x)

(Y _avg : brightness value calculated by the area determination unit, n(x): reliability determination value calculated by the reliability determination unit, k: arbitrary constant)

The luminance correction threshold Th(x) may be included in a range greater than 0 and less than 1.

As the difference between the luminance of the first image block and the luminance of the surrounding pixels increases, the first image block is determined as noise. In this case, the luminance correction threshold may be calculated as a high value close to 1.

The interpolator may calculate the corrected luminance information Y _out with respect to the first luminance information Y _{in through Equation 5 below.}

[Equation 5]

Yout = Ic * Th(x) + I _E *(1-Th(x))

(I _C : third luminance information, Th(x): luminance correction threshold, I _E : second luminance information)

An image processing method according to another embodiment of the present invention includes receiving first luminance information corresponding to a first image signal and second luminance information corresponding to a second image signal, and the first luminance information and the second luminance information generating third luminance information using calculating a brightness level value for the first image signal using the first brightness information; calculating a reliability determination value for the first image signal by using the first luminance information; generating a luminance correction threshold value of the first image signal using a brightness level value of the first image signal and a reliability determination value of the first image signal; and outputting corrected luminance information for the first luminance information using the luminance correction threshold and the third luminance information.

The first image signal may be an original image signal of a first image block among the received image signals of one frame.

The second image signal may be an image signal of the first image block filtered by a filter.

The first image block may be implemented as a single pixel or as a predetermined area including a plurality of pixels.

The third luminance information Ic may be generated through Equation 1 below.

[Equation 1]

If I _E > Imax Ic = Imax

Elseif I _E < Imin Ic = Imin

Else Ic = I _E

(I _E : second luminance information, Imax: maximum luminance value of image blocks including the first image signal, Imin: minimum luminance value of image blocks including the first image signal, I _C : third luminance information).

The brightness level value may be an average brightness value of the first image block.

The reliability determination value corresponds to a result of comparing the luminance of the first image block with the luminance of surrounding pixels, and the smaller the difference between the luminance of the first image block and the luminance with neighboring pixels, the lower the reliability determination value. is calculated, and as the difference between the luminance of the first image block and the luminance of the surrounding pixels increases, a higher reliability determination value may be calculated.

The luminance correction threshold Th(x) is calculated through Equation 4 below,

[Equation 4]

Th(x) = n(x)

(Y _avg : brightness value calculated by the area determination unit, n(x): reliability determination value calculated by the reliability determination unit, k: arbitrary constant)

The luminance correction threshold Th(x) may be included in a range greater than 0 and less than 1.

As the difference between the luminance of the first image block and the luminance of the surrounding pixels increases, the first image block is determined as noise. In this case, the luminance correction threshold may be calculated as a high value close to 1.

The corrected luminance information Y _out with respect to the first luminance information Y _in may be calculated through Equation 5 below.

[Equation 5]

Yout = Ic * Th(x) + I _E *(1-Th(x))

(I _C : third luminance information, Th(x): luminance correction threshold, I _E : second luminance information)

According to this embodiment of the present invention, it is possible to reduce the loss of original image data and suppress a boosting phenomenon that can be applied to low-illuminance noise to increase the image data transmission compression rate.

1 is a block diagram schematically showing the configuration of a surveillance camera system according to an embodiment of the present invention.
2 is a block diagram showing the configuration of an image processing apparatus according to an embodiment of the present invention;
3 is a view for explaining an example of a video image generated by image processing according to an embodiment of the present invention;
4 is a block diagram illustrating the configuration of the image processor of FIG. 2 ;
5 is a flowchart illustrating an image processing method according to an embodiment of the present invention.

The contents described in the technical field of the background of the present invention are only for helping the understanding of the background of the technical idea of the present invention, and therefore it can be understood as the content corresponding to the prior art known to those skilled in the art of the present invention. none.

In the following description, for purposes of explanation, numerous specific details are set forth to aid in understanding various embodiments. It will be evident, however, that various embodiments may be practiced without these specific details or in one or more equivalent manners. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the various embodiments.

Each block of the accompanying block diagram may be executed by computer program instructions (execution engine), which may be loaded into the processor of a general-purpose computer, special-purpose computer, or other programmable data processing equipment, so that the computer or The instructions, executed by the processor of the other programmable data processing equipment, will create means for performing the functions described in each block of the block diagram.

These computer program instructions may also be stored in a computer-usable or computer-readable memory that may direct a computer or other programmable data processing equipment to implement a function in a particular manner, and thus the computer-usable or computer-readable memory. It is also possible that the instructions stored in the block diagram produce an article of manufacture containing instruction means for performing the functions described in each block of the block diagram.

And, since the computer program instructions may be mounted on a computer or other programmable data processing equipment, a series of operational steps are performed on the computer or other programmable data processing equipment to create a computer-executed process to create a computer or other program. It is also possible that instructions for performing the possible data processing equipment provide functionality for performing the functions described in each block of the block diagram.

In addition, each block may represent a module, segment, or portion of code that includes one or more executable instructions for executing specified logical functions, and in some alternative embodiments the functions recited in the blocks or steps are ordered It is also possible to occur outside of

That is, the two illustrated blocks may be substantially simultaneously performed, and also, the blocks may be performed in the reverse order of the corresponding functions, if necessary.

The terminology used herein is for the purpose of describing particular embodiments and not for the purpose of limitation. Throughout the specification, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated. Unless otherwise defined, terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

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

1 is a block diagram schematically showing the configuration of a surveillance camera system according to an embodiment of the present invention.

Referring to FIG. 1 , a surveillance camera system according to an embodiment of the present invention may include a network camera 10 , a gateway 20 , and a network 30 . Although one network camera 10 is illustrated in FIG. 1 for convenience of description, it is apparent to those skilled in the art that a plurality of network cameras 10 may be implemented.

The surveillance camera system may provide a configuration in which the information of the network camera 10 collected by the gateway 20 is transmitted to the server through the network 30, whereby the administrator uses the monitor terminal to transmit the information to the server can be monitored.

The network camera 10 captures the surveillance area to obtain an image of the surveillance area, which may capture the surveillance area in real time for the purpose of monitoring or security.

The network camera 10 may be a PTZ camera capable of panning and tilting and adjustable zoom magnification of a lens. For example, the network camera 10 may be a fisheye camera having an angle of view of 180 degrees or more. An image captured by a fisheye camera may have various distortions as a wide-angle image.

Also, the network camera 10 may be a battery-powered, low-power camera. The low-power camera normally maintains a sleep mode, and periodically wakes up to check whether an event has occurred. The low-power camera switches to an active mode when an event occurs, and returns to a sleep mode when an event does not occur. As such, the low-power camera can reduce power consumption by maintaining the active mode only when an event occurs.

The network camera 10 communicates with the gateway 20 using various communication methods such as wired/wireless Local Area Network (LAN), Wi-Fi, ZigBee, Bluetooth, and Near Field Communication. can communicate. For example, the network camera 10 may communicate with the gateway 20 according to a low-power wireless communication protocol using a radio frequency of an industrial scientific medical band (ISM).

The gateway 20 may recognize the state of the network camera 10 based on the information transmitted from the network camera 10 , and according to the recognized state of the network camera 10 , the gateway 20 may send information to another network camera 10 or a server according to the recognized state of the network camera 10 . Commands or alarms can be sent. The gateway 20 may transmit information to the server using various wired/wireless communication methods such as Ethernet, Wi-Fi, and Bluetooth, and may receive commands from the server. The network 30 may include a wired network or a wireless network. The wireless network may be a 2G (Generation) or 3G cellular communication system, a 3rd Generation Partnership Project (3GPP), a 4G communication system, Long-Term Evolution (LTE), World Interoperability for Microwave Access (WiMAX), or the like.

FIG. 2 is a block diagram illustrating the configuration of an image processing apparatus according to an embodiment of the present invention, and FIG. 3 is a diagram for explaining an example of a video image generated by image processing according to an embodiment of the present invention.

Referring to FIG. 2 , an image processing apparatus 100 according to an embodiment of the present invention includes an image receiver 110 , an image processor 130 , an encoder 150 , and an image transmitter ( 170, image transmitter).

The image processing apparatus 100 may be included in the network camera 10 or the gateway 20 shown in FIG. 1 , but the embodiment of the present invention is not limited thereto.

The image receiver 110 receives image data from a camera module (eg, a lens assembly) included in the network camera 10 . For example, the image receiver 110 may be a camera module such as a charge-coupled device (CCD) module or a complementary metal-oxide-semiconductor (CMOS) module. Also, the image receiver 110 may be a communication interface for receiving an image from the network camera 10 . In this case, the image data received through the image receiver 110 may be an image signal of one frame including a plurality of image blocks.

The image processor 130 may process the image data received from the camera module and transmit the processed image data to the encoder 150 . In an embodiment of the present invention, the image processor 130 may emphasize the edge of the image signal received through the image receiver 110 . In this case, the edge of the received video signal may mean a corner portion of the object displayed in the video image of one frame. In an embodiment of the present invention, a technique of boosting the luminance of a region having a large change in brightness of an image (shaping) may be applied to emphasize the edge of one frame image, that is, to emphasize the edge of the object.

Such a sharpening technique may use a bandpass filter and luminance information for each block of the video image. The bandpass filter may be implemented by combining a high pass filter and a lowpass filter. Among the image data, high-frequency image data means image data corresponding to a region in which the brightness changes from a low value to a high value or from a high value to a low value among the image signals of one frame. Conversely, the low-frequency image data refers to the image signal of one frame. It means image data corresponding to an area in which there is no brightness change. Accordingly, the bandpass filter sharpening technique refers to a technique for boosting a region with a high luminance variation and reducing noise to obtain a visually clear image.

FIG. 3(a) shows a video image of one frame that displays image data before the sharpening technique is applied, and FIG. 3(b) shows a video image of one frame that displays image data after the sharpening technique is applied.

In addition, the first image block (A) of FIG. 3(b) is a block including a region in which image data of low luminance is displayed, and the second image block (B) is an image of a high-frequency region, that is, a region with a high luminance change. A block including an area in which data is displayed, and the third image block C is a block including an area in which high luminance image data is displayed.

Referring to FIGS. 3A and 3B , by applying the sharpening technique, a corner of an object displayed in a video image of one frame, that is, a high-frequency region with a high luminance change (eg, a second image block (B)) ), you can see the boosted result.

The encoder 150 may compress the image processed through the image processor 130 . For example, the image compression by the encoder 150 includes first blocks including a dynamic region with a large amount of motion compared to an image of a previous image frame, and second blocks including a static region with no change in motion. After dividing into , a technique for minimizing image quality deterioration by reducing the compression ratio of the image data corresponding to the first blocks and increasing the compression ratio of the image data corresponding to the second blocks may be used. Then, the encoder 150 transmits the compressed image to the image transmitter 170 .

The image transmitter 170 transmits the compressed image to the outside. The image transmitter 170 may transmit the compressed image to the gateway 20 or the network 30 .

The image processing apparatus 100 according to the embodiment of the present invention may be included in the network camera 10 of FIG. 1 or may be implemented as a device separate from the network camera 10 of FIG. 1 . Some of the components included in the image processing apparatus 100 according to the embodiment of the present invention are installed in the network camera 10 of FIG. 1 , and the remaining parts are installed in a device separate from the network camera 10 of FIG. 1 . may be

When the sharpening technique by the image processor 130 does not consider the compression technique by the encoder 150, it corresponds to a block including a low illuminance region, for example, the first image block A of FIG. 3(b). When the luminance values of the image data corresponding to the image data or the image data corresponding to some of the low-illuminance regions of the second image block B of FIG. 3(b) are boosted, invisible low-illuminance noise may also be boosted, which results in a compression ratio It may cause a problem of lowering the image quality or lowering the image quality.

More specifically, when the sharpening technique is applied, the luminance of the second image block B, which is the high-frequency region, is boosted at the edge of the object displayed in one frame image. In this case, the low-illuminance region of the second image block B is boosted. Low-illuminance noise included in image data corresponding to may also be boosted. At this time, when the second image block B corresponds to the first block including a dynamic region by the encoder 150, a low data compression rate is applied. In this case, a low data compression rate even with the boosted low-illuminance noise This may cause a problem in that the quality of the image is deteriorated. The embodiment of the present invention is devised to overcome such a problem, and is characterized in that it is possible to increase the compression rate of image data transmission by reducing the loss of original image data and suppressing a boosting phenomenon that can be applied to low-illuminance noise.

4 is a block diagram illustrating the configuration of the image processor of FIG. 2 .

The image processor 130 may be implemented as a processor, and the processor may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. Instructions may be provided to the processor by a memory or communication module. As an example, the processor may be configured to execute a received instruction according to a program code stored in a recording device such as a memory.

Referring to FIG. 4 , the image processor 130 may include a region comparator 132 , a region determiner 134 , a reliability determiner 136 , an extractor 138 , and an interpolator 139 . . At this time, the components in the image processor 130 implemented as a processor, that is, the region comparator 132 , the region determiner 134 , the reliability determiner 136 , the extractor 138 , and the interpolator 139 . It may be understood that different functions performed by the image processor 130 are distinguished and expressed according to a control command provided by a program code stored in the image processing apparatus 100 .

More specifically, the region comparator 132 may include a first luminance information Y _in corresponding to a first image signal and a second luminance information Y in corresponding to a second image signal among the image signals received through the image receiver 110 . An operation of receiving the luminance information I _{E and generating the third luminance information I C} by using the first luminance information and the second luminance information may be performed. For example, the first image signal may be an original image signal of a first image block among received image signals of one frame, and the second image signal is filtered through the filtered first image signal, that is, the filter 131 . It may be an image signal of the first image block. Also, the third luminance information may be luminance information corresponding to the first image block generated using the first and second luminance information.

_{The area determination unit 134 calculates a value of the brightness degree (Y avg} ) of the first image block corresponding to the first image signal through the first luminance information, and the reliability determination unit 136 . may perform an operation of calculating a reliability determination value n(x) for the first image block corresponding to the first image signal by using the first luminance information.

Also, the extractor 138 may perform an operation of generating a luminance correction threshold Th(x) using the brightness level and reliability determination value n(x) of the first image block, The interpolator 139 may output the _{corrected luminance information Y out} corresponding to the first image block using the luminance correction threshold and the third luminance information.

In this case, the filter 131 shown in FIG. 4 may be implemented as the aforementioned bandpass filter. Also, the first image block may be a block region including at least one pixel among image signals constituting one frame. For example, the first image block may be implemented as a single pixel or as a predetermined area including a plurality of pixels.

First, the operation of the region comparison unit 132 will be described as follows.

As mentioned above, the image data received through the image receiver 110 is an image signal of one frame including a plurality of image blocks, and noise is generated in image blocks corresponding to bright areas in the image data of one frame in general. This is relatively small, and noise is likely to occur in image blocks corresponding to the dark region.

Therefore, it is preferable to apply a high-pass filter to image blocks corresponding to a bright area because noise is small, and to image blocks corresponding to a dark area, noises are highly likely to exist even though they are not visually visible. Noise boosting by the pass filter should be minimized.

Accordingly, the image processor 130 according to the embodiment of the present invention is characterized in that, for example, an operation of controlling a halo phenomenon caused by strong edge boosting is performed in a high frequency region (a region having a large luminance change).

_{The region comparator 132 is configured to filter the first luminance information Y in} corresponding to the original image signal of the first image block among the image signals received through the image receiver 110 and the filter 131 . _{The second luminance information I E} corresponding to the image signal of the first image block is received, and the first luminance information and the second luminance information are compared based on the following Equation 1, whereby the first luminance information corresponding to the first image block is received. 3 An operation of generating the luminance information I _{C is performed.}

In Equation 1, I is the luminance information of the first image block, I _E is the filtered second luminance information (I _E ) for the first image block, and Imax is the first image block or an adjacent adjacent image block including the first image block. It is the maximum luminance value of the image blocks, and Imin means the minimum luminance value of the first image block or adjacent image blocks including the first image block. In addition, I _{C refers to the third luminance information I C} of the first image block output by the area comparison unit 132 based on Equation 1 above.

According to Equation 1, in the first image block, when the second luminance information I _E generated through the filter 131 exceeds a preset maximum luminance value Imax, the area comparison unit 132 outputs The luminance information to be used is set as the maximum luminance value, not the second luminance information I _{E .} In addition, in the first image block, when the second luminance information I _E generated through the filter 131 is less than a preset minimum luminance value Imin, the area comparison unit 132 compares the output luminance information with the second luminance information. It is set to the minimum luminance value, not the luminance information I _{E .} As a result, the region comparison unit 132 _{sets the maximum and minimum limits of the second luminance information I E} of the filtered first image block, so that the second luminance information I _E is boosted by the filter. It is possible to control the halo phenomenon caused by

The area determination unit 134 may perform an operation of determining _{the brightness level Y avg of the first image block.}

More specifically, the area determining unit 134 may calculate the value _{of the brightness degree Y avg of the first image block through Equation 2 below.}

Equation 2 represents the average luminance of the first image block, and is an average value of luminance values of at least one pixel included in the first image block, and the brightness degree (Y _avg ) value of the first image block can be calculated. For example, when the first image block is implemented as a single pixel, it is the luminance value of the single pixel, and when the first image block is a predetermined area including a plurality of pixels, the average luminance of the plurality of pixels can be a value.

The reliability determination unit 136 may perform an operation of calculating a reliability determination value n(x) capable of confirming the similarity of the first image block.

More specifically, the reliability determination value n(x) output from the reliability determination unit 136 may be calculated through Equation 3 below, and in this case, the first image block is a single image block as described above. It can be implemented with pixels.

According to Equation 3, the reliability determination value n(x) is the difference between the luminance Y(x) of the first image block (eg, a specific single pixel) and the surrounding pixels Y(xn). Corresponding to the result of comparing the luminance, if the difference between the luminance of the first image block and the luminance of the surrounding pixels is small, it is determined that the similarity is high, and the reliability judgment value n(x) according to this is determined is calculated as a low value.

On the other hand, as the difference between the luminance Y(x) of the first image block and the luminance Y(xn) of the surrounding pixels increases, it is determined that the similarity is lower, and thus the reliability determination value (n(x)) yields a high value.

That is, the higher the reliability determination value for the first image block, the higher the probability that the first image block is determined as noise.

Accordingly, the reliability determination unit 136 calculates the reliability determination value n(x), which is a new variable, in order to increase the reliability of the luminance correction threshold Th(x) generated by the extraction unit 138 . is to perform For example, when the first image block is noise, the degree of similarity to the first image block is significantly low, so the reliability determination value n(x) can be calculated to be a fairly high value. The reliability of the luminance correction threshold Th(x) generated by the extractor 138 may be increased.

That is, the luminance correction threshold value Th(x) generated by the extraction unit 138 does not only consider the brightness level of the first image block by the area determination unit 134, but through a deviation from adjacent pixels. It can increase reliability.

_{The extraction unit 138 uses the brightness degree Y avg} of the first image block output from the area determination unit 134 and the reliability determination value n(x) output from the reliability determination unit 136 . An operation of generating the luminance correction threshold Th(x) may be performed.

More specifically, the extractor 138 may calculate the luminance correction threshold Th(x) through Equation 4 below.

k is an arbitrary constant n(x) in Equation 4 is a reliability determination value of a specific pixel constituting a first image block to be searched, and the luminance correction threshold according to Equation 4 using the n(x) value The reliability of the value Th(x) may be determined.

According to Equation 4, the luminance correction threshold value Th(x) is directly proportional to the reliability determination value n(x), and is inversely proportional _{to the brightness level Y avg of the first image block.} Also, according to Equation 4, the luminance correction threshold Th(x) is included in a range greater than 0 and less than 1 (0 < Th(x) < 1).

For example, when the first image block, which is the search target, is noise, the similarity to the first image block is significantly low, so the reliability determination value n(x) is calculated to be a fairly high value, and the luminance correction threshold value (Th(x)) can be extracted with a high value close to 1.

On the other hand, when the first image block is included in a bright area and has a high similarity with neighboring pixels, the reliability determination value n(x) is calculated as a low value, and the luminance correction threshold Th( x)) can be extracted with a low value close to zero.

Accordingly, the extraction unit 138 extracts a flexible luminance correction threshold value according to the noise level in a low-light situation by using the _{brightness level Y avg and the reliability determination value n(x) of the first image block.} can do. Finally, the interpolator 139 outputs _{corrected luminance information Y out} corresponding to the first image block using the luminance correction threshold Th(x) and the third luminance information I _{C .} can do.

_{More specifically, the interpolator 139 may calculate the corrected luminance information Y out} corresponding to the first image block through Equation 5 below.

I _E is applied to the equation (5) the second luminance information (I _E) and, I _C is above the equation output by the first area comparing unit 132 on the basis of on the filtered first image block The third luminance information (I _C ) of the first image block to be In addition, Th(x) is the luminance correction threshold value Th(x) generated by the extractor 138 .

As briefly described above, in order to control a halo phenomenon caused by strong edge boosting in a high-frequency region (a region with a large luminance change) through the filter 131, the region comparator 132 performs the anti- The filtered second luminance information I _{E or third luminance information I C} limited to maximum/minimum luminance values is output using a halo technique.

The interpolator 139 includes the second luminance information I _E and the third luminance information I _C output from the region comparator 132 , and a luminance correction threshold value ( ) generated by the extraction unit 138 . Th(x)) is received and corrected luminance information (Y _out ) corresponding to the first image block is calculated according to Equation 5. Through this, it is possible to control fine noise without degrading the image quality of the image signal. there will be

For example, when the first image block is a bright area having a high similarity, the reliability determination unit 136 outputs a low reliability determination value n(x), and accordingly, the correction threshold Th( x)) can be extracted with a low value close to zero.

Accordingly, according to Equation 5, since the correction threshold Th(x) has a value close to 0, the corrected luminance information Y _out is not affected by the third luminance information I _{C .} It may be almost removed and corrected to a value corresponding to _{the second luminance information I E .}

In other words, the first case the image blocks contained in the light areas of high degree of similarity with the surrounding pixels, the second luminance which is determined that the end than the noise passing through the high-pass filter portion of the filter 131, the information (I _E ) to be transmitted to the encoder 150 .

On the other hand, when the first image block is a dark area having a low similarity, the reliability determination unit 136 outputs a high reliability determination value n(x), and accordingly, the correction threshold Th(x) )) can be extracted with a high value close to 1.

Accordingly, according to Equation 5, since the correction threshold Th(x) has a value close to 1, the corrected luminance information Y _out is not affected by the second luminance information I _{E .} It may be almost removed and corrected to a value corresponding to _{the third luminance information I C .}

In other words, the first image, because blocks are included in a dark region where the degree of similarity between neighboring pixels may more likely be a low illuminance noise determine if low, the limited third luminance information as the maximum / minimum luminance value (I _C ) to be transmitted to the encoder 150 .

In other words, the filtered second luminance information I _E output from the region comparator 132 and the third luminance information limited to maximum/minimum luminance values I _C are the result value to which the anti-halo technique is applied and edge boosting. Reflecting the applied result value, the luminance correction threshold Th(x) generated by the extraction unit 138 is the brightness degree Y _avg and the reliability determination value n(x) of the first image block. Since the value reflects , according to the embodiment of the present invention, the corrected luminance information (Y _out ) is transmitted to the encoder 150, thereby reducing the loss of original image data and a boosting phenomenon that can be applied to low-illuminance noise. It is possible to increase the compression rate of video data transmission by suppressing the

5 is a flowchart illustrating an image processing method according to an embodiment of the present invention.

An image processing method according to an embodiment of the present invention will be described with reference to FIGS. 2, 3 and 5 .

First, the image receiver 110 receives an image signal of one frame including a plurality of image blocks (ST 500). Also, the image receiver 110 may output the received image signal and luminance information corresponding to the image signal to the image processor 130 .

_{Thereafter, the region comparator 132 of the image processor 130 receives first luminance information Y in} corresponding to the original image signal of the first image block among the image signals received through the image receiver 110 . do (ST 510).

_{Also, the region comparison unit 132 receives second luminance information I E} corresponding to the image signal of the first image block filtered through the filter 131 (ST 520), and the first luminance information and comparing the second luminance information _{to generate third luminance information I C} corresponding to the first image block (ST 530).

More specifically, the region comparator 132 compares the first luminance information and the second luminance information based on Equation 1 described above to obtain the third luminance information I _{C corresponding to the first image block.} generating operation may be performed, and through this, the region comparison unit 132 _{sets the maximum and minimum limits of the second luminance information I E} of the filtered first image block, so that the second luminance information I _E ) can control the halo effect caused by boosting.

Thereafter, the area determining unit 134 may perform an operation of determining _{the brightness level Y avg of the first image block (ST 540 ).} More specifically, the area determining unit 134 may _{calculate the brightness level Y avg} of the first image block through Equation 2 described above.

Also, the reliability determination unit 136 may perform an operation of calculating the reliability determination value n(x) of the first image block (ST 550). More specifically, the reliability determination unit 136 may calculate the reliability determination value n(x) of the first image block through Equation 3 described above.

Next, the extractor 138 generates a luminance correction threshold Th(x) using the _{brightness degree Y avg} and the reliability determination value n(x) of the first image block. can (ST 560). More specifically, the extractor 138 may calculate the luminance correction threshold Th(x) through Equation 4 described above.

_{Finally, the interpolator 139 calculates the corrected luminance information Y out} corresponding to the first image block using the luminance correction threshold Th(x) and the third luminance information I _C . Can be printed (ST 570). _{More specifically, the interpolator 139 may calculate the corrected luminance information Y out} corresponding to the first image block through Equation 5 described above.

According to the image processing method according to the embodiment of the present invention, the result value to which the anti-halo technique is applied (third luminance information (I _C )) and the result value to which edge boosting is applied (filtered second luminance information (I _E )) ) and the luminance information corrected using the luminance correction threshold Th(x) generated by reflecting the _{brightness degree Y avg} and the reliability determination value n(x) of the first image block ( Y _out ) is generated and the corrected luminance information Y _out is transmitted to the encoder 150 , thereby reducing the loss of original image data and suppressing a boosting phenomenon that can be applied to low-illuminance noise to increase the image data transmission compression rate can

As described above, in the present invention, specific matters such as specific components, etc., and limited embodiments and drawings have been described, but this is provided only to help a more general understanding of the present invention, and the present invention is not limited to the above embodiments. , If a person of ordinary skill in the field to which the present invention belongs, various modifications and variations are possible from these descriptions.

Therefore, the spirit of the present invention is limited to the described embodiments and should not be defined, and all things that are equivalent or equivalent to the claims as well as the claims to be described later fall within the scope of the spirit of the present invention. .

Claims (20)

A region comparator for receiving first luminance information corresponding to the first image signal and second luminance information corresponding to the second image signal, and generating third luminance information by using the first luminance information and the second luminance information ;
an area determination unit calculating a brightness level value of the first image signal by using the first brightness information;
a reliability determination unit for calculating a reliability determination value for the first image signal by using the first luminance information;
an extractor configured to generate a luminance correction threshold value of the first image signal using the brightness level value of the first image signal output from the area determination unit and the reliability determination value of the first image signal output from the reliability determination unit; and
and an interpolator outputting corrected luminance information for the first luminance information using the luminance correction threshold and the third luminance information. The method of claim 1,
The first image signal is an original image signal of a first image block among the received image signals of one frame,
The second image signal is an image signal of the first image block filtered by a filter. The method of claim 2,
The first image block is implemented as a single pixel or as a predetermined area including a plurality of pixels. The method of claim 2,
The filter is an image processing device implemented as a bandpass filter. The method of claim 1,
The region comparator generates the third luminance information Ic through Equation 1 below.
[Equation 1]
If I _E > Imax Ic = Imax
Elseif I _E < Imin Ic = Imin
Else Ic = I _E
(I _E : second luminance information, Imax: maximum luminance value of image blocks including the first image signal, Imin: minimum luminance value of image blocks including the first image signal, I _C : third luminance information). The method of claim 2,
The brightness level value calculated by the area determination unit is an average brightness value of the first image block. The method of claim 2,
The reliability determination value calculated by the reliability determination unit corresponds to a result of comparing the brightness of the first image block with the brightness of surrounding pixels,
A lower reliability judgment value is calculated as the difference between the luminance of the first image block and the luminance between the neighboring pixels is small, and a high reliability judgment value is calculated as the difference between the luminance of the first image block and the luminance between the neighboring pixels is large. image processing device. The method of claim 2,
The extractor calculates the luminance correction threshold Th(x) through Equation 4 below,
[Equation 4]
Th(x) = n(x)

(Y _avg : brightness value calculated by the area determination unit, n(x): reliability determination value calculated by the reliability determination unit, k: arbitrary constant)
The luminance correction threshold Th(x) is included in a range greater than 0 and less than 1. The method of claim 8,
As the difference between the luminance of the first image block and the luminance of neighboring pixels increases, the first image block is determined as noise, and in this case, the luminance correction threshold is calculated as a high value close to 1. The method of claim 8,
The interpolator is an image processing apparatus for calculating the corrected luminance information (Y _out ) with respect to the first luminance information (Y _{in ) through the following Equation (5).}
[Equation 5]
Yout = Ic * Th(x) + I _E *(1-Th(x))
(I _C : third luminance information, Th(x): luminance correction threshold, I _E : second luminance information) receiving first luminance information corresponding to the first image signal and second luminance information corresponding to the second image signal, and generating third luminance information by using the first luminance information and the second luminance information;
calculating a brightness level value for the first image signal using the first brightness information;
calculating a reliability determination value for the first image signal by using the first luminance information;
generating a luminance correction threshold value of the first image signal using a brightness level value of the first image signal and a reliability determination value of the first image signal; and
and outputting corrected luminance information for the first luminance information using the luminance correction threshold and the third luminance information. The method of claim 11,
The first image signal is an original image signal of a first image block among the received image signals of one frame. The method of claim 12,
The second image signal is an image signal of the first image block filtered by a filter. The method of claim 12,
The image processing method in which the first image block is implemented as a single pixel or as a predetermined area including a plurality of pixels. The method of claim 11,
The third luminance information Ic is an image processing method that is generated through Equation 1 below.
[Equation 1]
If I _E > Imax Ic = Imax
Elseif I _E < Imin Ic = Imin
Else Ic = I _E
(I _E : second luminance information, Imax: maximum luminance value of image blocks including the first image signal, Imin: minimum luminance value of image blocks including the first image signal, I _C : third luminance information). The method of claim 12,
The brightness level value is an average brightness value of the first image block. The method of claim 12,
The reliability determination value corresponds to a result of comparing the luminance of the first image block with the luminance of surrounding pixels,
A lower reliability judgment value is calculated as the difference between the luminance of the first image block and the luminance between the neighboring pixels is small, and a high reliability judgment value is calculated as the difference between the luminance of the first image block and the luminance between the neighboring pixels is large. Image processing method. The method of claim 12,
The luminance correction threshold Th(x) is calculated through Equation 4 below,
[Equation 4]
Th(x) = n(x)

(Y _avg : brightness value calculated by the area determination unit, n(x): reliability determination value calculated by the reliability determination unit, k: arbitrary constant)
The luminance correction threshold value Th(x) is included in a range greater than 0 and less than 1. The method of claim 18,
As the difference between the luminance of the first image block and the luminance of the surrounding pixels increases, the first image block is determined as noise, and in this case, the luminance correction threshold is calculated as a high value close to 1. The method of claim 18,
The image processing method wherein the corrected luminance information (Y _out ) with respect to the first luminance information (Y _in ) is calculated through Equation (5) below.
[Equation 5]
Yout = Ic * Th(x) + I _E *(1-Th(x))
(I _C : third luminance information, Th(x): luminance correction threshold, I _E : second luminance information)

Images