KR20010073262A - Deinterlacing method and apparatus - Google Patents

Abstract

PURPOSE: A deinterlacing method and device are provided to improve image quality after interpolation by interpolating according to the motion amount and an edge direction of a field to be currently interpolated. CONSTITUTION: Temporally serial current field data, data of previous 2 fields and data of next 4 fields are stored in a field memory(100). A motion decision part(200) calculates the BD(brightness difference) and BPPD(brightness profile pattern difference) between respective field data, and calculates motion values in referring to the BD and the BPPD. A median filter part(600) removes noise components included in the motion values to group the areas in the motion values are contained. A motion expanding part(700) receives the output values of the median filter part(600) to expand the motion values to periphery pixels. A spatial interpolation part(300) calculates the directions of edges included in periphery pixel values of a pixel to be interpolated and calculates interpolation values within a field according to the directions. A temporal interpolation part(400) calculates an average field value of pixel values in a previous field and a next field of a field to be currently interpolated. A soft switch part(500) mixes the interpolation values within a field according to the edge directions and the average field value. A vertical line converting part(800) converts the number of vertical lines for display.

Description

Deinterlacing method and apparatus {DEINTERLACING METHOD AND APPARATUS}

The present invention relates to a motion adaptive interpolation technique, and more particularly, to a deinterlacing method and apparatus.

The deinterlacing method is a technique for converting interlaced scanning image data into progressive scanning image data in an image processing method.

In the progressive scan method, the image data of one frame is implemented as two fields of an odd field and an even field, as shown in FIG. 1.

However, depending on the display device, the screen is implemented by processing the image data of the forward scanning method used in a computer monitor without processing the image data of the conventional scanning method.

In this case, in order for the progressive scanning video signal to be normally processed in the display device processing the progressive scanning video data, a separate system for converting the traveling scanning video signal into the progressive scanning video signal is provided in the display device. It must be installed.

A method of converting an image signal of a progressive scan method into an image signal of a forward scanning method may be implemented in various ways as shown in FIGS. 2A to 2C.

First, a line repetition method as shown in FIG. 2A implements a frame by simply repeating line information of a current field.

In addition, inter-field interpolation without motion-compensation as shown in FIG. 2B implements one frame by simply sandwiching the immediately preceding line between the lines of the current field.

Finally, intra-field interpolation, as shown in FIG. 2C, implements a new field by inserting the data of the two lines in the field between two lines in one field.

However, although the line repetition method can be implemented with simple hardware, the image quality is poor after interpolation.

In addition, inter-field interpolation without motion compensation can be implemented by simple hardware. However, when interpolating an image with motion, an error occurs or the screen is deteriorated, thereby degrading image quality.

Intra-field interpolation has a lower image quality than the line repetition method and lower error than inter-field interpolation without motion compensation. However, when interpolating a still image, the image deteriorates and the image quality deteriorates.

That is, the above interpolation methods of FIGS. 2A to 2C all have disadvantages of degrading image quality after interpolation.

Accordingly, a motion compensation interpolation method for interpolating a current screen using field data of a previous screen and field data of a screen to be implemented in the future has been proposed.

The motion compensation interpolation method divides the screen into several blocks using temporally continuous field data based on the current field data, obtains a motion vector for each block, and interpolates the current frame screen with reference to the motion vector. It is.

By the way, the motion compensation interpolation method is composed of quite complicated hardware although the image quality is improved after interpolation.

Accordingly, in order to solve the problem of the motion compensation interpolation method, a motion adaptive interpolation method of estimating the degree of motion and interpolating a frame according to the motion has been proposed.

The motion adaptive interpolation method is implemented in relatively simple hardware compared to the motion compensation interpolation method, and the image quality after the interpolation is generally improved.

Examples of the motion adaptive interpolation method include the Bernard method disclosed in US Pat. No. 5,027,201 and the Faroundja method presented in Dongkuk Patent No. 5,159,451.

However, the conventional motion adaptive interpolation method has the advantage of being implemented with relatively simple hardware and improving the overall image quality after interpolation compared with the motion compensation interpolation method. Noise is generated and the manufacturing cost of the implementation circuit is increased due to the use of a plurality of field memories and complicated processing.

Accordingly, an object of the present invention is to provide a deinterlacing method and apparatus for improving image quality after interpolation by performing appropriate interpolation according to the degree of movement and edge direction of a field to be interpolated in order to improve the conventional problem.

In addition, another object of the present invention is to reduce the manufacturing cost of a circuit to be implemented by simplifying the circuit.

1 is an exemplary diagram of a screen according to a general interlacing method.

2 is a diagram illustrating field generation in the conventional line interpolation.

Figure 2a is an exemplary view showing a conventional line repetition method,

2B is an exemplary diagram showing a conventional interfield interpolation method without motion compensation;

2C is an exemplary diagram showing a conventional intrafield interpolation method.

3 is a block diagram of a deinterlacing apparatus for an embodiment of the present invention.

4 is an exemplary diagram showing region division for mapping of an edge portion.

5 is an exemplary view showing an interval matching method for interpolation direction detection.

6 is an exemplary view showing observation region division for the interval matching method in the present invention.

7 is an exemplary view showing pixels and field data used for median filtering.

Explanation of symbols on the main parts of the drawings

100: filter storage unit 200: motion detection unit

300: spatial interpolator 400: temporal interpolator

500: soft switch unit 600: median filter unit

700: motion determination unit 800: vertical line conversion unit

The present invention provides a deinterlacing method for detecting a degree of motion by detecting a difference in brightness and a difference in brightness contour pattern and interpolating the image with reference to the degree of movement, in order to achieve the above object, which corresponds to an image of a bipolar scan method. detecting pixels of a predetermined area including pixels to be interpolated from m field data, detecting a change direction of pixels to be interpolated with respect to the predetermined area, and wherein the pixels to be interpolated with respect to the predetermined area are horizontal or Setting an observation region and a movement region if not present on the vertical edge, dividing the observation region into a plurality, calculating a minimum section matching error in each of the divided plurality of regions, and calculating the above Represents a section matching error close to the vertical edge direction among the minimum section matching errors of the plurality of regions. Characterized by carrying out the step of calculating an interpolated value in fragrance.

In addition, the present invention provides a field storage unit for storing a plurality of previous and subsequent continuous field data including the field data on the basis of any field data to be interpolated to perform the above steps, and the field storage unit A motion determiner that detects a difference between the pixel value and the brightness contour pattern between each field data stored in the image, and calculates a motion degree of the image; and removes a noise component from the motion degree value calculated by the motion determiner. A median filter unit for clustering, a motion expansion unit for diffusing the motion degree values of the pixels to be interpolated to neighboring pixels adjacent to the pixels to be interpolated, pixel values of a previous field and pixels of a subsequent field with respect to a current field image to be interpolated A temporal interpolation unit that averages values to calculate a field average value, and a field of an area to be interpolated from the field storage unit at present Calculate the edge direction included in the pixel values around the pixel to interpolate the pixel value of data and the peripheral pixel value in the field as input, and set the observation area arbitrarily set when the edge direction does not exist on the horizontal or vertical edge The interpolation unit calculates the interpolation value according to the direction indicating the minimum section matching error among the section matching errors of each region by dividing a number into a plurality, and the brightness difference and the brightness contour pattern difference in the motion extension section. A soft switch unit for mixing the interpolation value in the field in consideration of the edge direction in the spatial interpolation unit and the field average value in the temporal interpolation unit 400, and the soft switch unit as input of data of the current field in the field storage unit. A vertical line converter that converts the number of vertical lines to fit the display by referring to interpolation line data from The Castle.

That is, when the pixel to be interpolated does not exist on a horizontal or vertical edge with respect to the surrounding area, the region matching is performed by dividing a randomly set observation area into a plurality of sections and applying a “section matching method” to each area. After detecting the error, the interpolation value is calculated in a direction indicating the minimum interval matching error among the detected interval matching errors.

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

3 is a block diagram of a de-interlacing apparatus for an embodiment of the present invention, as shown therein, a field storage unit for storing four field data of current field data, two previous field data, and four next field data, which are continuous in time And a brightness difference (BD) and a brightness contour pattern difference (BPPD) between the field data in the field storage unit 100 to calculate the brightness difference BD and the brightness. If the contour pattern difference (BPPD) is greater than or equal to a predetermined threshold, the motion determination unit 200 for mapping to a predetermined value and calculating the movement degree value with reference to the brightness difference (BD) and the brightness contour pattern difference (BPPD), and The median filter unit 600 removes the noise component included in the motion degree value and clusters the region having the motion degree value, and the motion value is inputted using the output value of the median filter part 600. A motion expansion unit 700 for diffusing a value into surrounding pixels, and a pixel around a pixel to interpolate the pixel value of the field data of the region currently interpolated from the field storage unit 100 and the peripheral pixel value in the field as input. The spatial interpolation unit 300 calculates an edge direction included in the values to calculate an interpolation value in the field according to the direction, and the pixel value of the previous field and the pixel of the subsequent field with respect to the current field image to be interpolated. A field considering an edge direction in the spatial interpolator 300 by referring to a temporal interpolator 400 that calculates a field average value by averaging values, and a difference in brightness and a difference in brightness contour pattern of the motion expander 700. The soft switch unit 500 mixing the interpolation value and the field average value in the temporal interpolation unit 400 and the data of the current field in the field storage unit 100 are input to the soft switch unit 500. The interpolation of the reference line data, and consists of a vertical line conversion unit 800 for converting the number of vertical lines to be suitable for display.

The motion determiner 200 detects the brightness change and the brightness outline pattern of each field data in the field storage unit 100 and compares the brightness change pattern and the brightness outline pattern between the previous field and the subsequent field based on the current field. The BD / BPPD detection unit 210 that calculates the brightness difference BD and the brightness outline pattern difference BPPD, and when the brightness difference BD and the brightness outline pattern difference BPPD are equal to or greater than a predetermined threshold, The BD / BPPD synthesis unit 220 maps the values and determines the movement degree value.

Referring to the operation and effect of the embodiment of the present invention configured as described above are as follows.

The field storage unit 100 m-fields consecutive in time such as image data corresponding to the nth field, the previous field, and the subsequent field among the plurality of field data for implementing the output image. Stores video data corresponding to

In other words, the field storage unit 100 stores field data before and after including the n-th field data and stores the stored field data in the motion determiner 200, the spatial interpolator 300, and the temporal interpolator ( 400).

At this time, the motion determiner 200 detects the difference between the pixel value of the specific lines existing in the field storage unit 100 and the brightness contour pattern and calculates the degree of motion of the video.

That is, the motion determiner 200 detects the brightness change and the brightness outline pattern of each field data in the field storage unit 100 by the BD / BPPD detector 210 to determine the brightness between the previous field and the subsequent field based on the current field. The brightness difference BD and the brightness contour pattern difference BPPD are calculated by comparing the change and the brightness contour pattern, and the BD / BPPD synthesis unit 220 calculates the brightness difference BD and the brightness contour pattern difference BPPD. ) To determine the movement value.

If the brightness difference BD and the brightness outline pattern difference BPPD are equal to or greater than a predetermined threshold value, the BD / BPPD synthesizing unit 220 may determine the brightness difference BD and the brightness outline pattern difference BPPD. Mapping to the set value determines the movement value.

Here, the concept of brightness difference (BD) is already widely used to perform line interpolation in the field of image processing such as digital TV.

The concept of Brightness Profile Pattern Difference (BPPD) is presented in Korean Patent Application No. 97-80719 filed by the present applicant.

In the Korean Patent Application No. 97-80719, the quantification of the brightness contour pattern for calculating the brightness difference BD and the brightness contour pattern difference BPPD may be performed on any of several lines.

For example, assuming that four field data of n-2, n-1, n, and n + 1 are consecutive in time, the brightness difference BD and the brightness contour pattern difference BPPD in the motion determiner 200 are assumed. The calculation process of is as follows.

First, the brightness outline pattern of the n-2 th field data is extracted using the pixel value of the n-2 th field data.

That is, the brightness outline pattern is extracted at the time point at which the n-th field is input.

Then, the brightness outline pattern of the n-th field data is extracted using the pixel value of the n-th field data.

That is, the brightness outline pattern is extracted at the time when the nth field is input.

Thereafter, the motion determiner 200 compares the brightness contour pattern of the n-th field with the brightness contour pattern of the n-th field to calculate a difference BPPD between the brightness contour patterns of the n-2nd field and the n-th field. In addition, the brightness difference (BD) between the n-th field and the n-th field is calculated.

The motion determiner 200 calculates the brightness difference and the brightness outline pattern difference between the n-1 th field and the n + 1 th field in the same process as described above.

However, an image transmitted through a broadcast channel or the like inevitably causes noise to be mixed in a coding step or a transmission step.

Accordingly, in the present invention, in order to accurately set the output value of the motion determiner 200, in particular, the BD / BPPD synthesizer 220, the noise component is removed from the output value of the BD / BPPD synthesizer 220 and motion in the image is detected. The median filter unit 600 for grouping the divided regions, and the motion extension unit 700 for expanding the movement degree value to other pixels adjacent to the moving pixel by inputting the output value from the median filter unit 600. It is provided.

In this case, the motion extension unit 700 expands the motion degree value to the adjacent pixel as follows.

In general, a motion of a video is not performed only in a specific pixel but in a pixel group of a predetermined region.

Thus, if a motion degree value is detected for a particular pixel, it may be due to the noise component of that pixel or the particular pixel and adjacent neighboring pixels are in a motion state.

However, since the motion degree value corresponding to the noise component is already removed in the median filter unit 600, the surrounding pixels are likely to be in the motion state.

Therefore, the motion extension unit 700 diffuses the motion degree value output from the median filter unit 600 to the periphery of the pixel where the motion degree value is detected.

Meanwhile, the spatial interpolator 300 inputs the field data of the region to be interpolated from the field storage unit 100 to input pixel values of the n-th field data corresponding to the region to be interpolated and peripheral pixels in the field. Then, the edge direction including the pixel values around the pixel to be interpolated is calculated using the correlation of the pixels in the field, and then an appropriate interpolation value according to the edge direction is extracted.

In particular, in the present invention, the spatial interpolator 300 maintains the spatial and temporal coherence of the pixels to be interpolated, and the spatial values adjacent to the pixel values of the pixels that are spatially adjacent from the pixels to be interpolated and the current fields of the pixels to be interpolated. A region matching method is applied by extracting an interpolation value of a pixel to be interpolated by filtering with a pixel value of.

"Region matching method" means extracting an interpolation value using the property that the pixel values of the edge portion of the region to be interpolated are continuous along the edge direction. It is described in detail in Korean Patent Application No. 99-26084 filed earlier.

An operation process of the “section matching method” will be described as follows.

First, a range of observation windows is set and a sliding window is set at symmetrical positions on the lines before and after the interpolation line with respect to the pixels to be interpolated.

At this time, the size of the moving area can be arbitrarily adjusted according to the system and its application.

Thereafter, the pixel value existing in the moving area existing on any edge including the pixel to be interpolated is detected.

Then, while shifting the up and down moving areas in opposite directions at regular intervals, the difference between pixels corresponding to each other in the up and down moving areas is continuously detected in the edge direction corresponding to the shifted amount.

At the same time, the direction of the edge including the pixel to be interpolated is detected by referring to the amount of change in the pixel value which is continuously detected.

However, when the interpolation pixel is determined by the pixels in the field that are spatially far from the current interpolation position or is present in a fairly fast motion, the interpolation pixel value may appear to be quite different than the adjacent pixels in the field.

Therefore, in the present invention, the interpolation pixel is filtered with the pixels adjacent to each other in the vertical direction in the field to prevent the above phenomenon.

First, the spatial interpolator 300 detects the edge direction by using the correlation of the pixels in the field.

At this time, in order to detect the edge direction of the pixel to be interpolated, as shown in the example of FIG. , , Assuming that the pixel is interpolated in three directions, the spatial interpolator 300 correlates the pixels adjacent to the top, bottom, left, and right sides of the pixel to be interpolated to determine in which direction edge the pixel to be interpolated belongs. The relationship is determined to determine whether the pixel to be interpolated belongs to a vertical or horizontal edge.

For example, in the case of interpolating the j-th pixel of the i-th line, a correlation in the vertical direction between the pixel to be interpolated and the adjacent pixel may be obtained by the following equation.

---- (One)

----- (2)

----- (3)

Thereafter, the spatial interpolator 300 performs the same process as the following program to calculate the edge direction of the pixel to be interpolated.

Here, the pixel to be interpolated This means the pixel in row i, column j of the nth field.

Used in the above formulas (1)-(3) The same meaning can be applied to.

That is, the spatial interpolation unit 300 has the maximum value of the difference value (a, b, c) between pixels obtained by equations (1) to (3) ( To calculate its maximum value ( If this value is smaller than the predetermined threshold, the edge direction of the pixel to be interpolated is changed. Judging by.

In addition, the horizontal correlation detection may also be performed in a similar manner to the vertical correlation detection except that the difference between the low pass filtered pixels is integrated in the horizontal direction instead of the vertical direction.

On the contrary, the maximum value of the difference (a, b, c) between pixels ( If it is equal to or larger than the predetermined threshold, the spatial interpolator 300 detects the edge direction by using the “section matching method”. This process will be described below.

For example, Fig. 5 is an exemplary diagram for edge direction determination by " section matching method ".

Here, the observation area was set to 15 pixels in the horizontal direction and the moving area was set to a 1x7 pixel area.

Therefore, referring to FIG. 5, the interval matching method according to the present invention will be described. A predetermined movement is made between the i + 1th line and the i-1th line within a certain observation window based on the ith line to be interpolated. Set the sliding window.

After that, the moving area of the i-1th line moves from the left to the right, and the moving area of the i + 1th line moves from the right to the left.

At this time, it is assumed that the moving area is moved in units of 1/4 pixels.

Accordingly, at each movement displacement, the difference value of pixels located diagonally between the movement areas is detected, and the difference value is calculated as in Equation (4) below to determine the interval matching error of the pixel value ( ) Is calculated.

---- (4)

Here, d represents the edge direction.

Thus, the edge direction d and the viewing area ( ) Can be expressed as below Equation (5), and the edge direction (d) and the moving distance ( ) Can be expressed as in Equation (6) below.

For example, if the pixel block of the moving area moves in units of 1/4 pixels, the moving interval ( ) Is 1/4.

----- (5)

------ (6)

If the range of the edge to be detected is wide, the observation area is expanded, and if the edge area is to be detected and the interpolation accuracy is increased, the unit of movement of the pixel block as the movement area is reduced.

That is, the size of the observation area and the moving area can be arbitrarily adjusted according to the application. Of course, the number of pixels included in the viewing area and the moving area may be arbitrarily adjusted.

However, in the present invention, when applying the "section matching method" in detail according to a given edge direction, the observation region is divided into a plurality and the "section matching method" is applied to each region.

In this case, the observation area is divided into a plurality of sections, and a "section matching method" is applied to each region.

Accordingly, the minimum section matching error of each region ( ) Is interpolated and the pixel value of the pixel position to be interpolated is interpolated according to the direction indicating the minimum interval matching error.

For example, as shown in FIG. 6, a process of interpolating a pixel value of a pixel position to be interpolated when it is divided into two regions A and B is as follows.

In Fig. 6, area A is the edge direction. In consideration of the size of the moving area in the left and right direction as a reference, it is set to the boundary of an appropriate degree, and the area B is set from the boundary of the area A to the end of the left and right observation area.

In this case, interval matching errors are obtained for each region (A) and (B) using the same operation as in Equation (4), and the region matching errors for each region (A) and (B) are compared to each region (A). Minimum interval matching error in (B) ) ( ).

After that, the minimum interval matching error for each area (A) (B) ( ) ( ).

At this time, the interval matching error ( ) Is an interval matching error ( If less than or equal to, the pixel value to be interpolated is the minimum section matching error ( The interpolated value depends on the direction indicated by

Conversely, the interval matching error ( ) Is an interval matching error ( Greater than), the minimum interval matching error ( The interpolated pixel value is obtained according to the direction indicated by) to determine whether the pixel value exists between the pixel values existing immediately above and below the pixel to be interpolated.

Accordingly, the minimum interval matching error ( If the interpolated pixel value is between the pixel values immediately above and below the pixel to be interpolated, the pixel value becomes the pixel value to be interpolated.

If the minimum interval matching error ( If the interpolated pixel value is not between the pixel values immediately above and below the pixel to be interpolated, the pixel value to be interpolated is the minimum section matching error of the region A. The interpolated value depends on the direction indicated by

That is, the above process is performed by the following program.

IF ( ) THEN

ELSE

IF (Median { } = ) THEN

ELSE

ENDIF

ENDIF

here, Denotes a pixel in row i, column j of the nth field, which is the pixel to be interpolated at present.

And, Wow Denotes values interpolated along directions indicating minimum section matching errors in regions A and B, respectively.

In addition, although the pixel values linearly interpolated along the direction indicating the minimum interval matching error may be used to obtain the interpolation pixels in the respective regions (A) and (B), the interpolation is performed as follows in order to perform a more stable interpolation. Used pixel values.

This process is performed by the following program.

IF ( ) THEN

ELSE

ENDIF

IF ( ) THEN

, In other words, There is no need to save.

ELSE

ENDIF

here, Denotes d = 0, that is, interval matching error in the vertical direction, Is a pixel value linearly interpolated according to the direction indicating the minimum section matching error in region A, Is a pixel value linearly interpolated along a direction indicating a minimum section matching error in region B. FIG.

That is, the interval matching error in the vertical direction ( If the value is approximate to '0', the interpolation value ( ) And the interval matching error in the vertical direction ( ) Is weighted if it is not an approximation to '0', so that the minimum interval matching error ( The interpolation value ( Obtain

Then, the minimum section matching error of the region B ( Interval matching error in the vertical direction Is greater than).

Accordingly, the minimum section matching error of the region B ( Value is the vertical section matching error ( Is greater than Becomes an interpolation value ( There is no need to save).

In contrast, the minimum interval matching error of the region B ( Value is the vertical section matching error ( Less than), the minimum interval matching error ( The interpolation value ( Obtain

Therefore, the spatial interpolation unit 300 performs interpolation using pixels that are spatially adjacent to the pixel to be interpolated as much as possible, and interpolates pixels to be interpolated when pixels are relatively far apart. By examining the correlation with adjacent pixels and interpolating using these pixels only when the correlation is high, more precise and stable interpolation is performed.

Then, the median filtering is performed on the surrounding pixels of the pixel to be interpolated in the current field, in particular, two pixels in the diagonal direction used for linear interpolation, pixels at the interpolated position, and two pixels at the interpolated positions of the previous and subsequent fields. Do this.

For example, FIG. 7 is an exemplary diagram showing adjacent pixels used for temporal and spatial filtering for interpolation pixel determination.

At this time, the peripheral pixels of the pixel to be interpolated in the current field (n-th field), in particular, two pixels in the diagonal direction used for linear interpolation ( , ) And the pixel at the interpolated position ( Then, the pixel of the interpolated position of the previous field (n-1th field) and the subsequent field (n + 1th field) ( , ), Median filtering is performed by the operation as shown in Equation (7) below to remove the noise component of the pixel.

----- (7)

Therefore, by performing the median filtering as shown in Equation (7), not only the noise component is removed by temporally and spatially filtering the pixels to be interpolated at present, but also the temporal interpolation of the still image which is considered as moving image by the motion extension unit 700. The effect can be exhibited and stability can be increased by maintaining consistency in the time axis direction.

In order to calculate a smoother and more stable interpolation value in the current field (n-th field), median filtering is performed by giving a predetermined weight to the interpolated pixel values according to the edge direction calculated above. can do.

Median filtering considering weight is performed by the operation as shown in Equation (8) below.

------(8)

However, as described above, the interpolation pixel in which all the median filtering is performed ( ) Is determined by other pixels that are spatially far from the current interpolation position or when they are present in very fast motion, the interpolation pixel value may represent a significantly different value than other adjacent pixels.

In order to prevent such a phenomenon, the spatial interpolation unit 300 performs median filtering in the vertical direction by the following program with reference to pixels adjacent in the vertical direction from the position of the pixel to be interpolated in the field.

The operation of the vertical median filtering is as follows.

If the distance horizontally away from the current position of the pixel to be interpolated is smaller than the m value determined above, the interpolation pixel estimated by Equation (7) or (8) is determined as the interpolation value.

However, if the distance horizontally away from the current position of the pixel to be interpolated is not smaller than the m value determined above, the interpolation value is the vertical direction of the pixel to be interpolated with the interpolation pixel estimated by Equation (7) or (8). The median filtered value is determined by referring to pixel values of adjacent pixels.

This means that the estimated interpolation pixel ( ) Is determined by the pixels in the field that are spatially far from the current position to interpolate or are present in a fairly fast motion to prevent this interpolating pixel value from boosting to a significantly different value than adjacent pixels in the field. This interpolation pixel performs median filtering with adjacent pixels in the field in the vertical direction.

The temporal interpolation unit 400 extracts a field average value by averaging pixel values of previous field data and pixel values of subsequent field data corresponding to the same position as the pixel to be interpolated at present.

For example, if it is necessary to interpolate the j-th pixel of the i-th line to newly generate the n-th field image, the temporal interpolation unit 400 includes the pixels of the n-1 th field data having the image data of the j-th pixel of the i-th line. The field average value is extracted by averaging the value and the pixel value of the n + 1th field data.

That is, the field average value in the temporal interpolation unit 400 is calculated by the following equation (9).

------ (9)

In this case, the soft switch unit 500 receives the brightness difference BD and the brightness contour pattern difference BPPD calculated by the motion determiner 200 and spatially refers to the motion degree value output from the motion expansion unit 700. The interpolation value in consideration of the edge direction output from the interpolation unit 300 and the field average value output from the temporal interpolation unit 400 are mixed and output.

The soft switch unit 500 outputs an operation value as shown in Equation (10) below.

----- (10)

here, Is a motion degree value output from the motion expansion unit 700 and is a value in the range of '0 or more and 1 or less'.

Accordingly, the vertical line converter 800 refers to the interpolation value output from the soft switch unit 500 and the current field data values stored in the field storage unit 100 to generate an interpolation line suitable for the display device. Convert the number of vertical lines on the screen.

If only the deinterlaced frame data is needed without line conversion, the vertical line converter 800 passes the values output from the field storage unit 100 and the soft switch unit 500 and outputs the same.

As described in detail above, the present invention has an effect of improving image quality performance by performing more precise edge direction detection and interpolation than the conventional deinterlacing method.

Claims (9)

A deinterlacing method of detecting a difference in brightness and a difference in brightness contour pattern to detect a degree of motion, and interpolating the image with reference to the degree of motion, the pixel comprising: pixels to be interpolated in m field data corresponding to a progressive scan method image; A first step of detecting a pixel of the predetermined region; a second step of detecting a change direction of the pixel to be interpolated by calculating correlation between the pixels of the predetermined region; and wherein the pixel to be interpolated with respect to the predetermined region is horizontal or A third step of calculating the interval matching error for each region by dividing the observation region when the image is not present on the vertical edge; and interpolating the interpolation value in a direction indicating the minimum interval matching error among the region matching errors extracted from the regions. A deinterlacing method, characterized in that performing a fourth step of calculating. The method of claim 1, wherein the third step is to change the direction of change of the pixel. A first process of setting the viewing area to the left and right and the moving area based on the second step, the second process of dividing the set observation area into the first and second areas, and the section for each of the divided areas And a fourth step of calculating a matching error, and a fourth step of calculating a minimum interval matching error for each of the calculated areas. The method of claim 2, wherein in the second process, the first and second regions have an edge direction. The first region is divided by the edge direction. The de-interlacing method of claim 1, wherein the deinterlacing method is set up to a boundary that can include the moving area in the left and right direction, and the second area is set from the boundary of the first divided area to the left and right ends of the viewing area. The method of claim 1, wherein the fourth step comprises: a first process of comparing interval matching errors of the first and second regions; and if the interval matching error of the first region is equal to or smaller than the interval matching error of the second region. A second process of calculating a linear interpolated value in a direction indicating a minimum section matching error in one region; and a section matching error in the second region when the section matching error in the first region is greater than the section matching error in the second region. The linear interpolation in the direction and comparing the interpolation value between the pixel values existing above and below the pixel to be interpolated; and the pixel value linearly interpolated in the direction indicating the minimum section matching error of the second region. In the fourth process of calculating the linear interpolated value in the direction indicating the minimum section matching error of the second area when the pixel value exists between the pixel values existing above and below the pixel to be interpolated. De-interlacing method, characterized in that the. The minimum interval matching error of the first region when the pixel value linearly interpolated in the direction indicating the minimum interval matching error of the second region is not between the pixel values existing above and below the pixel to be interpolated. Deinterlacing method further comprising the step of calculating a linear interpolated value in the indicated direction. 3. The method of claim 2, wherein the fourth step comprises: a first process of comparing interval matching errors of the first and second regions; and if the interval matching error of the first region is equal to or smaller than the interval matching error of the second region. Calculating a linear interpolated value in a direction indicating the minimum section matching error of the first region; and if the section matching error of the first region is greater than the section matching error of the second region, the minimum section matching error of the second region is vertical. A third step of comparing whether the interval is greater than the interval matching error in the direction; and if the minimum interval matching error of the second region is larger than the interval matching error in the vertical direction, the minimum interval matching error of the second region is considered in consideration of a weight. And a fourth process of calculating linearly interpolated values in the direction. The method of claim 6, further comprising: calculating linearly interpolated values in the direction indicating the minimum section matching error of the first region when the minimum section matching error of the second region is equal to or smaller than the section matching error in the vertical direction. Deinterlacing method comprising a. A motion determiner that detects the difference between brightness and brightness contour pattern by inputting arbitrary field data to be interpolated and its surrounding field data and calculates the degree of motion of the image; and A temporal interpolation unit that calculates a field average value by averaging pixel values of a field, and pixel values around pixels to interpolate pixel values of field data of a region currently interpolated from the field storage unit and peripheral pixel values in a field as inputs. Intra-field interpolation value according to the direction indicating the minimum section matching error among the section matching errors of each section by detecting the edge direction included in the segment and dividing the arbitrarily set observation region into a plurality of sections. The spatial interpolator calculates the spatial interpolation unit and the spatial interpolation unit according to the brightness difference and the brightness contour pattern difference De-interlacing apparatus which is characterized by formed by a mixture of the average value of the field in the interpolation value and the temporal interpolation of fields at the shaft comprising a soft switch for output to the vertical line conversion. 10. The edge direction of claim 8, wherein the spatial interpolation unit comprises an edge direction included in the pixel values of the field data of the region to be interpolated from the field storage unit and the pixel values around the pixel to interpolate the peripheral pixel values in the field. When the edge direction is not present at the horizontal or vertical edge when the P is detected, the pixel to be interpolated is not present at the horizontal or vertical edge with respect to the subsampled region by subsampling a predetermined region based on the pixel to be interpolated. Otherwise, the interpolation value according to the direction indicating the minimum section matching error among the section matching errors of each region is detected by dividing the observation direction arbitrarily set based on the detected direction by detecting the edge direction due to the gradient. Deinterlacing apparatus, characterized in that configured to calculate.