CN101551899B - Image edge detection method and image interpolation method using the method - Google Patents

Abstract

An image edge detection method. Three adjacent first, second and third pixel columns in the image are read, and a plurality of pixel values in each of the first, second and third pixel columns are read. At least one first diagonal edge region is created between the first and second pixel columns and at least one second diagonal edge region is created between the second third pixel column. Wherein, the first and the second slant edge regions are respectively the ones whose difference value of each pixel value between the corresponding pixel rows exceeds the edge threshold value. And detecting whether the first oblique edge area and the second oblique edge area have repeated parts or have a difference within a preset pixel point. And when the repeated part exists or the difference is within the preset pixel point, judging that the area between the first oblique edge area and the second oblique edge area is an oblique line edge.

Description

Image edge detection method and image interpolation method using the method

technical field

The present invention relates to a de-interlacing method, and in particular to an edge detection method in a de-interlacing method.

Background technique

One way to increase the resolution of television pictures is to convert interlaced pictures to progressive-scanned pictures. In de-interlacing (de-interlace) processing, in order to increase the resolution and eliminate the jagged edges of the oblique side of the image, oblique interpolation processing is often performed on the oblique line part in the image.

In known technologies, for example, US Pat. No. 6,133,957 proposes an adaptive diagonal interpolation method to improve image resolution. In this method, a certain interval is used to calculate pixel difference values at different angles. Finally, the angle with the smallest difference is used as the slope of the slope, and the interpolation is performed based on the slope.

However, the above method cannot accurately grasp the position where the slanted line exists in the image, or cannot accurately calculate the slope (angle) of the slanted line. If the position or angle is not correct, the jaggies in the image cannot be eliminated, and the resolution cannot be effectively improved, and even the interpolation effect is reduced, resulting in noise lines or spots on the screen.

Therefore, it is urgent to develop an accurate and simple way to detect the oblique edge and its inclination angle in the image in order to improve the resolution of the display image.

Contents of the invention

In view of the above problems, the present invention proposes an image edge detection method to enhance image resolution.

The invention provides an image edge detection method, which includes the following steps. Firstly, three adjacent first, second and third pixel columns in the image are read, and multiple pixel values in each of the first, second and third pixel columns are read. Then, at least one first oblique edge area is generated between the first and second pixel columns, and at least one second oblique edge area is generated between the second and third pixel columns. Wherein, the first and second oblique edge regions are respectively the difference between the pixel values of the corresponding upper and lower adjacent pixel columns in the same row exceeding the edge critical value, and the first and the second oblique edge regions are Refers to edge regions that are adjacent up and down and have the same label. Afterwards, it is detected whether the first and second oblique edge regions have overlapping portions or are within a predetermined pixel difference. When there is a repeating part between the first and the second oblique edge area or the difference is within a predetermined pixel point, it is determined that the area between the first and the second oblique edge area is an oblique edge.

According to an embodiment of the present invention, generating the first oblique edge region may further include the following steps. Each of the pixel values of the same row in the first and second pixel columns is subtracted to generate a pixel value difference between the first and second pixel columns. Next, it is compared whether the absolute value of the pixel value difference between the first and the second pixel columns exceeds an edge threshold. When the edge threshold is exceeded, a label is assigned between two pixels in the first and second pixel columns. Between the first and second pixel columns, a plurality of positions adjacent to each other and having the label are defined as a first oblique edge region. The generation of the second oblique edge region is done in the same way, but with the data of the second and third pixel columns.

In addition, the present invention also provides an image interpolation method, which includes the following steps. Firstly, three adjacent first, second and third pixel columns in the image are read, and multiple pixel values in each of the first, second and third pixel columns are read. Then, at least one first oblique edge area is generated between the first and second pixel columns, and at least one second oblique edge area is generated between the second and third pixel columns. Wherein, the first and second oblique edge regions are respectively the difference between the pixel values of the corresponding upper and lower adjacent pixel columns in the same row exceeding the edge critical value, and the first and the second oblique edge regions are Refers to edge regions that are adjacent up and down and have the same label. Afterwards, it is detected whether the first and second oblique edge regions have overlapping portions or are within a predetermined pixel difference. When there is a repeating part between the first and the second oblique edge area or the difference is within a predetermined pixel point, it is determined that the area between the first and the second oblique edge area is an oblique line and is an oblique interpolation area. Afterwards, the slope of the oblique line is determined according to the connection of specific points in the first and second oblique edge regions. In the oblique interpolation area, oblique interpolation processing is performed with a slope. Also, outside the oblique interpolation area, vertical interpolation is performed.

According to an embodiment of the present invention, the above-mentioned oblique interpolation area is a union of a plurality of the first and the second oblique edge areas overlapping or close to each other. In addition, the above-mentioned specific point is the first point, the last point, or the middle point of each of the first and second oblique edge regions.

In summary, according to the method of the present invention, by setting the oblique edge area, the position of the oblique line of the oblique edge can be detected more accurately, and in this method, the oblique edge area contains information about the slope of the oblique line , to be used as oblique interpolation processing, so that the oblique interpolation processing can be accurately performed at a more correct angle. Through the technology of the present invention, the resolution of the image can be further enhanced.

In order to make the above and other objects, features and advantages of the present invention more comprehensible, preferred embodiments will be described in detail below together with the accompanying drawings.

Description of drawings

FIG. 1 is an explanatory diagram for illustrating the oblique edge region used in this embodiment.

FIG. 2 is a schematic diagram illustrating a judging method for determining a region where an oblique edge exists.

FIG. 3 is a schematic diagram of regions requiring oblique interpolation in this embodiment.

FIG. 4 is a schematic diagram of detecting angles for oblique interpolation in this embodiment.

5A and 5B are schematic diagrams showing the slope of the oblique line towards the edge in this embodiment.

FIG. 6 is a schematic flow chart of the oblique line position detection method of the present invention.

[Description of main component labels]

100, 102, 110, 112, 114, 116, 118: Slanted edge area

L1, L2, L3: Adjacent lines

I, II overlapping area

Detailed ways

When increasing the resolution of a displayed image, an interpolation method is often used to insert one or more lines between two adjacent pixels to improve the resolution. In this way, oblique interpolation is used for the portion of the image with oblique lines, and vertical interpolation is used if there is no part of the image. For the oblique interpolation part, the present invention proposes a method for more effectively and accurately judging the correct position of the oblique line. Moreover, through this method, a more accurate slope of the oblique line can be provided, so that the oblique interpolation is more accurate and the resolution improvement effect is better.

FIG. 1 is an explanatory diagram for illustrating the oblique edge region used in this embodiment. As shown in FIG. 1 , it shows the pixel values of two adjacent lines L1 and L2 in an image signal. In this figure, the numerical values listed are for illustration only, and are not intended to limit the scope of this patent.

In this embodiment, there are two types of oblique edge regions, one is a negative oblique edge region, and the other is a positive oblique edge region. Next, the definition of oblique edge pixels and oblique edge regions will be described.

Firstly, when the method of this embodiment is executed, an edge threshold value is firstly defined, and the edge threshold value is used as a benchmark for judging whether it is an oblique edge pixel. The edge threshold can be set according to various situations in actual implementation. In this embodiment, an edge threshold value of 10 is used for illustration, but it is not used to limit the implementation scope of the present invention. The edge threshold is mainly to judge whether the pixel value difference of corresponding points in adjacent lines in the image is large enough to be oblique edge pixels.

As shown in Figure 1, in two adjacent lines of pixel data L1, L2, the pixel value of each pixel point Xi (in this example, i=1-15) of the following line L2 minus the corresponding pixel value of the upper column line L1 If the pixel value of the pixel point Xi is different, the difference between positive and negative pixel values will be obtained at each point. Here, the pixel value may be a grayscale value, a brightness value, a lightness value, etc., or other various appropriate display values that can be conceived by those skilled in the art.

For each pixel point Xi, when the pixel value of the point on the lower line L2 is smaller than the pixel value of the corresponding point on the upper line L1, and the absolute value of the difference is greater than the above-mentioned edge critical value, the value of "-" is given. Label (tag); on the contrary, if the pixel value of the point on the lower line L2 is greater than the pixel value of the corresponding point on the upper line L1, and the absolute value of the difference is greater than the above-mentioned edge threshold value, then assign the label of "+". Here, the labels "+" and "-" are used for illustration only, and any two different labels that can be distinguished can be used for marking, such as "1" and "0" instead of "+" and "- "wait.

In Fig. 1, for the case where the pixel value difference of the pixel points corresponding to the upper and lower columns L1 and L2 is a negative label ("-"), it is called a negative edge. For example, for the pixel point corresponding to row X3 in Figure 1, the pixel value in column L1 is 119, the pixel value in column L2 is 96, the difference between the two is -23, and its absolute value is greater than the set critical value 10, Hence the "-" label is given between the two columns, i.e. the negative margin. In addition, a plurality of consecutive negative edges with “-” labels constitute the so-called negative edge region 100 in this embodiment, such as the region surrounded by corresponding rows X3 to X10 in FIG. 1 .

Conversely, for the case where the pixel value difference of the pixel points corresponding to the upper and lower columns L1 and L2 is a positive label (“+”), it is called a positive edge. For example, for the pixel point corresponding to row X11 in Figure 1, the pixel value in column L1 is 124, the pixel value in column L2 is 167, the difference between the two is 43, and its absolute value is greater than the set critical value of 10, so Give a "+" label between two columns, i.e. a positive edge. In addition, a plurality of continuous positive edges with “+” labels constitute the so-called positive edge area 102 in this embodiment, such as the area surrounded by corresponding rows X11 to X15 in FIG. 1 .

In addition, for each pixel corresponding to the row X1 to X2, since the absolute value of the pixel value difference between the upper and lower columns L1 and L2 does not exceed the edge threshold value 10, no label is assigned.

The negative edge area and the positive edge area determined in the above manner can be used to detect the oblique line position in the image.

Next, the use of the method of this embodiment to mark the position of the oblique line in the image will be described. 2 to 4 illustrate the method of marking oblique edges with three adjacent lines.

According to the method described in FIG. 1 , through the data of three consecutive pixel columns L1 , L2 , L3 , labels of two edge regions can be generated. FIG. 2 shows the pixels of rows X1 to X31, and the 31 rows are only used for illustrative purposes, and are not used to limit the number of rows in actual implementation. As shown in FIG. 2 , the pixel data of the column L1 and the column L2 generate the negative edge area 110 , the negative edge area 112 and the positive edge area 114 respectively. Similarly, the pixel data of the column L2 and the column L3 generate the negative edge area 116 and the positive edge area 118 respectively.

After determining the edge regions between two adjacent pixels, the next step is to determine whether there is overlap or proximity between the two adjacent edge regions. Here, the so-called overlapping or close range refers to the edge points with the same label between the pixels in the corresponding row between the upper and lower adjacent edge regions, that is, the pixel positions between the upper and lower columns belong to the same row. For example, as shown in FIG. 2, between the pixels of rows X6-X8, the negative edge region 110 between column L1 and column L2, and the negative edge region 116 between column L2 and column L3 are between rows X7-X8. Overlapping, namely area I. Similarly, between the pixels in the rows X19-X23, the positive edge region 114 between the columns L1 and L2, and the positive edge region 118 between the columns L2 and L3 are overlapping, ie region II. In addition, when judging whether they are close, a critical value can be set to determine whether two oblique edge regions are close. For example, a difference of 5 pixels is used as the basis for judging whether it is close, and the determination of the number of points can be changed according to the actual implementation situation.

Once the overlapping range is determined, it can be judged that there is an oblique edge. In other words, when the ranges of the upper and lower adjacent edge areas overlap or are close to each other, it is determined that the image of the area where these edge areas are located has an oblique edge in the image. An edge area that exists alone, that is, an area that does not overlap or be close to other areas, is judged to have no oblique edge.

After the region where the oblique edge exists is determined, it is necessary to determine (mark) the region that needs to be interpolated obliquely. FIG. 3 is a schematic diagram of regions requiring oblique interpolation in this embodiment.

When an area with an oblique edge is detected, de-interlacing is performed. As mentioned above, when de-interlacing, the so-called oblique interpolation process is performed between two columns of pixels in the area where oblique edges exist in the same image, and the so-called interpolation process is performed between two columns of pixels in areas without oblique edges. vertical interpolation processing. Therefore, it is necessary to demarcate the area associated with the oblique edge at the oblique edge, and only oblique interpolation is performed in this area, and the part outside the area is subjected to vertical interpolation; however, the area The outer parts can also be interpolated in other ways.

As shown in Figure 3, when the oblique edge position is determined by the edge area (positive and negative) as described in Figure 1 and Figure 2, the edge areas adjacent up and down and overlapping or close to each other have already been marked The area that needs to be processed by oblique interpolation. This interpolation processing area is the union of positive and negative edge areas. Next, further explanation will be given.

As mentioned above in FIG. 2 , the overlapping part of the negative edge area is the area I, and therefore the adjacent negative edge areas 110 , 112 , and 116 are the area 1 that needs to be obliquely interpolated. Similarly, the overlapping portion of the positive edge area is area II, and therefore the overlapping area II and the adjacent edge areas 114 and 118 are all areas 2 that need to be interpolated obliquely. The union of area 1 and area 2 shown in FIG. 3 , that is, the entire area covering row X1 to row X31 is subject to oblique interpolation.

Then, after the oblique interpolation processing area is determined, it is necessary to determine the angle for oblique interpolation. FIG. 4 is a schematic diagram of detecting angles for oblique interpolation in this embodiment.

After detecting the position of the oblique edge and the area to be interpolated obliquely, the angle of the oblique edge should be determined next. The correct angle can make the jagged edges of the slanted lines disappear, making the display more comfortable and clear, and improving the resolution. Conversely, an incorrect angle will reduce the effect of oblique interpolation, and even produce errors or noise on the screen, degrading the resolution.

In the preceding steps, in the detected oblique line area with an oblique edge, the relevant upper and lower adjacent edge areas (such as 114 and 118 in FIG. 2 ) already contain angle (slope) information. The following will be described with reference to FIG. 4 and FIGS. 5A and 5B . FIG. 4 is a schematic diagram of detecting angles for oblique interpolation in this embodiment. 5A and 5B are schematic diagrams showing the slope of the oblique line towards the edge in this embodiment.

As shown in FIG. 4 , the aforementioned positive edge region is used for illustration. The overlapping area II in FIG. 2 is the location where it is judged that there is a slanted edge. Then, based on the overlapping area II, the upper and lower adjacent related areas are the positive edge area 114 and the positive edge area 118 . The slope of the oblique line determined by the positive edge areas 114 and 118 is the distance between the positions of the edge areas themselves, that is, the detected slope of the oblique line, or the angle formed by connecting the upper and lower related edge areas. Therefore, the angle can be determined in the following manner.

As shown in FIG. 4 , take the first point (row X19 ) A of the positive edge region 114 and the first point (row X9 ) B of the positive edge region 118 as two endpoints, and connect the point endpoints A and B to obtain a line AB. This slope AB can determine the slope. As shown in FIGS. 5A and 5B , the illustration of FIG. 4 is simplified for illustration. It can be seen more clearly from FIGS. 5A and 5B that the oblique lines AB are 10 pixels apart in the horizontal direction, and because they are two columns of pixels, the height is two pixels. Therefore, a slope (angle θ) of 5 can be obtained.

In addition, as explained above, the interval of 5 pixels on the left and right of the center point P is the area where oblique interpolation is to be performed, and the slope when performing oblique interpolation is the oblique line obtained by the above method The slope of AB is carried out. Therefore, by determining the position of the oblique edge oblique line and the oblique interpolation angle in this embodiment, the resolution can be enhanced accurately.

In the above example, the oblique line is determined by connecting the first points in the adjacent upper and lower oblique edge regions, and then the slope is determined. In addition, it can also be determined by using the last points in the two oblique edge regions, such as points C and D shown in FIG. 4 . It can be seen from the figure that the slopes determined by the two oblique lines AB and CD are almost the same. In addition, the intermediate points in the two oblique edge regions can also be used for determination, or the slopes of AB and CD are used to interpolate at both ends, and the middle part is interpolated with the average slope of the two slopes.

In this way, it is possible to accurately obtain the inclination trend of the interpolated pixels during the oblique interpolation, so that the display of the image is more accurate and reliable.

FIG. 6 is a schematic flowchart of a method for detecting oblique edges and oblique interpolation using the method according to the present embodiment.

As shown in FIG. 6 , first in step S100 , three adjacent pixel columns are selected (read). Basically, an image frame is composed of a plurality of horizontal pixel columns, and three continuous pixel columns are required to implement this embodiment. In addition, for the whole picture, all pixel columns are sequentially read in this way to perform the oblique edge detection and oblique interpolation processing described above, and the resolution increase process for the whole picture has been completed.

Next, in step S102, first and second oblique edge regions are generated from the two adjacent pixel columns in step S100. For example, in the manner described above, a first oblique edge region 110 , 112 or 114 is generated from a column L1 , L2 and a second oblique edge region 116 , or 118 is generated from a column L2 , L3 . Here, the first and second oblique edge regions refer to edge regions that are adjacent up and down and have the same label, for example, both are positive or negative.

The edge area is generated by subtracting the pixel values of the two pixel columns from each other, and then comparing the absolute value with the edge threshold to determine whether there is a positive or negative edge point between two adjacent pixel points. A set of adjacent positive or negative edge points in the same column constitutes an oblique edge region.

Afterwards, in step S104 , it is detected whether there is an overlapping or close portion between the first oblique edge region and the second oblique edge region. For the definition of overlapping or proximity, reference may be made to the above description. When there is an overlapping or close portion between the first oblique edge area and the second oblique edge area, it can be determined that oblique lines of oblique edges exist in the area, and the edge detection is completed. On the contrary, if there is no overlapping or close portion between the first oblique edge area and the second oblique edge area, it is determined that there is no oblique line of oblique edge in the area.

Next, in step S106 , the overlapping or close oblique edges are used to obtain the region requiring oblique interpolation processing. The overlapping or close first and second oblique edge regions determined in step S104 are set as regions requiring oblique interpolation. That is, in the three adjacent pixel columns, all overlapping or close to the first and second oblique edge areas are combined, and the covered area is the area that needs to be subjected to oblique interpolation in the three pixel columns .

Next, step S108 determines the slope (angle) of the oblique line to the edge. After step S106 determines the area that needs to be interpolated obliquely, use the above-mentioned overlapping or close first and second oblique edge areas to calculate the slope (angle) of the oblique line of the oblique edge, the detailed method can be found in Description of Figure 4 and Figures 5A, 5B.

Finally, in the region determined in step S106, oblique interpolation processing is performed using the obtained slope. That is to say, in the region requiring oblique interpolation between two adjacent pixel columns, the oblique interpolation process is performed with the slope. In addition, the other parts outside the area are processed by vertical interpolation; however, the parts outside the area can also be interpolated in other ways. This increases the resolution during deinterlacing to eliminate jagged edges on the slanted sides of the image.

In summary, according to the method of the present invention, by setting the oblique edge area, the position of the oblique line of the oblique edge can be detected more accurately, and in this method, the oblique edge area contains information about the slope of the oblique line , to be used as oblique interpolation processing, so that the oblique interpolation processing can be accurately performed at a more correct angle. Through the technology of the present invention, the resolution of the image can be further enhanced.

Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art may make some changes and modifications without departing from the spirit and scope of the present invention. Therefore, this The scope of protection of the invention should be defined by the appended claims.

Claims (16)

1. the detection method of an image border comprises:

Read in this image three adjacent first, second and the 3rd pixel column, and read respectively this first, this second with the 3rd pixel column in a plurality of pixel values;

Between this first and second pixel column, produce at least one first oblique fringe region; And between the two or three pixel column, produce at least one second oblique fringe region, wherein this first be respectively respectively this pixel value between corresponding with it neighbouring pixel column same lines with this second oblique fringe region difference above the edge critical value;

Whether detect this first has repeating part or differs within the intended pixel point with this second oblique fringe region; And

When this first and this second oblique fringe region between have repeating part or differ within the intended pixel point, judge this first and this second oblique fringe region between the zone be oblique edge.

2. the detection method of image border according to claim 1 wherein produces this first oblique fringe region and also comprises:

With this first with this second pixel column in respectively this pixel value of same lines subtract each other, with produce this first and this second pixel column between margin of image element;

Relatively this first and this second pixel column between the absolute value of this margin of image element whether surpass this edge critical value;

When surpassing this edge critical value, with this first and this second pixel column in give label between two pixels; And

With this first and this second pixel column between, a plurality of adjacent one another are and location definitions that have this label are this first oblique fringe region.

3. the detection method of image border according to claim 2 wherein produces this second oblique fringe region and also comprises:

With this second with the 3rd pixel column in respectively this pixel value of same lines subtract each other, to produce the margin of image element between this second and the 3rd pixel column;

Relatively whether the absolute value of this margin of image element between this second and the 3rd pixel column surpasses this edge critical value;

When surpassing this edge critical value, with giving this label between two pixels in this second and the 3rd pixel column; And

Between this second and the 3rd pixel column, a plurality of adjacent one another are and location definitions that have this label are this second oblique fringe region.

4. the detection method of image border according to claim 2, wherein this label is a two-value data.

5. the detection method of image border according to claim 4, wherein this two-value data is a plus or minus.

6. the detection method of image border according to claim 1, wherein this oblique edge is a plurality of the overlapping each other or the couplet collection of approaching this first and this second oblique fringe region.

7. image interpolation method comprises:

Read in this image three adjacent first, second and the 3rd pixel column, and read respectively this first, this second with the 3rd pixel column in a plurality of pixel values;

Between this first and second pixel column, produce at least one first oblique fringe region; And between the two or three pixel column, produce at least one second oblique fringe region, wherein this first be respectively respectively this pixel value between corresponding with it neighbouring pixel column same lines with this second oblique fringe region difference above the predetermined edge critical value;

Whether detect this first has repeating part or differs within the intended pixel point with this second oblique fringe region;

When this first and this second oblique fringe region between have repeating part or differ within the intended pixel point, judge this first and this second oblique fringe region between the zone be oblique line, and be to insert the zone in oblique;

Respectively with this first with this second oblique fringe region in the couplet collection of specified point, determine the slope of this oblique line; And

In this is oblique, insert in the zone, carry out oblique interior inserting with this slope and handle.

8. image interpolation method according to claim 7 also comprises: in this is oblique, insert outside the zone, carry out vertical interpolation and handle.

9. image interpolation method according to claim 7, wherein this inserts the couplet collection that zone be a plurality of overlappings each other or approaching this first and this second oblique fringe region in oblique.

10. image interpolation method according to claim 7, wherein this specified point be this first with this second oblique fringe region in each first point.

11. image interpolation method according to claim 7, wherein this specified point be this first with this second oblique fringe region in last point.

12. image interpolation method according to claim 7, wherein this specified point be this first with this second oblique fringe region in intermediate point.

13. image interpolation method according to claim 7 wherein produces this first oblique fringe region and also comprises:

With this first with this second pixel column in respectively this pixel value of same lines subtract each other, with produce this first and this second pixel column between margin of image element;

Relatively this first and this second pixel column between the absolute value of this margin of image element whether surpass this edge critical value;

When surpassing this edge critical value, with this first and this second pixel column in give label between two pixels; And

With this first and this second pixel column between, a plurality of adjacent one another are and location definitions that have this label are this first oblique fringe region.

14. image interpolation method according to claim 13 wherein produces this second oblique fringe region and also comprises:

With this second with the 3rd pixel column in respectively this pixel value of same lines subtract each other, to produce the margin of image element between this second and the 3rd pixel column;

Relatively whether the absolute value of this margin of image element between this second and the 3rd pixel column surpasses this edge critical value;

When surpassing this edge critical value, with giving this label between two pixels in this second and the 3rd pixel column; And

Between this second and the 3rd pixel column, a plurality of adjacent one another are and location definitions that have this label are this second oblique fringe region.

15. image interpolation method according to claim 13, wherein this label is a two-value data.

16. image interpolation method according to claim 15, wherein this two-value data is a plus or minus.

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