JP2001346037A - Image interpolating method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image interpolating method capable of preventing generation of ruggedness and blur on an edge part and reproducing a smooth image when an image is interpolated. SOLUTION: This image interpolating method for interpolating a pixel at an intermediate position between a first original pixel and a second original pixel adjacent to the first original pixel comprises a first step of calculating edge components to decide whether or not interpolation pixels exist in the vicinity of an edge position of original image data, a second step of calculating a settable range of pixel data of the interpolation pixels based on the calculated edge components and a third step of selecting plural sets of opposite pixels to hold the interpolation pixels in the oblique direction and to calculate the pixel data and the minimum correlation value of the interpolation pixels the correlation value of which to be expressed by the sum of absolute values of the difference between the pixel data of the interpolation pixels and each opposite pixel becomes minimum in the settable range of the pixel data of the interpolation pixels by every set are provided.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to an image interpolation method for interpolating an image.

[0002]

2. Description of the Related Art Conventionally, when an interlaced image is converted into a progressive image, when an image is enlarged, or when the resolution of the image is increased, pixel data of adjacent original pixels (a data amount representing luminance on a display) is used. Various methods have been proposed for interpolating an image by using (equivalent).

[0005] Representative image interpolation methods include a simple interpolation method and a linear interpolation method. The simple interpolation method is a method in which any pixel data of a pixel adjacent above and below (or left and right) of a pixel to be interpolated is given to the pixel to be interpolated as pixel data. The linear interpolation method is a method of giving, as pixel data, a value obtained by averaging pixel data of pixels adjacent above and below (or left and right) of a pixel to be interpolated.

[0004]

However, in the simple interpolation method, since the pixel data of the pixel adjacent to the pixel to be interpolated is given as it is, when an image reproduced on a display or the like has an oblique edge portion, There is a problem that rattling occurs at the edge portion. Further, in the linear interpolation method, an average value of pixel data of pixels vertically and vertically (or left and right) adjacent to the pixel to be interpolated is given. If the difference between the pixel data of the pixels adjacent to ()) is large, there is a problem that the interpolated pixel becomes an intermediate value and blur occurs at the edge portion.

According to the present invention, it is possible to prevent rattling or blurring at an edge portion when interpolating an image.
It is an object of the present invention to provide an image interpolation method capable of reproducing a smooth image.

[0006]

Means for Solving the Problems [1] Description of First Image Interpolation Method According to the Present Invention The first image interpolation method according to the present invention comprises a first original pixel and a second original pixel adjacent to the first original pixel. A first step of calculating an edge component for determining whether an interpolated pixel exists near an edge position of original image data in an image interpolation method for interpolating a pixel at an intermediate position with respect to an original pixel A second settable range of pixel data of the interpolated pixel is obtained based on the pixel data of the first and second original pixels.
Step: A plurality of sets of opposing pixels sandwiching the interpolated pixel in the oblique direction are selected. For each set, the absolute difference between the pixel data of the interpolated pixel and each opposing pixel is set within the settable range of the pixel data of the interpolated pixel. A third step of obtaining pixel data of an interpolated pixel having a minimum correlation value represented by a sum of values and a minimum correlation value, and pixel data of an interpolated pixel having a minimum correlation value obtained for each of the sets; And the correlation minimum,
A fourth step of obtaining pixel data of the interpolation pixel.

[0007] An original pixel adjacent to the first original pixel and on the opposite side of the second original pixel is referred to as a third original pixel, and adjacent to the second original pixel and on the opposite side of the first original pixel. A certain original pixel is
In the first step, an edge component is calculated based on the pixel data of the first to fourth original pixels.

More specifically, the pixel data of the first original pixel is d1, the pixel data of the second original pixel is d2, the pixel data of the third original pixel is d3, and the pixel data of the fourth original pixel is d1. Is d4, the edge component E is calculated based on the following equation (1).

E = −d3 + d1 + d2-d4 (1)

The edge component obtained in the first step is E, the predetermined threshold is Th, and the larger of the pixel data of the first original pixel and the pixel data of the second original pixel is d.
_Assuming that _{max is} smaller and d _{min is} smaller and d _max -d _min is d, in the second step, the settable range S of the pixel data of the interpolation pixel is obtained based on the following equation (2).

If E> Th, then d _min + d / 2 ≦ S ≦ d _max , if −Th ≦ E ≦ Th, then d _min + d / 4 ≦ S ≦ d _max −d / 4, if E <−Th, then d _min ≦ S ≦ d _min + d / 2 (2)

The settable range S obtained in the second step
Let x be the pixel data of, and let da and db be the pixel data of the two original pixels that make up a set of opposing pixels, respectively. The correlation value L for that set is calculated by the following equation (3).

L = | da−x | + | db−x | (3)

The fourth step is, for example, a step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each pair in the third step, and a pixel of an interpolation pixel giving the selected minimum correlation minimum value. Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, The method includes a step of determining the average value of the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel.

The fourth step includes, for example, the step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each set in the third step, and the pixel of the interpolated pixel giving the selected minimum correlation minimum value. Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Extracts the maximum value and the minimum value from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and determines the average value of the extracted maximum value and the minimum value as the pixel data of the interpolation pixel. Those having steps are used.

The fourth step is, for example, a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each set in the third step, and a pixel of an interpolation pixel which gives the selected minimum correlation minimum value. Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Selects the pixel data obtained from the opposing pixel closest to the interpolation pixel among the pixel data of the interpolation pixel giving the minimum correlation minimum value thereof,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. Those having steps are used.

[2] Description of Second Image Interpolation Method According to the Present Invention The second image interpolation method according to the present invention employs an intermediate method between a first original pixel and a second original pixel adjacent to the first original pixel. A first step of calculating an edge component for determining whether an interpolated pixel exists near an edge position of original image data in an image interpolation method of interpolating a pixel at a position, and calculating the calculated edge component as a predetermined pseudo noise component A second step of correcting based on the corrected edge component and the pixel data of the first and second original pixels, and a third step of obtaining a settable range of the pixel data of the interpolation pixel based on the corrected edge component and the pixel data of the first and second original pixels. A plurality of pairs of opposing pixels sandwiched in the direction are selected, and for each set, the sum of the absolute value of the difference between the pixel data of the interpolated pixel and each opposing pixel and the Around the pixel A fourth step of obtaining pixel data and a minimum correlation value of the interpolated pixel in which the correlation value represented by the correction value calculated based on the pixel data of the original pixel is the minimum, and the fourth step of obtaining the minimum correlation value; A fifth step of obtaining pixel data of the interpolated pixel based on the pixel data of the interpolated pixel having the minimum correlation value and the minimum correlation value is provided.

An original pixel adjacent to the first original pixel and on the opposite side of the second original pixel is defined as a third original pixel, and is adjacent to the second original pixel and on the opposite side of the first original pixel. A certain original pixel is
In the first step, an edge component is calculated based on the pixel data of the first to fourth original pixels.

More specifically, the pixel data of the first original pixel is d1, the pixel data of the second original pixel is d2, the pixel data of the third original pixel is d3, and the pixel data of the fourth original pixel is d1. Is d4, the edge component E is calculated based on the following equation (4).

E = −d3 + d1 + d2-d4 (4)

Assuming that the pseudo noise component is Q and the edge component calculated in the first step is E, the corrected edge component E1 obtained in the second step is represented by the following equation (5).

If-Q ≦ E ≦ Q, then E1 = 0, if E> Q or E <−Q, then E1 = E (5)

The corrected edge component obtained in the second step is E1, the larger of the pixel data of the first original pixel and the pixel data of the second original pixel is d _max , and the smaller one is d _max .
_min, and the average of d _max and _{d min dc, α (0 ≦} α ≦
Assuming that 1) and γ are predetermined coefficients, in the third step, the settable range S of the pixel data of the interpolation pixel is obtained based on the following equation (6).

If E1 ≧ 0, then d _min · α + dc (1-α) ≦ S ≦ d _max · α + dc (1-α) + E1 · γ, if E1 <0, then d _min · α + dc (1-α) + E1 · γ ≦ S ≦ _dmax · α + dc (1-α) (6)

A direction connecting the first original pixel and the second original pixel is defined as an up-down direction, a direction perpendicular to the up-down direction is defined as a left-right direction, and one set of opposing pixels is D12, D24. The two original pixels on both the left and right sides of the opposite pixel D12
1, D13, the two original pixels on the upper and lower sides of the opposite pixel D12 are D02 and D22, and the other opposite pixel D24
The two original pixels on both the left and right sides of are D23 and D25,
The two original pixels on the upper and lower sides of the opposing pixel D24 are D
14, D34, and the original pixels D02, D11, D12,
The pixel data of D13, D14, D22, D23, D24, D25 and D34 are converted to d02, d11, d12, d1.
3, d14, d22, d23, d24, d25 and d
Assuming that β is 34, β1 and β2 are predetermined coefficients, and x is the pixel data of the settable range S obtained in the third step, the equation for calculating the correlation value L for the set is represented by the following equation (7). .

L = | d12−x | + | d24−x | + β1 · H1−β2 · V1 H1 = MAX ｛(| d11−d12 | + | d12−d13 |), (| d23−d24 | + | d24 −d25 |)｝ V1 = MIN ｛(| d02−d12 | + | d12−d22 |), (| d14−d24 | + | d24−d34 |)} (7)

The fifth step includes, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each set in the fourth step, the pixel of the interpolated pixel giving the selected minimum correlation minimum value. Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, The method includes a step of determining the average value of the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel.

The fifth step is, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each set in the fourth step, the pixel of the interpolation pixel giving the selected minimum correlation minimum value, Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Extracts the maximum value and the minimum value from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and determines the average value of the extracted maximum value and the minimum value as the pixel data of the interpolation pixel. Those having steps are used.

The fifth step is, for example, the step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each set in the fourth step, the pixel of the interpolation pixel giving the selected minimum correlation minimum value, Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Selects the pixel data obtained from the opposing pixel closest to the interpolation pixel among the pixel data of the interpolation pixel giving the minimum correlation minimum value thereof,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. Those having steps are used.

[3] Description of Third Image Interpolation Method According to the Present Invention According to the third image interpolation method according to the present invention, a first original pixel, a second original pixel, and a first original pixel adjacent in the left-right direction are provided. In an image interpolation method of interpolating a pixel at the center position of four original pixels consisting of a third pixel adjacent below and a fourth pixel below the second original pixel, the first original pixel, 4
Of the original pixel, the fifth original pixel, the first original pixel, and the fourth original pixel, which are on the extension of the line connecting the first original pixel and the fourth original pixel, and which are adjacent to the diagonally upper left of the first original pixel. Whether the interpolated pixel exists near the edge position of the original image data based on the pixel data of the sixth original pixel which is on the extension of the line connecting the original pixels and is diagonally lower right of the fourth original pixel. A first step of calculating a first edge component for determining, a second original pixel, a third original pixel, an extension of a line connecting the second original pixel and the third original pixel, and The seventh original pixel adjacent to the second original pixel on the upper right and the seventh original pixel on the extension of the line connecting the second original pixel and the third original pixel and the lower left adjacent to the third original pixel on the left. 8 for determining whether the interpolated pixel exists near the edge position of the original image data based on the pixel data of the original pixel No. 8
A second step of calculating an edge component of the first pixel component and a first settable range of pixel data of the interpolation pixel based on the first edge component and the pixel data of the first and fourth original pixels. A third step of obtaining a second settable range of the pixel data of the interpolated pixel based on the edge component and the pixel data of the second and third original pixels, the first settable range and the second settable A fourth step of determining whether or not there is an overlapping portion in the range; if there are no overlapping portions in the first settable range and the second settable range, the first to fourth steps Fifth step of calculating the average value of the pixel data of the original pixel and determining the calculation result as the pixel data of the interpolation pixel, when there is a portion where the first settable range and the second settable range overlap each other Is that heavy After setting the matching portion as a settable range, a plurality of sets of opposing pixels sandwiching the interpolated pixel in the oblique direction are selected, and for each set, the pixel data of the interpolated pixel is set within the settable range of the pixel data of the interpolated pixel. A sixth step of obtaining pixel data of an interpolated pixel having a minimum correlation value represented by a sum of absolute values of differences between the pixel data and each of the opposing pixels and a minimum correlation value; The method further comprises a seventh step of obtaining pixel data of the interpolated pixel based on the pixel data of the interpolated pixel having the minimum correlation value and the minimum correlation value.

The pixel data of the first original pixel is d1, the pixel data of the fourth original pixel is d4, the pixel data of the fifth original pixel is d5, and the pixel data of the sixth original pixel is d6. In the first step, the first edge component EL is calculated based on the following equation (8).
Also, the pixel data of the second original pixel is d2, the pixel data of the third original pixel is d3, and the pixel data of the seventh original pixel is d2.
Assuming that the pixel data of the seventh and eighth original pixels is d8 and the second edge component is ER, in the second step, the following equation (9) is used.
Is calculated based on the second edge component ER.

EL = −d5 + d1 + d4-d6 (8) ER = −d7 + d2 + d3-d8 (9)

The first edge component is EL, the second edge component is ER, the predetermined threshold is Th, and the larger of the pixel data of the first original pixel and the pixel data of the fourth original pixel is dL. _max , the smaller one is dL _min , dL _max −dL _min
Is set to dL, the larger one of the pixel data of the second original pixel and the pixel data of the third original pixel is dR _max , and the smaller one is dR _max .
R _min , dR _max −dR _min is defined as dR. In the third step, a first settable range SL is obtained based on the following equation (10), and a second settable range SL is obtained based on the following equation (11). A range SR is determined.

[0034] _{if EL> Th, then dL min} + dL / 2 ≦ SL ≦ dL max, if -Th ≦ EL ≦ Th, then dL min + dL / 4 ≦ SL ≦ dL max -dL / 4, if EL <-Th, _{then dL min ≦ SL ≦ dL min} + dL / 2 ... (10)

[0035] _{if ER> Th, then dR min} + dR / 2 ≦ SR ≦ dR max, if -Th ≦ ER ≦ Th, then dR min + dR / 4 ≦ SR ≦ dR max -dR / 4, if ER <-Th, then dR _min ≦ SR ≦ dR _min + dR / 2 (11)

The settable range S set in the sixth step
Where x is the pixel data within the pixel, and 2 constitutes a set of opposing pixels.
Assuming that the pixel data of the two original pixels are da and db, respectively, the correlation value L for the pair is calculated based on the following equation (12).

L = | da−x | + | db−x | (12)

As the seventh step, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each pair in the sixth step, the pixel of the interpolation pixel giving the selected minimum correlation minimum value, Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, The method includes a step of determining the average value of the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel.

As the seventh step, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each set in the sixth step, the pixel of the interpolation pixel giving the selected minimum correlation minimum value, Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Extracts the maximum value and the minimum value from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and determines the average value of the extracted maximum value and the minimum value as the pixel data of the interpolation pixel. Those having steps are used.

As the seventh step, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each pair in the sixth step, the pixel of the interpolation pixel giving the selected minimum correlation minimum value, Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Selects the pixel data obtained from the opposing pixel closest to the interpolation pixel among the pixel data of the interpolation pixel giving the minimum correlation minimum value thereof,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. Those having steps are used.

[4] Description of the Fourth Image Interpolation Method According to the Present Invention The fourth image interpolation method according to the present invention employs a first original pixel, a second original pixel, and a first original pixel adjacent in the left-right direction. In an image interpolation method of interpolating a pixel at the center position of four original pixels consisting of a third pixel adjacent below and a fourth pixel below the second original pixel, the first original pixel, 4
Of the original pixel, the fifth original pixel, the first original pixel, and the fourth original pixel, which are on the extension of the line connecting the first original pixel and the fourth original pixel, and which are adjacent to the diagonally upper left of the first original pixel. Whether the interpolated pixel exists near the edge position of the original image data based on the pixel data of the sixth original pixel which is on the extension of the line connecting the original pixels and is diagonally lower right of the fourth original pixel. A first step of calculating a first edge component for determining, a second original pixel, a third original pixel, an extension of a line connecting the second original pixel and the third original pixel, and The seventh original pixel adjacent to the second original pixel on the upper right and the seventh original pixel on the extension of the line connecting the second original pixel and the third original pixel and the lower left adjacent to the third original pixel on the left. 8 for determining whether the interpolated pixel exists near the edge position of the original image data based on the pixel data of the original pixel No. 8
Second step of calculating the edge component of the calculated first component
A third step of correcting each of the edge component and the second edge component based on a predetermined pseudo noise component, and interpolating based on the corrected first edge component and the pixel data of the first and fourth original pixels. The first settable range of the pixel data of the pixel is obtained, and the second settable of the pixel data of the interpolated pixel is determined based on the corrected second edge component and the pixel data of the second and third original pixels. The fourth to find the range
Step, a fifth step of determining whether or not there is a portion overlapping each other in the first settable range and the second settable range, overlapping each other in the first settable range and the second settable range If no portion exists, a sixth step of calculating the average value of the pixel data of the first to fourth original pixels and determining the calculation result as the pixel data of the interpolation pixel; In the case where there is an overlapping part in the settable range of 2, when the overlapping part is set as a settable range, a plurality of sets of opposing pixels sandwiching the interpolation pixel in the oblique direction are selected, and for each set, Within the settable range of the pixel data of the interpolation pixel, a correction value calculated based on the sum of the absolute values of the differences between the pixel data of the interpolation pixel and each of the opposite pixels and the pixel data of the original pixels around each of the opposite pixels And represented by A seventh step of obtaining the pixel data of the interpolated pixel having the minimum correlation value and the minimum correlation value, and based on the pixel data of the interpolated pixel having the minimum correlation value and the minimum correlation value obtained for each of the sets. And an eighth step of obtaining pixel data of the interpolated pixel.

The pixel data of the first original pixel is d1, the pixel data of the fourth original pixel is d4, the pixel data of the fifth original pixel is d5, and the pixel data of the sixth original pixel is d6. In the first step, the first edge component EL is calculated based on the following equation (13). The pixel data of the second original pixel is d2, the pixel data of the third original pixel is d3, the pixel data of the seventh original pixel is d7, the pixel data of the eighth original pixel is d8, and the second Assuming that the edge component is ER, in the second step, the following equation (1)
The second edge component ER is calculated based on 4).

EL = −d5 + d1 + d4-d6 (13) ER = −d7 + d2 + d3-d8 (14)

Assuming that the pseudo noise component is Q, the first edge component is EL, and the second edge component is ER, the corrected first edge component EL1 obtained in the third step is given by the following equation (15). Expressed and corrected second edge component ER1
Is represented by the following equation (16).

If−Q ≦ EL ≦ Q, then EL1 = 0, if EL> Q or EL <−Q, then EL1 = EL (15)

If−Q ≦ ER ≦ Q, then ER1 = 0, if ER> Q or ER <−Q, then ER1 = ER (16)

The corrected first edge component is EL1, the corrected second edge component is ER1, and the larger of the pixel data of the first original pixel and the pixel data of the fourth original pixel is dL.
_max , the smaller one is dL _min , the average of dL _max and dL _min is dLc, the larger one of the pixel data of the second original pixel and the third original pixel is dR _max , and the smaller one is dR _max .
When the average of R _min , dR _max and dR _min is dRc, α and γ are coefficients set in advance, in the fourth step, the first settable range SL is obtained based on the following equation (17). The second settable range SR is obtained based on the following equation (18).

If EL1 ≧ 0, then dL_min・ Α + dLc (1−α) ≦ SL ≦ dL _max .Alpha. + DLc (1-.alpha.) + EL1.gamma., If EL1 <0, then dL_min・ Α + dLc (1-α) + EL1 ・ γ ≦ SL ≦ dL_max.Alpha. + DLc (1-.alpha.) (17)

If ER1 ≧ 0, then dR_min・ Α + dRc (1−α) ≦ SR ≦ dR _max ・ Α + dRc (1-α) + ER1 ・ γ, if ER1 <0, then dR_min・ Α + dRc (1-α) + ER1 ・ γ ≦ SR ≦ dR_max.Alpha. + DRc (1-.alpha.) (18)

The settable range S set in the seventh step
Where x is the pixel data within the pixel, and 2 constitutes a set of opposing pixels.
Assuming that the pixel data of the two original pixels are da and db, respectively, the correlation value L for the pair is calculated by the following equation (19).

L = | da−x | + | db−x | (19)

The eighth step includes, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each pair in the seventh step, the pixel of the interpolation pixel giving the selected minimum correlation minimum value. Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, The method includes a step of determining the average value of the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel.

As the eighth step, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each pair in the seventh step, the pixel of the interpolation pixel giving the selected minimum correlation minimum value, Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Extracts the maximum value and the minimum value from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and determines the average value of the extracted maximum value and the minimum value as the pixel data of the interpolation pixel. Those having steps are used.

The eighth step includes, for example, the step of selecting the minimum correlation minimum value among the correlation minimum values obtained for each pair in the seventh step, the pixel of the interpolation pixel providing the selected minimum correlation minimum value, Extracting data,
When the minimum correlation minimum value is one, determining the pixel data of the interpolation pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel; and when there are a plurality of minimum correlation minimum values, Selects the pixel data obtained from the opposing pixel closest to the interpolation pixel among the pixel data of the interpolation pixel giving the minimum correlation minimum value thereof,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. Those having steps are used.

[0055]

Embodiments of the present invention will be described below with reference to the drawings.

[1] Description of First Image Interpolation Method An outline of the first image interpolation method will be described with reference to FIGS. A two-dimensional image has a two-dimensional spread in the horizontal and vertical directions. However, in the outline description of the first image interpolation method described below, a one-dimensional interpolation method in the vertical direction will be described in order to simplify the description.

FIG. 1 shows the relationship between original pixels and interpolated pixels to be interpolated. In FIG. 1, lines (n-1),
n, (n + 1), (n + 2) are horizontal lines of the original image, and lines (i-1), i, (i + 1) are horizontal lines to be interpolated.

Here, a case in which a pixel X on a line i (hereinafter, referred to as an interpolated pixel) is interpolated will be described. The original pixel immediately above the interpolation pixel X is D12, and the original pixel immediately below the interpolation pixel X is D22. The original pixel on both sides of the original pixel D12 is D
11, D13. The original pixel on both sides of the original pixel D22 is D
21, D23. The original pixel immediately above the original pixel D12 is D02, and the original pixel immediately below the original pixel D22 is D32
And

In the following description, the original pixels D11, D
12, D13, D21, D22, D23, D02, D3
2 and the pixel data of the interpolated pixel X are d11,
d12, d13, d21, d22, d23, d02, d
32 and an interpolation pixel x. In this example, it is assumed that the pixel data is 8 bits, the black data is “0”, and the white data is “255”.

FIG. 2 shows a procedure for obtaining the pixel data x of the interpolated pixel X by the first image interpolation method.

First, an edge component E is calculated to determine whether or not the interpolation pixel X is near the edge of the original image (step 1). That is, using the pixel data of the two original pixels D02 and D12 just above the interpolation pixel X and the pixel data of the original pixels D22 and D32 just below the interpolation pixel X, the edge component E is obtained from the following equation (20). .

E = −d02 + d12 + d22−d32 (20)

When the interpolation pixel X exists near the black edge of the original image, the edge component E takes a relatively large negative value, and the interpolation pixel X exists near the white edge of the original image. In this case, the edge component E takes a relatively large positive value.

Next, the settable range of the pixel data x of the interpolation pixel X is determined (step 2). That is, step 1
The settable range of the pixel data x of the interpolation pixel X is determined as shown in FIG. In FIG. 3, d _max represents the larger of the pixel data d12 and d22 of the original pixels D12 and D22, and d _min is the pixel data d1 of the original pixels D12 and D22.
2 and d22, whichever is smaller. Also,
d is pixel data d12, d2 of the original pixels D12, D22.
2 (d _max -d _min ).

If Th is a predetermined threshold value,
The relationship between the edge component E and the settable range of the pixel data x of the interpolation pixel X is as follows.

Settable range S _dmin + (d / 2) ≦ S ≦ d _max of pixel data x of interpolation pixel X when E> Th In this case, interpolation pixel X exists near the white edge of the original image and that the assumed, among the settable range S in the range of d _min to d _max, it is set in a range close to d _max side.

Interpolated pixel X when −Th ≦ E ≦ Th
Range S _dmin + (d / 4) ≦ S ≦ d _max − (d / 4)

Settable range S _dmin ≦ S ≦ _dmin + (d / 2) of pixel data x of interpolation pixel X when E <−Th In this case, interpolation pixel X is located near the black edge of the original image. Assuming that it exists, the settable range S is set to a range closer to the d _min side in the range from d _min to d _max .

Next, based on the pixel data of the opposite pixel sandwiching the interpolation pixel X in the oblique direction, a candidate for the pixel data of the interpolation pixel X is determined from the settable range of the pixel data x of the interpolation pixel X (step 3). ). That is, as described below, the minimum values L _min , R of the two diagonal correlation values L, R
_min and pixel data xl, xr that gives the minimum value thereof,
It is determined from the settable range S of the pixel data x of the interpolation pixel X.

There are two methods for obtaining pixel data candidates for the interpolated pixel X. These methods will be described.

(1) Description of First Method The following equation (21) representing the correlation value L of the pixel data between the two opposing pixels D11 and D23 sandwiching the interpolated pixel X in the oblique direction (the upper left oblique direction) and the interpolated pixel X. in, will all the pixel data x in the settable range S substituted respectively, and the correlation value L _min of a minimum, pixel data x which gives the minimum correlation value L _min
and l.

L = | d11−x | + | d23−x | (21)

Similarly, the interpolation pixel X is set in the oblique direction (upper right
Direction), two opposing pixels D13, D21 and an interpolation pixel
The following equation (22) representing the correlation value R of the pixel data with X is set as
Substitute all pixel data x in the settable range S
And the minimum correlation value R _minAnd the minimum correlation value R_min
And the pixel data xr that gives

R = | d13−x | + | d21−x | (22)

The pixel data x obtained as described above
l and xr are pixel data candidates for the interpolation pixel X. However, in such a method, as the pixel data xl which gives the minimum correlation value L _min, there is a case where a plurality of pixel data corresponds. Similarly, a plurality of pixel data may be applicable as the pixel data xr giving the minimum correlation value _Rmin .

The minimum correlation value L_minPixel data xl giving
If more than one pixel data is applicable,
Is the average correlation value L_minPixel data xl giving
It is sufficient to determine it. Similarly, the minimum correlation value R
_min, A plurality of pixel data xr
, The average value thereof is calculated as the minimum correlation value R
_minIs determined as pixel data xr that gives
I just need.

(2) Description of the Second Method FIG. 4 shows the relationship between the correlation value L and the pixel data x. In FIG. 4, x _min indicates the smaller one of the pixel data d11 and d23 of the opposing pixels D11 and D23, and x _max indicates the larger one of the pixel data d11 and d23. Further, xd represents the difference between the pixel data _{d11, d23 (x max -x min} ).

From the relationship between the correlation value L and the pixel data x shown in FIG. 4, the above equation (21) can be modified into the following equation (23).

L = xd + 2 (xx _min ) (x> x _max ) L = xd (x _min ≦ x ≦ x _max ) L = xd + 2 (x _min −x) (x <x _min ) (23)

Although only the modification formula for the correlation value L is shown, the correlation value R in the above equation (22) can be similarly modified.

Hereinafter, a method (second method) for obtaining the minimum correlation values L _min and R _min and the pixel data xl and xr will be described. Here, a method of obtaining the minimum correlation value L _min and the pixel data xl will be described.

FIGS. 5A to 5F show a graph indicating the relationship between the correlation value L and the pixel data x and the settable range of the pixel data x.

In FIG. 5, xa indicates the minimum value of the pixel data x within the settable range, and xb indicates the maximum value of the pixel data x within the settable range.

When xb ≦ x _{min As} shown in FIG. 5A, the settable range of the pixel data x is x
When it is equal to or less than _min , the correlation value L in the pixel data xb
Is minimum, the minimum correlation value L _min is xd + 2 (x
_min− xb). The pixel data xl at this time is xb.

When x _max ≦ xa As shown in FIG. 5B, the settable range of the pixel data x is x
_If it is equal to or greater than _max , the correlation value L in the pixel data xa
Is minimum, the minimum correlation value L _min is xd + 2 (xa
−x _max ). The pixel data xl at this time is x
a.

[0086] When x _min ≦ xa and xb ≦ x _max as shown in FIG. 5 (c), when the setting range of the pixel data x is between pixel data x _min ~x _{ma x} is any settable range Is the minimum value x in the pixel data x of
minimum correlation value L _min since the d becomes xd. In this case, the pixel data xl is a value (x
a + xb) / 2.

[0087] xa <x _min and x _max <As shown in FIG. 5 (d) when xb, when the settable range of the pixel data x is a range wider than the range of the pixel data x _min ~x _{ma x} is the pixel The correlation value L becomes the minimum value xd in any pixel data x of the data x _{min to} x _max . Therefore,
Minimum correlation value L _{mi n} becomes xd. In this case, the pixel data xl is an average of the pixel data x _min and x _max (x
_min + _xmax ) / 2.

Xa <x _min and x _min <xb ≦ x
As shown in FIG. 5 (e) when the _max, when the settable range of the pixel data x is shifted to the left side than the range of the pixel data x _min ~x _{ma x} is any pixel data in the pixel data x _min ～Xb At x, the correlation value L becomes the minimum value xd. Therefore,
Minimum correlation value L _{mi n} becomes xd. In this case, the pixel data xl is an average of the pixel data x _min and xb (x _min
+ Xb) / 2.

X _min ≦ xa <x _max and x _max ≦ x
When b as shown in FIG. 5 (f), the when the settable range of the pixel data x is shifted to the right side than the range of the pixel data x _min ~x _{ma x} is any pixel data in the pixel data Xa～x _max At x, the correlation value L becomes the minimum value xd. Therefore,
Minimum correlation value L _{mi n} becomes xd. In this case, the pixel data xl is pixel data xa, the average value of x _max (xa +
x _max ) / 2.

Thus, the minimum correlation value L _min and the pixel data xl are obtained. The minimum correlation value R _min and the pixel data xr are obtained in the same manner as the minimum correlation value L _min and the pixel data xl.

In step 3, the minimum correlation value L _min ,
When R _min and the pixel data xl and xr that provide it are obtained, the pixel data that provides the smaller one of the two minimum correlation values L _min and R _min is extracted (step 4).

If the two minimum correlation values L _min and R _min are different, one pixel data is extracted and the two minimum correlation values L _min and R _min are extracted.
_{If min} and _Rmin are the same, two pixel data are extracted.

In step 4, one pixel data xl
Or, if xr is extracted (YE in step 5)
S), the extracted pixel data is determined as the pixel data x of the interpolation pixel X (step 6). If two (plural) pixel data xl, xr are selected in step 4 (NO in step 5), the pixel data xl, x
The average value of r is determined as the pixel data x of the interpolation pixel X (step 7). The details are as follows.

If L _min <R _min , then x = xl if L _min > R _min , then x = xr if L _min = R _min , then x = (xl + x
r) / 2

In step S3, two pairs of opposing pixels sandwiching the interpolation pixel X in the oblique direction are selected. However, more than two pairs may be selected. For example,
As shown in FIG. 6, D11 and D27, D12 and D26,
D13 and D25, D15 and D23, D16 and D22, D
Six sets of opposing pixels, such as 17 and D21, may be selected. In this case, for each pair of opposing pixels,
Pixel data that gives the minimum value of the correlation value is obtained in step 3. That is, six pixel data candidates are obtained.

If there are three or more of the minimum correlation values among the six pairs of opposing pixels, in step 4, three or more of the six pixel data candidates are selected from among these six pixel data candidates. Is extracted.

When three or more pieces of pixel data are selected in step 4, there are the following three methods for determining the pixel data x of the interpolated pixel X.

The first is a method of calculating an average value of three or more pixel data selected in step 4 and determining the calculation result as pixel data x of the interpolation pixel X. Second,
In this method, the maximum value and the minimum value of the three or more pixel data selected in step 4 are extracted, the average value thereof is calculated, and the calculation result is determined as the pixel data x of the interpolation pixel X.

Third, from among the three or more pixel data selected in step 4, pixel data obtained from the opposing pixel closest to the interpolation pixel X is selected, and the selected pixel data is converted to the pixel data of the interpolation pixel X. It is a method of determining as x. However, when there are two pieces of pixel data obtained from the opposite pixel closest to the interpolation pixel X, the average is calculated, and the calculation result is determined as the pixel data x of the interpolation pixel X.

[1-1] Description of Image Interpolation Device Using First Image Interpolation Method [1-1-1] Description of First Image Interpolation Device In [1], a group of diagonally opposed pixels is described. The image interpolation method when the number is 2 has been described. Here, as described with reference to FIG. 6, a case where the number of diagonally opposed pixels is 6 will be described. To simplify the description, an image interpolating device that performs one-dimensional interpolation in the vertical direction will be described.

FIG. 7 shows the configuration of the first image interpolation device. The memory unit 1 stores pixel data of original pixels input via the input terminal IN. Interpolated correlation value calculator 2
Are the six minimum correlation values L1 _{min to} L3 _min and R1 _{min to} R3 _min obtained from six sets of opposing pixels using the pixel data of the original pixels stored in the memory unit 1, and the six minimum correlation values. The pixel data x11 to x31 and x1r to x3r of the interpolation pixel X to be given values are calculated.

The minimum value extracting section 3 calculates the six minimum correlation values L1 _{min to} L1 calculated by the interpolation correlation value calculating section 2.
The minimum correlation value which is the minimum among 3 _min and R1 _{min to} R3 _min is identified. The pixel data selection unit 4 includes the minimum value extraction unit 3
Of the six pixel data x11 to x31, x1r to x3r provided from the interpolation correlation value calculation unit 2 based on the identification result of
, Pixel data which is a candidate for the pixel data of the interpolation pixel X is selected.

The maximum value / minimum value extraction unit 5 extracts the maximum and minimum pixel data from the pixel data selected by the pixel data selection unit 4. The average value calculation unit 6 calculates the average value of the two pixel data extracted by the maximum value minimum value extraction unit 5, and outputs the calculation result to the output terminal OUT as the pixel data of the interpolation pixel X.

The operation of the image interpolation device will be described.

FIG. 6 shows the relationship between original pixels and interpolated pixels to be interpolated. As shown in FIG. 6, the original pixels D04, D11 to D17, D21 to D27,
It is assumed that D34 is provided. The pixel data of the interpolation pixel X and the original pixels D04, D11 to D17, D21 to D27, and D34 are respectively converted to x, d04, d11 to d17, d
21 to d27 and d34.

First, pixel data of four original pixels D04, D14, D24, and D34 immediately above and below the interpolation pixel X are input from the memory unit 1 to the interpolation correlation value calculation unit 2,
The edge component E is obtained from the following equation (24).

E = −d04 + d14 + d24−d34 (24)

The edge component E thus obtained is used to calculate the interpolation pixel X in the same manner as in step 2 of FIG.
The settable range S of the pixel data x is obtained. Then, the correlation value L1 of the pixel data between the opposing pixels D11 and D27 and the interpolation pixel X, and the opposition pixels D12 and D26 and the interpolation pixel X
The pixel data correlation value L2 with the opposite pixels D13 and D25
Value L3 of the pixel data between the pixel and the interpolation pixel X, and the opposite pixel D
17, D21 and the correlation value R of the pixel data between the interpolation pixel X
1, the following equations (25) to (25) representing the correlation value R2 of pixel data between the opposing pixels D16 and D22 and the interpolation pixel X and the correlation value R3 of pixel data between the opposing pixels D15 and D23 and the interpolation pixel X, respectively. 30) based on step 3 in FIG.
In the same manner as above, the minimum values L1 _{min to} L3 _min and R1 _{min to} R3 _min of the correlation values L1 to L3 and R1 to R3, and the pixel data x11 to x31 and x1r to give these minimum values.
x3r is determined.

L1 = | d11−x | + | d27−x | (25) L2 = | d12−x | + | d26−x | (26) L3 = | d13−x | + | d25−x | (27) R1 = | d17-x | + | d21-x | (28) R2 = | d16-x | + | d22-x | (29) R3 = | d15-x | + | d23-x ｜… (30)

As described above, the correlation values L1 to L3, R1 to R3
3 minimum values L1 _{min to} L3 _min , R1 _{min to} R3
_min and pixel data x11 to x that give these minimum values
When 3l, x1r to x3r are obtained by the interpolation correlation value calculator 2, the minimum values L1 _{min to} L3 _min and R1 _{min to} R3 _{min are obtained.}
Are stored in the minimum value extracting unit 3 as pixel data x11 to x31, x1.
r to x3r are provided to the pixel data selection unit 4.

The minimum value extracting section 3 calculates the minimum correlation value L1 _min
L3 _min , R1 _{min to} R3 _min are input,
The input minimum correlation values L1 _{min to} L3 _min , R1
Flag1 to Flag3 to F3 which are control signals corresponding to _{min to} R3 _min
lag6 is output.

The minimum value extracting section 3 calculates the correlation values L1 to L
3, the minimum value of R1 to R3 L1 _{min to} L3 _min , R1 _min
Control signals respectively corresponding to ~R3 _min Flag1~6
Is output. Minimum value L of correlation values L1 to L3 and R1 to R3
A control signal corresponding to the smallest value among 1 _{min to} L3 _min and R1 _{min to} R3 _min is High, and a control signal corresponding to other values is Low.

For example, the minimum values L1 _{min to} L3 _min , R1
_When L1 _min and R2 _min are the minimum among _{min to} R3 _min , the control signals Flag1 and Flag5 are set to Hi.
gh, and other control signals Flag2 to Flag4.
Flag 6 is set to Low. Note that the number of control signals that become High is not limited to two as in this example, but is any one of 1 to 6.

Control signal F output from minimum value extracting section 3
Flag 1 to Flag 6 are provided to the pixel data selection unit 4. The pixel data selector 4 outputs pixel data corresponding to a High control signal among the control signals supplied from the minimum value extractor 3 to the maximum value / minimum value extractor 5.

When the control signal supplied from the minimum value extracting unit 3 is the control signal Flag1, Flag1,
5 is High, and other control signals Flag2 to Flag
When g4 and Flag6 are Low, pixel data x1
1, x2r is selected and given to the maximum / minimum value extraction unit 5.

The maximum value minimum value extraction unit 5 selects the maximum pixel data and the minimum pixel data from the pixel data supplied from the pixel data selection unit 4 and supplies the selected pixel data to the average value calculation unit 6. . The average value calculation unit 6 calculates the average value of the two pixel data provided from the maximum value / minimum value extraction unit 5, and outputs the calculation result to the output terminal OUT as the pixel data x of the interpolation pixel X.

When only one piece of pixel data is given to the maximum value / minimum value extracting section 5, the maximum value / minimum value extracting section 5 supplies the one piece of pixel data to the average value calculating section 6. In this case, the average calculator 6 outputs the given one pixel data as it is as the pixel data x of the interpolated pixel X.

The pixel data of the original pixel is stored in the memory 1
The signal is output to the output terminal OUT via the interpolating correlation value calculation unit 2. That is, after the pixel data of the original pixel on the n-th line is output, the pixel data of the interpolation pixel on the i-th line is output.

The threshold value Th for comparing the edge components in the interpolation correlation value calculator 2 can be input from the outside, and the threshold value Th
Can be changed, optimal interpolation processing can be performed on the reproduced image.

The first image interpolation device increases the number of lines. To increase the number of pixels on a line, a similar interpolation process may be performed in the horizontal direction.

In FIG. 7, the maximum value / minimum value extraction unit 5 and the average value calculation unit 6 are omitted, and an average value calculation unit is provided at the subsequent stage of the pixel data selection unit 4. When pixel data is selected,
An average value of the pixel data may be calculated, and the calculation result may be output to the output terminal OUT as pixel data x of the interpolation pixel X.

[1-1-2] Description of Second Image Interpolation Device FIG. 8 shows the configuration of the second image interpolation device. FIG.
In FIG. 7, the same components as those in FIG. 7 are denoted by the same reference numerals, and description thereof will be omitted. It is assumed that the relationship between the interpolation pixel X and the original pixel is as shown in FIG.

This image interpolation apparatus comprises an input terminal IN, an output terminal OUT, a memory unit 1, an interpolation correlation value calculation unit 2
, The minimum value extracting unit 3, the pixel data selecting unit 4, and the interpolation pixel X based on the pixel data given from the pixel data selecting unit 4.
And an interpolation pixel data extraction unit 7 for extracting pixel data obtained from the opposing pixel closest to the pixel data.

The operations of the memory unit 1, the interpolation correlation value calculation unit 2, the minimum value extraction unit 3, and the pixel data selection unit 4 are the same as those of the memory unit 1, interpolation correlation value calculation unit 2, minimum value extraction unit 3, The operation is the same as that of the pixel data selection unit 4.

The minimum correlation value L1 _min is calculated by the interpolation correlation value calculation unit 2.
~ L3 _min , R1 _min ~ R3 _min and pixel data x11
To x31, x1r to x3r are obtained, and the minimum correlation value L1
_{min to} L3 _min and R1 _{min to} R3 _min are the minimum value extraction units 3
And the pixel data x11 to x31, x
1r to x3r are sent to the pixel data selection unit 4.

From the minimum value extracting section 3, the minimum correlation value L1
Control signals Flag1 to Flag6 corresponding to _{min to} L3 _min and R1 _{min to} R3 _min are output. In the pixel data selection unit 4, the pixel data corresponding to the control signal of High is set to pixel data x11 to x31, x
1r to x3r, the interpolation pixel data extraction unit 7
Given to.

The interpolated pixel data extraction unit 7 extracts pixel data obtained from the set of opposing pixels closest to the interpolated pixel X from the pixel data given by the pixel data selection unit 4, The data x is output to the output terminal OUT. At this time, when there are two extracted pixel data, the average of these pixel data is calculated, and the calculation result is output to the output terminal OUT as the pixel data x of the interpolation pixel X.

For example, when the pixel data selected by the pixel data selection unit 4 is x11, x21, x1r, the pixel data obtained from the set of opposing pixels closest to the interpolation pixel X is obtained from the opposing pixels D12 and D26. Pixel data x
2l, the pixel data x21 is the interpolation pixel X
Is output to the output terminal OUT as pixel data x.

When the pixel data selected by the pixel data selection section 4 is x11, x21, x2r, the interpolation pixel X
The pixel data obtained from the pair of opposing pixels closest to the pixel data is the pixel data x obtained from the opposing pixels D12 and D26.
Since the pixel data x2r is obtained from 2l and the opposite pixels D16 and D22, the average value (x21 + x2r) / 2 of the pixel data x21 and x2r is output to the output terminal OUT as the pixel data x of the interpolation pixel X.

The pixel data of the original pixel is stored in the memory 1
The signal is output to the output terminal OUT via the interpolating correlation value calculation unit 2. That is, after the pixel data of the original pixel on the n-th line is output, the pixel data of the interpolation pixel on the i-th line is output.

The second image interpolating apparatus increases the number of lines. To increase the number of pixels on a line, a similar interpolation process may be performed in the horizontal direction.

In the first image interpolation method, the settable range of the pixel data of the interpolation pixel is determined based on the edge component E, and then the pixel data candidates of the interpolation pixel are extracted based on the diagonal correlation value. ing. FIG. 9 illustrates the advantage of determining the settable range of the pixel data of the interpolation pixel.
This will be described with reference to FIG. In FIG. 9, black circles indicate original pixels of black data, and white circles indicate original pixels of white data. Also, X
Indicates an interpolation pixel. In the description of FIG. 9, for the sake of simplicity, white data is set to "1" and black data is set to "0".

As shown in FIG. 9, when there is a thin black line in a white background, it is preferable to set the pixel data of the interpolation pixel X to black data “0”.

A case will be described in which pixel data candidates for an interpolation pixel are extracted based on a correlation value in an oblique direction without determining the settable range of the pixel data of the interpolation pixel. In this case, the minimum value of the correlation value (| d13−x | + | d25−x |) corresponding to the opposing pixels D13 and D25 is | 1
-1 | + | 1-1 | = 0, and the pixel data x that gives the minimum correlation value is 1. Further, the opposite pixels D15, D
23 (| d15−x | + | d23−x)
|) Is | 0-0 | + | 0-0 | = 0,
The pixel data x that gives the minimum correlation value is 0. Therefore, the pixel data x of the interpolation pixel X is (1 + 0) / 2
= 0.5 and no black data.

A case will be described in which the settable range of the pixel data of the interpolation pixel is determined as in the first image interpolation method, and then the candidate of the pixel data of the interpolation pixel is extracted based on the correlation value in the oblique direction. In this case, the edge component E
(= −d04 + d14 + d24−d34) is −1 + 0
+ 1-1 = -1, and the settable range of the pixel data x of the interpolation pixel X is 0 ≦ x ≦ 0.5.

Within this set range, the opposite pixel D1
3, the minimum value of the correlation value corresponding to D25 is | 1
−0.5 | + | 1-0.5 | = 1, and the pixel data x that gives the minimum correlation value is 0.5. The minimum value of the correlation value corresponding to the opposing pixels D15 and D23 is | 0−
0 | + | 0-0 | = 0, and the pixel data x that gives the minimum correlation value is 0. Therefore, the pixel data x of the interpolation pixel X is 0.

[2] Description of Second Image Interpolation Method The second image interpolation method will be described. A two-dimensional image has a two-dimensional spread in the horizontal and vertical directions. However, in order to simplify the description, a one-dimensional interpolation method in the vertical direction will be described.

FIG. 10 shows an image interpolation processing procedure according to the second image interpolation method. Here, as shown in FIG. 11, the original pixel D13 on the line i between the line n and the line (n + 1) and the line (n +
1) A method for obtaining pixel data of the interpolated pixel X between the original pixel D23 and the original pixel D23 will be described.

First, an edge component E is calculated to determine whether or not the interpolation pixel X is near the edge of the original image (step 11). That is, 2 directly above the interpolation pixel X
The edge component E is obtained from the following equation (31) using the pixel data of the original pixels D03 and D13 and the original pixels D23 and D33 immediately below the interpolation target pixel X.

E = −d03 + d13 + d23−d33 (31)

Next, a pseudo noise component set in advance is set to N
It is determined whether or not the edge component E is within the range of −Q ≦ E ≦ Q (step 12). This pseudo noise component Q is a variable that can be controlled from the outside.

The edge component E is corrected based on the result of the determination. That is, assuming that the corrected edge component is E1, if the edge component E is within the range of −Q ≦ E ≦ Q, the corrected edge component E1 is set to 0 (step 13).

If the edge component E is out of the range of −Q ≦ E ≦ Q, that is, if E <−Q or E> Q, the corrected edge component E1 is set to E (step 1).
4). Therefore, the relationship between the edge component E and the corrected edge component E1 is expressed by the following equation 32,
It is represented by a graph such as

E1 = 0 (−Q ≦ E ≦ Q) E1 = E (E> Q or E <−Q) (32)

As described above, by correcting the edge component E using the pseudo noise component Q, the influence of noise appearing in the edge component E is reduced.

Next, the settable range S of the pixel data x of the interpolated pixel X is determined based on the corrected edge component E1 (step 15).

The method for determining the settable range S will be described with reference to FIG. In FIG. 13, d _max represents the larger of the pixel data d13 and d23 of the original pixels D13 and D23, and d _min represents the pixel data d13 and d23.
Represents the smaller value. Dc is d
_It represents the average value of _max and d _min (d _max + d _min ) / 2.

(1) Settable range S of pixel data x when E1 ≧ 0 As shown in FIG. 13A, d _min × α + dc × (1-
α) ≦ S ≦ d _max × α + dc × (1−α) + E1 × γ. Here, α and γ are variables that can be controlled from the outside.

That is, when the edge component E1 is 0 or more, the settable range S of the pixel data x is a range centered at dc [d _min × α + dc × (1−α) ≦ x ≦ d _max ×
α + dc × (1−α)], the range is extended upward by the value of γ · E1.

(2) Settable range S of pixel data x when E1 <0 As shown in FIG. 13B, _dmin × α + dc × (1-
α) + E1 × γ ≦ S ≦ _dmax × α + dc × (1−α).

That is, when the edge component E1 is smaller than 0, the settable range S of the pixel data x is a range centered on dc [d _min × α + dc × (1−α) ≦ x ≦ d
_max × α + dc × (1−α)], the range extending downward by the value of γ · E1.

Next, pixel data candidates for the interpolated pixel X are obtained from the settable range S of the interpolated pixel X based on the pixel data of the opposing pixels sandwiching the interpolated pixel X in the oblique direction (step S1). 16).

The method of obtaining pixel data candidates for the interpolated pixel X is substantially the same as that of step 3 in FIG. 2, but the equation for obtaining the correlation values L and R is different from that of step 3 in FIG.

The correlation value L of the pixel data between the opposed pixels D12 and D24 and the interpolation pixel X is expressed by the following equation (33). The correlation value R of the pixel data between the opposed pixels D14 and D22 and the interpolation pixel X is It is represented by the following equation (34).

L = | d12−x | + | d24−x | + β1 × H1−β2 × V1 (33)

R = | d14−x | + | d22−x | + β1 × Hr−β2 × Vr (34)

In the above equations (33) and (34),
β1 and β2 are variables that can be controlled from the outside.

Further, Hl is the change amount H11 of the quantities d11 to d13 obtained by the following equation (35) and the following equation (3).
Change amount H12 of d23 to d25 obtained by 6)
Of which represents the larger one. That is, Hl = MAX
(H11, H12). MAX (a, b) is a symbol indicating that the larger value of a and b is selected.

Further, Vl is a change amount V11 of d02 to d22 obtained by the following equation (37), and the following equation (38).
Represents the smaller one of the change amounts V12 of d14 to d34 obtained by the above. That is, Vl = MIN (V
11, Vl2). MIN (a, b) is a symbol indicating that the smaller value of a and b is selected.

H11 = | d11−d12 | + | d12−d13 | (35) H12 = | d23−d24 | + | d24−d25 | (36) V11 = | d02−d12 | + | d12−d22 | (37) V12 = | d14−d24 | + | d24−d34 | (38)

Further, Hr is a change amount Hr1 of d13 to d15 obtained by the following equation (39) and Hr1 is obtained by the following equation (40).
Represents the larger one of the change amounts Hr2 of d21 to d23 obtained by the above. That is, Hr = MAX (H
r1, Hr2).

Further, Vr is the change amount Vr1 of d12 to d32 obtained by the following equation (41) and the following equation (42).
Represents the smaller one of the change amounts Vr2 of d04 to d24 obtained by the above. That is, Vr = MIN (V
r1, Vr2).

Hr1 = | d13−d14 | + | d14−d15 | (39) Hr2 = | d21−d22 | + | d22−d23 | (40) Vr1 = | d12−d22 | + | d22−d32 | .. (41) Vr2 = | d04−d14 | + | d14−d24 | (42)

FIG. 14 shows the correlation value L and the pixel data x.
Represents the relationship with In FIG. 14, x _min
Indicates the smaller pixel data among the pixel data d12, d24, x _max indicates the direction of pixel data larger one of the pixel data d12, d24. Also, xd = x
_max− x _min + β1 × H1−β2 × Vl.

[0165] _{xd = x max -x min + β1} × Hl-β2
Assuming that × V1, the correlation value L in the above equation (33) can be modified as in the following equation (43). The correlation value R can be similarly modified.

L = xd + 2 (x−x _min ) (x> x _max ) L = xd (x _min ≦ x ≦ x _max ) L = xd + 2 (x _min −x) (x <x _min ) (43)

The minimum correlation values L _min and R _min and the pixel data xl and xr can be obtained by the method described in the second method in step 3 of FIG. 2, that is, the same method as that described with reference to FIG. it can. At this time, x in the graph of FIG.
d will represent x _max −x _min + β1 × H1−β2 × Vl.

At step 16, the minimum correlation values L _min , R _min and the pixel data xl, x giving them are obtained.
When r is obtained, pixel data that gives the smaller one of the two minimum correlation values L _min and R _min is extracted (step 17).

If the two minimum correlation values L _min and R _min are different, one pixel data is extracted and the two minimum correlation values L _min and R _min are extracted.
_{If min} and _Rmin are the same, two pixel data are extracted.

In step 17, one pixel data x
If l or xr is extracted (Y in step 18)
ES), the extracted pixel data is determined as the pixel data x of the interpolation pixel X (step 19). Step 17
In the case where two (plural) pieces of pixel data xl and xr are selected (NO in step 18), the average value of the pixel data xl and xr is determined as the pixel data x of the interpolation pixel X (step 20). ).

Although the image interpolation method has been described using two sets of opposing pixels, two or more sets of opposing pixels may be used.

When the image interpolation apparatus having the configuration as shown in FIG. 7 or FIG. 8 is to execute the image interpolation using the second image interpolation method, the interpolation correlation value calculation section 2 causes the interpolation correlation value calculation section 2 to execute steps 11 to 16 in FIG. May be performed.

Here, the operation of the interpolation correlation value calculator 2 when obtaining the pixel data x of the interpolation pixel X shown in FIG. 15 will be described. Further, a case where the number of pairs of the opposite pixels in the oblique direction is 6 will be described.

The interpolation correlation value calculation unit 2 first calculates the edge component E by the following equation (4) as described in step 11 of FIG.
4) Determined based on equation.

E = −d05 + d15 + d25−d35 (44)

Next, as described in steps 12 to 14 in FIG. 10, based on the edge component E, the edge component E1 in which the influence of the noise component is reduced is obtained. That is,
The corrected edge component E1 is calculated based on the following equation (45).
Will be corrected.

E1 = 0 (−Q ≦ E ≦ Q) E1 = E (E> Q or E <−Q) (45)

Next, the settable range S of the pixel data x of the interpolation pixel X is obtained from the edge component E1 thus obtained, as described in step 15 of FIG.

Next, pixel data candidates for the interpolated pixel X are obtained in the same manner as described in step 16 of FIG. However, in this example, the number of pairs of opposing pixels sandwiching the interpolation pixel X in the oblique direction is six.

That is, the correlation value L1 of the pixel data between the opposing pixels D12, D28 and the interpolation pixel X, the opposing pixels D13, D
The correlation value L2 of pixel data between the pixel 27 and the interpolation pixel X, the correlation value L3 of pixel data between the pixels D14 and D26 and the interpolation pixel X, the correlation value R1 of pixel data between the pixels D18 and D22 and the interpolation pixel X, The correlation value R2 of the pixel data between the opposing pixels D17, D23 and the interpolated pixel X and the opposing pixels D16, D16,
Based on the following equations (46) to (51) representing the correlation value R3 of the pixel data between D24 and the interpolated pixel X, respectively, the minimum values L1 _{min to} L1 of the correlation values L1 to L3 and R1 to R3.
3 _min , R1 _{min to} R3 _min, and pixel data x11 to x31, x1r to x3r that give the minimum value are obtained.

L1 = | d12−x | + | d28−x | + β1 × Hla−β2 × Vla (46) L2 = | d13−x | + | d27−x | + β1 × Hlb−β2 × Vlb (47) L3 = | d14−x | + | d26−x | + β1 × Hlc−β2 × Vlc (48) R1 = | d18−x | + | d22−x | + β1 × Hra−β2 × Vra (49) R2 = | D17−x | + | d23−x | + β1 × Hrb−β2 × Vrb (50) R3 = | d16−x | + | d24−x | + β1 × Hrc−β2 × Vrc (51)

Note that Hl in the above formulas (46) to (51)
a to Hlc, Hra to Hrc, Vla to Vlc, Vra
To Vrc are represented by the following equations (52) to (63).

Hla = MAX (Hla1, Hla2) (52) Hlb = MAX (Hlb1, Hlb2) (53) Hlc = MAX (Hlc1, Hlc2) (54) Hra = MAX (Hra1, Hra2) (55) Hrb = MAX (Hrb1, Hrb2) (56) Hrc = MAX (Hrc1, Hrc2) (57) Vla = MIN (Vla1, Vla2) (58) Vlb = MIN (Vlb1, Vlb2) (59) Vlc = MIN (Vlc1, Vlc2) (60) Vra = MIN (Vra1, Vra2) (61) Vrb = MIN (Vrb1, Vrb2) (62) Vrc = MIN (Vrc1, Vrc2) (63)

Further, H in the above formulas (52) to (63)
la1-Hlc1, Hla2-Hlc2, Hra1-H
rc1, Hra2 to Hrc2, Vla1 to Vlc1, V
la2-Vlc2, Vra1-Vrc1, Vra2-V
rc2 is represented by the following equations (64) to (87).

Hla1 = | d11−d12 | + | d12−d13 | (64) Hlb1 = | d12−d13 | + | d13−d14 | (65) Hlc1 = | d13−d14 | + | d14−d15 | ... (66) Hla2 = | d27-d28 | + | d28-d29 | ... (67) Hlb2 = | d26-d27 | + | d27-d28 | ... (68) Hlc2 = | d25-d26 | + | d26-d27 ｜… (69)

Hra1 = | d17-d18 | + | d18-d19 | (70) Hrb1 = | d16-d17 | + | d17-d18 | (71) Hrc1 = | d15-d16 | + | d16-d17 | ... (72) Hra2 = | d21-d22 | + | d22-d23 | ... (73) Hrb2 = | d22-d23 | + | d23-d24 | ... (74) Hrc2 = | d23-d24 | + | d24-d25 ｜… (75)

Vla1 = | d02-d12 | + | d12-d22 | (76) Vlb1 = | d03-d13 | + | d13-d23 | (77) Vlc1 = | d04-d14 | + | d14-d24 | (78) Vla2 = | d18-d28 | + | d28-d38 | (79) Vlb2 = | d17-d27 | + | d27-d37 | (80) Vlc2 = | d16-d26 | + | d26-d36 ｜ (81)

Vra1 = | d08-d18 | + | d18-d28 | (82) Vrb1 = | d07-d17 | + | d17-d27 | (83) Vrc1 = | d06-d16 | + | d16-d26 | (84) Vra2 = | d12-d22 | + | d22-d32 | (85) Vrb2 = | d13-d23 | + | d23-d33 | (86) Vrc2 = | d14-d24 | + | d24-d34 ｜ (87)

Thus, the minimum correlation values L1 _{min to} L1
When 3 _min , R1 _{min to} R3 _min and pixel data x11 to x31, x1r to x3r that give the minimum value are obtained by the interpolation correlation value calculation unit 2, the minimum correlation values L1 _{min to} L3 are obtained.
_min and R1 _{min to} R3 _min are supplied to the minimum value extracting unit 3, and the pixel data x11 to x31 and x1r to x3r are supplied to the pixel data selecting unit 4.

Settable range S in step 15 of FIG.
Is different from the method of determining the settable range S in step 2 of FIG. The advantage of the method for determining the settable range S in step 15 in FIG. 10 will be described with reference to FIG.

In FIG. 16, black circles indicate original pixels of black data, white circles indicate original pixels of white data, and hatched circles indicate original pixels of gray. Also, X
Indicates an interpolation pixel. In the description of FIG. 16, for the sake of simplicity, white data is set to “1”, black data is set to “0”, and gray data is set to “0.5”.

As shown in FIG. 16, there are cases where there are two black lines on a white background, and the joint between them is gray. In such a case, the pixel data of the pixel X to be interpolated between the gray pixels at the joint is represented by black data "
Preferably, it is 0 ".

The case where pixel data of the interpolated pixel X is obtained by the first image interpolation method will be described. In this case, the edge component E (= −d04 + d14 + d24−d3
4) is -1 + 0.5 + 0.5-1 = -1, and the settable range S of the pixel data x of the interpolation pixel X is 0.5. Therefore, the pixel data x of the interpolation pixel X is 0.5
And no black data.

A case in which pixel data of an interpolated pixel X is obtained as in the second image interpolation method will be described. Also in this case, the edge component E (= −d04 + d14 + d24−d3)
4) is -1 + 0.5 + 0.5-1 = -1. Also, E1 = -1.

Since E1 <0, the settable range S of the pixel data x of the interpolation pixel X is d _min × α + dc × (1−α)
+ E1 × γ ≦ S ≦ _dmax × α + dc × (1−α). Here, for convenience of explanation, if α = 1 and γ = 0.5, the settable range S is d _min + E1 × 0.5 ≦ S ≦ d
_max . That is, 0.5−0.5 ≦ S ≦ 0.5, that is, 0 ≦ S ≦ 0.5.

Further, for convenience of explanation, when β in the equations (46) to (51) for obtaining the correlation value is set to 0 and the minimum value of the correlation value corresponding to the opposing pixels D13 and D25 is obtained within this set range S. , | 1-0.5 | + | 1-0.5 | =
1, and the pixel data x that gives the minimum correlation value is 0.1.
It becomes 5. The minimum value of the correlation value corresponding to the opposing pixels D15 and D23 is | 0-0 | + | 0-0 | = 0,
The pixel data x that gives the minimum correlation value is 0. Therefore, the pixel data x of the interpolation pixel X is 0.

The equation for calculating the correlation value used in step 16 of FIG. 10 is different from the equation for calculating the correlation value used in step 3 of FIG. The advantage of the correlation value calculation formula used in step 16 of FIG. 10 will be described with reference to FIG.

In FIG. 17, black circles indicate original pixels of black data, and white circles indicate original pixels of white data.
X indicates an interpolation pixel. In the description of FIG. 17, for the sake of simplicity, white data is set to “1”, black data is set to “0”, and gray data is set to “0.5”.

As shown in FIG. 17, when there is a black line on a white background, the first image interpolation method uses the original pixel D1
4 and the original pixel D24, the pixel data of the interpolated pixel X becomes larger than the pixel data of the interpolated pixel between the original pixel D13 and the original pixel D23, and the line thickness changes. Would.

In such a case, when the correlation value is determined in consideration of the connection between the adjacent pixels of the opposing pixel and the adjacent pixels as in the second image interpolation method, the interpolation pixel X between the original pixel D14 and the original pixel D24 is obtained. Can be made equal to the pixel data of the interpolation pixel between the original pixel D13 and the original pixel D23.

[3] Description of Third Image Interpolation Method Next, a third image interpolation method will be described.

FIG. 18 shows the relationship between original pixels and interpolated pixels to be interpolated. In the third image interpolation method, FIG.
, Four original pixels D12, D13, D22,
Pixels are interpolated at the center position of D23.

Hereinafter, the four original pixels D12, D13, D2
A method for obtaining the pixel data of the interpolated pixel X arranged at the center of D2 and D23 will be described.

The original pixels D01 to D04, D11 to D11 in FIG.
The pixel data of D14, D21 to D24, D31 to D34 and the interpolated pixel X are respectively represented by d01 to d04 and d1.
1 to d14, d21 to d24, d31 to d34 and x
Expressed by

FIG. 19 shows an image interpolation processing procedure according to the third image interpolation method. First, two types of edge components EL and ER are calculated to determine whether or not the interpolation pixel X is near the edge of the original image (step 31). That is, using the pixel data of the original pixels D01, D12, D23, and D34, the edge component EL is calculated based on the following equation (88), and the original pixels D04, D13, D22,
The edge component ER is calculated based on the following equation (89) using the pixel data of D31.

EL = −d01 + d12 + d23−d34 (88) ER = −d04 + d13 + d22−d31 (89)

Next, the settable ranges SL and SR of the pixel data x of the interpolation pixel X are determined for each of the edge components EL and ER (step 32).

That is, as in step 2 of FIG. 2, the settable range SL of the pixel data x of the interpolation pixel X is determined based on the edge component EL, and the pixel data of the interpolation pixel X is determined based on the edge component ER. x settable range SR
Ask for.

More specifically, a predetermined threshold value is set to Th, and the larger one of the pixel data d12 of the original pixel D12 and the pixel data d23 of the original pixel D23 is dL _max ,
Assuming that the smaller one is dL _min and dL _max −dL _min is dL, the settable range SL is obtained based on the following equation (90).

[0210] _{if EL> Th, then dL min} + dL / 2 ≦ SL ≦ dL max, if -Th ≦ EL ≦ Th, then dL min + dL / 4 ≦ SL ≦ dL max -dL / 4, if EL <-Th, _{then dL min ≦ SL ≦ dL min} + dL / 2 ... (90)

The larger one of the pixel data d13 of the original pixel D13 and the pixel data d22 of the original pixel D22 is dR _max , the smaller one is dR _min , dR _max -dR.
_{When min} is dR, the settable range SR is given by the following equation (9).
It is determined based on 1).

[0212] _{if ER> Th, then dR min} + dR / 2 ≦ SR ≦ dR max, if -Th ≦ ER ≦ Th, then dR min + dR / 4 ≦ SR ≦ dR max -dR / 4, if ER <-Th, then dR _min ≦ SR ≦ dR _min + dR / 2 (91)

Next, it is determined whether or not there is an overlapping portion between both settable ranges SL and SR (step 33).

As shown in FIG. 20 (a), when there is an overlapping portion between the settable ranges SL and SR, the overlapping portion is determined by the pixel data x of the interpolation pixel X.
(Step 34).

Then, based on the pixel data of the opposite pixel sandwiching the interpolation pixel X in the oblique direction, a candidate for the pixel data of the interpolation pixel X is determined from the settable range of the pixel data x of the interpolation pixel X (step 35). .

That is, the correlation value L1 of the pixel data between the original pixels D11 and D24 and the interpolation pixel X, the original pixels D12 and D23
Value L2 of the pixel data between the pixel data and the interpolation pixel X, the original pixel D0
2, a correlation value L3 of pixel data between D33 and the interpolation pixel X,
Correlation value R1 of pixel data between original pixels D14 and D21 and interpolation pixel X, correlation value R2 of pixel data between original pixels D13 and D22 and interpolation pixel X, and pixel data between original pixels D03 and D32 and interpolation pixel X Based on the equations (92) to (97) respectively representing the correlation values R3, the correlation values L1 to L3, R1 to R3 in the same manner as the second method in step 3 in FIG.
The minimum values of L1min to L3min, R1min to R3min,
Pixel data x11 to x31, x1r giving this minimum value
To x3r.

L1 = | d11−x | + | d24−x | (92) L2 = | d12−x | + | d23−x | (93) L3 = | d02−x | + | d33−x | (94) R1 = | d14-x | + | d21-x | (95) R2 = | d13-x | + | d22-x | (96) R3 = | d03-x | + | d32-x ｜… (97)

The thus obtained minimum correlation value L1_min
~ L3_min, R1_min~ R3 _minIs the smallest of
Select the minimum correlation value and select the image corresponding to the selected minimum correlation value.
The raw data is converted to pixel data x11 to x31, x1r to x3
r (step 36).

The pixel data x of the interpolated pixel X is obtained based on the pixel data extracted in step 36 (step 3).
7).

That is, after the maximum pixel data and the minimum pixel data are extracted from the pixel data extracted in step 36, the average value of the two pixel data is calculated, and the calculation result is used as the pixel of the interpolation pixel X. Let it be data x. If the pixel data selected in step 36 is one,
The pixel data is determined as the pixel data x of the interpolation pixel X.

The average value of the pixel data extracted in step 36 may be calculated, and the calculation result may be determined as the pixel data x of the interpolation pixel X.

Further, from the pixel data selected in step 36, pixel data obtained from the counter pixel closest to the interpolation pixel X is extracted, and the extracted pixel data is extracted from the interpolation pixel X.
Pixel data x. At this time, when there are two pieces of pixel data obtained from the set of the opposing pixels closest to the interpolation pixel X, the average value of the pixel data is used as the pixel data x of the interpolation pixel X.

In the above step 33, the edge component E
Settable range S determined by each of L and ER
If it is determined that L and SR do not overlap as shown in FIG. 20B, the original pixels D12, D13, D22,
D23 pixel data d12, d13, d22,
average value of d23 (d12 + d13 + d22 + d23) /
4 is determined as pixel data x of the interpolation pixel X (step 38).

When the image interpolation apparatus having the configuration shown in FIG. 7 or FIG. 8 is to perform image interpolation using the third image interpolation method, the interpolation correlation value calculation unit 2 causes the interpolation correlation value calculation unit 2 to execute steps 31 to 35 in FIG. And the processing in step 38 may be performed.

That is, the interpolation correlation value calculation unit 2 first obtains the edge components EL and ER, and obtains the obtained edge components EL and E.
The settable ranges SL and SR are obtained for each R. When there are overlapping portions in these settable ranges SL and SR, the minimum correlation values L1min to L3min and R1min to R3mi
n and pixel data x11 to x31, x1 for providing them
Find r to x3r. Then, the obtained minimum correlation value L1mi
n to L3min and R1min to R3min are sent to the minimum value extracting unit 3, and the pixel data x11 to x31, x1r to x
3r is sent to the pixel data selection unit 4.

On the other hand, when the settable ranges SL and SR obtained from the edge components EL and ER do not overlap each other, the average value of the pixel data of the four pixels D12, D13, D22 and D23 is used as the pixel of the interpolation pixel X. Output to the output terminal OUT as data x.

In the above example, the pixel data of the interpolated pixel is obtained by using six sets of opposing pixels. However, the number of sets of opposing pixels is not limited to six. The pixel data of the interpolation pixel may be obtained using the pixel.

[4] Description of Fourth Image Interpolation Method Next, a fourth image interpolation method will be described.

In the fourth image interpolation method, similar to the third image interpolation method, as shown in FIG.
Pixels are interpolated at the center positions of 2, D13, D22, and D23. However, it is slightly different from the third image interpolation method.

Here, four original pixels D12, D13,
A method for obtaining the pixel data of the interpolated pixel X arranged at the center of D22 and D23 will be described.

The original pixels D01 to D04, D11 to D11 in FIG.
The pixel data of D14, D21 to D24, D31 to D34 and the interpolated pixel X are respectively represented by d01 to d04 and d1.
1 to d14, d21 to d24, d31 to d34 and x
Expressed by

FIG. 21 shows an image interpolation processing procedure according to the fourth image interpolation method. First, two types of edge components EL and ER are calculated to determine whether or not the interpolation pixel X is near the edge of the original image (step 41). That is, using the pixel data of the original pixels D01, D12, D23, and D34, the edge component EL is calculated based on the following expression (98), and the original pixels D04, D13, D22,
The edge component ER is calculated based on the following equation (99) using the pixel data of D31.

EL = −d01 + d12 + d23−d34 (98) ER = −d04 + d13 + d22−d31 (99)

Next, a correction process is performed on the edge component EL. That is, assuming that the preset pseudo noise component is N, it is determined whether or not the edge component EL is within the range of -Q ≦ EL ≦ Q (step 42).

The edge component EL is corrected based on the result of the determination. That is, the corrected edge component is expressed as EL
If the edge component EL is within the range of −Q ≦ EL ≦ Q, the corrected edge component EL1 is set to 0 (step 43).

If the edge component EL is out of the range of -Q≤EL≤Q, that is, if EL <-Q or EL> Q, the corrected edge component EL1 is set to EL (step 44). .

Next, the same correction processing is performed on the edge component ER. That is, assuming that the preset pseudo noise component is N, it is determined whether or not the edge component ER is within the range of -Q ≦ ER ≦ Q (step 45).

The edge component ER is corrected based on the result of this determination. In other words, the corrected edge component is ER
If the edge component ER is within the range of −Q ≦ ER ≦ Q, the corrected edge component ER1 is set to 0 (step 46).

If the edge component ER is out of the range of -Q ≦ ER ≦ Q, that is, if ER <−Q or ER> Q, the corrected edge component ER1 is set to ER (step 47). .

Next, the settable range SL of the pixel data x of the pixel X is determined based on the corrected EL1.
The settable range SR of the pixel data x of the pixel X is determined based on the corrected ER1 (step 48). How to obtain these settable ranges SL and SR is described in step 1 in FIG.
Same as 5.

That is, the pixel data d12 of the original pixel D12
And the larger one of the pixel data d23 of the original pixel D23 is d
Assuming that L _max , the smaller one is dL _min , the average of dL _max and dL _min is dLc, and α and γ are predetermined coefficients, the settable range SL is calculated based on the following equation (100).
Desired.

If EL1 ≧ 0, then dL_min・ Α + dLc (1−α) ≦ SL ≦ dL _max .Alpha. + DLc (1-.alpha.) + EL1.gamma., If EL1 <0, then dL_min・ Α + dLc (1-α) + EL1 ・ γ ≦ SL ≦ dL_max.Alpha. + DLc (1-.alpha.) (100)

The larger of the pixel data d13 of the original pixel D13 and the pixel data d22 of the original pixel D22 is referred to as dR
_max, the smaller the dR _min, DRC an average of the dR _max and dR _min, when a preset coefficient α and gamma, settable range SR is based on the following equation (101),
Desired.

If ER1 ≧ 0, then dR_min・ Α + dRc (1−α) ≦ SR ≦ dR _max ・ Α + dRc (1-α) + ER1 ・ γ, if ER1 <0, then dR_min・ Α + dRc (1-α) + ER1 ・ γ ≦ SR ≦ dR_max.Alpha. + DRc (1-.alpha.) (101)

Next, it is determined whether or not there is an overlapping portion between the two settable ranges SL and SR (step 4).
9).

If both settable ranges SL and SR have a portion overlapping each other, the overlapped portion is set as a settable range S of the pixel data x of the interpolation pixel X (step 50).

Then, based on the pixel data of the opposite pixel sandwiching the interpolation pixel X in the oblique direction, a candidate for the pixel data of the interpolation pixel X is determined from the settable range of the pixel data x of the interpolation pixel X (step 51). .

That is, the correlation value L1 of the pixel data between the original pixels D11 and D24 and the interpolation pixel X, the original pixels D12 and D23
Value L2 of the pixel data between the pixel data and the interpolation pixel X, the original pixel D0
2, a correlation value L3 of pixel data between D33 and the interpolation pixel X,
Correlation value R1 of pixel data between original pixels D14 and D21 and interpolation pixel X, correlation value R2 of pixel data between original pixels D13 and D22 and interpolation pixel X, and pixel data between original pixels D03 and D32 and interpolation pixel X Based on the following equations (102) to (107) respectively representing the correlation values R3, the correlation values L1 to L3 are calculated in the same manner as the second method in step 3 in FIG.
Minimum values of R1 to R3 L1min to L3min, R1min to R
3min, and pixel data x11 to x3 giving the minimum value.
1, x1r to x3r are obtained.

L1 = | d11−x | + | d24−x | (102) L2 = | d12−x | + | d23−x | (103) L3 = | d02−x | + | d33−x | ... (104) R1 = | d14-x | + | d21-x | ... (105) R2 = | d13-x | + | d22-x | ... (106) R3 = | d03-x | + | d32-x ｜… (107)

The thus obtained minimum correlation value L1_min
~ L3_min, R1_min~ R3 _minIs the smallest of
Select the minimum correlation value and select the image corresponding to the selected minimum correlation value.
The raw data is converted to pixel data x11 to x31, x1r to x3
r (step 52).

Based on the pixel data extracted in step 52, the pixel data x of the interpolated pixel X is obtained (step 5).
3).

That is, after the maximum pixel data and the minimum pixel data are extracted from the pixel data extracted in step 52, the average value of the two pixel data is calculated, and the calculation result is used as the pixel of the interpolation pixel X. Let it be data x. If the pixel data extracted in step 52 is one,
The pixel data is determined as the pixel data x of the interpolation pixel X.

The average value of the pixel data extracted in step 52 may be calculated, and the calculation result may be determined as the pixel data x of the interpolation pixel X.

Also, from the pixel data selected in step 52, pixel data obtained from the closest pixel to the interpolation pixel X is extracted, and the extracted pixel data is extracted from the interpolation pixel X.
Pixel data x. At this time, when there are two pieces of pixel data obtained from the set of the opposing pixels closest to the interpolation pixel X, the average value of the pixel data is used as the pixel data x of the interpolation pixel X.

In the above step 49, the edge component E
If it is determined that the settable ranges SL and SR obtained by L1 and ER1 do not overlap,
The average value (d1) of pixel data d12, d13, d22, and d23 of four pixels of original pixels D12, D13, D22, and D23.
2 + d13 + d22 + d23) / 4 is determined as the pixel data x of the interpolation pixel X (step 54).

When the image interpolation apparatus having the configuration shown in FIG. 7 or FIG. 8 is to execute the image interpolation using the fourth image interpolation method, the interpolation correlation value calculation section 2 causes the interpolation correlation value calculation section 2 to execute steps 41 to 51 in FIG. And the processing of step 54 may be performed.

[0257]

According to the present invention, when interpolating an image,
It is possible to prevent rattling and blurring at the edge portion and to reproduce a smooth image.

[Brief description of the drawings]

FIG. 1 is a schematic diagram illustrating a relationship between an original pixel and an interpolation pixel.

FIG. 2 is a flowchart illustrating a procedure of a first image interpolation method.

FIG. 3 is a graph showing a relationship between an edge component E and a settable range S of pixel data x of an interpolation pixel X;

FIG. 4 is a graph showing a relationship between a correlation value L and pixel data x.

FIG. 5 is a schematic diagram showing a relationship between a correlation value L and pixel data x and a settable range S of pixel data.

FIG. 6 is a schematic diagram illustrating a relationship between an original pixel and an interpolation pixel.

FIG. 7 is a block diagram illustrating a configuration of a first image interpolation device.

FIG. 8 is a block diagram illustrating a configuration of a second image interpolation device.

FIG. 9 is a schematic diagram for explaining an advantage of the first image interpolation method.

FIG. 10 is a flowchart illustrating a procedure of a second image interpolation method.

FIG. 11 is a schematic diagram illustrating a relationship between an original pixel and an interpolation pixel.

FIG. 12 is a graph showing a relationship between an edge component E and a corrected edge component E1.

FIG. 13 shows a settable range S of pixel data x of an interpolation pixel X;
FIG.

FIG. 14 is a graph showing a relationship between a correlation value L and pixel data x.

FIG. 15 is a schematic diagram illustrating a relationship between original pixels and interpolation pixels.

FIG. 16 is a schematic diagram for explaining an advantage of the second image interpolation method.

FIG. 17 is a schematic diagram for explaining an advantage of the second image interpolation method.

FIG. 18 is a schematic diagram illustrating a relationship between original pixels and interpolation pixels.

FIG. 19 is a flowchart illustrating a procedure of a third image interpolation method.

FIG. 20 is a schematic diagram showing a relationship between a first settable range SL and a second settable range SR.

FIG. 21 is a flowchart illustrating a procedure of a fourth image interpolation method.

[Explanation of symbols]

 Reference Signs List 1 memory section 2 interpolation correlation value calculation section 3 minimum value extraction section 4 pixel data selection section 5 maximum value minimum value extraction section 6 average value calculation section 7 interpolation pixel data extraction section

 ──────────────────────────────────────────────────続 き Continued on front page (31) Priority claim number Japanese Patent Application No. 2000-89664 (P2000-89664) (32) Priority date March 28, 2000 (2000. 3.28) (33) Priority claim country Japan (JP) (72) Inventor Susumu Tanase 2-5-5 Keihanhondori, Moriguchi City, Osaka Prefecture Inside Sanyo Electric Co., Ltd. (72) Inventor Haruhiko Murata 2-5-5 Keihanhondori, Moriguchi City, Osaka Prefecture F-term (reference) in Sanyo Electric Co., Ltd.

Claims (32)

[Claims] 1. An image interpolation method for interpolating a pixel at an intermediate position between a first original pixel and a second original pixel adjacent to the first original pixel, wherein the interpolated pixel exists near an edge position of the original image data. A first step of calculating an edge component for determining whether or not to perform setting, based on the calculated edge component and pixel data of the first and second original pixels, determining a settable range of pixel data of the interpolation pixel. In two steps, a plurality of sets of opposing pixels sandwiching the interpolated pixel in the oblique direction are selected, and for each set, the difference between the pixel data of the interpolated pixel and each opposing pixel is set within the settable range of the pixel data of the interpolated pixel. A third step of obtaining the pixel data of the interpolated pixel having the minimum correlation value represented by the sum of the absolute values and the minimum correlation value, and the pixel of the interpolated pixel having the minimum correlation value obtained for each of the sets; Data and minimum correlation A fourth step of obtaining pixel data of the interpolation pixel based on the image data. 2. An original pixel adjacent to the first original pixel and on the opposite side of the second original pixel is defined as a third original pixel, adjacent to the second original pixel and opposite to the first original pixel. The edge component is calculated based on the pixel data of the first to fourth original pixels in the first step, assuming that the original pixel on the side is a fourth original pixel. Image interpolation method. 3. The method according to claim 1, wherein the pixel data of the first original pixel is d1,
If the pixel data of the original pixel is d2, the pixel data of the third original pixel is d3, and the pixel data of the fourth original pixel is d4,
The edge component E is calculated by the following equation: E = -d3 + d1 + d2-d4
The image interpolation method according to claim 2, wherein the calculation is performed based on: 4. An edge component obtained in the first step is E, a predetermined threshold is Th, and a larger one of pixel data of the first original pixel and pixel data of the second original pixel is d.
_4. A settable range S of pixel data of an interpolated pixel is obtained in the second step in the second step, where _{max is} smaller than d _min and d _max -d _min is d. The image interpolation method described in 1. if E> Th, then d _min + d / 2 ≦ S ≦ d
_max , if−Th ≦ E ≦ Th, then _min + d / 4 ≦
S ≦ d _max −d / 4, if E <−Th, then d _min ≦ S ≦ d _min + d
/ 2. 5. The pixel data of the settable range S obtained in the second step is defined as x, and a pair of opposite pixels 2
Assuming that the pixel data of the two original pixels are da and db, respectively, the correlation value L for the set is L = | da−x |
2. The image interpolation method according to claim 1, wherein the value is calculated by + | db-x |. 6. The fourth step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each pair in the third step; and the pixel data of the interpolated pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value 2. The method according to claim 1, further comprising the step of: determining, as the pixel data of the interpolation pixel, the average value of the pixel data of the interpolation pixel that gives the minimum correlation minimum value when there are a plurality of the correlation pixels. Image interpolation method. 7. A fourth step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each pair in the third step, and pixel data of an interpolated pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of pixels, the maximum value and the minimum value are extracted from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and the average value of the extracted maximum value and the minimum value is calculated as the interpolation pixel value. 2. The image interpolation method according to claim 1, further comprising: determining the pixel data as pixel data. 8. The fourth step is a step of selecting a minimum correlation minimum value among the correlation minimum values obtained for each pair in the third step, and pixel data of an interpolation pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of, from among the pixel data of the interpolated pixel giving the minimum correlation minimum value thereof, select the pixel data obtained from the opposite pixel closest to the interpolated pixel,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. The image interpolation method according to claim 1, further comprising the steps of: 9. An image interpolation method for interpolating a pixel at an intermediate position between a first original pixel and a second original pixel adjacent to the first original pixel, wherein the interpolated pixel exists near an edge position of the original image data. A first step of calculating an edge component for determining whether to perform the correction, a second step of correcting the calculated edge component based on a predetermined pseudo noise component, and a corrected edge component and first and second original pixels. A third step of obtaining a settable range of pixel data of the interpolated pixel based on the pixel data of (a), a plurality of pairs of opposing pixels sandwiching the interpolated pixel in an oblique direction are selected, and the pixel data of the interpolated pixel is determined for each set. Within the settable range, the correlation represented by the sum of the absolute values of the differences between the pixel data of the interpolation pixel and each of the opposing pixels and the correction value calculated based on the pixel data of the original pixel around each of the opposing pixels The complement that minimizes the value Fourth seeking the minimum correlation value between the pixel of the pixel data
And a fifth step of obtaining pixel data of the interpolated pixel based on the pixel data of the interpolated pixel having the minimum correlation value and the minimum correlation value obtained for each of the sets. Image interpolation method. 10. An original pixel adjacent to the first original pixel and on the opposite side of the second original pixel is defined as a third original pixel, adjacent to the second original pixel and opposite to the first original pixel. Assuming that the original pixel on the side is the fourth original pixel, in the first step, first to fourth
10. The image interpolation method according to claim 9, wherein an edge component is calculated based on the pixel data of the original pixel. 11. Assuming that pixel data of a first original pixel is d1, pixel data of a second original pixel is d2, pixel data of a third original pixel is d3, and pixel data of a fourth original pixel is d4. , The edge component E is calculated by the following equation:
The image interpolation method according to claim 9, wherein the calculation is performed based on d4. 12. When the pseudo noise component is Q and the edge component calculated in the first step is E, the corrected edge component E1 obtained in the second step is represented by the following equation. An image interpolation method according to claim 11. if −Q ≦ E ≦ Q, then E1 = 0, if E> Q or E <−Q, then E1 = E. 13. The corrected edge component obtained in the second step is E1, the larger of the pixel data of the first original pixel and the pixel data of the second original pixel is d _max , and the smaller one is d _min. , D _max and d _min are represented by dc, α (0 ≦ α ≦
If 1) and γ are predetermined coefficients, the settable range S of the pixel data of the interpolation pixel is obtained in the third step based on the following equation:
The image interpolation method described in 1. if E1 ≧ 0, then d _min · α + dc (1-
α) ≦ S ≦ d _max · α + dc (1-α) + E1 · γ, if E1 <0, then d _min · α + dc (1-
α) + E1 · γ ≦ S ≦ _dmax · α + dc (1-α). 14. A direction connecting the first original pixel and the second original pixel is defined as an up-down direction, a direction perpendicular to the up-down direction is defined as a left-right direction, and one set of opposing pixels is D12, D24. ,
Two original pixels on the left and right sides of one opposing pixel D12 are D11 and D13, two original pixels on the upper and lower sides of the opposing pixel D12 are D02 and D22, and the other opposing pixel D12
The two original pixels on both left and right sides of D24 are D23 and D25, and the two original pixels on both upper and lower sides of the opposing pixel D24 are D14 and D34, and each of the original pixels D02, D11, D1
2, D13, D14, D22, D23, D24, D25
And the pixel data of D34 are d02, d11, d12,
d13, d14, d22, d23, d24, d25 and d34, β1 and β2 are predetermined coefficients,
The pixel data of the settable range S obtained in the step is x
10. The image interpolation method according to claim 9, wherein the equation for calculating the correlation value L for the set is represented by the following equation. L = | d12−x | + | d24−x | + β1 · H1−β
2 · Vl Hl = MAX ｛(| d11−d12 | + | d12−d1
3 |), (| d23-d24 | + | d24-d25
|)｝ Vl = MIN ｛(| d02−d12 | + | d12−d2
2 |), (| d14-d24 | + | d24-d34
｜)｝ 15. A fifth step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each pair in the fourth step, and pixel data of an interpolated pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value Determining the average value of the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolated pixel when there are a plurality of interpolated pixel values. Image interpolation method. 16. The fifth step is a step of selecting a minimum correlation minimum value among the correlation minimum values obtained for each set in the fourth step, and pixel data of an interpolated pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of pixels, the maximum value and the minimum value are extracted from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and the average value of the extracted maximum value and the minimum value is calculated as the interpolation pixel value. 10. The image interpolation method according to claim 9, further comprising: determining as pixel data. 17. The fifth step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each pair in the fourth step, and the pixel data of the interpolated pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of, from among the pixel data of the interpolated pixel giving the minimum correlation minimum value thereof, select the pixel data obtained from the opposite pixel closest to the interpolated pixel,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. The image interpolation method according to claim 9, further comprising: 18. A first original pixel and a second original pixel adjacent in the left-right direction, a third pixel adjacent below the first original pixel, and a fourth adjacent pixel below the second original pixel. In an image interpolation method for interpolating a pixel at a center position of four original pixels including pixels, a first original pixel, a fourth original pixel, and an extension of a line connecting the first original pixel and the fourth original pixel. The fifth original pixel adjacent to the upper left of the first original pixel and the extension of the line connecting the first original pixel and the fourth original pixel and the lower right of the fourth original pixel A first step of calculating a first edge component for determining whether an interpolated pixel exists near an edge position of the original image data based on pixel data of an adjacent sixth original pixel; a second original pixel , On the extension of the line connecting the third original pixel, the second original pixel and the third original pixel, and obliquely above and to the right of the second original pixel. On the basis of the pixel data of the eighth original pixel which is on the extension of the line connecting the seventh original pixel, the second original pixel, and the third original pixel which are in contact and which is adjacent to the third original pixel at the lower left of the third original pixel. A second step of calculating a second edge component for determining whether the interpolated pixel exists near the edge position of the original image data, and calculating the first edge component and the pixel data of the first and fourth original pixels. , A first settable range of the pixel data of the interpolated pixel is obtained, and a second set of the pixel data of the interpolated pixel is obtained based on the second edge component and the pixel data of the second and third original pixels. A third step of determining a settable range of the first settable range, a fourth step of determining whether or not there is an overlapping portion between the first settable range and the second settable range, and a first settable range and a second settable range. Parts that overlap each other within the settable range of Does not exist, the fifth step of calculating the average value of the pixel data of the first to fourth original pixels and determining the calculation result as the pixel data of the interpolation pixel, the first settable range and the second In the settable range, if there is a part overlapping each other, after setting the overlapping part as a settable range, a plurality of sets of opposing pixels sandwiching the interpolation pixel in the oblique direction are selected, and for each set, interpolation is performed. Within the settable range of the pixel data of the pixel, the pixel data of the interpolated pixel and the minimum correlation value that minimize the correlation value represented by the sum of the absolute value of the difference between the pixel data of the interpolation pixel and each of the opposite pixels are obtained. A sixth step, and a seventh step of obtaining pixel data of the interpolated pixel based on the pixel data of the interpolated pixel having the minimum correlation value and the minimum correlation value obtained for each pair in the sixth step. prepare for Image interpolation method comprising Rukoto. 19. The pixel data of the first original pixel is d1, the pixel data of the fourth original pixel is d4, the pixel data of the fifth original pixel is d5, the pixel data of the sixth original pixel is d6, Assuming that the first edge component is EL, in the first step, the first edge component EL is calculated based on the arithmetic expression EL = −d5 + d1 + d4-d6, the pixel data of the second original pixel is d2, and the third The pixel data of the original pixel is d3, the pixel data of the seventh original pixel is d7,
Let d8 be the pixel data of the original pixel and ER be the second edge component. In the second step, the arithmetic expression ER = −d7
19. The image interpolation method according to claim 18, wherein the second edge component ER is calculated based on + d2 + d3-d8. 20. The first edge component is EL, the second edge component is ER, the predetermined threshold is Th, and the larger of the pixel data of the first original pixel and the pixel data of the fourth original pixel. Is dL _max , the smaller one is dL _min , dL _max −dL
_{When min} is dL, the larger of the pixel data of the second original pixel and the pixel data of the third original pixel is dR _max , the smaller one is dR _min , and dR _max -dR _min is dR.
In the step, based on the following equation, the first settable range S
20. The image interpolation method according to claim 19, wherein L and a second settable range SR are obtained. if EL> Th, then dL _min + dL / 2 ≦ S
L ≦ dL _max , if−Th ≦ EL ≦ Th, then dL _min + dL
_{/ 4 ≦ SL ≦ dL max -dL} / 4, if EL <-Th, then dL min ≦ SL ≦ dL
_min + dL / 2. if ER> Th, then dR _min + dR / 2 ≦ S
R ≦ dR _max , if−Th ≦ ER ≦ Th, then dR _min + dR
/ 4 ≦ SR ≦ dR _max −dR / 4, if ER <−Th, then dR _min ≦ SR ≦ dR
_min + dR / 2. 21. The pixel data within the settable range S set in the sixth step is defined as x, and the pixel data of two original pixels forming one set of opposed pixels are respectively da and d.
b, the correlation value L for the set is L = | da−
19. The image interpolation method according to claim 18, wherein the calculation is performed by x | + | db-x |. 22. A seventh step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each pair in the sixth step, and pixel data of an interpolation pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value 19. The method according to claim 18, further comprising the step of: determining, as the pixel data of the interpolation pixel, an average value of the pixel data of the interpolation pixel that gives the minimum correlation minimum value when there are a plurality of the pixel data. Image interpolation method. 23. A seventh step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each pair in the sixth step, and pixel data of an interpolation pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of pixels, the maximum value and the minimum value are extracted from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and the average value of the extracted maximum value and the minimum value is calculated as the interpolation pixel value. 19. The image interpolation method according to claim 18, further comprising: determining as pixel data. 24. The seventh step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each set in the sixth step, and the pixel data of the interpolated pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of, from among the pixel data of the interpolated pixel giving the minimum correlation minimum value thereof, select the pixel data obtained from the opposite pixel closest to the interpolated pixel,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. The image interpolation method according to claim 18, comprising the following steps: 25. A first original pixel and a second original pixel adjacent in the left-right direction, a third pixel adjacent below the first original pixel, and a fourth adjacent pixel below the second original pixel. In an image interpolation method for interpolating a pixel at a center position of four original pixels including pixels, a first original pixel, a fourth original pixel, and an extension of a line connecting the first original pixel and the fourth original pixel. The fifth original pixel adjacent to the upper left of the first original pixel and the extension of the line connecting the first original pixel and the fourth original pixel and the lower right of the fourth original pixel A first step of calculating a first edge component for determining whether an interpolated pixel exists near an edge position of the original image data based on pixel data of an adjacent sixth original pixel; a second original pixel , On the extension of the line connecting the third original pixel, the second original pixel and the third original pixel, and obliquely above and to the right of the second original pixel. On the basis of the pixel data of the eighth original pixel which is on the extension of the line connecting the seventh original pixel, the second original pixel, and the third original pixel which are in contact and which is adjacent to the third original pixel at the lower left of the third original pixel. A second step of calculating a second edge component for determining whether or not the interpolation pixel exists near an edge position of the original image data; and determining the calculated first edge component and the calculated second edge component respectively. A third step of correcting based on the pseudo-noise component of the above, based on the corrected first edge component and the pixel data of the first and fourth original pixels, to set a first settable range of the pixel data of the interpolation pixel. A fourth step of obtaining a second settable range of pixel data of the interpolated pixel based on the corrected second edge component and the pixel data of the second and third original pixels. Range and second settable range A fifth step of determining whether or not there is an overlapped portion; if there are no overlapping portions in the first settable range and the second settable range, the first to fourth original pixels A sixth step of calculating the average value of the pixel data of, and determining the calculation result as the pixel data of the interpolation pixel. If there are overlapping portions in the first settable range and the second settable range, After setting the overlapping portion as a settable range, a plurality of sets of opposing pixels sandwiching the interpolated pixel in the oblique direction are selected, and for each set, the set of the interpolated pixel Pixel data of the interpolated pixel that minimizes the correlation value represented by the sum of the absolute values of the differences between the pixel data and each opposing pixel and the correction value calculated based on the pixel data of the original pixel around each opposing pixel And correlation A seventh step of obtaining pixel values of the interpolated pixels based on the pixel data of the interpolated pixels having the minimum correlation value and the minimum correlation value obtained for each pair. An image interpolation method, comprising: 26. The pixel data of the first original pixel is d1, the pixel data of the fourth original pixel is d4, the pixel data of the fifth original pixel is d5, the pixel data of the sixth original pixel is d6, Assuming that the first edge component is EL, in the first step, the first edge component EL is calculated based on the arithmetic expression EL = −d5 + d1 + d4-d6, the pixel data of the second original pixel is d2, and the third The pixel data of the original pixel is d3, the pixel data of the seventh original pixel is d7,
Let d8 be the pixel data of the original pixel and ER be the second edge component. In the second step, the arithmetic expression ER = −d7
26. The image interpolation method according to claim 25, wherein the second edge component ER is calculated based on + d2 + d3-d8. 27. Assuming that a pseudo noise component is Q, a first edge component is EL, and a second edge component is ER,
First edge component EL1 after correction obtained in step
The image interpolation method according to claim 26, wherein the corrected second edge component ER1 is expressed by the following equation. if -Q ≦ EL ≦ Q, then EL1 = 0, if EL> Q or EL <−Q, then EL1
= EL. if −Q ≦ ER ≦ Q, then ER1 = 0, if ER> Q or ER <−Q, then ER1
= ER. 28. The corrected first edge component is represented by EL1,
The corrected second edge component is ER1, and the image of the first original pixel is
The larger of the raw data and the pixel data of the fourth original pixel
dL_max, The smaller one is dL_min, DL_maxAnd dL_minWhen
Is the average of dLc, the pixel data of the second original pixel and the third original pixel.
The larger of the pixel data of the pixel is dR_max, The smaller one
To dR_min, DR_maxAnd dR_minDRc, α
If γ and γ are predetermined coefficients, the fourth step
Then, based on the following equation, the first settable range SL and
The second settable range SR is obtained.
An image interpolation method according to claim 27. if EL1 ≧ 0, then dL_min・ Α + dLc
(1−α) ≦ SL ≦ dL _max・ Α + dLc (1-α) +
EL1 · γ, if EL1 <0, then dL_min・ Α + dLc
(1−α) + EL1 · γ ≦ SL ≦ dL_max・ Α + dLc
(1-α). if ER1 ≧ 0, then dR_min・ Α + dRc
(1−α) ≦ SR ≦ dR _max・ Α + dRc (1-α) +
ER1 · γ, if ER1 <0, then dR_min・ Α + dRc
(1−α) + ER1 · γ ≦ SR ≦ dR_max・ Α + dRc
(1-α). 29. The pixel data within the settable range S set in the seventh step is defined as x, and the pixel data of two original pixels forming one set of opposed pixels are respectively da and d.
b, the correlation value L for the set is L = | da−
26. The image interpolation method according to claim 25, wherein the value is calculated by x | + | db-x |. 30. An eighth step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each pair in the seventh step, and pixel data of an interpolation pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value Determining the average value of the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolated pixel, when there are a plurality of interpolated pixel values. Image interpolation method. 31. An eighth step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each set in the seventh step, and pixel data of an interpolation pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of pixels, the maximum value and the minimum value are extracted from the pixel data of the interpolation pixel giving the minimum correlation minimum value, and the average value of the extracted maximum value and the minimum value is calculated as the interpolation pixel value. 26. The image interpolation method according to claim 25, further comprising: determining as pixel data. 32. An eighth step is a step of selecting the smallest correlation minimum value among the correlation minimum values obtained for each set in the seventh step, and pixel data of an interpolation pixel giving the selected minimum correlation minimum value. Extracting the pixel data of the interpolated pixel that gives the minimum correlation minimum value as the pixel data of the interpolation pixel when the minimum correlation minimum value is one, and the minimum correlation minimum value When there are a plurality of, from among the pixel data of the interpolated pixel giving the minimum correlation minimum value thereof, select the pixel data obtained from the opposite pixel closest to the interpolated pixel,
When the number of selected pixel data is one, the pixel data is determined as the pixel data of the interpolation pixel. When the number of the selected pixel data is two, the average value thereof is determined as the pixel data of the interpolation pixel. The image interpolation method according to claim 25, comprising: