JP2015106318A - Image processor and image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a technique capable of improving the elimination degree of a blur occurring near a contour while reducing overshoot or undershoot.SOLUTION: There is provided an image processor 1 including at least a direction determination part 12, an inclination determination part 13 and an interpolation calculation part 15. The direction determination part 12 determines a contour direction in an object pixel included in an input image. The inclination determination part 13 determines an inclination kind perpendicular to a contour direction at a position near the object pixel in an enlarged image on the basis of the input image. The interpolation calculation part 15 performs interpolation processing of the pixel of the position near the enlarged image on the basis of a position in the input image separated from the near position by a predetermined length in a direction corresponding to the inclination kind among directions perpendicular to the contour direction.

Description

  The present invention relates to an image processing apparatus and an image processing method.

  In recent years, television devices having a large display capable of displaying high-resolution images have been developed. When trying to display a low resolution image on such a large display, it is necessary to enlarge the low resolution image in accordance with the size of the large display. At this time, it is usual that the sharpness of the image is degraded only by stretching the low-resolution image based on a predetermined magnification. Therefore, a technique for enlarging an image while suppressing a decrease in the sharpness of the image is required.

  For example, a high-frequency component that can be expressed in a high-resolution image but cannot be included in a low-resolution image is lost from an enlarged image generated as a result of enlarging a low-resolution image. Therefore, blurring may occur near the contour of the enlarged image. As a technique for eliminating such blur, a technique called edge enhancement in which a secondary differential value in an original image is added to a pixel value is generally used. However, when such a method is employed, image degradation called overshoot or undershoot may occur near the contour of the enlarged image.

  Therefore, various methods have been disclosed as methods for reducing overshoot or undershoot. For example, a technique is disclosed in which it is determined whether a pixel to be interpolated is present in the left or right region with reference to an edge, and interpolation is performed with pixels on a straight line connecting two pixels in the region in which the pixel to be interpolated exists (For example, refer to Patent Document 1). In addition, a technique is disclosed in which a secondary differential value added to a pixel value in the above contour enhancement is controlled in accordance with a shape of a polygonal line formed by connecting an adjacent pixel and the pixel (for example, Patent Literature 2).

Japanese Patent Laying-Open No. 2005-063197 JP 2010-226260 A

  However, according to the technique described in Patent Document 1, the technique described in Patent Document 2, and the like, overshoot or undershoot can be reduced, but the degree of elimination of blur occurring in the vicinity of the contour may not be improved. . Therefore, the present invention provides a technique capable of improving the degree of elimination of blur occurring near the contour while reducing overshoot or undershoot.

  According to an embodiment of the present invention, a direction determination unit that determines a contour direction in a target pixel included in an input image, and a tilt type in a direction perpendicular to the contour direction in a position near the target pixel in an enlarged image Based on the position in the input image that is a predetermined distance away from the neighboring position in a direction corresponding to the inclination type in a direction perpendicular to the contour direction. An image processing apparatus is provided that includes an interpolation calculation unit that performs an interpolation process on pixels in the vicinity of the enlarged image.

  According to such a configuration, it is possible to improve the degree of elimination of blur occurring near the contour while reducing overshoot or undershoot.

  The interpolation calculation unit may perform the interpolation processing based on a position in the input image that is away from the vicinity position by the predetermined length in a direction with a gentler slope. According to such a configuration, the interpolation processing is performed based on the position where the inclination is further away in a gentler direction, so that it is possible to more reliably improve the degree of elimination of blurring that occurs near the interpolation contour.

  The interpolation calculation unit obtains pixel data corresponding to a position in the input image that is a predetermined length away from the neighboring position in a direction with a gentler slope, and performs the interpolation processing based on the pixel data. Good. According to such a configuration, interpolation processing can be performed more appropriately based on pixel data corresponding to a position that is a predetermined length away from the neighboring position.

  The interpolation calculation unit may acquire an interpolation coefficient and perform the interpolation processing based on the interpolation coefficient and the pixel data. According to such a configuration, since the interpolation coefficient necessary for the interpolation process is acquired, the interpolation process can be performed more easily.

  The predetermined length may be equal to or greater than a distance between pixels separated by one pixel in the enlarged image, and may be equal to or less than a distance between pixels separated by two pixels. If the predetermined length is set to such a length, it is expected that the degree of elimination of blur occurring near the contour is more reliably improved.

  The inclination determination unit is configured to determine an inclination type based on a difference in luminance value between the first adjacent position and the second adjacent position in a direction perpendicular to the contour direction with respect to the vicinity position and the vicinity position. May be determined. According to such a configuration, the determination of the inclination type can be made by a simpler method.

  According to another embodiment of the present invention, a step of determining a contour direction in a target pixel included in an input image, and an inclination type in a direction perpendicular to the contour direction in a position near the target pixel in an enlarged image are determined. In the enlarged image based on the step of determining based on the input image and a position in the input image that is a predetermined length away from the neighboring position in a direction corresponding to the inclination type in a direction perpendicular to the contour direction Performing an interpolation process on the pixels at the neighboring positions.

  According to such a method, it is possible to improve the degree of elimination of blur occurring near the contour while reducing overshoot or undershoot.

  As described above, according to the present invention, it is possible to improve the degree of elimination of blur occurring near the contour while reducing overshoot or undershoot.

It is a figure which shows an example of the gradation change of an input image. It is a figure which shows an example of the gradation change of the enlarged image obtained by enlarging an input image. It is a figure which shows an example of the gradation change of the enlarged image after the outline emphasis of the general emphasis degree. It is a figure which shows an example of the gradation change of the enlarged image after the outline emphasis of a very strong emphasis degree. An example of a gradation change of an image obtained by clipping a pixel value around a target pixel of a magnified image before contour enhancement with a minimum value and a maximum value of the magnified image after contour enhancement with an extremely strong enhancement level FIG. It is a figure which shows an example of the gradation change of the enlarged image obtained by the image processing apparatus which concerns on embodiment of this invention. It is a figure which shows an example of a function structure of the image processing apparatus which concerns on the embodiment. It is a figure which shows the modification of the function structure of the image processing apparatus which concerns on the embodiment. It is a figure for demonstrating the example which calculates the parameter used for determination of a contour direction from an input image. It is a figure for demonstrating the example which calculates the parameter used for determination of a contour direction from the rotation image obtained by rotating an input image clockwise 15 degree | times. It is a figure for demonstrating the direction perpendicular | vertical to an outline direction. It is a figure which shows the 1st inclination classification to a direction perpendicular | vertical to an outline direction. It is a figure which shows the 2nd inclination classification to a direction perpendicular | vertical to an outline direction. It is a figure which shows the 3rd inclination classification to a direction perpendicular | vertical to an outline direction. It is a figure which shows the 4th inclination classification to a direction perpendicular | vertical to an outline direction. It is a figure for demonstrating the example of interpolation in case an inclination corresponds to the 1st inclination classification or the 3rd inclination classification. It is a figure for demonstrating the example of interpolation in case an inclination corresponds to a 2nd inclination classification or a 4th inclination classification.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In the present specification and drawings, components having substantially the same functional configuration are denoted by the same reference numerals, and redundant description is omitted.

  In the present specification and drawings, a plurality of constituent elements having substantially the same functional configuration may be distinguished by attaching different alphabets or numbers after the same reference numeral. However, when it is not necessary to particularly distinguish each of a plurality of constituent elements having substantially the same functional configuration, only the same reference numerals are given.

(General technology)
First, general techniques will be described. FIG. 1 is a diagram illustrating an example of gradation change of an input image. As shown in FIG. 1, it is assumed that the gradation of the original image changes in the horizontal direction. In this case, when sampling is performed at the position of the thick broken line shown in FIG. 1, each point filled in black is sampled. FIG. 1 shows the case where the contour direction included in the input image corresponds to the vertical direction of the input image, and the direction perpendicular to the contour direction corresponds to the horizontal direction of the input image. It is not limited to the case.

  FIG. 2 is a diagram illustrating an example of gradation change of an enlarged image obtained by enlarging an input image. Specifically, FIG. 2 shows the gradation change of the enlarged image obtained by enlarging the input image to twice the resolution, and enlargement with each white dot surrounded by a solid line as a pixel. An image is obtained. As an enlargement method, a Bi-Linear method, a Lanczos method, or the like can be employed. FIG. 2 also shows an example of the gradation change of the original image shown in FIG. Referring to FIG. 2, it can be understood that the inclination of the enlarged image is gentler than that of the original image, and blur is likely to occur in an image obtained by enlarging a low-resolution image.

  FIG. 3 is a diagram illustrating an example of a gradation change of an enlarged image after outline enhancement having a general enhancement degree. Specifically, FIG. 3 shows the gradation change of the enlarged image after contour enhancement obtained by performing contour enhancement on the enlarged image. Each white point surrounded by a broken line is represented by a pixel. An enlarged image is obtained. As a contour enhancement method, a method of adding a result obtained by multiplying a secondary differential value of an enlarged image of a target pixel by a predetermined coefficient to the target pixel may be employed.

  FIG. 3 also shows an example of the gradation change of the enlarged image shown in FIG. Referring to FIG. 3, it can be understood that blurring can be eliminated in the enlarged image after contour enhancement because the inclination of the enlarged image after contour enhancement is steeper than that of the enlarged image. It is understood that a shoot or undershoot is likely to occur.

  FIG. 4 is a diagram illustrating an example of a gradation change of an enlarged image after edge enhancement with a very strong enhancement degree. Specifically, FIG. 4 shows the gradation of the magnified image after contour enhancement obtained by performing contour enhancement on the magnified image using a coefficient with a very strong enhancement degree as a coefficient to be multiplied by the secondary differential value. A change is shown, and an enlarged image is obtained in which each white dot surrounded by a broken line is a pixel.

  FIG. 4 also shows an example of gradation change of the enlarged image shown in FIG. Referring to FIG. 4, the slope of the magnified image after edge enhancement with a very strong enhancement level is steeper than the slope of the magnified image after contour enhancement with a general enhancement degree in FIG. It is understood that undershoot is likely to occur and image degradation is likely to increase.

  FIG. 5 shows a result obtained by clipping the enlarged image after the edge enhancement of the extremely strong enhancement level with the minimum value and the maximum value of the pixel values around the target pixel of the enlarged image before the edge enhancement. It is a figure which shows an example of a tone change. Specifically, FIG. 5 shows that an area below a predetermined minimum value is corrected to the minimum value, and an area above a predetermined maximum value is corrected to the maximum value with respect to an enlarged image after contour enhancement with a very strong enhancement level. The gradation obtained as a result of performing the correction processing is shown, and an enlarged image having pixels as white dots surrounded by a broken line is obtained.

  FIG. 5 also shows an example of gradation change of the enlarged image shown in FIG. Referring to FIG. 5, it can be understood that overshoot or undershoot generated in a result obtained by clipping the enlarged image after the edge enhancement with the extremely strong enhancement degree by the minimum value and the maximum value is more easily reduced. However, it is understood that the gradation change tends to be unnatural and image deterioration is likely to occur.

(Image processing apparatus according to an embodiment of the present invention)
FIG. 6 is a diagram illustrating an example of a gradation change of an enlarged image obtained by the image processing apparatus according to the embodiment of the present invention. FIG. 6 also shows an example of gradation change of an enlarged image obtained by enlarging the input image shown in FIG. As shown in FIG. 6, according to the image processing apparatus according to the embodiment of the present invention, the pixels located on the left side of the tilt center among the pixels near the contour are based on the pixels that are farther leftward from the tilt center. Interpolation is done. On the other hand, among the pixels in the vicinity of the contour, a pixel located on the right side of the tilt center is interpolated based on a pixel that is further away from the tilt center in the right direction.

  As can be understood with reference to FIG. 6, according to the image processing apparatus of the embodiment of the present invention, it is possible to improve the degree of elimination of the blur that occurs near the contour while reducing overshoot or undershoot. It becomes. In addition, referring to FIG. 6, according to the image processing apparatus according to the embodiment of the present invention, it is also understood that the gradation change is likely to be natural and the image deterioration is not easily caused.

  Subsequently, a functional configuration example of the image processing apparatus 1 according to the embodiment of the present invention will be described. FIG. 7 is a diagram illustrating an example of a functional configuration of the image processing apparatus 1 according to the embodiment of the present invention. As shown in FIG. 7, the image processing apparatus 1 according to the embodiment of the present invention includes a direction determination unit 12, a tilt determination unit 13, an interpolation coefficient table 14, and an interpolation calculation unit 15. FIG. 8 is a diagram showing a modification of the functional configuration of the image processing apparatus 1 according to the embodiment of the present invention. As shown in FIG. 8, the image processing apparatus 1 further includes a luminance generation unit 11.

  First, as shown in FIG. 7, an input image is input from the outside to the image processing apparatus 1. The format of the input image is not particularly limited. Here, the image processing apparatus 1 uses the luminance information of the input image. For example, when the format of the input image is a format including luminance information (for example, YUV format), the luminance information included in the input image can be used by the image processing apparatus 1, and therefore the example illustrated in FIG. As described above, the image processing apparatus 1 may not include the luminance generation unit 11.

  On the other hand, when the format of the input image is a format that does not include luminance information (for example, RGB format), the image processing apparatus 1 includes the luminance generation unit 11 as illustrated in FIG. The luminance information may be generated from the input image by the unit 11. The method for generating luminance information is not particularly limited. Although there is no particular distinction in the following, for example, when the input image format is RGB, the processing of the direction determination unit 12 and the inclination determination unit 13 is performed separately for each element of Red, Green, and Blue. Alternatively, elements other than luminance may be calculated from the entire elements of Red, Green, and Blue.

  For example, in such a determination, an element having the highest contour or inclination strength among RGB may be used, or brightness instead of luminance, or another element may be calculated and used. Interpolating RGB in different directions may change the color of the original image, so basically all RGB should be interpolated in the same direction. Even when an image is input in the YUV format, the contour or the inclination may be determined based on only Y (luminance), and all elements of YUV may be interpolated in the same direction based on the determination result. In this specification, the case where each element is interpolated in the same direction will be mainly described, but the case where each element is interpolated in different directions is not excluded.

The direction determination unit 12 determines the contour direction in the target pixel included in the input image. The method for determining the contour direction is not particularly limited. Here, an example of the contour direction determination method will be described. FIG. 9A is a diagram for explaining an example of calculating a parameter f (0) used for determining a contour direction from an input image. FIG. 9A shows the pixels A _{0 to} A ₄ , B _{0 to} B ₄ , and C _{0 to} C ₄ of the input image so that the target pixel B ₂ is at the center position.

In the following description, an example in which pixels A _{0 to} A ₄ , B _{0 to} B ₄ , and C _{0 to} C ₄ corresponding to 5 rows and 3 columns are used by the direction determination unit 12 will be described. The range of pixels used by the unit 12 is not limited to such an example. In the following description, there are cases where numerals in the pixel _{(e.g., A 0 ~A 4, B 0 ~B} 4, C 0 ~C 4) is directly used as the luminance of the pixels.

  Here, the direction determination unit 12 can calculate h (0) by Expression (1) and v (0) by Expression (2). Moreover, the direction determination part 12 can calculate f (0) by Formula (3). Note that the calculation method of the parameters h, v, and f shown here is only an example. Therefore, the calculation method of the parameters h, v, and f is not limited to such an example.

FIG. 9B is a diagram for explaining an example in which the parameter f (1) used for determining the contour direction is calculated from a rotated image obtained by rotating the input image 15 degrees clockwise. As illustrated in FIG. 9B, the direction determination unit 12 rotates the pixels A _{0 to} A ₄ , B _{0 to} B ₄ , and C _{0 to} C ₄ of the input image illustrated in FIG. 9A clockwise with the target pixel B ₂ as the center. And rotated 15 degrees to obtain a rotated image. Here, a case where the rotation angle is 15 degrees will be described as an example, but the rotation angle is not particularly limited. The pixel other than the target pixel B ₂ in the rotation image based on the input image (e.g., the Bi-Linear method) may be interpolated pixel.

  Here, the direction determination unit 12 can calculate h (1) by Equation (4) and v (1) by Equation (5). Moreover, the direction determination part 12 can calculate f (1) by Formula (6). Similarly, the direction determination unit 12 rotates the input image 10 times by 15 degrees, and calculates the parameters f (2) to (11) from the respective rotated images. In this way, the input image is rotated until 180 degrees are finished, and the parameter f is calculated from each rotated image.

  The direction determination unit 12 determines a direction obtained by rotating the vertical direction in the input image by the rotation angle when the parameter f is minimum as the contour direction. The direction determination unit 12 may determine the contour direction unconditionally, but may determine the contour direction when other conditions are additionally satisfied. For example, when the parameter f is less than the threshold, the direction determination unit 12 determines the direction rotated by the rotation angle when the parameter f is the minimum as the contour direction as the contour direction. If it is not less than, it may be determined that there is no contour.

  FIG. 10 is a diagram for explaining a direction perpendicular to the contour direction. FIG. 10 shows an example in which the direction in which the vertical direction in the input image is rotated by a rotation angle of 15 degrees when the parameter f is minimum is determined as the contour direction. FIG. 10 shows a direction perpendicular to the contour direction. Here, the inclination determination unit 13 determines, based on the input image, the inclination type in the direction perpendicular to the contour direction at the position near the target pixel in the enlarged image. The method for determining the inclination is not particularly limited.

FIG 10, (which may correspond to the target pixel B ₂ above) of the expanded image vicinity B of the target pixel D, E, F, are shown G is. FIG. 10 also shows adjacent positions A and C in a direction perpendicular to the contour direction with the vicinity position B as a reference. As shown in FIG. 10, the adjacent positions A and C may be positions separated from the neighboring position B in a direction different from that of the input image by one pixel in the direction perpendicular to the contour direction. Further, the pixels at the adjacent positions A and C may be pixels interpolated based on the input image (for example, by the Bi-Linear method).

  For example, the inclination determination unit 13 can determine the inclination type based on the difference in luminance value between the adjacent position A and the adjacent position C and the adjacent position B. If the inclination type is determined in this way, the inclination type can be determined by a simpler method. Hereinafter, an example of the determination of the inclination type will be described. 11A to 11D are diagrams illustrating first to fourth inclination types in a direction perpendicular to the contour direction.

  As illustrated in FIG. 11A, the inclination determination unit 13 determines that the position from the adjacent position C to the vicinity position when the expressions (7) to (9) are satisfied (when the inclination corresponds to the first inclination type). It is determined that the degree of inclination from the adjacent position A to the neighboring position B with respect to the inclination to B is gentle beyond a certain level. On the other hand, as illustrated in FIG. 11B, the inclination determination unit 13 starts from the adjacent position C when the expressions (10) to (12) are satisfied (when the inclination corresponds to the second inclination type). It is determined that the degree of inclination from the adjacent position A to the neighboring position B with respect to the inclination to the neighboring position B exceeds a certain level and is steep.

  As illustrated in FIG. 11C, the inclination determination unit 13 determines that the position from the adjacent position C to the vicinity position when the expressions (13) to (15) are satisfied (when the inclination corresponds to the third inclination type). It is determined that the degree of inclination from the adjacent position A to the neighboring position B with respect to the inclination to B is gentle beyond a certain level. On the other hand, as illustrated in FIG. 11D, the inclination determination unit 13 starts from the adjacent position C when the expressions (16) to (18) are satisfied (when the inclination corresponds to the fourth inclination type). It is determined that the degree of inclination from the adjacent position A to the neighboring position B with respect to the inclination to the neighboring position B exceeds a certain level and is steep.

  In some cases, the inclination determination unit 13 cannot determine the inclination type in the direction perpendicular to the contour direction in the vicinity position B (the inclination determination part 13 determines that the inclination is any of the first to fourth inclination types). It may be determined that it does not apply). Subsequently, the interpolation calculation unit 15 performs an interpolation process on the pixel at the neighboring position B. Here, FIG. 12A is a diagram for explaining an example of interpolation in a case where the slope corresponds to the first slope type or the third slope type.

  For example, the interpolation calculation unit 15 applies to the pixel at the neighboring position B in the enlarged image based on the position in the input image that is a predetermined length H away from the neighboring position B in the direction according to the inclination type in the direction perpendicular to the contour direction. Interpolation processing may be performed. More specifically, when the inclination corresponds to the first inclination type or the third inclination type, the interpolation calculation unit 15 sets a predetermined length in a direction from the neighboring position B to the adjacent position A where the inclination is gentler. Interpolation with respect to the pixel at the neighboring position B may be performed based on the position B ′ in the input image separated by H. By doing so, it is expected that the degree of elimination of blur occurring near the contour is more reliably improved.

  On the other hand, FIG. 12B is a diagram for explaining an example of interpolation when the inclination in the direction perpendicular to the contour direction corresponds to the second inclination type or the fourth inclination type. For example, when the inclination corresponds to the second inclination type or the fourth inclination type, the interpolation calculation unit 15 is separated by a predetermined length H in the direction from the neighboring position B to the adjacent position C where the inclination is gentler. What is necessary is just to interpolate with respect to the pixel of the vicinity position B based on position B 'in an input image. By doing so, it is expected that the degree of elimination of blur occurring near the contour is more reliably improved.

  The predetermined length H is not particularly limited, but may be a length that is greater than or equal to the distance between pixels separated by one pixel in the enlarged image and less than or equal to the distance between pixels separated by two pixels. If the predetermined length H is set to such a length, it is expected that the degree of elimination of blur occurring in the vicinity of the contour is more reliably improved.

  Specifically, the interpolation calculation unit 15 may acquire pixel data corresponding to a position B ′ that is a predetermined length H away from the neighboring position B, and perform interpolation processing based on the acquired pixel data. For example, an interpolation coefficient necessary for interpolation may be acquired from the interpolation coefficient table 14. That is, the interpolation calculation unit 15 may acquire an interpolation coefficient from the interpolation coefficient table 14 and perform an interpolation process based on the acquired interpolation coefficient and pixel data. The interpolation method is not particularly limited, but the Lanczos method may be used as the interpolation method.

  For example, when the Lanczos-2 method is used as the interpolation method, the pixel data referred to in the interpolation may be the pixel value of each pixel having the position B ′ as the center pixel and the distance within two pixels from the center pixel. Further, when the Lanczos-3 method is used as an interpolation method, the pixel data referred to in the interpolation may be the pixel value of each pixel having a position B ′ as the central pixel and a distance within 3 pixels from the central pixel. In such a case, the interpolation calculation unit 15 may perform interpolation based on the result of product-sum calculation between each pixel value and an interpolation coefficient corresponding to each pixel value.

  As described above, there may be a case where the inclination determination unit 13 cannot determine the type of inclination in the direction perpendicular to the contour direction at the vicinity position B (the inclination determination unit 13 uses the first to fourth inclinations). It may be determined that it does not correspond to any of the types). In such a case, the interpolation calculation unit 15 may acquire pixel data corresponding to the neighboring position B and perform interpolation processing based on the acquired pixel data.

  For example, an interpolation coefficient necessary for interpolation may be acquired from the interpolation coefficient table 14. That is, the interpolation calculation unit 15 may acquire an interpolation coefficient from the interpolation coefficient table 14 and perform an interpolation process based on the acquired interpolation coefficient and pixel data.

  As described above, according to the embodiment of the present invention, the image processing apparatus 1 including at least the direction determination unit 12, the inclination determination unit 13, and the interpolation calculation unit 15 is provided. The direction determination unit 12 determines the contour direction in the target pixel included in the input image. Moreover, the inclination determination part 13 determines the inclination classification to the direction perpendicular | vertical to the outline direction in the vicinity position of a target pixel among enlarged images based on an input image. In addition, the interpolation calculation unit 15 performs an interpolation process on the pixel at the neighboring position in the enlarged image based on the position in the input image that is a predetermined length away from the neighboring position in the direction according to the inclination type in the direction perpendicular to the contour direction. Do.

  According to such a configuration, it is possible to improve the degree of elimination of blur occurring near the contour while reducing overshoot or undershoot.

  Further, according to the embodiment of the present invention, the step of determining the contour direction in the target pixel included in the input image, and the inclination type in the direction perpendicular to the contour direction in the vicinity of the target pixel in the enlarged image are input image. And a process of interpolating the pixels at the neighboring position in the enlarged image based on the position in the input image that is a predetermined distance away from the neighboring position in the direction corresponding to the inclination type in the direction perpendicular to the contour direction. Performing an image processing method.

  According to such a method, it is possible to improve the degree of elimination of blur occurring near the contour while reducing overshoot or undershoot.

  The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to such examples. It is obvious that a person having ordinary knowledge in the technical field to which the present invention pertains can come up with various changes or modifications within the scope of the technical idea described in the claims. Of course, it is understood that these also belong to the technical scope of the present invention.

  In the embodiment of the present invention, the operation of the image processing apparatus 1 with respect to the target pixel included in the input image has been described. However, the target pixel that is the target of the operation of the image processing apparatus 1 may be one or a plurality of target pixels. It may be. For example, the operation of the image processing apparatus 1 may be performed on all the pixels included in the input image, or the operation of the image processing apparatus 1 may be performed on a partial area included in the input image.

  A program for causing hardware such as a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory) built in the computer to exhibit functions equivalent to the functions of the image processing apparatus 1 described above. Can also be provided. A computer-readable recording medium in which such a program is recorded can also be provided.

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 11 Luminance generation part 12 Direction determination part 13 Inclination determination part 14 Interpolation coefficient table 15 Interpolation calculation part A Adjacent position B2 (D) Target pixel B Neighbor position C Adjacent position

Claims (7)

A direction determination unit that determines a contour direction in a target pixel included in the input image;
A tilt determination unit that determines a tilt type in a direction perpendicular to the contour direction at a position near the target pixel in the enlarged image based on the input image;
Interpolation for performing interpolation processing on pixels at the neighboring position in the enlarged image based on a position in the input image that is a predetermined length away from the neighboring position in a direction corresponding to the inclination type in a direction perpendicular to the contour direction An arithmetic unit;
An image processing apparatus comprising: The interpolation calculation unit performs the interpolation process based on a position in the input image that is away from the vicinity position by the predetermined length in a direction with a gentler slope.
The image processing apparatus according to claim 1. The interpolation calculation unit obtains pixel data corresponding to a position in the input image that is away from the neighboring position in the direction with a gentler inclination by the predetermined length, and performs the interpolation processing based on the pixel data.
The image processing apparatus according to claim 2. The interpolation calculation unit obtains an interpolation coefficient, and performs the interpolation processing based on the interpolation coefficient and the pixel data.
The image processing apparatus according to claim 3. The predetermined length is not less than the distance between pixels separated by one pixel in the enlarged image and not more than the distance between pixels separated by two pixels.
The image processing apparatus according to claim 1. The inclination determination unit is configured to determine an inclination type based on a difference in luminance value between the first adjacent position and the second adjacent position in a direction perpendicular to the contour direction with respect to the vicinity position and the vicinity position. Determine
The image processing apparatus according to claim 1. Determining a contour direction in a target pixel included in the input image;
Determining an inclination type in a direction perpendicular to the contour direction at a position near the target pixel in the enlarged image based on the input image;
A step of performing an interpolation process on the pixel at the neighboring position in the enlarged image based on a position in the input image that is a predetermined distance away from the neighboring position in a direction corresponding to the inclination type in a direction perpendicular to the contour direction. When,
Including an image processing method.

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