JP2000076430A - Image data interpolating device, its method, and medium having recorded image data interpolating program thereon - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image data interpolating device, its method and a medium recording image data interpolating program capable of obtaining an optimal interpolating result with respect to an optional interpolating magnification. SOLUTION: In a computer system provided with a scanner, etc., as an image inputting device and with a color printer, etc., as an image outputting device, a printer driver inputs original image data at a step 202, inputs the size of interpolating image data at a step 204, and executes interpolating processing by the three cubic methods of steps 210 to 214 according to the interpolation magnification while obtaining the interpolating magnification at a step 208. These interpolation are different in an influence degree to sharpness and become sharper with the reduction of interpolating magnification to avoid generation of jaggedness in the case of large interpolating magnification and to sharpen an image in the case of small interpolating magnification. Thus, an optimal interpolating result according to interpolating magnification can be obtained extremely easily.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image data interpolation device, an image data interpolation method, an image data interpolation program recording medium, and an image output device for interpolating image data composed of dot matrix pixels at a predetermined magnification.

[0002]

2. Description of the Related Art When handling images on a computer or the like,
An image is represented by pixels in a dot matrix, and each pixel is represented by a gradation value. For example, photographs and computer graphics are often displayed on a computer screen with 640 dots in the horizontal direction and 480 dots in the vertical direction.

On the other hand, the performance of a color printer has been remarkably improved, and its dot density is extremely high, such as 720 dpi. In this case, when an image of 640 × 480 dots is printed in correspondence with each dot, the size becomes extremely small. In this case, since the gradation value is different and the meaning of the resolution itself is different, it is necessary to convert between dots to print data by interpolating between dots. Conventionally, as a method of interpolating dots in such a case, a nearest neighbor interpolation method (hereinafter, referred to as a nearest neighbor method) or a third-order convolution interpolation method (a cubic convolution interpolation: A technique such as the cubic method is known. Also, JP-A-6-2
Japanese Patent No. 25140 discloses a technique in which a dot pattern is prepared in advance so as to have an enlarged form in which the edge is smoothed when smoothing the edge when the dots are interpolated.

[0004]

The conventional interpolation technique described above has the following problems. Various methods, such as the near-list method and the cubic method, have their own advantages and disadvantages, but it is difficult for the user to select it considering the relationship with the interpolation magnification, and it is said that it is fixed to either one. Then, there is a possibility that the quality of the interpolation result for an image which is not good may be degraded. In addition, although the cubic method is suitable when image quality is emphasized, there have been requests for further improvement in image quality.

In the invention disclosed in Japanese Patent Application Laid-Open No. 6-225140, the interpolation magnification must be fixed because a pattern is prepared in advance, and it is not possible to cope with an arbitrary interpolation magnification. Further, assuming a color image, the number of patterns becomes enormous, and it is difficult to prepare them in advance. The present invention has been made in view of the above problems, and has an image data interpolating apparatus, an image data interpolating method, and a medium in which an image data interpolating program capable of obtaining an optimal interpolation result for an arbitrary interpolation magnification. For the purpose of providing.

[0006]

According to a first aspect of the present invention, there is provided an image data acquiring means for acquiring image data in which an image is represented by pixels in a dot matrix, and a configuration in the image data. A pixel interpolation unit that can be selected and executed from a plurality of interpolation processes having different degrees of influence on the sharpness of an image when performing an interpolation process for increasing the number of pixels, and an interpolation magnification for acquiring the interpolation magnification for the image data Acquiring means for selecting the interpolation processing based on the interpolation magnification acquired by the interpolation magnification acquisition means, and selecting the interpolation processing in which the image becomes sharper as the interpolation magnification is smaller, and causing the pixel interpolation means to execute the interpolation processing And an interpolation processing selecting means.

In the invention according to claim 1 configured as described above, when performing an interpolation process for increasing the number of constituent pixels of image data in which an image is represented by pixels in a dot matrix at a predetermined magnification, the pixel interpolating means includes: Can be selected from a plurality of interpolation processes having different degrees of influence on sharpness, and when the image data acquisition unit acquires the target image data, the interpolation magnification acquisition unit The interpolation magnification is obtained, and the interpolation processing selecting means selects the interpolation processing in which the smaller the interpolation magnification is, the sharper the image becomes when selecting the interpolation processing based on the interpolation magnification obtained by the interpolation magnification obtaining means. The above-mentioned pixel interpolation means.

When interpolating and enlarging a dot-matrix image, interpolation processing may result in smooth continuation or a step. The sharpness is jagged when trying to emphasize it, and the blur is blurred when trying to weaken it. This selection is difficult unless a skilled operator is used, but if the magnification is not large, the jaggy is not noticeable because the number of pixels to be interpolated is small even if sharpness is emphasized, resulting in sharpness. It's convenient because it doesn't look blurry. However, when the magnification is large, if sharpness is emphasized, it will appear as a jaggy, which is inconvenient. Therefore, an optimum interpolation process is selected according to the magnitude of the enlargement magnification or the interpolation magnification.

The image data represents the image by dot matrix pixels. Any image data may be used as long as it is represented by data for each pixel. The image data may be a color image.
It may be a monochrome image. Further, the gradation value may be of two gradations or of multiple gradations.
Here, the image data obtaining means is for obtaining such image data, and is such that the pixel interpolating means holds the target image data when performing the interpolation processing for increasing the number of constituent pixels. Good. Therefore, the acquisition method is not particularly limited, and various methods can be adopted. For example, the information may be obtained from an external device via an interface, or may be an image capturing device provided with an image capturing unit. Alternatively, a computer graphic application may be executed to perform input from a mouse or a keyboard.

The interpolation processing for sharpening is executed when the interpolation magnification is small, but it is sufficient if the relative relationship between the two is recognized. That is, it is not necessary to be able to execute optimal interpolation processing for each interpolation magnification. There are two types of interpolation processing, and the interpolation magnification is selected according to the magnitude of comparison with a predetermined threshold value. May be. Also,
It is sufficient that the sharpness is substantially different in the interpolation processing result, and it is not necessary that all options be independent interpolation methods. As an example, the invention according to claim 2
2. The image data interpolating apparatus according to claim 1, wherein the pixel interpolating means can execute a plurality of interpolation processes having different degrees of influence on the sharpness of the image by changing a parameter in a higher-order interpolation operation for generating an interpolation function. It is configured in.

In the invention according to claim 2 configured as described above, the pixel interpolating means executes a higher-order interpolation operation to generate an interpolation function. Changes the degree of influence on sharpness. For example, when a pixel value changes linearly in interpolating a pixel between two grids, the image becomes blurred, but becomes sharp when a so-called S-shaped curve is formed. In the higher-order interpolation calculation, it is easy to change such a shape depending on parameters, and an interpolation function for obtaining a desired interpolation result is generated by changing the slope of the S-shaped curve or adjusting the amount of undershoot or overshoot as appropriate. Thus, a plurality of interpolation processes having different degrees of influence on sharpness can be executed.

When changing the parameters of the higher-order interpolation calculation, it is not always possible to set the parameters corresponding to an arbitrary interpolation magnification, and there may be a case where only the parameters corresponding to the discrete interpolation magnifications can be set. In this case, it seems that the interpolation magnification of the interpolable function that can be generated must be fixed, but it is possible to obtain an interpolation function with an arbitrary interpolation magnification even if the parameters are fixed. .
As an example, the invention according to claim 4 is based on claims 1 to
4. The image data interpolating apparatus according to claim 3, wherein said pixel interpolating means corresponds to a fixed interpolation magnification and said parameter is based on each parameter when realizing a desired interpolation magnification. It is configured to generate an interpolation function corresponding to an arbitrary interpolation magnification by weighting and adding the operation results of the functions.

In the invention according to claim 4 configured as described above, even if the original interpolation function corresponds to the fixed interpolation magnification, the calculation result of the interpolation function based on each parameter is weighted and added. As a result, an interpolation function corresponding to an arbitrary interpolation magnification is generated. For example, even if the interpolation function corresponds only to the case of 2 times and 3 times, by taking the average of both, a 2.5 times interpolation function can be generated.

Although the interpolation magnification may be arbitrarily arbitrary, the magnification itself is often fixed. Although not necessarily limited to a fixed case, if the image data linearly reflects the interpolation operation result as in the case of higher-order interpolation operation processing, a relative relationship at a predetermined lattice position is obtained. Need and the results are naturally available at other grid locations. For this reason, the invention according to claim 4 is the image data interpolation device according to any one of claims 1 to 3, wherein the pixel interpolating means corresponds to each predetermined grid position in an existing grid section. In this configuration, the coefficient values of the interpolation calculation to be performed are stored in a table, and the interpolation processing is executed.

In the invention according to claim 4 configured as described above, the coefficient values of the interpolation calculation corresponding to each of the predetermined grid positions in the existing grid section are stored in a table, so that the interpolation processing is performed. When performing the above, by referring to the coefficient value at each grid position, every calculation processing becomes unnecessary, and it can be realized by linear superposition processing on the data of the original image. According to a fifth aspect of the present invention, in the image data interpolating apparatus according to any one of the first to fourth aspects, the interpolation magnification obtaining unit is configured to execute the processing when the image data obtaining unit obtains the image data. It is configured to acquire the specified magnification.

In the invention according to claim 5 configured as described above, in a situation where the interpolation magnification is designated as the image data acquiring means acquires the image data, the interpolation magnification acquiring means is designated. To obtain the same magnification. That is, when the interpolation magnification itself is designated, the magnification is used. On the other hand, the interpolation magnification may not always be specified, and as an example, the invention according to claim 6 provides the image data interpolation apparatus according to any one of claims 1 to 5, The means is configured to acquire a magnification based on a ratio between the image data acquired by the image data acquiring means and the size of the image data to be interpolated.

In the sixth aspect of the present invention, when the size of the image data to be interpolated is obtained instead of specifying the interpolation magnification, the size of the image data to be interpolated is obtained. Then, the ratio between the size of the image data after interpolation and the size of the image data after interpolation is calculated to obtain the magnification. This is because, when information such as an image size after interpolation is notified as information necessary for interpolation, the interpolation magnification can be calculated if the ratio to the image size of the interpolation source is known.

As described above, the method of selecting the interpolation processing according to the interpolation magnification is not necessarily limited to a substantial device, and it can be easily understood that the method also functions as the method. For this reason, an interpolation processing method for increasing the number of constituent pixels at a predetermined interpolation magnification for image data representing an image by dot matrix pixels, wherein the step of acquiring the image data and the step of acquiring the image data The step of acquiring the interpolation magnification, and based on the acquired interpolation magnification, assuming a plurality of interpolation processings having different degrees of influence on the sharpness of the image when performing the interpolation processing to increase the number of constituent pixels in the image data. The configuration includes a step of selecting an interpolation process in which an image becomes sharper as the interpolation magnification is smaller, and a step of increasing the number of constituent pixels in the image data by the selected interpolation process.

That is, there is no difference in that the present invention is not necessarily limited to a substantial device but is also effective as a method. By the way, such an image data interpolation device may exist alone or may be used in a state of being incorporated in a certain device, and the idea of the invention is not limited to this, but includes various aspects. It is a thing. Therefore, if it is software or hardware,
Can be changed. When the software of the image data interpolating device is realized as an example of realizing the idea of the invention, it naturally exists on a recording medium on which such software is recorded, and it cannot be said that the software is used.

As an example, the invention according to claim 8 is an interpolation process in which a computer executes interpolation processing so as to increase the number of constituent pixels at a predetermined interpolation magnification with respect to image data representing an image by dot matrix pixels. A medium on which a program is recorded, wherein the step of obtaining the image data, the step of obtaining the interpolation magnification for the obtained image data, and the step of performing an interpolation process for increasing the number of constituent pixels in the image data Presuming a plurality of interpolation processes having different degrees of influence on the sharpness of the image, based on the obtained interpolation ratio, selecting an interpolation process in which the image becomes sharper as the interpolation ratio becomes smaller, and the selected interpolation process And increasing the number of constituent pixels in the image data.

Of course, the recording medium may be a magnetic recording medium, a magneto-optical recording medium, or any recording medium to be developed in the future. Also, the duplication stages of the primary duplicated product, the secondary duplicated product, and the like are equivalent without any question. In addition, the present invention is not limited to the case where the present invention is used even when the supply is performed using a communication line. further,
The concept of the present invention is not completely different even when part is software and part is realized by hardware, and part is stored on a recording medium and read as needed as needed. Such a form may be adopted.

[0022]

As described above, according to the present invention, the interpolation processing is switched in accordance with the interpolation magnification. Therefore, it is possible to provide an image data interpolation apparatus capable of obtaining an optimum interpolation result extremely easily. it can. In particular, when the interpolation magnification is small, the image quality can be improved in the sense that the image does not become jaggy and sharp.
Further, according to the second aspect of the present invention, it is possible to execute the optimal interpolation processing by a simple processing of only changing the parameters.

Further, according to the third aspect of the present invention,
When using parameters, an arbitrary interpolation magnification can be easily obtained. Furthermore, according to the invention according to claim 4, it is possible to execute a part of the calculation on the grid points scheduled in advance, and it is possible to improve the calculation speed in the case of the actual processing. Further, according to the fifth aspect of the present invention, the designated interpolation magnification is acquired, so that the processing is facilitated.

Further, according to the invention according to claim 6,
Even if the interpolation magnification is not specified, the interpolation magnification can be easily obtained based on the size of the image data before and after the interpolation. Further, according to the invention according to claim 7, it is possible to provide an image data interpolation method capable of achieving the same effect, and according to the invention according to claim 8, a medium storing an image data interpolation program Can be provided.

[0025]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 shows an image data interpolation apparatus according to an embodiment of the present invention by a claim correspondence diagram, and FIG. 2 shows a computer system 10 as an example of hardware for realizing the image data interpolation apparatus by a block diagram. I have. First, the computer system 10 will be described.

The computer system 10 includes a scanner 11a, a digital still camera 11b, and a video camera 11c as image input devices for directly inputting image data, and is connected to the computer main body 12. Each input device is capable of generating image data expressing an image by dot matrix pixels and outputting the image data to the computer main unit 12. Here, the image data is displayed in 256 gradations in three primary colors of RGB. , About 16.7 million colors can be expressed.

The computer main body 12 is connected to a floppy disk drive 13a, a hard disk 13b, and a CD-ROM drive 13c as external auxiliary storage devices, and the hard disk 13b stores main system-related programs. Necessary programs and the like can be read from a floppy disk or a CD-ROM as needed. The computer body 1
A modem 14a is connected as a communication device for connecting 2 to an external network or the like. The modem 14a is connected to the external network via the public communication line, and software and data can be downloaded and introduced.
In this example, the modem 14a accesses the outside through a telephone line. However, a configuration in which a network is accessed through a LAN adapter is also possible. In addition, a keyboard 15a for operating the computer main body 12 and a mouse 15b as a pointing device are also connected.

Further, a display 17a and a color printer 17b are provided as image output devices.
The display 17a has a display area of 800 pixels in the horizontal direction and 600 pixels in the vertical direction, and can display the above-mentioned 16.7 million colors for each pixel. Of course, this resolution is only an example, 640x48
0 pixels or 1024 x 768 pixels
It can be changed as appropriate.

The color printer 17b is an ink jet printer, and is capable of printing an image with dots on printing paper as a recording medium using four color inks of CMYK. The image density can be printed at a high density such as 360 × 360 DPI or 720 × 720 DPI, but the gradation table is expressed in two gradations such as whether or not to apply color ink. On the other hand, a predetermined program is executed in the computer main body 12 in order to display or output an image output device while inputting an image using such an image input device.
Among them, an operating system (OS) 12a is operating as a basic program, and the operating system 12a has a display driver (DSP DR) for performing display on the display 17a.
V) 12b and a printer driver (PRT DRV) 12c for causing the color printer 17b to perform print output are incorporated. These drivers 12b and 12c depend on the model of the display 17a and the color printer 17b, and can be additionally changed to the operating system 12a according to each model. Further, depending on the model, additional functions beyond the standard processing can be realized. That is, it is possible to realize various additional processes within an allowable range while maintaining a common processing system on the standard system of the operating system 12a.

The application 12d is executed on the operating system 12a as the basic program. The processing contents of the application 12d are various, and include a keyboard 15a and a mouse 1 as operation devices.
5b is monitored, and when it is operated, various external devices are appropriately controlled to execute corresponding arithmetic processing and the like. Further, the processing result is displayed on the display 17a,
For example, the data is output to the color printer 17b.

In the computer system 10, image data is acquired by a scanner 11a or the like which is an image input device, a predetermined image process is executed by an application 12d, and then output to a display 17a or a color printer 17b as an image output device. It is possible to In this case, focusing on the correspondence between pixels, if the pixel density of the color printer 17b and the pixel density of the scanner 11a match, the size of the scanned original image matches the size of the printed image.
If there is a difference between the two, the size of the image will be different.
In many cases, the pixel density of the scanner 11a is similar to the pixel density of the color printer 17b. However, the pixel density of the color printer 17b whose pixel density is improved for higher image quality is higher than that of a general image input device. It is often higher than the pixel density. In particular, the display 17a
The display density is higher in each stage as compared with the display density, and if the display on the display 17a is made to correspond to each pixel and printed, an extremely small image may result.

Therefore, the operating system 12
Resolution conversion is performed in order to eliminate the difference in the actual pixel density of each device while determining the reference pixel density in a. For example, if the resolution of the display 17a is 72D
When it is assumed to be a PI, the operating system 1
If 2D is based on 360 DPI, the display driver 12b performs resolution conversion between the two. In a similar situation, the resolution of the color printer 17b is 72
If it is 0 DPI, the printer driver 12c performs resolution conversion.

In the above, the process of acquiring image data from an image input device or the like constitutes the image data acquiring means A1 shown in FIG. 1, and the hardware and software related to this actually correspond. In addition, resolution conversion corresponds to interpolation processing because it corresponds to processing for increasing the number of constituent pixels in image data, and the display driver 12b and the printer driver 12c perform interpolation processing as one of the functions. Here, the display driver 12b and the printer driver 12c execute not only the pixel interpolation means A2 but also the interpolation magnification acquisition means A3 and the interpolation processing selection means A4 as described below, and the interpolation becomes sharper as the interpolation magnification becomes smaller. The image quality is improved by the processing. The display driver 12b and the printer driver 12c are stored in the hard disk 13b, and are read and operated by the computer main body 12 at the time of startup. Also, at the time of introduction, it is recorded and installed on a medium such as a CD-ROM or a floppy disk. Therefore, these media constitute a medium on which the image data interpolation program is recorded.

In the present embodiment, the image data interpolation device is realized as the computer system 10,
Such a computer system is not necessarily required, and any system that requires interpolation processing for similar image data may be used. For example, as shown in FIG. 3, a digital still camera 11b1 incorporates an image data interpolating device for performing an interpolation process, and displays the image data on the display 17a1 using the interpolated image data.
7b1 may be used. As shown in FIG. 4, in a color printer 17b2 that inputs and prints image data without going through a computer system, image data input via a scanner 11a2, a digital still camera 11b2, a modem 14a2, or the like is automatically processed. It is also possible to configure so as to perform resolution conversion and print processing. In recent years, such a printer 17b2 is often used as a video printer for connecting to a home television or a video to make a hard copy of one scene, and obtains resolution while acquiring image data from a removable recording medium. An optimal interpolation process may be performed in the conversion.

In addition, a color facsimile machine 18a as shown in FIG. 5 and a color copier 1 as shown in FIG.
It is naturally applicable to various devices that handle image data such as 8b. FIGS. 7 and 8 show a software flow relating to the resolution conversion executed by the printer driver 12c described above. Here, the former shows a general-purpose flow, and the latter shows a specific flow of the present embodiment.

In step 102, the original image data is input. When an image is read from the scanner 11a by the application 12d and subjected to predetermined image processing and then subjected to print processing, print data of a predetermined resolution is transferred to the printer driver 12c via the operating system 12a. Applicable. Of course, the image may be read by the scanner 11a, and in any case, the process corresponds to the image data acquisition unit A1.

Step 104 is a process for obtaining an interpolation magnification for the read image data. Details of the interpolation magnification obtaining process will be described later. In step 108, an interpolation process optimal for the image data is selected in accordance with the obtained interpolation magnification, and any one of the interpolation processes 1 to N in steps 110, 112, and 114 is executed.
These interpolation processes 1 to N have different degrees of influence on the sharpness of the image corresponding to the interpolation magnification. In this example, the sharpness is most emphasized in the interpolation process 1 selected when the interpolation magnification is small. Then, in the interpolation processing N selected when the interpolation magnification is large, the sharpness enhancement is the weakest. Of course, steps 110 and 1
Each of the interpolation processes 1 to N shown in 12 and 114 specifically constitutes the image interpolation means A2, and the step 108 selects the interpolation processing based on the interpolation magnification, so that the interpolation processing selection means A4 is formed. become.

When the interpolation processing is completed, step 1 is executed.
In step 20, the interpolated image data is output. In the case of the printer driver 12c, print data cannot be obtained only by resolution conversion, but requires color conversion or halftone processing. Therefore, outputting the image data here means transferring the data to the next stage. Next, more specific processing for the above-described general-purpose flow will be described. Step 20
In step 2, original image data is input as in step 102, and in step 204, an interpolated image data size is input to obtain an interpolation magnification.

The reason for inputting the interpolated image data size is to acquire the interpolation magnification corresponding to step 104 described above. Here, the interpolation magnification acquisition means will be described. FIG. 9 shows an example in which the printer driver 12c acquires an interpolation magnification based on information obtained from the operating system 12a. As a first example, the operating system 12a directly operates the printer driver 12c.
In some cases, the interpolation magnification may be specified. In this case, the interpolation magnification is used. As a second example, there is a case where the operating system 12a specifies the size of an image to be printed in pixel units or the like. In this case, the interpolation magnification is calculated based on the magnitude. For example, if the vertical and horizontal dimensions of the original image data are Ws × Hs pixels and the vertical and horizontal dimensions of the interpolated image data are Wd × Hd pixels, the interpolation magnification is Wd / Ws (Hd / Hs) on the assumption that the aspect ratio is not changed.

As a third example, there is a case where a resolution managed by the operating system 12a is specified. In this case, the printer driver 12c calculates the ratio based on the resolution of the color printer, and obtains the interpolation magnification. For example, if the resolution managed by the operating system 12a is 360 DPI and the resolution of the color printer is 720 DPI, the interpolation magnification is twice. In the present embodiment, it is assumed that the interpolation magnification is obtained based on the second example among these, and as described above, step 204 is performed.
Then, input the interpolation image data size.

As described above, when the interpolation image data size is input in step 204, the interpolation magnification Wd / Ws is calculated in step 208 based on the ratio with the size of the original image data input in step 202. Step 2
In any one of Steps 10 to 214, an appropriate bicubic interpolation process is executed. Here, the interpolation processing method of the cubic method will be described. As shown in FIG. 10, the cubic method uses data of a total of 16 grid points including not only four grid points surrounding a point Puv to be interpolated but also grid points around one point. A general expression using a cubic convolution function is as follows.

[0042]

(Equation 1) Becomes Expanding this on P,

[0043]

(Equation 2) Becomes In addition,

[0044]

(Equation 3) Can be replaced with

In the cubic method, the distance gradually changes from one grid point to the other grid point.
The characteristic is that the degree of the change becomes a so-called cubic function. According to the cubic method, the quality of the interpolation result can be influenced by adjusting the shape of the curve as long as it can be expressed as a cubic function. While the original cubic method described above is referred to as a third cubic method, as an example of the adjustment,

[0046]

(Equation 4) Is called the second cubic method.

[0047]

(Equation 5) Is referred to as a first cubic method.

The cubic interpolation processing is characterized in that the change state is a cubic function, and is common in that the change gradually changes from one grid point to the other grid point. However, there is a large difference in the sense given by the image constituted by the interpolated pixels due to the change shape. FIG. 11 is a diagram illustrating an interpolation function in a two-dimensional manner in order to make it easier to understand the difference between the interpolation results in the first cubic method to the third cubic method. In the figure, the horizontal axis indicates the position (coordinate), and the vertical axis indicates the interpolation function.
Grid points exist at positions of t = 0, t = 1, and t = 2, and interpolation points are at positions of t = 0 to 1. For each cubic method, there is a difference in the steepness of the curve in the cubic function, which affects the sharpness of the entire image.

FIGS. 12 to 17 show specific examples when interpolation is performed by the first to third cubic methods. To facilitate understanding, a model in which there is no change in data in the vertical direction and an edge occurs in the horizontal direction will be described. Here, FIGS. 12 and 13 are specific examples of the first cubic method, and the interpolation point is one point (Pn1) because the interpolation magnification is twice. FIGS. 14 and 15 show a specific example of the second cubic method. Since the interpolation magnification is three, the interpolation points are two (Pn1, Pn2). 16 and 17 show a specific example of the third cubic method. Since the interpolation magnification is four times, the interpolation point is three.
Point (Pn1, Pn2, Pn3).

The specific numerical values in these specific examples will be described with reference to FIG. The gradation value of the pixel before interpolation is indicated as “Original”, and four pixels (P0, P1, P2, P3) having a gradation value of “64” are arranged, and a pixel (P4) having a gradation value of “128” is arranged. (P5, P6, P7, P8, P9)
Are lined up. In this case, the edge has the gradation value “12”.
8 ".

Here, three pixels (Pn1, Pn) are located between each pixel.
n2, Pn3), the distance between the interpolated pixels is “0.25”, and the above-described x1 to x4
Is the value in the middle column of the table for each interpolation point. f (x1) to f (x4) are also uniquely calculated corresponding to x1 to x4. For example, x1, x2, x3, and x4 are "1.25" and "0.25", respectively. , "0.75",
When “1.75” is obtained, f (t) corresponding thereto is approximately “−0.14” and “0.8” as shown in Expression 3.
9 "," 0.30 ", and" -0.05 ". Also, x
1, x2, x3, and x4 are “1.50”,
When “0.50”, “0.50”, and “1.50” are obtained, f (t) corresponding thereto is “−0.12”.
5 "," 0.625 "," 0.625 "," -0.12 "
5 ". Also, x1, x2, x3, and x4 are “1.75”, “0.75”, “0.25”, and “1.
25 ", the f (t) corresponding thereto is:
In general, "-0.05", "0.30", "0.89",
It becomes "-0.14".

The result of calculating the gradation value of the interpolation point using the above result is shown in the right-hand column of FIG.
In the graph. The meaning of this graph will be described later in detail.

Of course, the same is true for the first cubic method and the second cubic method, and the interpolation points x1 to x
4 and f (x1) to f (x4) corresponding thereto are calculated based on Expressions 4 and 5, and finally an interpolation operation result is obtained.

Before comparing FIG. 13, FIG. 15, and FIG. 17 showing the results of the interpolation calculation in graph form, the characteristic amount of such an S-shaped curve will be described with reference to FIG.
Assuming that a change in an image is considered as a monochrome model of only a change in luminance, a solid line shown in FIG. 18 indicates an edge portion where a luminance difference continuously occurs. If the luminance changes gently at the edge, the image will be blurred. Therefore, when the edge portion is enlarged by interpolation, if the image is enlarged gently, the blurred feeling will be emphasized in the actual image by the enlarged amount. However, as shown by the diagonal lines in FIG. 18, the inclination angle of the edge portion becomes steep, and overshoot and undershoot occur before and after the edge portion. Since the rate of change also increases, the image becomes sharper.

Looking at such feature values for the first cubic method in FIG. 13, the second cubic method in FIG. 15, and the third cubic method in FIG. It is the steepest, and the angle becomes gentler as it changes to the second cubic method and the third cubic method. Also, the absolute amount of overshoot and undershoot is largest in the case of the first cubic method, and the absolute amount decreases as the method changes to the second cubic method and the third cubic method. Such a difference in the feature amounts means that the sharpness enhancement degree is the largest in the first cubic method and the smallest enhancement degree in the third cubic method.

In step 208, the interpolation magnification Wd / W
When s is calculated, if the magnification is not more than 2 times, the interpolation calculation processing by the first cubic method is executed in step 210. This is an interpolation processing in which the degree of sharpness enhancement is large when the interpolation magnification is small. Is equivalent to executing
If the magnification is 4 times or more, the third
The interpolation calculation processing by the cubic method is executed. If the magnification is three times, the interpolation calculation processing by the second cubic method is executed in step 212. That is, this corresponds to executing an interpolation process in which the degree of sharpness is reduced as the interpolation magnification is increased.

The difference in the selection of the interpolation calculation processing is as follows.
The smaller the interpolation magnification, the sharper the image becomes,
The larger the interpolation magnification, the less sharpness is emphasized. Originally, if the sharpness was emphasized too much when the interpolation magnification was large, jaggies would increase, but by associating the interpolation magnification with the interpolation calculation processing as described above, such jaggies would hardly appear, When the interpolation magnification, at which jaggies are relatively unlikely to appear, is low, the sharpness can be enhanced to prevent the image from being blurred while being enlarged.

In FIGS. 12, 14 and 16, f (x
Referring to 1) to f (x4), since the coordinate position of the interpolation point is determined based on the interpolation magnification, the calculated value of the interpolation function at each interpolation magnification is constant. Therefore, the calculation of the interpolation function is performed in advance for each interpolation point corresponding to the interpolation magnification, and the calculation result is stored as a table. By doing so, steps 210 to 210
It is only necessary to refer to the table in the actual processing scene in step 214.

When a table is used in this way, it is impossible to specify what the original interpolation formula is. Conversely, an inclination angle, an overshoot, and an undershoot may be determined for an S-shaped curve as shown in FIG. 18 and a table value for realizing the same may be prepared. Of course, when a cubic convolution function is assumed, consistency in the range of 0 <t <1 and the range of 1 <t <2 is required in the interpolation function shown in FIG. 3 as high-order interpolation operation
This is because the following convolution function is assumed, and it is possible to apply a plurality of interpolation calculations having different degrees of influence on sharpness by specifying the inclination angle, overshoot, and undershoot described above and forming a table without any problem. . In this case, the S-shaped curve and the presence of the overshoot and the undershoot are not essential requirements, and it is possible even if only the inclination angle is steep and there is no overshoot or undershoot. On the other hand, it is not necessary to gradually reduce the degree of sharpness enhancement when the interpolation magnification increases. It suffices that the relationship is such that the smaller the interpolation magnification in relative terms, the greater the degree of sharpness enhancement.

In the above example, three interpolation calculations are used, but only the parameters of the third-order convolution function are actually changed. However, it cannot be said that such a parameter can be easily set according to an arbitrary interpolation magnification, so that the interpolation magnification may be fixed by itself. That is, when the S-shaped curve shown in FIG. 18 is used as a reference, it is easy to obtain a weighted addition result by taking an average of a plurality of interpolation results obtained based on the respective interpolation magnifications.

For example, the interpolation result of “2.5” times is “2”.
It is also possible to obtain the average value of the doubled interpolation result and the “3” times interpolation result. Of course, if it is desired to obtain an interpolation result of "2.3" times, the interpolation result of "2" times and the interpolation result of "3" times should be weighted and added at a ratio of 7: 3. FIG. 19 schematically shows a graph in a case where the result of the interpolation operation of "2.3" times is obtained by equally weighting and adding the result of the double operation and the result of the triple operation in this manner. .

After all the new coordinate values have been interpolated by one of the interpolation processes in steps 210 to 214 based on the judgment in step 208, the interpolated image data is transferred to the next stage in step 216. However, the data amount of the interpolated image data may be extremely large depending on the interpolation magnification, and the memory area available for the printer driver 12c may not be so large in the first place. In such a case, the data may be output separately for each fixed data amount.

As described above, in the computer system 10 having the scanner 11a and the like as the image input device and the color printer 17b and the like as the image output device, the printer driver 12c inputs the original image data in the step 202, and proceeds to the step 204. By inputting the size of the interpolated image data, the interpolation processing is executed by the three cubic methods of steps 210 to 214 according to the interpolation magnification while obtaining the interpolation magnification in step 208. The degree of influence on the image is different, and the smaller the interpolation magnification is, the sharper the image becomes.If the interpolation magnification is large, no jaggies occur, and if the interpolation magnification is small, the image can be sharpened. Optimal interpolation result according to interpolation magnification It can be easily obtained Te fit.

[Brief description of the drawings]

FIG. 1 is a diagram corresponding to claims of an image data interpolation device according to an embodiment of the present invention.

FIG. 2 is a block diagram of specific hardware of the image data interpolation device.

FIG. 3 is a schematic block diagram showing another application example of the image data interpolation device of the present invention.

FIG. 4 is a schematic block diagram showing another application example of the image data interpolation device of the present invention.

FIG. 5 is a schematic block diagram showing another application example of the image data interpolation device of the present invention.

FIG. 6 is a schematic block diagram showing another application example of the image data interpolation device of the present invention.

FIG. 7 is a general-purpose flowchart in the image data interpolation device of the present invention.

FIG. 8 is a more specific flowchart in the image data interpolation device of the present invention.

FIG. 9 is a diagram illustrating a situation where an interpolation magnification is designated from an operating system to a printer driver.

FIG. 10 is a conceptual diagram of the cubic method.

FIG. 11 is a diagram showing a change state of an interpolation function.

FIG. 12 is a diagram showing, in the form of a table, an interpolation calculation process in the first cubic method.

FIG. 13 is a diagram showing, in the form of a graph, an interpolation operation process in the first cubic method.

FIG. 14 is a diagram showing, in the form of a table, an interpolation calculation process in the second cubic method.

FIG. 15 is a diagram showing, in the form of a graph, an interpolation operation process in the second cubic method.

FIG. 16 is a diagram showing, in the form of a table, an interpolation calculation process in the third cubic method.

FIG. 17 is a diagram showing, in the form of a graph, an interpolation operation process in the third cubic method.

FIG. 18 is a diagram illustrating a characteristic amount of an S-shaped curve related to an interpolation calculation.

FIG. 19 is a diagram showing an interpolation operation result of an arbitrary magnification by weighted addition from an interpolation operation result of a fixed interpolation magnification.

[Explanation of symbols]

 10 Computer system 11a Scanner 11a2 Scanner 11b Digital still camera 11b1 Digital still camera 11b2 Digital still camera 11c Video camera 12 Computer body 12a Operating system 12b Display driver 12b Driver 12c Printer driver 12d Application 13a Floppy disk drive 13b Hard disk 13c CD-ROM drive 14a Modem 14a2 Modem 15a Keyboard 15b Mouse 17a Display 17a1 Display 17b Color printer 17b1 Color printer 17b2 Color printer 18a Color facsimile machine 18b: color copy machine

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 5B056 AA08 BB26 BB55 HH03 5B057 AA01 AA11 CA01 CA02 CA06 CA08 CA16 CB01 CB02 CB06 CB08 CB12 CB16 CC01 CD06 CE03

Claims (8)

[Claims] 1. An image data acquiring means for acquiring image data expressing an image by dot matrix pixels, and a degree of influence on the sharpness of the image when performing an interpolation process for increasing the number of constituent pixels in the image data. A pixel interpolation unit that can be selected and executed from among a plurality of interpolation processes; an interpolation magnification acquisition unit that acquires the interpolation magnification for the image data; and an interpolation magnification acquisition unit that acquires the interpolation magnification based on the interpolation magnification acquired by the interpolation magnification acquisition unit. An image data interpolation apparatus comprising: an interpolation processing selection unit that selects an interpolation process in which an image becomes sharper as the interpolation magnification becomes smaller when the interpolation process is selected, and causes the pixel interpolation unit to execute the interpolation process. 2. The image data interpolating apparatus according to claim 1, wherein said pixel interpolating means changes a parameter in a higher-order interpolation operation for generating an interpolation function and has a different degree of influence on image sharpness. An image data interpolating apparatus capable of executing the interpolation processing of (1). 3. The image data interpolating apparatus according to claim 2, wherein said pixel interpolating means corresponds to a fixed interpolation magnification and said parameter corresponds to each parameter for realizing a desired interpolation magnification. An image data interpolating apparatus for generating an interpolation function corresponding to an arbitrary interpolation magnification by weighting and adding an operation result of an interpolation function based on the image data. 4. The image data interpolating apparatus according to claim 1, wherein said pixel interpolating means performs an interpolation operation corresponding to each predetermined grid position in an existing grid section. An image data interpolating apparatus characterized in that a numerical value is stored in a table, and an interpolation process is executed by holding the numerical value. 5. The image data interpolating apparatus according to claim 1, wherein said interpolation magnification acquiring means comprises a magnification designated when said image data acquiring means acquires said image data. Image data interpolating apparatus. 6. The image data interpolating apparatus according to claim 1, wherein the interpolation magnification obtaining means is configured to determine the size of the image data to be interpolated by the image data obtained by the image data obtaining means. An image data interpolating device for acquiring a magnification based on a ratio of the image data to the image data. 7. An interpolation processing method for increasing the number of constituent pixels at a predetermined interpolation magnification with respect to image data in which an image is represented by pixels in a dot matrix, comprising: a step of acquiring the image data; And the step of obtaining the interpolation magnification of the above, assuming a plurality of interpolation processing different degrees of influence on the sharpness of the image upon performing the interpolation processing to increase the number of constituent pixels in the image data, An image data interpolation method comprising: a step of selecting an interpolation process in which an image becomes sharper as the interpolation magnification is smaller based on the interpolation process; and a process of increasing the number of constituent pixels in the image data by the selected interpolation process. . 8. A medium in which an interpolation processing program for executing an interpolation processing by a computer so as to increase the number of constituent pixels at a predetermined interpolation magnification with respect to image data representing an image by dot matrix pixels is recorded. Obtaining image data; obtaining the interpolation magnification of the obtained image data; and performing a plurality of interpolation processes to increase the number of constituent pixels in the image data. Selecting an interpolation process in which the image becomes sharper as the interpolation factor becomes smaller based on the obtained interpolation factor, and increasing the number of constituent pixels in the image data by the selected interpolation process. And a medium storing an image data interpolation program.