JPH07114636A - Pixel density converting device - Google Patents

Abstract

PURPOSE:To excellently and speedily perform pixel density conversion. CONSTITUTION:This pixel density converting device is equipped with an interpolation part 1 which generates pixels corresponding to the deficiency in the resolution of an image of low resolution as unknown pixels and interpolates them when the image of low resolution is converted in pixel density into an image of high resolution to generate the image of high resolution, and an image process part 2 which sets values for the respective unknown pixels interpolated by the interpolation part 1. The image process part 2 determines the values of the respective interpolated pixels as known ones by using the values of pixels whose values are already known by regarding the respective unknown pixels of the image, into which the unknown pixels are interpolated, as completely unknown values and respective pixels in the area corresponding to the image of low resolution except the area of the unknown area as known pixels which all have known values.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION The present invention relates to an optical filing device,
The present invention relates to a pixel density conversion device used in a facsimile device, a display device, a printing device, and the like.

[0002]

2. Description of the Related Art Conventionally, for example, the resolution of a scanner used in an optical filing apparatus using an optical disk is 2
Most of them are 00 dpi.

[0003]

[Problems to be Solved by the Invention] However, in the future,
Scanners having higher resolutions of 300 dpi and 400 dpi are expected to become widespread, and at this time, compatibility in resolution is required between low-resolution models and high-resolution models. That is, it is expected by those skilled in the art that there is a demand for realizing a function of converting a low-resolution image into a high-resolution image in a good pixel density.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a pixel density conversion device which can perform pixel density conversion satisfactorily and quickly and which can be applied to perform high quality image conversion in various applications. I am trying.

[0005]

In order to achieve the above object, the present invention provides an interpolating means for generating and interpolating a pixel corresponding to a lack of resolution as an unknown pixel for a low resolution image. And an image processing unit that sets a value for the interpolated unknown pixel, and the image processing unit sets a known value among the neighboring pixels of the unknown pixel when focusing on a specific unknown pixel. Only when the number of known pixels with is greater than a predetermined threshold value, the value of the unknown pixel is determined using the value of the known pixel among the neighboring pixels, while when the number of known pixels is less than the predetermined threshold value, The value of the unknown pixel is not determined and is left as an unknown pixel, and after the above-described processing with a predetermined threshold value is performed for all unknown pixels, the unknown pixel whose value is determined is a known pixel, and Change the threshold,
Repeat the process for the remaining unknown pixels,
Pixel density conversion of a low resolution image into a high resolution image is performed. Thereby, the pixel density conversion can be performed satisfactorily and quickly, and it can be applied to perform high-quality image conversion in various applications.

[0006]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing a configuration example of a pixel density conversion device according to the present invention. Referring to FIG. 1, this pixel density conversion apparatus is used for a low resolution image PC as shown in FIG.
1 (300 dpi in the example of FIG. 2A) is a high-resolution image P
When converting the pixel density to C2 (400 dpi in the example of FIG. 2B), a pixel corresponding to the lack of resolution is generated as an unknown pixel and interpolated to the low resolution image PC1, and the high resolution image PC2 And the interposing unit 1 to be in the state of
And an image processing unit 2 for setting a value for each unknown pixel interpolated by.

Here, in the image processing unit 2 in which the unknown pixels are initially completely unknown in the image PC2 in which the unknown pixels are interpolated, the original low resolution other than the area PCU of the unknown pixels is used. It is assumed that all the pixels of the area PCK corresponding to the image PC1 are known pixels having known values, and the value of each interpolated unknown pixel is set to a known value by using the value of the known pixel PCK. ing. That is, the image processing unit 2
Does not process all the pixels in the image PC2, but only the unknown pixels in the area PCU in the image PC2.

Further, the image processing unit 2 pays attention to a pixel in the vicinity of the specific unknown pixel in order to perform processing on the specific unknown pixel in the area PCU, and has a known value having a known value among the adjacent pixels. The value of the specific unknown pixel is determined (assumed to be known) using the pixel. At this time, the image processing unit 2 counts the number of pixels having a known value among the neighboring pixels of the specific unknown pixel in the area PCU, and the number of pixels having the known value is larger than a predetermined threshold value. Only when the value of the unknown pixel is determined using the value of the known pixel having the known value among the neighboring pixels, and when the number of pixels having the known value is smaller than the predetermined threshold value, The unknown pixel is left as it is without determining the value. Then, after the above-described processing is performed for each pixel in the area PCU with a predetermined threshold value, the unknown pixel whose value is determined is set as a known pixel, and the threshold value is gradually changed from a large value to a small value, The same process is repeatedly performed on the unknown pixels that have not been determined.

In order to realize such a processing function, FIG.
In the above configuration example, the image processing unit 2 includes a control unit 3 that controls the entire process, a neighboring pixel definition unit 4 that defines neighboring pixels, and a threshold initial setting unit that sets an initial value of a threshold. 5 and an operation type setting unit 6 for setting the operation type
And a calculation unit 7 that performs a calculation of the type set in the calculation type setting unit 6.

FIG. 3 is a flowchart showing a processing example of the image processing unit 2. Note that, in the following, for simplification of description, as an example, it is assumed that each unknown pixel in the area PCU is processed on a pixel-by-pixel basis.

Assuming that the image processing unit 2 starts the actual processing, for a low resolution image PC1 as shown in FIG. 2 (a), a pixel corresponding to the lack of resolution is an unknown pixel in a predetermined area (position) PCU. It is necessary that the high resolution image PC2 as shown in FIG. That is, it is necessary for the interpolating unit 1 to generate an image PC2 including an area PCU of unknown pixels and an area (area including known pixels) PCK corresponding to the original low-resolution image PC1. At this time, in order to identify each unknown pixel in the area PCU, it is assumed that a number j is assigned to each unknown pixel and the total number N of unknown pixels in the area PCU is known.

In addition, it is necessary for the neighboring pixel defining section 4 to define a neighboring pixel for one unknown pixel in advance (for example, the shape and size of the neighborhood). Further, the threshold initial setting unit 5 needs to set the initial value of the threshold k. The initial value of the threshold value k can be set, for example, by the operator's designation. Further, the type of processing calculation (for example, the type of calculation such as taking the average value of the values of known pixels among the neighboring pixels) needs to be set by the calculation type setting unit 6.

That is, the definition of the neighboring pixels, the initial value of the threshold value, and the type of calculation are the images PC1 and PC2 to be processed.
Depending on the type (for example, whether the image is a binary image or a multi-valued image, or whether the image is a document image, a photographic image, or a pictorial image), or
Type of interpolated area PCU (size of processing area,
It should be set appropriately according to the shape).

After such a premise is established (step S
1) and j are initialized to "1" (step S2). Next, the image processing unit 2 takes in the j-th pixel from the interpolated region PCU in the image PC2 (step S
3) The number of known pixels having a known value among the neighboring pixels of this pixel is counted (step S4). Then, the count value CNT is compared with the threshold value k (step S5), and the count value C
When NT is equal to or larger than the threshold value k, the calculation unit 7 determines the value of the jth pixel based on the known pixel having the known value among the pixels adjacent to the jth pixel (step S6). ). When the type of calculation is, for example, “average value”, the average value of the values of the known pixels is calculated, and this is determined as the value of the jth pixel. On the other hand, in step S5, when the count value CNT is smaller than the threshold value k,
Leave the value of the j-th pixel as unknown without performing calculation
(Step S7).

After the processing of step S6 or step S7 is performed for the j-th pixel, j is incremented by "1" (step S8), the process returns to step S3 again, and the next pixel in the processing target area PCU is returned. The same processing is repeatedly performed for. Such processing is sequentially repeated for each pixel in the processing target area PCU to obtain the processing target area PC.
When the processing for the last pixel in U is completed (step S9), the value of the unknown pixel in the processing target area PCU is rewritten according to the processing result for each pixel (step S10). As a result, regarding the unknown pixel whose value is determined by the process of step S6, the determined value is set as a known value, and this unknown pixel becomes the known pixel at this point. On the other hand, unknown pixels whose values have not been determined by the process of step S7 are not rewritten and remain as unknown pixels.

Next, in the rewriting process of step S10, it is determined whether or not there are no unknown pixels (or whether or not the number is equal to or less than a predetermined number), or whether or not the threshold value k is the minimum value k _0. (Step S11). As a result, when the threshold value k is not the minimum value k ₀ and the unknown pixels still remain, the threshold value k is reduced to determine the values for these unknown pixels (step S1).
2) Then, the process returns to step S3 again. At this time, a number j is newly added to the remaining unknown pixels. In this way, the value for the unknown pixel is determined stepwise, and when the unknown pixel is eliminated or the number of unknown pixels becomes equal to or less than the predetermined number in step S11, or the threshold value k is the minimum value. When k ₀ is reached, the process ends.

FIGS. 4A to 4D are views for explaining a concrete example of the image processing. In this specific example, a 3 × 3 size mask M _ij as shown in FIG. 4A is defined as the neighboring pixels. That is, the center of this mask M _ij is set to an unknown pixel, whereby the eight parts M ₁₁ , M ₁₂ , M ₁₃ , M ₂₁ , M ₂₃ , M ₃₁ , M ₃₂ , M ₃₃ of the mask are set.
Is a neighboring pixel of the unknown pixel set at the center M ₂₂ of the mask. Also, in this case, the type of calculation is, for example, “average value”.
And the initial value of the threshold value k is set to, for example, “6”.

Now, in the case of the high resolution image PC2, the interpolated area PCU is as shown in FIG. 4 (b).
(Note that FIG. 4A shows a part of the image PC2 shown in FIG. 2B.) To simplify the explanation, for example, three pixels # 1 to # 1 in the processing target area PCU are shown. Pay attention to 3. These pixels # 1 to # 3 is initially since become a thing of the unknown values, each pixel center M ₂₂ of the mask M # 1 to #
The number is sequentially set to 3, and the process is performed. For example, the mask M _ij
If the center M ₂₂ of the pixel is set to pixel # 1, M ₁₁ , M ₁₃ ,
The six pixels of M ₂₁ , M ₂₃ , M ₃₁ , and M ₃₃ are known areas PC.
K pixels, have known values, and M ₁₂ ,
Since the pixel in the M ₃₂ portion is an unknown pixel, there are 6 known pixels having known values among the 8 neighboring pixels. Therefore, it is the same as the threshold value k (= 6), and the threshold value k (= 6)
Since it is not smaller, the value of the unknown pixel # 1 is determined based on the values of the 6 known pixels. For example, this value is determined as the average value of the values of 6 known pixels.

On the other hand, the center M ₂₂ of the mask is set to the pixel #
When set to 2, or # 3, out of 8 neighboring pixels
There are four pixels with known values. Therefore, since it is smaller than the threshold value k (= 6), the values of the unknown pixels # 2 and # 3 are not determined at this stage.

In this way, the threshold value k is set to "6",
When the unknown pixels # 1 to # 3 are processed, the value of the pixel # 1 is determined, and thus the determined value of the pixel # 1 is set as a known value. That is, at this time, the pixel # 1 becomes a known pixel having a known value, and the two pixels # 2 and # 3 remain unknown as shown in FIG. 4C.

In the next step, the threshold value k is changed from "6" to "5".
And the center M ₂₂ of the mask M _ij is changed to the unknown pixel # 2, #
The number is sequentially set to 3, and the process is performed. In this case, when the center M ₂₂ of the mask is set to the pixel # 2, 5 out of the 8 neighboring pixels have known values, which is the same as the threshold value k (= 5). Are determined based on the values of the five known pixels.

On the other hand, the center M ₂₂ of the mask is set to the pixel # 3.
When set to, four of the eight neighboring pixels have known values. Since it is smaller than the threshold value k (= 5), the value of the pixel # 3 is not determined at this stage. It is determined based on the values of 6 known pixels.

In this way, the threshold value k is set to "5",
When the process is performed for the unknown pixels # 2 to # 3, the value is determined for the pixel # 2, and thus the determined value is set for the pixel # 2 as a known value. That is, at this time, the pixel # 2 becomes a known pixel having a known value, and one pixel # 1 remains unknown as shown in FIG. 4 (d).

In the next step, the threshold value k is changed from "5" to "4".
, The center M ₂₂ of the mask M _ij is set to the unknown pixel # 1, and the process is performed. In this case, when the center M ₂₂ of the mask is set to the pixel # 1, four out of eight neighboring pixels have known values, which is the same as the threshold value k (= 4).
The value of pixel # 1 is determined based on the values of four known pixels.

In this way, at the stage when the threshold value k is set to "4", the value of the pixel # 1 is determined and set as a known value. In this example, at this stage, all the pixels become known pixels having known values, and there are no unknown pixels remaining, so the processing ends.

The first of the above-mentioned processing in the image processing section 2
The feature (advantage) is that the processing target area PC
It consists in determining only the value of the unknown pixel in U. That is, since the processing is not performed on all the pixels in the image PC2 but only on the pixels in a part of the image PC2, the image processing time can be shortened as compared with the conventional case. Since the pixels in the known area PCK that do not need to be processed are not processed, the overall image quality does not deteriorate even when the resolution is increased.

The second characteristic (advantage) of the above-mentioned processing
Is to determine the value in order from the pixel whose value can be determined most reliably among the unknown pixels. That is, in the example of FIG. 4B, the pixel # 1 has a larger number of neighboring pixels having a known value than the pixels # 2 and # 3, and the value is most reliably determined. First the value is determined.

The third characteristic (advantage) of the above-mentioned processing
When the value of an unknown pixel is determined, and this unknown pixel becomes a known pixel having a known value, in the next step, this pixel is added to a group of pixels having a known value of neighboring pixels, and It is to determine the values of the remaining pixels. That is, in the example of FIG. 4C, for example, in determining the value of the pixel # 2, the value of the pixel # 1 that has become the known value in the previous stage is taken into consideration. Thereby, continuity of each pixel can be secured.

The fourth characteristic (advantage) of the above-mentioned processing
Is that all types of images can be processed regardless of the types of images. That is, even if the image is a binary image such as a document image, a multi-valued image such as a photographic image or a pictorial image can be obtained by appropriately setting the definition of neighboring pixels, the initial value of the threshold value, and the type of calculation. Even
This is to be able to favorably perform image restoration and estimation. In the specific example described above, no reference is made to the type of image, but when the image is a multi-valued image, the calculated value (for example, the average value) of the pixel values having known values in the neighboring images. That can be determined as the value of the unknown pixel. Further, when the image is a binary image, when the calculated value (for example, average value) of the pixels having known values in the neighboring images is “0.5” or less, “0” is set as the value for the unknown pixel. When the calculated value (for example, the average value) is "0.5" or more, "1" can be determined as the value for the unknown pixel.

Due to having such features (advantages), the pixel density conversion device of the present invention can be applied to various applications in which a process of converting a low resolution image into a high resolution image is required. .

As a first application example of the pixel density conversion device of the present invention, in an optical filing device, for example, a scanner has a low resolution (for example, 200 dpi) model and a scanner has a high resolution (for example, 300 dpi or 400 dpi) model. There may be a case where the images are interchanged between them.
That is, in order to use an image file obtained with a low-resolution model in a high-resolution model, it may be possible to increase the resolution. In such a case, with respect to the low resolution image PC1 obtained by the low resolution model, as described above, an unknown pixel of a quantity corresponding to the scaling factor for high resolution is inserted in a predetermined area (predetermined position) to increase the resolution. A high-resolution image PC2 handled by a high-resolution model is created, and the unknown pixels of the image PC2 are subjected to the above-described image processing to obtain the image PC2.
2 can be repaired satisfactorily and quickly. In this way, it is possible to automatically perform high resolution and high image quality for an image file input at low resolution.

Further, as a second application example of the pixel density conversion apparatus of the present invention, image conversion in a facsimile machine on the receiving side can be considered. That is, when a document is transmitted by the facsimile machine on the transmission side, the resolution of the transmitted image is usually 4 lines / mm (normal mode) in the sub-scanning direction due to the transmission speed and communication cost. When a higher resolution received image (for example, an image in the fine mode) is desired in the facsimile machine on the receiving side, the pixel density conversion device of the present invention can be applied to the facsimile machine on the receiving side.

For example, when the image received from the sending side is 4 mm in length in the sub-scanning direction (when the original image is sent from the sending side in the normal mode), the facsimile machine on the receiving side responds to this received image. For example, the unknown pixel line is interleaved every other sub-scanning line to increase the resolution, and the interpolated unknown pixel line is subjected to the above-described image processing to restore the unknown pixel line satisfactorily and quickly. can do. As a result, the received image can be restored to the same level as when it was sent in the fine mode, and a high resolution and high image quality can be obtained.

Further, as a third application example of the pixel density conversion device of the present invention, it is conceivable that image compatibility is achieved between devices having different resolutions such as a display and a printer. That is, devices such as displays
The resolution is generally lower than that of a device such as a printer. For example, when a hard copy of a display is output to a printer, a very small image may be output due to the difference in resolution, or even if the image is scaled, the quality is reduced. Only deteriorated images can be obtained.

In order to solve such a problem, the pixel density conversion device of the present invention can be used on the low resolution device side. That is, when the pixel density conversion device of the present invention is used for a low resolution device such as a display and the hard copy of the display is output to a printer as a high resolution device, the pixel density conversion is performed on the hard copy of the display as described above. By achieving high resolution and high image quality by outputting it to the printer, it is possible to print out a normal size image in which the image quality is not deteriorated.

As a fourth application example of the pixel density conversion device of the present invention, for example, when transmitting / receiving an image between transmitting and receiving, the transmitting side compresses the image and sends it to the receiving side. When receiving, it may be expanded and restored. Alternatively, in the filing apparatus, when an image is saved, the image is compressed and saved, and when the saved image is reproduced, the image may be expanded and restored.

Even when the image compressed as described above is restored, by applying the pixel density conversion device of the present invention, it is possible to restore the state of high resolution and high image quality.

In the above-described embodiment, the unknown pixel in the area PCU is processed in the unit of one pixel.
In order to perform the processing at high speed, for example, as shown in FIG. 5, a set of a plurality of pixels can be regarded as one pixel, and the processing can be performed for each pixel. In addition, in the example of FIG. 5, the group of a plurality of pixels is assumed to be composed of 2 × 2 pixels, and in this case, the neighboring pixels can also be defined as being composed of a group of a plurality of pixels. For example, one pixel of the neighboring pixels can be defined as having 2 × 2 pixels like the pixels in the area PCU.

In this way, when a set of a plurality of pixels is regarded as one pixel and processing is performed in pixel units, 1 is set.
The number of pixels to be processed can be reduced as compared with the case where processing is performed in pixel units, and the processing can be performed at high speed. For example, when 2 × 2 pixels are regarded as one pixel and processing is performed in pixel units, the processing speed can be increased four times. However, the resolution of the image is deteriorated by performing such processing. In the above example, the resolution deteriorates to 1/2. Therefore, it can be applied to applications where the resolution may be deteriorated.

As an example of its application, for example, a facsimile machine on the transmission side has a capability of transmitting an image signal at a resolution of 400 dpi, while a facsimile machine on the reception side has a reproduction capability of a resolution of 200 dpi. If not. In this case, the receiving facsimile machine
When the above-described processing is performed on the 400 dpi image from the facsimile apparatus on the transmission side, it is not necessary to maintain the resolution of 400 dpi on the transmission side.
A resolution of 0 dpi is sufficient. Therefore, by treating a 2 × 2 pixel as one pixel and performing image processing for each pixel, the processing speed can be increased four times and the resolution required on the receiving side can be satisfied.

[0041]

As described above, according to the present invention, interpolating means for generating and interpolating a pixel corresponding to a lack of resolution as an unknown pixel in an image of low resolution and interpolating the pixel. And an image processing unit that sets a value for the unknown pixel, and when the image processing unit focuses on a specific unknown pixel, the number of known pixels having a known value among the neighboring pixels of the unknown pixel. When the number of known pixels is smaller than the predetermined threshold value, the value of the unknown pixel is set to the unknown pixel value using the value of the known pixel among the neighboring pixels only when is larger than the predetermined threshold value. The unknown pixels are left undetermined, and after the above-mentioned processing with a predetermined threshold value is performed for all unknown pixels, the unknown pixels whose values are determined are known pixels, and the threshold value is changed. Repeat the process for the remaining unknown pixels However, since the low-resolution image is converted into the high-resolution image in the pixel density, the pixel density conversion can be performed satisfactorily and quickly, and the high-quality image conversion can be performed in various applications. Can be applied to.

[Brief description of drawings]

FIG. 1 is a diagram showing a configuration example of a pixel density conversion device according to the present invention.

2A and 2B are diagrams for explaining an interpolation process of unknown pixels.

3 is a flowchart for explaining the operation of the pixel density conversion device of FIG.

4 (a) to (d) are diagrams showing a specific example of processing of the pixel density conversion apparatus of FIG.

5 (a) and 5 (b) are diagrams showing an example of processing an unknown pixel in a region by regarding a set of a plurality of pixels as one pixel.

[Explanation of symbols]

 1 Interpolation unit 2 Image processing unit 3 Control unit 4 Neighboring pixel definition unit 5 Threshold initial setting unit 6 Calculation type setting unit PC1 Low resolution image PC2 High resolution image PCU Unknown pixel region PCK Known region

Claims (5)

[Claims] 1. A pixel density conversion device for converting a low-resolution image into a high-resolution image in pixel density, wherein a pixel corresponding to a lack of resolution is generated as an unknown pixel and interpolated in the low-resolution image. And an image processing unit that sets a value for the interpolated unknown pixel, the image processing unit, when focusing on a specific unknown pixel, among the neighboring pixels of the unknown pixel. The value of the unknown pixel is determined using the value of the known pixel among the neighboring pixels only when the number of the known pixels having the known value is larger than the predetermined threshold, while the number of the known pixels is the predetermined threshold. When the value is smaller than the above, the unknown pixel value is not determined and the unknown pixel is left as it is, and after the above-mentioned processing with a predetermined threshold value is performed for all unknown pixels, the unknown pixel with the determined value is known. Pixel,
Further, the pixel density conversion device is characterized in that the threshold value is changed and the above process is repeated for the remaining unknown pixels. 2. The pixel density conversion device according to claim 1, wherein the pixel density conversion device is applicable to an optical filing device, and a low resolution image file and a high resolution image file are included in the optical filing device. A pixel density conversion device characterized by being used for compatibility between devices. 3. The pixel density conversion device according to claim 1, wherein the pixel density conversion device is applicable to a facsimile device, and the reception side facsimile device receives a low resolution image from the transmission side. A pixel density conversion device, which is sometimes used to increase the resolution of the image. 4. The pixel density conversion device according to claim 1, wherein the pixel density conversion device is used for image compatibility between devices having different resolutions. . 5. The pixel density converter according to claim 1, wherein the pixel density converter receives or reproduces the compressed image when the image is communicated or stored in a compressed state. A pixel density conversion device, which is used to restore the pixel density.