JP2005051379A - Image processing apparatus and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To effectively reduce noise included in an image. <P>SOLUTION: Difference values between a plurality of smoothed images and an input image are found and compared with a threshold to select smoothed pixels or input pixels, or further compared with pixels of low smoothness. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image processing device and an image processing method, and more particularly to an image processing device and an image processing method for performing noise reduction processing of multi-value image data.
[0002]
[Prior art]
Image data captured by a digital camera or image data optically read by a scanner or the like includes various noises derived from an optical sensor such as a CCD, for example, high frequency noise and low frequency such as relatively large patchy noise. Noise is included.
[0003]
One of these means for reducing noise contained in an image is the method disclosed in Japanese Patent Laid-Open No. 2000-207551. In this, noise is reduced by preparing an image with reduced granularity with a low-pass filter or the like and an image with enhanced sharpness in advance, and performing selection processing together with the pixels of the original input image. I am trying.
[0004]
[Problems to be solved by the invention]
However, in the case of noise reduction by the selection process as described above, it is very difficult to set a threshold value as a criterion for image selection. For example, if an image with reduced granularity is set so that it can be easily selected, a low-pass filter is applied more than necessary, resulting in a blurred image, or conversely, if it is difficult to select, the noise reduction effect This is because there is a risk that it will not rise.
[0005]
SUMMARY An advantage of some aspects of the invention is that it provides an image processing apparatus and an image processing method capable of increasing the noise reduction effect by performing selection with higher accuracy.
[0006]
[Means for Solving the Problems]
In order to achieve the above object, an image processing apparatus and an image processing method according to the first invention of the present invention include:
Means for performing a plurality of smoothing processes on the input image data;
Means for holding a plurality of smoothed data created by the smoothing process;
Means for comparing a difference absolute value of one pixel data of the plurality of smoothed data and the pixel data of the input image with a threshold value;
Based on the result of the comparison means, the smoothing data or the input pixel data is selected, and the result of the comparison means is the pixel data and the input pixel that are not compared among the plurality of smoothed data. Means for comparing a difference absolute value with the data with a threshold value.
[0007]
In order to achieve the above object, an image processing apparatus and an image processing method according to the second invention of the present application are provided.
Means for repeatedly performing smoothing processing on input image data;
Means for holding smoothed data created by the smoothing process;
Means for comparing a difference absolute value between pixel data of the smoothed data and pixel data of the input image with a threshold value;
Means for selecting the smoothed data or the input pixel data according to the result of the comparing means;
And means for changing the number of repetitions of the smoothing process according to the result of the comparison means.
[0008]
DETAILED DESCRIPTION OF THE INVENTION
An embodiment of the present invention is shown below. Of course, the following embodiments are provided for facilitating implementation by those skilled in the art of the present invention, and are only included in the technical scope of the present invention defined by the claims. It is only an embodiment of the part. Therefore, it will be apparent to those skilled in the art that even embodiments that are not directly described in the present specification are included in the technical scope of the present invention as long as they share the same technical idea.
[0009]
Note that although a plurality of embodiments are described for convenience, those skilled in the art can easily understand that these are not only individually established as inventions, but of course that the invention can also be realized by appropriately combining a plurality of embodiments. I can do it.
[0010]
[First Embodiment]
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
[0011]
FIG. 4 is a block diagram illustrating the configuration of the image processing apparatus according to the first embodiment of the present invention. This image processing apparatus is an apparatus that can perform printing by performing the noise removal processing according to the present invention on an image photographed by a digital camera.
In the figure, reference numeral 400 denotes a processing device control unit. An operation panel 403 is connected to the processing device control unit 400, which allows the user to select an image and start printing. The operation panel 403 is controlled by the operation control unit 404. When the print start is executed, the card control unit 402 reads a predetermined image from the PC card 401, executes a decoding process if necessary, and transfers the data to the noise removal unit 405. The noise removing unit 405 removes the noise by processing described later, and sends the processed image to the image processing unit 406. The image processing unit 406 performs correction processing that enables more suitable color reproduction, and then converts the data into a printable data format, for example, CMY format. The printable data is sent to the printer control unit 407, and based on the data, the printer engine 408 is controlled to execute printing.
[0012]
Although not shown in the figure, the CPU controls each of these units, and a ROM for storing programs and various parameters for executing them and a RAM for executing them are prepared.
[0013]
FIG. 1 shows details of the noise removing unit. In FIG. 1, reference numeral 100 denotes an input image acquisition unit. The image obtained by the input image acquisition unit 100 is sent to the smoothing processing units 101, 102, 103, and 104, and smoothing processing is executed by a low-pass filter (hereinafter referred to as LPF). In this embodiment, four smoothed images are used for selection, but this varies depending on the usable memory capacity. As the memory capacity increases and the number of selected images can be increased, more effective noise removal processing can be performed. In order to use the memory efficiently, the number of smoothed images may be dynamically changed according to the number of pixels of the input image.
[0014]
LPFs used for smoothing have different smoothness. The smoothness performed by the smoothing processing unit 101 is the strongest, and the processed image is a blurred image with the least amount of high frequency components. As the smoothing processing units 102, 103, and 104 become smoother, the smoothness becomes weaker and approaches the input image.
[0015]
FIG. 2 shows four filter masks used in this embodiment. In this filter processing, all pixel values of the pixel of interest and the pixels in the mask are added together, and a gradual calculation is performed by the number of pixels. LPF1 in the figure corresponds to taking the average value of the pixel of interest and the surrounding 80 pixels. LPF1 to LPF4 indicate a case where the smoothness is changed depending on the mask size. It is also possible to change the smoothness by changing the weight of each component instead of the mask size.
[0016]
The four smoothed images 105 to 108 having different smoothness obtained by these processes are sent to the pixel selection processing unit 109 together with the input image, and the image from which noise has been removed is obtained by performing pixel selection processing described later. can get. Thereafter, the image output unit 110 outputs the image data.
[0017]
FIG. 3 is a flowchart showing the flow of the pixel selection processing unit. The pixel-by-pixel comparison is performed in order from the highest smoothness. In S300, the smoothed image 1 having the highest smoothness is set as the target pixel. In S301, the difference between the input pixel and the target pixel is calculated, and the value is compared with a preset threshold value Th1. As a result, when the threshold value is larger, it is regarded as an image flat portion that does not interfere with smoothing, and the process proceeds to the target pixel selection unit in S309. If the threshold value is smaller, if the target pixel is used, it is considered that the image is blurred due to excessive smoothing, and the process proceeds to S302. In S302, the target pixel is reset to the smoothed image 2, and the same comparison process is executed in S303. If the threshold value Th2 is large, the target pixel is selected in S309. Otherwise, the process proceeds to S304. Thereafter, in the same manner as described above, the setting of the smoothed image 3 of the target pixel and the comparison with the threshold value Th3 are respectively performed in S304 and S305, and the setting of the smoothed image 4 of the target pixel is respectively performed in S306 and S307. Comparison with the threshold Th4 is performed. If the threshold value Th4 is larger than the threshold value Th4 in the comparison in S307, it is regarded as the sharpest part of the image, and the input pixel is selected in S308. Thereafter, in S310, it is determined whether or not processing has been performed for all pixels. If processing has not been performed for all pixels, the input pixel is advanced by one (S311), and the processing returns to S300 to perform similar processing. Is executed. If the process is completed for all the pixels, the pixel selection process ends.
[0018]
The parameters Th1 to Th4 listed here are preset values. Further, although the threshold value is divided according to the smoothness, it is also possible to use a common threshold value for all.
[0019]
As described above, according to the first embodiment of the present invention, four images smoothed with different LPFs are prepared, and the selection process is performed to improve the noise removal effect and photographed with a digital camera. Enables high-quality printing of images.
[0020]
In this embodiment, a printer is used as the processing apparatus, but the present invention is not limited to this. For example, there is no problem in applying the present invention to a display device that displays noise-removed data or a digital camera that creates data.
[0021]
[Second Embodiment]
In the second embodiment, the noise removing unit 405 is a different part in the image processing apparatus of FIG. 4 in the first embodiment. Accordingly, the noise removal portion 405 will be described in detail below.
[0022]
FIG. 5 is a block diagram for explaining a noise removing portion in the second embodiment of the present invention. The image obtained by the input image acquisition unit 500 is sent to the smoothing processing unit 501. The smoothing process in 501 is a smoothing process using LPF as in the first embodiment. As the LPF used here, it is not desirable to perform a strong smoothing process in a single process, so it is appropriate to use LPF4 or LPF3 in FIG. The comparison unit 502 obtains a difference value between the pixel of the input image and the pixel of the smoothed image, and compares the value with a preset threshold value. The smoothing number determination unit 503 monitors how many times the smoothed image being compared has been smoothed. The image output unit 504 outputs an image on which noise removal processing has been performed.
[0023]
The processing flow when this is used is as shown in FIG. In S600, the LPF counter used in the smoothing number determination unit is set to the number of smoothing times. In this example, the smoothing process is executed a maximum of four times as in the first embodiment, so 4 is set. In S601, the smoothing process is executed. At this time, the smoothing process is repeatedly executed by the LPF counter times. In S602, the target pixel is set to the smoothed pixel, and in S603, the threshold value ThN (N = 1 to 4) to be used is set with reference to the LPF counter. In S604, the difference between the input pixel and the target pixel is obtained, and the value is compared with the threshold value ThN. If the threshold value ThN is larger, the target pixel value is selected as the output value in S605. If it is smaller, the process proceeds to S606, and it is determined whether the LPF counter is larger than zero. If the counter is 0 or less, the input pixel is selected in S609. If larger than 0, the LPF counter is decremented by 1 in S608, and then the smoothed image is cleared again so as to start smoothing the input image (S607), and the process returns to S601. After the pixel selection process is executed in S605 or S609, it is determined in S610 whether the process has been performed for all the pixels. If the process has not been completed, the target pixel is advanced in S611. In step S607, the image is cleared, and in step S600, similar processing is executed again. If the process has been executed for all the pixels, the process ends.
[0024]
As described above, in the second embodiment of the present invention, a high noise removal effect is realized by repeatedly performing the smoothing process instead of preparing a plurality of smoothed images. As a result, although the number of smoothing processes increases, it is not necessary to prepare a memory that holds four smoothed images, and the memory can be realized with a smaller memory capacity than in the first embodiment.
[0025]
[Third Embodiment]
In the first embodiment and the second embodiment, LPF is used in the smoothing process. In the third embodiment, a case where a reduction / enlargement process is used instead of the filter process will be described.
[0026]
FIG. 7 shows a block diagram in which the first embodiment is executed by reduction / enlargement processing. Only a different part from the noise removal part of FIG. 1 is demonstrated.
[0027]
In the smoothing processing units 700 to 703, reduction / enlargement processing is used. Since the smoothness of the smoothed image 1 is the highest, it is assumed that the reduction / enlargement rate of the smoothing processing unit 700 is the highest. In addition, as the process proceeds from 700 to 704, the reduction / enlargement ratio decreases. FIG. 8 shows an example of this embodiment. In the reduction / enlargement processes 1, 2, 3, and 4, the reduction rates are 20%, 40%, 60%, and 80%, respectively, and the enlargement processes are 500%, 250%, 167%, and 125%, respectively.
[0028]
FIG. 9 is a block diagram in which the second embodiment is realized by reduction / enlargement processing. A different part from the noise removal part of FIG. Here, after 80% reduction processing, smoothing is performed by 125% enlargement processing.
[0029]
Note that the reduction / enlargement processing used in FIG. 7 and FIG. 9 uses a bilinear method or a bicubic method that can reduce high-frequency components, rather than an interpolation processing that uses approximate values such as the real neighbor method. .
[0030]
As described above, in the third embodiment of the present invention, a high noise removal effect is realized by using a reduction / enlargement process without using a filter process when creating a smoothness image. As a result, noise removal can be realized without performing exceptional edge processing that occurs in filter processing.
[0031]
(Other embodiments)
As described above, the object of the present invention is to provide a system or apparatus with a storage medium storing software program codes for realizing the functions of the embodiment, and the computer of the system or apparatus (or CPU or MPU) stores it. It is also achieved by reading and executing the program code stored on the medium. In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code constitutes the present invention. As a storage medium for supplying such a program code, for example, a floppy disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like is used. Can do.
[0032]
Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) running on the computer based on the instruction of the program code Includes a case where the function of the above-described embodiment is realized by performing part or all of the actual processing.
[0033]
Furthermore, after the program code read from the storage medium is written in the memory provided in the function expansion board inserted into the computer or the function expansion unit connected to the computer, the function is determined based on the instruction of the program code. This includes the case where the CPU of the expansion board or function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.
[0034]
The present invention also applies to a case where the program is distributed to a requester via a communication line such as personal computer communication from a storage medium in which a program code of software that realizes the functions of the above-described embodiments is recorded. Needless to say, it can be applied.
[0035]
【The invention's effect】
As described above, according to the first aspect, according to the first aspect, a plurality of smoothed images are created, an absolute value of a difference from the input pixel is obtained for each pixel from an image with high smoothness, and a comparison process with a threshold value is performed. By selecting smoothed pixel data or input pixel data and using pixel data with low smoothness, a more effective noise removal effect can be realized.
[0036]
In addition, according to the second aspect, by executing the smoothing process repeatedly first, an image with high smoothness is obtained, the absolute value of the difference from the input pixel is obtained for each pixel, and the comparison with the threshold value is performed. By selecting smoothed pixel data or input pixel data and using smoothed pixel data with a reduced number of smoothing operations, a more effective noise removal effect is realized. By doing so, the same effect can be realized with a smaller memory capacity than in the first aspect.
[0037]
Furthermore, in the first and second aspects, by using the image reduction / enlargement processing for creating a smooth image, the same effect can be realized without performing edge processing by filtering.
[Brief description of the drawings]
FIG. 1 is a block diagram illustrating a configuration of a noise removing unit according to a first embodiment.
FIG. 2 is a diagram illustrating a filter mask used in the smoothing process according to the first embodiment.
FIG. 3 is a flowchart for explaining a detailed operation procedure of a pixel selection unit according to the first embodiment;
FIG. 4 is a block diagram illustrating a configuration of an exemplary image processing apparatus according to the first embodiment.
FIG. 5 is a block diagram illustrating a configuration of a noise removing unit according to a second embodiment.
FIG. 6 is a flowchart for explaining a detailed operation procedure of the noise removing unit according to the second embodiment;
FIG. 7 is a block diagram illustrating a configuration of a noise removing unit according to a third embodiment.
FIG. 7 is a diagram for explaining reduction / enlargement processing according to the third embodiment;
FIG. 7 is a block diagram illustrating a configuration of a noise removing unit according to a third embodiment.

Claims (10)

Means for performing a plurality of smoothing processes on the input image data;
Means for holding a plurality of smoothed data created by the smoothing process;
Means for comparing a difference absolute value of one pixel data of the plurality of smoothed data and the pixel data of the input image with a threshold value;
Based on the result of the comparison means, the smoothing data or the input pixel data is selected, and the result of the comparison means is the pixel data and the input pixel that are not compared among the plurality of smoothed data. An image processing apparatus and an image processing method comprising: means for comparing a difference absolute value with data with a threshold value. Means for selecting pixel data having the highest smoothness from the plurality of smoothed data;
The image processing apparatus and the image processing method according to claim 1, wherein smoothing data is selected in order of decreasing smoothness based on a result of the comparison unit. The image processing apparatus and the image processing method according to claim 1, wherein the means for executing the plurality of smoothing processes is a means for using a different filter mask. The image processing apparatus and the image processing method according to claim 1, wherein the means for executing the plurality of smoothing processes is an image reduction / enlargement means at a different ratio. 5. The image processing apparatus and the image processing method according to claim 1, wherein the number of the plurality of smoothed data to be held is changed according to the number of pixels of the input image data. Means for repeatedly performing smoothing processing on input image data;
Means for holding smoothed data created by the smoothing process;
Means for comparing a difference absolute value between pixel data of the smoothed data and pixel data of the input image with a threshold value;
Means for selecting the smoothed data or the input pixel data according to the result of the comparing means;
An image processing apparatus and an image processing method characterized by comprising means for changing the number of repetitions of the smoothing process according to the result of the comparison means. 7. The image processing apparatus and image processing method according to claim 6, wherein the means for executing the smoothing process is a means using a filter mask or an image reduction / enlargement means. The image processing apparatus and the image processing method according to claim 6, wherein the means for changing the number of repetitions of the smoothing process is changed so as to decrease. Performing a plurality of smoothing processes on the input image data;
Holding a plurality of smoothed data created by the smoothing process;
Comparing a difference absolute value between one pixel data of the plurality of smoothed data and the pixel data of the input image with a threshold value;
Based on the result of the comparison step, the step of selecting the smoothed data or the input pixel data, and the result of the comparison step, the pixel data that has not been compared among the plurality of smoothed data and the input pixel An image processing program for causing a computer to execute a step of comparing a difference absolute value with data with a threshold value. Repeatedly executing smoothing processing on input image data;
Holding the smoothed data created by the smoothing process;
Comparing a difference absolute value between pixel data of the smoothed data and pixel data of the input image with a threshold value;
Selecting the smoothed data or the input pixel data according to the result of the comparing step;
An image processing program for causing a computer to execute a step of changing the number of repetitions of the smoothing process according to a result of the comparison step.

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