JP2006203716A - Formation of high resolution image using a plurality of low resolution images - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technology for attaining a high definition image while suppressing increase in noise incident to high resolution by synthesis of low resolution images. <P>SOLUTION: An image processor comprises an edge detecting section and a high resolution processing section. The high resolution processing section selects and executes high resolution processing by synthetic high resolution processing mode at a position where an edge is detected by the edge detecting section, and selects and executes high resolution processing by simple high resolution processing mode at a position where an edge is not detected. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a technique for generating a high resolution image from a plurality of low resolution images.

  A moving image photographed by a digital video camera includes a plurality of frame images each representing one scene of the moving image. Conventionally, a process for generating a still image having a higher pixel density (that is, higher resolution) than a frame image using a plurality of frame images is known (see, for example, Patent Document 1). This processing is also called “high resolution processing” or “high definition processing”.

  In the present specification, the phrase “high definition” means that not only the resolution (pixel density) is high but also the amount of image information is large. Therefore, for example, when the resolution is doubled by the simple padding process, the resolution is doubled, but the definition is not changed.

Japanese Patent Laid-Open No. 2004-272751

  In this high resolution processing, a single high resolution image is created by combining a plurality of frame images, so that a higher definition image can be obtained. However, in an image region (so-called low-frequency image region) in which the image component is smooth in the frame image, the definition of the image is not greatly improved by increasing the resolution. On the other hand, in a smooth image area, noise is enhanced due to high resolution, and image quality may deteriorate. In particular, since a moving image includes a considerable amount of noise, there is a tendency that a problem that noise in a smooth image region increases by combining a plurality of frame images.

  Such a problem is not limited to a case where a still image is generated using a moving image, but is generally a problem common to a case where a high resolution image is generated using a plurality of low resolution images.

  The present invention has been made to solve the above-described problems, and provides a technique capable of obtaining a high-definition image while reducing an increase in noise caused by a higher resolution by combining low-resolution images. The purpose is to do.

An image processing apparatus according to the present invention includes:
An image processing apparatus that creates a single high-resolution image using a plurality of low-resolution images including a reference image,
An edge detection unit that detects edges in the reference image by analyzing the reference image;
A high-resolution processing unit that executes a high-resolution processing for creating one high-resolution image based on the plurality of low-resolution images;
With
The high resolution processing
A combined high-resolution processing mode for creating the high-resolution image by combining the plurality of low-resolution images;
A simple high resolution processing mode for creating the high resolution image using only the reference image, and
The high resolution processing unit
(I) In the position where the edge is detected by the edge detection unit, select and execute high resolution by the synthetic high resolution processing mode;
(Ii) At the position where no edge is detected, resolution enhancement by the simple resolution enhancement processing mode is selected and executed.

  Since an image portion with an edge has a large change in pixel value, a higher resolution image can be obtained by creating a high resolution image by combining a plurality of low resolution images. In addition, since there is little change in the pixel value of an image portion without an edge, a high resolution obtained when combining a plurality of low resolution images to increase the resolution and when increasing the resolution using only the reference image is obtained. There is no significant difference in the resolution of the resolution image. Further, when noise is included in an image portion having no edge, there is a possibility that noise is emphasized by synthesizing a plurality of low resolution images to increase the resolution, and the image quality is deteriorated. Since the image processing apparatus according to the present invention selectively executes the combined high resolution processing mode and the simple high resolution processing mode depending on whether or not the edge is detected, the noise increases due to the high resolution by combining the low resolution images. High-definition images can be obtained while reducing the above.

  The selection of the combined high resolution processing mode and the simple high resolution processing mode may be performed for each pixel in the reference image.

  According to this configuration, high definition and noise reduction can be achieved in pixel units.

  Alternatively, the selection of the combined high resolution processing mode and the simple high resolution processing mode may be performed for each line in the reference image.

  According to this configuration, the processing mode can be selected for each line, so that the processing time can be shortened.

  The present invention can be realized in various forms, for example, an image processing method and apparatus, a computer program for realizing the function of the method or apparatus, a recording medium on which the computer program is recorded, It can be realized in the form of a data signal including the computer program and embodied in a carrier wave.

Next, embodiments of the present invention will be described in the following order based on examples.
A. Example:
B. Details of composite high-resolution processing:
C. Variations:

A. Example:
FIG. 1 is a block diagram showing a configuration of an image processing system as an embodiment of the present invention. The image processing system 800 includes a printer 500 and a digital video camera 300. The printer 500 includes a data processing unit 100 and a print execution unit 700 (printing mechanism). Although not shown, the printer 500 includes a display unit for displaying images and operation guidance, and an operation unit for the user to specify the operation of the printer 500. The operation of selecting a plurality of frames used for increasing the resolution from the moving image is performed using these display units and operation units.

  The data processing unit 100 receives a moving image from the video camera 300, performs a resolution increasing process (described later), generates a high resolution image, and generates print data thereof. The print execution unit 700 receives this print data and performs printing. As the printing execution unit 700, various known printing mechanisms such as an ink jet printing mechanism and a thermal transfer printing mechanism can be adopted.

  FIG. 2 is a block diagram illustrating an internal configuration of the data processing unit 100. The data processing unit 100 includes an edge detection unit 420, a plurality of line buffers 430, a resolution enhancement processing unit 440, a print data generation unit 450, and a motion vector detection unit 460. The functions of the edge detection unit 420, the resolution enhancement processing unit 440, the print data generation unit 450, and the motion vector detection unit 460 are realized by a CPU (not shown) executing a computer program. Therefore, these units can be called “program modules” or simply “modules”.

  In the present embodiment, one high-resolution image Oimg is generated using three frame images Iimg1 to 3 (hereinafter referred to as “input images”), and printing is executed. The three input images Iimg1 to 3 are selected from the moving images. Here, three frame images separated by a predetermined time interval Δt are selected. However, the number of input images and the time interval can be arbitrarily set.

  The central image Iimg2 of the three input images Iimg1 to 3 is used as a reference input image Rimg (also referred to as “reference image”). As will be described later, the reference input image Rimg is used for various purposes. That is, (i) it becomes an object of edge detection, and (ii) it is used as an original image for simple high resolution processing. As the reference input image Rimg, it is possible to select any image from among the plurality of input images Iimg.

  The line buffer 430 is a buffer that holds image data of three lines Li-1, Li, Li + 1 (i is a line number) of the reference input image Rimg for edge detection processing. The edge detection unit 420 detects the presence or absence of an edge from the image data for these three lines (details will be described later).

  The high resolution processing unit 440 includes a simple high resolution processing unit 442 and a combined high resolution processing unit 444. The simple high resolution processing unit 442 performs high resolution using only the reference input image Rimg. On the other hand, the synthetic high resolution processing unit 444 performs high resolution by synthesizing the three input images Iimg1 to Iimg1-3. In this specification, the processing by the simple high resolution processing unit 442 is referred to as “simple high resolution mode”, and the processing by the composite high resolution processing unit 444 is referred to as “combined high resolution mode”. The resolution enhancement processing unit 440 selects and executes one of the simple resolution enhancement mode and the composite resolution enhancement mode according to the edge detection result. In the present embodiment, the resolution is increased for each line Li to be processed.

  The high-resolution image Oimg created by the high resolution is supplied to the print data generation unit 450. The print data generation unit 450 generates print data of the high resolution image Oimg and supplies it to the print execution unit 700 (FIG. 1) to execute printing.

  FIG. 3 is an explanatory diagram illustrating an example of a relationship between pixel positions of a low resolution image and a high resolution image. In FIG. 3, the pixel position of the low-resolution image is indicated by a circle, and the pixel position of the high-resolution image is indicated by a cross. In this example, the pixel pitch Phigh of the high resolution image is half of the pixel pitch Plow of the low resolution image. That is, the high resolution image has twice the resolution (that is, twice the pixel density) of the low resolution image. The pixel position of the high resolution image is shifted from the pixel position of the low resolution image in the horizontal direction and the vertical direction by 1/2 of the high resolution pixel pitch Phigh.

  In FIG. 3, a frame indicated by a broken line indicates a range of four high-resolution pixels associated with each low-resolution pixel. In the simple high resolution, the pixel value of one low resolution image is copied to the four high resolution pixels in the broken line. That is, the pixel value of the high resolution pixel in the broken line is set to be the same as the pixel value of the low resolution pixel. Therefore, with this simple high resolution, the resolution is increased, but the definition is not changed. However, in the simple high resolution processing, the pixel value of the high resolution pixel may be calculated using an interpolation calculation by a bilinear method or the like. When interpolation is used for higher resolution, the definition is slightly improved. On the other hand, in the composite high-resolution processing, pixel values of high-resolution pixels are calculated using not only the reference input image Rimg but also a plurality of input images Iimg1 to 3 (details will be described later). Therefore, in the composite high resolution processing, not only the resolution but also the definition is improved.

  FIG. 4 is an explanatory diagram illustrating another example of the relationship between the pixel positions of the low resolution image and the high resolution image. In this example, the position of the quarter pixel in the high resolution image matches the position of the pixel in the low resolution image. As the relationship between the pixel positions of the low-resolution image and the high-resolution image, various things other than those shown in FIGS. 3 and 4 can be adopted. However, in the embodiment described below, the positional relationship shown in FIG. 3 is used.

  In general, the pixel pitch Phigh of the high resolution image can be set to 1 / M times the pixel pitch Plow of the low resolution image (M is an arbitrary value larger than 1). However, M is preferably set to 2 or more, and in this embodiment, M = 2.

  FIG. 5 is a flowchart showing the overall procedure of the resolution enhancement processing in this embodiment. In step S10, various initializations are performed. At this time, the target line number Nline indicating the target line of the resolution enhancement process and the target pixel number Npix indicating the target pixel are also initialized to zero. The target line Nline and the target pixel Npix indicate lines and pixels (low resolution pixels) in the reference image Rimg.

  In step S11, the motion vector detection unit 460 calculates the motion vector (relative movement amount) of each input image Iimg. This motion vector is a vector representing the relative position of the entire reference input image Rimg and the other input images (Iimg1 or Iimg3). Therefore, when there are three input images, two motion vectors are obtained. These motion vectors are used in the synthetic high resolution processing. In general, when the number of input images Iimg is N + 1 (N is an integer equal to or greater than 1) including the reference input image Rimg, N motion vectors are calculated.

  In step S12, three lines of image data centered on the target line Nline are selected from the reference input image Rimg and input to the line buffer 430 (FIG. 2). If Nline = 0 indicates the upper end line of the image area, when Nline = 0, the line Li-1 before the target line Nline (= Li) does not actually exist. In this case, the image data of the target line Nline (= Li) may be copied and used as the image data of the line Li-1. Or you may make it start the process after step S12 from Nline = 1. The same applies to the target pixel Npix.

  In step S13, the edge detecting unit 420 detects the edge of the target pixel Npix in the reference image Rimg using the image data in the line buffer 430. FIG. 6 is an explanatory diagram showing a method of edge detection. FIG. 6A shows primary differential filters FLx and FLy for edge detection in the x and y directions. FIG. 6B shows Sobel filters FLx and FLy for edge detection in the x and y directions. In the present embodiment, primary differential filters FLx and FLy are used. However, as the edge detection filter (also referred to as “edge amount calculation filter”), any filter other than these can be used, and for example, a secondary differential filter can also be used.

  By performing filter processing on the target pixel Npix using the two first-order differential filters FLx and FLy, the edge amount component Edx in the x direction and the edge amount component Edy in the y direction of the target pixel Npix can be calculated. The edge amount Ed and the edge direction θ of the target pixel Npix can be calculated, for example, according to the equation shown in FIG. This edge amount Ed is an edge amount (also referred to as “total edge amount”) obtained by combining the edge amount component Edy in the x direction and the edge amount component Edy in the y direction. As in this example, as the edge amount used for edge detection (edge presence / absence determination), it is preferable to use a total edge amount including edge amount components in two directions. For example, the edge amount obtained using a Laplacian filter can be considered as a kind of total edge amount.

  The determination of the presence / absence of an edge is performed by comparing the edge amount Ed with a predetermined threshold value Eth. That is, when the edge amount Ed is equal to or greater than the threshold Eth, it is determined that the target pixel has an edge, and when it is less than the threshold Eth, the target pixel is determined to have no edge.

  If it is determined in step S14 in FIG. 5 that the target pixel has an edge, in step S15, the combined high resolution processing unit 444 executes the high resolution processing, and a plurality of high resolutions associated with the target pixel are processed. Pixel values of resolution pixels (four high resolution pixels surrounded by a broken line in FIG. 3) are calculated. In this composite high resolution processing, not only the reference input image Rimg but also the plurality of input images Iimg1 to 3 are used together to calculate pixel values of high resolution pixels. Details of the composite high resolution processing will be described later.

  On the other hand, when it is determined that the target pixel does not have an edge, in step S16, the simple high resolution processing unit 442 executes the high resolution processing, and a plurality of high resolution pixel pixels associated with the target pixel. Calculate the value. This simple high resolution processing is realized by, for example, copying pixel values of a low resolution image to four high resolution pixels. Instead of copying the pixel value, the pixel value of the high resolution pixel may be determined by interpolating the pixel values of a plurality of low resolution pixels adjacent to the high resolution pixel. That is, in the simple high resolution process, only the reference input image Rimg is used, and the pixel value of each high resolution pixel can be generated by referring to one or more nearest pixels.

  The pixel values of the resolution-enhanced image created in this way are sequentially supplied from the resolution-enhancement processing unit 440 to the print data generation unit 450 (FIG. 2).

  In step S17 of FIG. 5, the target pixel number Npix is updated. When the target pixel reaches the end of each line, the target line number Nline is also updated. If the processing for all the pixels has not been completed, the process returns from step S18 to step S12, the image data in the line buffer 430 is updated as necessary, and the processes in steps S13 to S18 are repeated.

  In this way, in this embodiment, since the composite high resolution processing is executed at the pixel position determined to have an edge, a higher definition image can be obtained for an image portion where the pixel value changes sharply. . On the other hand, since a simple high-resolution process is executed at the pixel position determined to have no edge, noise is emphasized due to the combined high-resolution process for an image portion whose pixel value changes slowly. Can be prevented. Further, the simple high resolution processing has an advantage that the entire processing time can be shortened because the processing time is shorter than the synthetic high resolution processing.

  In the above embodiment, the high resolution processing mode is selected for each individual low resolution pixel, but instead, the high resolution processing mode may be selected for each line. For example, for each line of the reference input image Rimg, an edge amount index value (for example, a sum of edge amounts or a square sum of edge amounts) having a correlation with the sum of edge amounts is calculated, and the edge amount index value is calculated. If the presence / absence of an edge is determined accordingly, it is possible to select a high resolution processing mode for each line.

B. Details of composite high-resolution processing:
FIG. 7 is a block diagram showing an internal configuration of the composite high resolution processing unit 444. The combined high resolution processing unit 444 includes a control unit 210, an image selection unit 215, a low resolution image estimation unit 220, a high resolution image estimation unit 230, a low resolution difference image generation unit 240, and a movement amount calculation unit 250. A high-resolution difference image generation unit 260, and an output high-resolution image update unit 270. The functions of these components will be described later.

  FIG. 8 is an explanatory diagram showing the contents of the composite high resolution processing. In the example of FIG. 8, one high-resolution output image Oimg is generated from three input images Iimg. Hereinafter, in the figure, an image with a symbol LR (Low Resolution) represents a low resolution image, and an image with a symbol HR (High Resolution) represents a high resolution image.

  FIG. 9 is a flowchart showing the procedure of the composite high resolution processing. In step S110, the high resolution image estimation unit 230 (FIG. 7) generates a temporary output image Oimg using the input image Iimg. In the example of FIG. 8, the temporary output image Oimg is generated using the reference input image Rimg having the center in the order along the time series. Specifically, the high-resolution image estimation unit 230 generates a high-resolution temporary output image Oimg from the low-resolution reference input image Rimg using a known bilinear method.

  As will be described later, the final output image Oimg is generated by correcting the temporary output image Oimg. Therefore, the method for generating the temporary output image Oimg is not limited to the bilinear method, and various methods can be employed. For example, the nearest neighbor method may be used.

  Further, the reference input image Rimg may be determined according to other rules. For example, the first input image Iimg in the order along the time series may be used as the reference input image Rimg.

  In the next step S120, the movement amount calculation unit 250 (FIG. 7) calculates the relative movement amount of each input image Iimg. This relative movement amount is a value representing a relative position between the entire input image Iimg and the entire reference input image Rimg. As such a relative movement amount (also referred to as a relative motion amount), for example, a motion vector of the entire input image Iimg relative to the entire reference input image Rimg can be used. The relative movement amount is not limited to the movement amount representing the parallel movement of the image, and other movement amounts representing various movements can be employed. For example, you may employ | adopt the movement amount showing the motion containing a parallel movement and a rotational movement. In either case, various known methods can be employed as a method for calculating the relative movement amount. For example, a method of calculating a relative movement amount by extracting a feature point from each input image Iimg and calculating a movement amount of the feature point can be employed.

  In the processing procedure shown in FIG. 5, a motion vector (relative movement amount) is calculated in step S11. Therefore, in step S120, there is no need to perform the calculation again, and the value obtained in step S11 can be used as it is. In this case, step S120 and the movement amount calculation unit 250 can be omitted.

  In the next step S130, the low resolution image estimation unit 220 (FIG. 7) generates three low resolution estimated images Eimg using the high resolution temporary output image Oimg (details will be described later). These estimated images Eimg represent input images that are consistent with the temporary output image Oimg. In other words, these estimated images Eimg represent images that each input image Iimg should have, assuming that the temporary output image Oimg is an optimal image. Here, each estimated image Eimg and each input image Iimg are associated one to one.

  Specifically, in step S130, the low resolution image estimation unit 220 generates each estimated image Eimg using the temporary output image Oimg and each relative movement amount. In the example of FIG. 8, the low-resolution image estimation unit 220 performs a blurring process on the temporary output image Oimg, further moves the image according to the relative movement amount, and executes the low-resolution process, thereby estimating the estimated image. Eimg is generated. Various known processes can be adopted as the blurring process (smoothing process). In the image moving process, the temporary output image Oimg is moved so as to overlap each input image Iimg. Various known processes can be adopted as the resolution reduction process. For example, an interpolation process such as a bilinear method or a nearest neighbor method can be employed. Further, when the pixel position of each estimated image Eimg overlaps the pixel position of the temporary output image Oimg, a process of simply thinning out the pixels may be employed.

  In the next step S140, the low resolution difference image generation unit 240 (FIG. 7) generates a low resolution difference image LDimg for each input image Iimg using the three input images Iimg and the three estimated images Eimg. To do. Each pixel value of the low resolution difference image LDimg is set to a difference (= Eimg−Iimg) of pixel values at the same pixel position between the input image Iimg and the estimated image Eimg. The meaning of this low resolution difference image LDimg can be explained as follows. When the relationship between the temporary output image Oimg and each input image Iimg is in an ideal state, that is, the temporary output image Oimg and each input image Iimg are the same in only the position (relative movement amount). In the case of representing an image, each pixel value of each low resolution difference image LDimg is a value close to zero. On the other hand, when the difference between the temporary output image Oimg and the ideal output image is large, that is, when the difference between the temporary output image Oimg and each input image Iimg is large, The pixel value of the low resolution difference image LDimg will depart from zero. Thus, the magnitude of the deviation of the pixel value of the low resolution difference image LDimg from zero means the magnitude of the difference between the temporary output image Oimg and the ideal output image. Therefore, if the pixel value of the low resolution difference image LDimg is fed back to the temporary output image Oimg, the temporary output image Oimg can be brought close to an ideal output image.

  In the next step S150, the high resolution difference image generation unit 260 (FIG. 7) generates a high resolution difference image HDimg for each low resolution difference image LDimg. Specifically, the high-resolution difference image generation unit 260 performs high-resolution processing on the low-resolution difference image LDimg, further performs sharpness enhancement processing, and then moves the image according to the estimated relative movement amount. Each high-resolution difference image HDimg is generated. As the resolution enhancement process, various known processes can be employed. For example, a bilinear method or a nearest neighbor method can be employed. As the sharpness enhancement process, various known processes can be employed. For example, processing using an unsharp mask may be employed. Furthermore, the image moving process is performed so that the high-resolution difference image HDimg overlaps the temporary output image Oimg. At this time, each pixel value of each high-resolution difference image HDimg is corrected so as to represent a pixel value at the same pixel position as that of the temporary output image Oimg. Various known interpolation processes can be employed as the process for correcting the pixel value.

  In the next step S160, the high resolution difference image generation unit 260 combines each high resolution difference image HDimg to generate one combined high resolution difference image CHDimg. Each pixel value of the combined high-resolution difference image CHDimg is set to the sum of pixel values at the same pixel position in each high-resolution difference image HDimg.

  In the next step S170, the output high-resolution image update unit 270 feeds back the synthesized high-resolution difference image CHDimg to the temporary output image Oimg. This feedback is performed by correcting each pixel value of the temporary output image Oimg according to the following equation (1).

  Pixel value after update = Pixel value before update + α × Difference pixel value ... (1)

  Here, the updated pixel value is the pixel value of the provisional output image Oimg after feedback. The pre-update pixel value is a pixel value of the temporary output image Oimg before feedback. The difference pixel value is a pixel value at the same pixel position in the combined high-resolution difference image CHDimg. α is a coefficient representing the strength of feedback. This coefficient α may be experimentally set in advance so that feedback does not become excessive. The sign α of the coefficient α is determined so as to realize negative feedback. In the present embodiment, the difference pixel value is obtained from a value obtained by subtracting the input image Iimg from the estimated image Eimg (Eimg−Iimg), and thus the coefficient α is a negative value.

  Through the above processing, the temporary output image Oimg can be updated to an image more suitable for the input image Iimg. After step S170, the process returns to step S130, and the processes of steps S130 to S170 are repeatedly executed. Then, when the pixel value of the combined high-resolution difference image CHDimg becomes sufficiently small, the control unit 210 determines that the process has converged and completes the update. The output image Oimg finally updated in this way is used as the final output image Oimg.

  In this embodiment, since the blurring process (smoothing process) is executed in step S130, the absolute value of the pixel value of the sharp part of each input image Iimg in the low resolution difference image LDimg is the smooth part. The absolute value of the pixel value can be made larger. Furthermore, since the sharpness enhancement process is executed in step S150, it is possible to emphasize a sharp portion of each input image Iimg in the high resolution difference image HDimg. As a result, the updated temporary output image Oimg can be a sharp image that is consistent with each input image Iimg.

  Note that the composite high resolution processing shown in FIGS. 8 and 9 can be executed for the entire image, or can be executed for each line. When the process is executed for each line, at least one line image to be processed is generated as each image Eimg, LDimg, HDimg, CHDimg, and Oimg in FIG.

  Incidentally, the selection of the high resolution processing mode described with reference to FIG. 5 can be executed for each pixel or for each line as described above. When selecting the high resolution processing mode for each pixel element, for example, the composite high resolution processing shown in FIGS. 8 and 9 is executed for each line, and then the simple high resolution processing is selected. With respect to the pixel to be used, it is possible to generate a high-resolution image by using the pixel value obtained by the simple high-resolution processing instead of the pixel value obtained by the synthetic high-resolution processing.

C. Variations:
The present invention is not limited to the above-described examples and embodiments, and can be implemented in various modes without departing from the gist thereof. For example, the following modifications are possible.

C1. Modification 1:
Various processes other than those shown in FIGS. 8 and 9 can be employed as the composite high resolution process. For example, as another composite high resolution processing, low resolution pixels close to each high resolution pixel are selected one by one from the three input images Iimg1 to Iimg3, and the pixel values of these three low resolution pixel pixels are selected. A method of obtaining the pixel value of the high resolution pixel by interpolation can be employed. Also, as a pixel value interpolation calculation method, various methods such as a bilinear method and a bicubic method can be used.

C2. Modification 2:
In the above embodiment, the data processing unit 100 is provided in the printer, but instead, the data processing unit 100 may be configured using a general personal computer. The data processing unit 100 may be mounted on various other electronic devices such as an information portable terminal, a mobile phone, a digital video camera, and a digital still camera.

C3. Modification 3:
In each of the above embodiments, a high-resolution still image is generated from a moving image. Instead, a high-resolution still image may be generated from a plurality of low-resolution still images.

C4. Modification 4:
In each of the above embodiments, a part of the configuration realized by software may be replaced by hardware, and conversely, a part of the configuration realized by hardware may be replaced by software. .

1 is a block diagram illustrating a configuration of an image processing system as an embodiment of the present invention. It is a block diagram which shows the internal structure of a data processing part. It is explanatory drawing which shows an example of the relationship between the pixel position of a low resolution image and a high resolution image. It is explanatory drawing which shows the other example of the relationship between the pixel position of a low resolution image and a high resolution image. It is a flowchart which shows the whole procedure of the resolution increasing process in a present Example. It is explanatory drawing which shows the method of edge detection. It is a block diagram which shows the internal structure of a synthetic | combination high resolution process part. It is explanatory drawing which shows the content of the synthetic | combination high resolution process. It is a flowchart which shows the procedure of a synthetic | combination high resolution process.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Data processing part 210 ... Control part 215 ... Image selection part 220 ... Low resolution image estimation part 230 ... High resolution image estimation part 240 ... Low resolution difference image generation part 250 ... Movement amount calculation part 260 ... High resolution difference image generation part 270: Output high-resolution image update unit 300: Digital video camera 420 ... Edge detection unit 430 ... Line buffer 440 ... High resolution processing unit 442 ... Simple high resolution processing unit 444 ... Composite high resolution processing unit 450 ... Print data generation Unit 460 ... motion vector detection unit 500 ... printer 700 ... print execution unit 800 ... image processing system

Claims (5)

An image processing apparatus that creates a single high-resolution image using a plurality of low-resolution images including a reference image,
An edge detection unit that detects edges in the reference image by analyzing the reference image;
A high-resolution processing unit that executes a high-resolution processing for creating one high-resolution image based on the plurality of low-resolution images;
With
The high resolution processing
A combined high-resolution processing mode for creating the high-resolution image by combining the plurality of low-resolution images;
A simple high resolution processing mode for creating the high resolution image using only the reference image, and
The high resolution processing unit
(I) In the position where the edge is detected by the edge detection unit, select and execute high resolution by the synthetic high resolution processing mode;
(Ii) An image processing apparatus that selects and executes high resolution in the simple high resolution processing mode at a position where no edge is detected. The image processing apparatus according to claim 1,
The image processing apparatus in which selection of the combined high resolution processing mode and the simple high resolution processing mode is performed for each pixel in the reference image. The image processing apparatus according to claim 1,
The image processing apparatus, wherein selection of the combined high resolution processing mode and the simple high resolution processing mode is performed for each line in the reference image. An image processing method for creating a single high-resolution image using a plurality of low-resolution images including a reference image,
(A) detecting an edge in the reference image by analyzing the reference image;
(B) executing a high resolution process for creating one high resolution image based on the plurality of low resolution images;
With
The high resolution processing
A combined high-resolution processing mode for creating the high-resolution image by combining the plurality of low-resolution images;
A simple high resolution processing mode for creating the high resolution image using only the reference image, and
The step (b)
(I) At the position where the edge is detected, select and execute high resolution in the combined high resolution processing mode;
(Ii) An image processing method including a step of selecting and executing high resolution in the simple high resolution processing mode at a position where no edge is detected. A computer program for creating one high-resolution image using a plurality of low-resolution images including a reference image,
An edge detection function for detecting an edge in the reference image by analyzing the reference image;
A high resolution processing function for executing a high resolution processing for creating a single high resolution image based on the plurality of low resolution images;
Including a computer program for causing a computer to realize
The high resolution processing
A combined high-resolution processing mode for creating the high-resolution image by combining the plurality of low-resolution images;
A simple high resolution processing mode for creating the high resolution image using only the reference image, and
The high resolution processing unit function is:
(I) At the position where the edge is detected, select and execute high resolution in the combined high resolution processing mode;
(Ii) A computer program including a function of selecting and executing high resolution in the simple high resolution processing mode at a position where no edge is detected.

Images