JP5121639B2 - Image processing apparatus and image processing method - Google Patents

Description

  The present invention relates to an image processing apparatus and an image processing method, and more particularly, to a technique suitable for use when converting an interlaced image into a progressive image.

  When displaying an interlaced image, which is a moving image, on a display screen as a still image or printing, the interlaced image is converted into a progressive image, and the still image is displayed or printed.

  When performing interlace / progressive conversion, obtain motion between field images of interlaced images, and when combining paired field images, adjust the pixel position with reference to the obtained motion amount and then compose Is also known.

  There is also a prior art that generates interpolated pixels according to the edge of an image in a configuration in which a non-interlaced signal is generated by interpolating a line signal with respect to a video signal obtained by interlaced scanning (for example, patents) Reference 1).

JP 2007-110217 A

  However, in the conventional technique, for a user who views the generated progressive image, there are many cases where the high frequency component of the image is missing at a place where the movement between the field images is large, etc. . In addition, there is a problem that it is impossible to change the display of the progressive image according to the magnitude of the motion between the field images, or to clearly indicate the location where the motion is large so that the user can recognize it.

In view of such problems, an object of the present invention is to make it possible to identify a portion in which a high frequency component is missing due to a motion between field images in an image obtained by converting an interlaced image into a progressive image.
It is a further object of the present invention to make it possible to generate a suitable progressive image with little motion by clearly indicating a portion with a large motion between field images.

In order to achieve the above object, an image processing apparatus according to the present invention is an image processing apparatus that converts interlaced image data into progressive image data, and includes pixels between a plurality of field images constituting the interlaced image data. Detecting means for detecting a motion amount for each pixel; determining means for determining a pixel region having a large motion by comparing the motion amount for each pixel detected by the detecting means with a predetermined threshold; and the interlace A predetermined pattern is combined with the pixel area determined by the determining means included in the progressive image converted by the converting means and the converting means for converting the image data into progressive image data. And an image processing means.
Another image processing apparatus of the present invention is an image processing apparatus that converts interlaced image data into progressive image data, and a motion amount for each pixel between a plurality of field images constituting the interlaced image data. And a portion where the high frequency component of the image is lost due to the motion between the plurality of field images by comparing the motion amount for each pixel detected by the detection device with a predetermined threshold. Determination means for determining the interlaced image data into progressive image data, and lack of the high-frequency component determined by the determination means included in the progressive image converted by the conversion means And image processing means for synthesizing a predetermined pattern with the portion. .

The image processing method of the present invention is an image processing method for converting interlaced image data into progressive image data, and detects a motion amount for each pixel between a plurality of field images constituting the interlaced image data. Comparing the detected motion amount for each pixel with a predetermined threshold value to determine a pixel region having a large motion, and converting the interlaced image data into progressive image data. And a step of synthesizing a predetermined pattern with the pixel region having a large motion included in the converted progressive image.
Another image processing method of the present invention is an image processing method for converting interlaced image data into progressive image data, and a motion amount for each pixel between a plurality of field images constituting the interlaced image data. And a step of determining a missing portion of the high frequency component of the image by the motion between the plurality of field images by comparing the detected amount of motion for each pixel with a predetermined threshold value. And converting the interlaced image data into progressive image data, and synthesizing a predetermined pattern with the missing portion of the high frequency component included in the converted progressive image. It is characterized by.

  According to the present invention, it is possible to easily identify missing high-frequency components in an image obtained by converting an interlaced image into a progressive image. In addition, by specifying a portion where the motion between the field images is large, it is possible to generate or select a suitable progressive image with little motion.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is a block diagram illustrating a configuration example of an image processing apparatus according to an embodiment of the present invention.
In FIG. 1, reference numeral 10 denotes an image processing apparatus. Reference numeral 20 denotes a playback device, and reference numeral 30 denotes a display device. The playback device 20 is connected to an input terminal 101 in the image processing device 10, and the display device 30 is connected to an output terminal 108 in the image processing device 10.

  In the image processing apparatus 10, reference numeral 101 denotes an input terminal to which image data for interlace scanning is input from the reproduction apparatus 20. 102 is a control circuit (CPU), 103 is a memory, 104 is a data bus, 105 is a decoder, and 106 is an edge detection circuit. Reference numeral 107 denotes an interlace / progressive conversion circuit (IP conversion circuit), which converts interlaced scan image data into progressive scan image data. Reference numeral 108 denotes an output terminal for outputting progressively converted image data.

Next, the operation of the image processing apparatus 10 of the present embodiment configured as described above will be described.
The image data reproduced by the reproduction device 20 is input through the input terminal 101. Here, the input image data is interlaced compressed image data that has been compression-encoded by a compression encoding method such as MPEG (Moving Picture Experts Group). The input compressed image data is input to the decoder 105 via the data bus 104.

  The compressed image data input to the decoder 105 is decoded by a predetermined decoding method, becomes a decoded image, and is stored in the memory 103 via the data bus 104. The decoded image stored in the memory 103 is read according to the control of the CPU 102 and supplied to each unit. In this case, the CPU 102 functions as a data reading unit.

  When interlaced image data is output as it is, the image data read from the memory 103 is supplied to the output terminal 108 via the data bus 104. Then, the image data is output from the output terminal 108 to the display device 30.

  On the other hand, when interlaced image data is converted into progressive image data, the image data read from the memory 103 is transferred to the edge detection circuit 106 and the IP conversion circuit 107 via the data bus 104 in the screen display order. Supplied.

  The edge detection circuit 106 detects an edge for each field image included in the interlaced image that is the input decoded image. Edge detection is performed in units of one pixel or pixel block. Then, the CPU 102 acquires information (edge information) related to the position and movement amount of the edge detected by the edge detection circuit 106, and controls the conversion from the interlaced image to the progressive image based on the edge information.

  The conversion from the interlaced image to the progressive image is performed in the IP conversion circuit 107. Specifically, the IP conversion circuit 107 synthesizes two continuous field images among the input decoded images, and sequentially generates progressive images.

  The IP conversion circuit 107 performs a conversion process from an interlaced image to a progressive image, and performs a correction process and a special process on a portion where an edge is moved between field images under the control of the CPU 102. The correction process is a process for modifying an image to be combined so as to cancel out the amount of movement of the edge. Further, the special processing is processing that performs image processing so that a portion where the edge is extremely moved, that is, a portion having a large movement between field images is visually conspicuous. It is also an emphasis process for clearly showing a portion in which a high frequency component is missing due to the motion between field images, which is seen when an interlaced image is converted into a progressive image. A specific description when converting an interlaced image to a progressive image will be described later.

  The decoded image that has become a progressive image by the conversion processing in the IP conversion circuit 107 is stored again in the memory 103 via the data bus 104. Thereafter, the data is read again by the CPU 102, supplied to the output terminal 108 via the data bus 104, and can be output to the display device 30.

Here, an example of processing related to interlace / progressive conversion related to the CPU 102, the edge detection circuit 106, and the IP conversion circuit 107 will be described.
FIG. 2 is a diagram illustrating an example of an interlaced image. This interlaced image is supplied from the memory 103 to the IP conversion circuit 107. Further, the same interlaced image is also supplied to the edge detection circuit 106.

  FIG. 3A and FIG. 3B are diagrams showing examples of field images, respectively. The edge detection circuit 106 divides the input interlaced image into images for each field as shown in FIGS. 3A and 3B, and then performs edge detection for each field image. 4A and 4B are diagrams illustrating examples of edge detection results of field images, respectively. The results of edge detection performed by the edge detection circuit 106 on the field images in FIGS. 3A and 3B are shown in FIGS. 4A and 4B, respectively. Further, the edge detection circuit 106 compares the edges for each field image as shown in FIGS. 4A and 4B and calculates the number of moving pixels of the pixels in which the edges are detected.

  FIG. 5A and FIG. 5B are diagrams illustrating a state in which a part of the edge detection result of the field image is enlarged. The number of moving pixels is calculated by comparing the edges of field images as shown in FIGS. 4A and 4B at the pixel level as shown in FIGS. 5A and 5B. Can do. In the example of FIGS. 5A and 5B, it can be seen that the edge has moved by 14 pixels in the X-axis direction (the horizontal direction of the screen). In the present embodiment, the movement in the X-axis direction is shown as an example. However, in the case of performing the motion amount determination between the fields of the interlaced image, the moving pixel for each of the X-axis and the Y-axis (the vertical direction of the screen) Calculate the number.

  For example, a Canny filter or a Laplacian filter is used for edge detection. Since the degree of edge detection can be changed by changing the coefficients of these filters, it is possible to change the coefficients and obtain the movement of pixels capable of edge detection. Furthermore, the movement of pixels whose edges are not detected can be obtained from the number of moving pixels of the peripheral pixels.

  When the edge movement between the field images is detected by the edge detection circuit 106, the CPU 102 performs correction control according to the edge movement for the interlace / progressive conversion processing performed by the IP conversion circuit 107. Then, the IP conversion circuit 107 sequentially generates one progressive image from two consecutive field images while following the correction instruction from the CPU 102.

Here, a progressive image generated by the IP conversion circuit 107 will be described.
FIG. 6 is a diagram illustrating an example when an interlaced image is converted to a progressive image. As in the example of FIG. 6, an image obtained by performing interlace / progressive conversion while correcting for motion is different from a display of an interlaced image as shown in FIG. 2 as it is, and there is no blur between fields. .

  However, especially for fast-moving subject images, the correction process cannot be performed well, or the high frequency area is lost in the first place, so even if converted to a progressive image, it will not be a good image. . That is, it becomes a progressive image including a portion where a high frequency component is missing due to movement between field images.

  Therefore, in the present embodiment, the IP conversion circuit 107 performs the special processing described above. The special processing will be specifically described. First, the CPU 102 acquires edge information indicating the amount of movement of the edge pixel from the edge detection circuit 106. Then, the CPU 102 determines the number of edge moving pixels when two field images are converted into progressive images based on the edge information. Further, based on the determination result, the CPU 102 instructs the IP conversion circuit 107 to process (emphasize processing) the progressive image generated from the two field images.

  The CPU 102 determines that the edge pixel whose amount of movement is equal to or greater than a predetermined threshold is missing a high frequency component, and visually recognizes the portion where the high frequency component is missing from the generated progressive image. The IP conversion circuit 107 is made to perform such enhancement processing.

  Here, as the image processing related to the enhancement processing, for example, an example in which another image signal is superimposed on one of the pixel regions of the region where the edge motion is larger or smaller than a predetermined threshold is combined. Can be considered. By using another image signal to be synthesized as a predetermined pattern, for example, a zebra pattern signal, a zebra pattern can be synthesized in a specific area.

  Further, the hue of the specific area may be changed, or may be used in combination with a zebra pattern. Of course, the predetermined pattern is not limited to the zebra pattern, and may be a pattern having another pattern. In addition, the luminance of the moving pixels may be reversed, or may be displayed so as to blink in units of frames or fields. Furthermore, highlighting may be performed so that pixels with reduced high-frequency components appear to be more blurred by replacing moving pixels with the average value of the surrounding pixels.

  FIG. 7 is a diagram illustrating a progressive image in which a zebra pattern is combined with a portion having a large movement as described above. According to the present embodiment, the display device 30 can display a progressive image as shown in FIG. Note that the zebra pattern in the present embodiment is an oblique stripe pattern (stripe) whose luminance level is within the first and second threshold level ranges. The first threshold level is a black level value that can be identified as an image, and the second threshold level is a white level value that does not saturate the luminance of the image.

  According to the present embodiment, by combining the zebra pattern with the specific area of the decoded image, the striped pattern is displayed so as to overlap the moving object or the like in the decoded image as shown in FIG.

  In this embodiment, the IP conversion circuit 107 is configured to perform image enhancement processing. However, after the progressively converted image is stored in the memory 103, a predetermined pattern (zebra pattern) is stored on the memory 103 under the control of the CPU 102. ) May be synthesized. Further, the generated progressive image may not be directly processed, and a predetermined pattern (zebra pattern) as another image layer may be modified to be displayed as an overlay on the generated progressive image.

FIG. 8 is a flowchart showing an outline of a processing procedure for determining a motion and highlighting a portion with a large motion.
In FIG. 8, first, the CPU 102 determines whether or not a moving image pause is being performed (step S81). The process of step S81 is a step of determining whether the image data input from the playback device 20 is due to the playback device 20 being playing back a moving image or during moving image pause.

  When the moving image pause is being performed (YES in step S81), the CPU 102 sets a threshold value for determining the edge motion amount to "threshold value = P" (step S82). On the other hand, when the video pause is not in progress (NO in step S81), the CPU 102 sets a threshold value for determining the amount of movement of the edge to “threshold value = Q” (step S83). Note that the playback image is displayed as a still image during the video pause. In this case, the purpose is to observe and evaluate one screen in detail.

  On the other hand, during moving image reproduction, the purpose is to roughly observe a plurality of screens. Therefore, the threshold value P is set to a value lower than the threshold value Q, and the threshold value P is in a state where edge detection is easier. The threshold value P and the threshold value Q are prepared in advance and stored in the memory 103, and the CPU 102 selectively uses parameters.

Next, the edge detection circuit 106 detects an edge for each field image constituting the input interlaced image (step S84).
Next, the edge detection circuit 106 calculates the number of moving pixels for the pixel (edge pixel) from which the edge is detected (step S85). The number of moving pixels of the edge pixel is calculated by comparing the edges of the field images as described above.

  Here, how to determine the number of moving pixels of edge pixels will be described. FIG. 9 is a diagram for explaining how to determine the number of moving pixels of edge pixels. In FIG. 9, the horizontal line is one line in the field. Further, for the same one line, three fields of the (N−1) th field, the Nth field, and the (N + 1) th field are shown. Black circles indicate the pixels present on the line.

  Since the (N−1) -th field and the (N + 1) -th field are the same even field, there are pixels at the same position in the vertical direction, and the N-th field is an odd field, so there is a pixel at a position shifted by one pixel. ing. Taking the pixel on the line of the (N-1) th field as an example, the pixel exists at the positions i-4, i-2, i, i + 2, and i + 4. That is, in each field, the position of the pixel can be expressed by i + 2x (x is an integer), and is shifted by one pixel every other field.

  For example, when calculating the number of moving pixels of the edge pixel included in the Nth field, the edge detection circuit 106 obtains a pixel movement amount with respect to the (N−1) th field, and further, the pixel with respect to the (N + 1) th field. Find the amount of movement.

At this time, the edge detection circuit 106 obtains the interpolation pixel p [N] [i] (white circle in FIG. 9). Based on temporal correlation, p [N−1] [i−y] and p [N + 1] [i + y] (y is an integer greater than or equal to 0) Find pixel motion. This can be expressed by the following equation 1.
| P [N−1] [i−y] −p [N + 1] [i + y] | (Formula 1)

  As a result of the calculation of Equation 1, the value that is the minimum value has the highest temporal correlation, and y at that time is determined to be the number of moving pixels. In this way, the number of moving pixels can be obtained for each pixel (edge pixel) in each field.

  Next, the CPU 102 compares the number of moving pixels calculated in step S85 with the threshold set in step S82 or step S83, and determines whether or not the amount of motion for each pixel is greater than a predetermined amount of motion. Is determined (step S86). If the result of this determination is that the number of moving pixels is greater than or equal to the threshold value (YES in step S86), the CPU 102 and the IP conversion circuit 107 perform image processing for emphasis display on the pixel area that has moved greatly. This is done (step S87).

  On the other hand, if the result of determination in step S86 is that the number of moving pixels is less than the threshold value (NO in step S86), highlighting is not performed for that pixel area, and this flow ends.

  Next, the image processing for highlighting performed in step S87 of FIG. 8 will be described in detail using the flowchart of FIG. FIG. 10 is a detailed flowchart of a processing procedure for highlighting a portion with a large movement.

  The main cause of pixel movement is the influence of imaging blur caused by the light receiving time of the image sensor and the amount of motion of the subject when image data is generated. According to the present embodiment, a predetermined pattern is synthesized as in the process of FIG. 10 at a portion where the high frequency component is reduced when an interlaced image is converted into a progressive image due to the movement of the subject. Can be highlighted.

In FIG. 10, the IP conversion circuit 107 converts two consecutive field images constituting the input interlaced image into a progressive image (step S101).
Next, the IP conversion circuit 107 determines whether each pixel in the progressive image is a pixel moved by a threshold value or more according to the control information from the CPU 102 (step S102).

  If the pixel has not moved beyond the threshold (NO in step S102), the IP conversion circuit 107 outputs the pixel as it is (step S103). In other words, the pixel enhancement process with little motion is not performed.

  On the other hand, if the pixel has moved beyond the threshold value (YES in step S102), the IP conversion circuit 107 synthesizes a zebra pattern with the pixel in the specific area according to the control information from the CPU 102 (step S104). Here, the specific region is a pixel region in which the number of moving pixels is equal to or greater than a threshold value.

  Then, when the conversion processing of one progressive image and the image processing related to highlighting are completed, it is determined whether or not to proceed to the processing of the next frame (step S105). If a moving image is being played back, the process proceeds to the next frame (YES in step S105), and the process returns to step S101 to repeat the progressive image conversion process and the image process related to highlight display for the next and subsequent interlaced images.

  On the other hand, if the video is paused, the process does not proceed to the next frame (NO in step S105), and this flow ends. Even when the moving image is being reproduced, this flow is forcibly terminated when the reproduction is stopped.

  According to the present embodiment, in step S104, the progressive image combined with the zebra pattern is displayed on the display device 30 or the like, so that the region where the high frequency component is missing in the converted progressive image is clearly indicated to the user. be able to. In addition, since zebra pattern synthesis and non-synthesis can be selected for each pixel region of the progressively converted image, the zebra pattern can be displayed only in a portion with motion, and the portion with little motion can be displayed as the original image. . By performing such processing, the user can easily determine whether the desired subject is an image that sufficiently includes the high-frequency component or an image that lacks the high-frequency component.

  In the present embodiment, the CPU 102 controls display or non-display of a predetermined pattern (zebra pattern). In addition, the CPU 102 has a function of changing a threshold value for determining the amount of edge movement according to whether the moving image is being reproduced or the moving image is being paused.

  Further, the CPU 102 also has a function of changing a threshold value for determining the amount of edge movement according to the operation mode of the playback device 20 (moving image playback mode, still image playback mode, print image selection mode, etc.). Have. For example, in the moving image reproduction mode, a high threshold value is set so that only edge pixels that are extremely moving are highlighted.

  When a still image reproduction mode or a print image selection mode is executed, a low threshold value may be set so that the user can check the details of the image. As a result, when a still image is displayed or a print image is selected, the user will be able to select a progressive image that has the least movement and retains the highest frequency component. Note that the threshold may be set lower in the mode for selecting a print image than in the still image reproduction mode.

As described above, according to the present embodiment, it is possible to easily identify missing high-frequency components in an image obtained by converting an interlaced image into a progressive image. In addition, by specifying a portion where the motion between the field images is large, it is possible to generate or select a suitable progressive image with little motion.
(Another embodiment according to the present invention)
Each means constituting the image processing apparatus according to the embodiment of the present invention described above can be realized by operating a program stored in a RAM or ROM of a computer. This program and a computer-readable recording medium recording the program are included in the present invention.

  In addition, the present invention can be implemented as a system, apparatus, method, program, storage medium, or the like, and can be applied to a system composed of a plurality of devices. Moreover, you may apply to the apparatus which consists of one apparatus.

  In the present invention, a software program (in the embodiment, a program corresponding to the flowcharts shown in FIGS. 8 and 10) for executing each step in the above-described image processing method is directly or remotely supplied to the system or apparatus. To do. In addition, this includes a case where the system or the computer of the apparatus is also achieved by reading and executing the supplied program code.

  Therefore, the program code installed in the computer in order to realize the functional processing according to the embodiment of the present invention by the computer also realizes the present invention. That is, the computer program itself for realizing the functional processing according to the embodiment of the present invention is also included in the present invention.

In that case, as long as it has the function of a program, it may be in the form of object code, a program executed by an interpreter, script data supplied to the OS, and the like.
Various recording media can be used as a recording medium for supplying the program. For example, floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card, ROM, DVD (DVD-ROM, DVD- R).

  As another program supply method, a browser on a client computer is used to connect to an Internet home page. Then, the computer program itself according to the embodiment of the present invention or a compressed file including an automatic installation function can be downloaded from the homepage by downloading to a recording medium such as a hard disk.

  It can also be realized by dividing the program code constituting the program according to the embodiment of the present invention into a plurality of files and downloading each file from a different home page. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing according to the embodiment of the present invention by a computer is also included in the present invention.

  Further, the program according to the embodiment of the present invention is encrypted, stored in a storage medium such as a CD-ROM, distributed to users, and decrypted from a home page via the Internet for users who satisfy predetermined conditions. Download key information. It is also possible to execute the encrypted program by using the key information and install the program on a computer.

  In addition to the functions of the above-described embodiments being realized by the computer executing the read program, the OS running on the computer performs part or all of the actual processing. Also, the functions of the above-described embodiments can be realized.

  Further, the program read from the recording medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer. Thereafter, the CPU of the function expansion board or function expansion unit performs part or all of the actual processing based on the instructions of the program, and the functions of the above-described embodiments are realized by the processing.

It is a block diagram which shows the structural example of the image processing apparatus which concerns on embodiment of this invention. It is a figure which shows an example of an interlace image. (A) And (b) is a figure which shows the example of a field image, respectively. (A) And (b) is a figure which shows the example of the edge detection result of a field image, respectively. (A) And (b) is a figure which shows a mode that a part of edge detection result of the field image was expanded, respectively. It is a figure which shows the example when converting from an interlace image to a progressive image. It is a figure which shows the progressive image which synthesize | combined the zebra pattern in the part with the big motion. It is a flowchart which shows the outline of the process sequence which performs a motion determination and highlights the part with a big motion. It is a figure for demonstrating how to obtain | require the moving pixel number of an edge pixel. It is a detailed flowchart of the process sequence which highlights a part with a big motion.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Image processing apparatus 20 Playback apparatus 30 Display apparatus 101 Input terminal 102 Control circuit (CPU)
103 Memory 104 Data Bus 105 Decoder 106 Edge Detection Circuit 107 Interlace Progressive Conversion Circuit (IP Conversion Circuit)
108 Output terminal

Claims (12)

An image processing device for converting interlaced image data into progressive image data,
Detecting means for detecting a motion amount for each pixel between a plurality of field images constituting the interlaced image data;
A determination unit that determines a pixel region having a large movement by comparing the amount of movement of each pixel detected by the detection unit with a predetermined threshold;
Conversion means for converting the interlaced image data into progressive image data;
An image processing apparatus comprising: an image processing unit that synthesizes a predetermined pattern with respect to the pixel region having a large motion determined by the determination unit included in the progressive image converted by the conversion unit.   The image processing apparatus according to claim 1, wherein the detection unit detects an amount of movement of an edge included in each of the plurality of field images.   2. The determination unit according to claim 1, wherein the determination unit changes the predetermined threshold value depending on whether the interlaced image data is an image during moving image reproduction or an image during a moving image pause. 2. The image processing apparatus according to 2. Reproducing means for reproducing the interlaced image data,
3. The image according to claim 1, wherein the determination unit changes the predetermined threshold value when the reproduction unit is in a moving image reproduction mode and when the reproduction unit is in a still image reproduction mode. 4. Processing equipment.   5. The image processing apparatus according to claim 1, wherein the image processing unit synthesizes a zebra pattern as the predetermined pattern by superimposing the zebra pattern on the pixel region having a large movement. 6. An image processing device for converting interlaced image data into progressive image data,
Detecting means for detecting a motion amount for each pixel between a plurality of field images constituting the interlaced image data;
A determination unit that determines a missing portion of a high-frequency component of an image due to the movement between the plurality of field images by comparing the amount of movement of each pixel detected by the detection unit with a predetermined threshold;
Conversion means for converting the interlaced image data into progressive image data;
Image processing means comprising: an image processing means for synthesizing a predetermined pattern with respect to a portion lacking the high frequency component determined by the determination means included in the progressive image converted by the conversion means. apparatus.   The image processing apparatus according to claim 6, wherein the detection unit detects a motion amount of an edge included in each of the plurality of field images.   7. The determination unit according to claim 6, wherein the determination unit changes the predetermined threshold value between when the interlaced image data is an image during moving image reproduction and when the interlaced image data is an image during moving image pause. 8. The image processing apparatus according to 7. Reproducing means for reproducing the interlaced image data,
8. The image according to claim 6, wherein the determination unit changes the predetermined threshold value when the reproduction unit is in a moving image reproduction mode and when the reproduction unit is in a still image reproduction mode. Processing equipment.   The image processing apparatus according to claim 6, wherein the image processing unit synthesizes a zebra pattern as the predetermined pattern by superimposing the zebra pattern on a portion lacking the high frequency component. An image processing method for converting interlaced image data into progressive image data,
Detecting a motion amount for each pixel between a plurality of field images constituting the interlaced image data;
Determining a pixel area having a large movement by comparing the detected amount of movement for each pixel with a predetermined threshold;
Converting the interlaced image data into progressive image data;
And a step of synthesizing a predetermined pattern with the pixel region having a large motion included in the converted progressive image. An image processing method for converting interlaced image data into progressive image data,
Detecting a motion amount for each pixel between a plurality of field images constituting the interlaced image data;
Determining the missing portion of the high frequency component of the image by the motion between the plurality of field images by comparing the detected amount of motion for each pixel with a predetermined threshold;
Converting the interlaced image data into progressive image data;
And a step of synthesizing a predetermined pattern with a portion lacking the high frequency component included in the converted progressive image.

Images