JP2000013816A - Video signal converter, its method and served medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To generate a component video signal from a composite video signal by preventing dot disturbance. SOLUTION: A VIF 3 processes a signal received by a tuner 2 and a composite video signal is given to a classification adaptive processing circuit 11. The classification adaptive processing circuit 11 classifies the received composite video signal corresponding to the magnitude of clot disturbance and predicts and generates a component signal consisting of a luminance signal Y and color difference signals R-Y, B-Y by using a prediction coefficient corresponding to the class. A matrix circuit 6 generates primary color RGB signals from the component signal and provides an output of them to a CRT 7, on which the RGB signals are displayed.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a video signal converting apparatus and method, and a providing medium, and more particularly, to a method for directly converting a composite video signal into a baseband video signal by a class classification adaptive process. The present invention relates to a video signal conversion device and method, and a providing medium.

[0002]

2. Description of the Related Art FIG. 10 shows a configuration example of a conventional television receiver. The tuner 2 demodulates the signal received by the antenna 1 and generates a video intermediate frequency signal processing circuit (VIF)
Output to 3. The composite video signal processed and output by the VIF 3 is input to the Y / C separation circuit 4. Y /
The C separation circuit 4 separates the luminance signal Y and the chroma signal C from the input composite video signal, and outputs them to the matrix circuit 6 and the chroma demodulation circuit 5, respectively. The chroma demodulation circuit 5 demodulates the input chroma signal C, generates a color difference signal RY and a color difference signal BY, and supplies it to the matrix circuit 6. The matrix circuit 6
The input luminance signal Y and color difference signals RY, BY
, A primary color RGB signal is generated, output to the CRT 7 and displayed.

Next, the operation will be described. The tuner 2 receives the radio wave of the broadcasting station of the channel designated by the user via the antenna 1 and outputs the demodulated signal to the VIF 3. The VIF 3 processes the signal output from the tuner 2 and converts, for example, an NTSC composite video signal into a Y / C signal.
Output to the separation circuit 4. The Y / C separation circuit 4 separates a luminance signal Y and a chroma signal C from the composite video signal.

[0004] The chroma demodulation circuit 5 demodulates the chroma signal C input from the Y / C separation circuit 4 to generate a color difference signal RY and a color difference signal BY. The matrix circuit 6 has a Y /
The luminance signal Y supplied from the C separation circuit 4 and the color difference signals RY and BY input from the chroma demodulation circuit 5 are combined to generate primary color RGB signals, which are output to the CRT 7 for display.

[0005]

As described above, in the conventional television receiver, the composite video signal is first separated into the luminance signal Y and the chroma signal C by the Y / C separation circuit 4, and thereafter, The chroma signal C is demodulated and converted into a component signal composed of a baseband luminance signal Y and color difference signals RY and BY. Then, the primary color RGB signals are generated from the component signals by the matrix circuit 6. For this reason, there has been a problem that the circuit configuration becomes complicated, the scale thereof becomes large, and the cost increases.

Further, especially in the edge portion of an image or in a moving image portion, Y / Y values such as dot disturbance and cross color are considered.
There is a problem that the image quality is easily deteriorated due to the C separation error.

The present invention has been made in view of such circumstances, and has a simple configuration, a small-scale circuit configuration,
This is to enable a high-quality baseband video signal to be obtained.

[0008]

According to a first aspect of the present invention, there is provided a video signal conversion apparatus comprising: a classification means for classifying an input composite video signal; a storage means for storing prediction coefficients; and a classification means. Generating means for predictively generating a baseband video signal based on a prediction coefficient corresponding to the class.

According to a fifth aspect of the present invention, there is provided a video signal conversion method, comprising: a classification step of classifying an input composite video signal; a storage step of storing prediction coefficients; and a prediction coefficient corresponding to the class classified in the classification step. And a generation step of predictively generating a baseband video signal based on

According to a sixth aspect of the present invention, there is provided the providing medium, wherein a classification step of classifying the input composite video signal into a class, a storage step of storing a prediction coefficient, and a prediction coefficient corresponding to the class classified in the classification step. A computer-readable program that causes a video signal conversion device to execute a process including a generation step of predictively generating a baseband video signal.

[0011] In the video signal conversion apparatus according to the first aspect, the video signal conversion method according to the fifth aspect, and the providing medium according to the sixth aspect, the base is based on the prediction coefficient corresponding to the classified class. A video signal of the band is predicted and generated.

[0012]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described below. In order to clarify the correspondence between each means of the invention described in the claims and the following embodiments, each means is described. When the features of the present invention are described by adding the corresponding embodiment (however, an example) in parentheses after the parentheses, the result is as follows. However, of course, this description does not mean that each means is limited to those described.

The video signal conversion device according to the first aspect of the present invention includes a classification unit (for example, the pattern detection unit 52 in FIG. 2) for classifying the input composite video signal, and a storage unit (for example, for storing prediction coefficients). The coefficient memory 54 in FIG. 2)
And a generation unit (for example, the prediction calculation unit 56 in FIG. 2) that predictively generates a baseband video signal based on a prediction coefficient corresponding to the class classified by the classification unit.

According to a third aspect of the present invention, in the video signal conversion apparatus, the classification means includes a detection means for detecting a dot interference component (for example, the dot interference component detection circuits 22-1 and 22 in FIG. 5).
2) and determining means for determining the class based on the magnitude of the dot interference component detected by the detecting means (for example, the magnitude comparison circuit 31-1 in FIG. 5).

According to a fourth aspect of the present invention, in the video signal conversion device, the detecting means calculates the luminance signal component by adding the values of the plurality of pixels (for example, the adders 21-1 and 21 in FIG. 5).
-2) and extraction means for extracting a color signal component from the calculation result by the calculation means (for example, BPFs 23-1, 23-23 in FIG. 5)
2) and amplitude detecting means for detecting the amplitude of the color signal component extracted by the extracting means (for example, the amplitude detecting circuit 2 shown in FIG. 5).
4-1 and 24-2), and the determining means determines the class by comparing the magnitudes of the plurality of color signal components detected by the amplitude detecting means.

FIG. 1 is a block diagram showing a configuration example of a television receiver to which the present invention is applied, and portions corresponding to those in FIG. 10 are denoted by the same reference numerals. In this configuration example, between the VIF 3 and the matrix circuit 6,
A classification adaptive processing circuit 11 is provided. This class classification adaptive processing circuit 11 uses the NTS input from VIF3.
A component signal including a luminance signal Y and color difference signals RY and BY signals is directly generated from the C-system composite video signal by a class classification adaptive process. The prediction coefficient for predicting and generating a component signal from a composite video signal uses the component signal as a teacher signal,
An NTSC signal created by NTSC modulation of the component signal is generated by learning as a student image. Then, a component signal is generated by mapping (prediction calculation processing) using the prediction coefficient.

FIG. 2 shows an example of the configuration of the class classification adaptive processing circuit 11. The NTSC composite video signal output from the VIF 3 is divided into an area extracting section 51 and an area extracting section 5.
5 is supplied. The area extracting unit 51 extracts pixels (class taps) (FIG. 3) necessary for class classification from the input composite video signal, and outputs the pixels to the pattern detecting unit 52. The pattern detection unit 52 detects a pattern of the composite video signal based on the input class tap. Specifically, it will be described later with reference to FIG.
It is detected which pattern the size of the dot interference component belongs to.

A class code determining section 53 determines a class based on the pattern detected by the pattern detecting section 52 and stores a class code corresponding to the class in the coefficient memory 5.
4 is output. The coefficient memory 54 stores a prediction coefficient for each class obtained by learning in advance, reads a prediction coefficient corresponding to the class code input from the class code determination unit 53, and outputs the prediction coefficient to the prediction calculation unit 56. It has been made to be. How to determine the prediction coefficients in the coefficient memory 54 will be described later with reference to FIG.

The area extraction unit 55 extracts pixels (prediction taps) necessary for predictively generating a component signal from the composite video signal input from the VIF 3 and outputs the extracted pixels to the prediction calculation unit 56. The prediction calculation unit 56 multiplies the prediction tap input from the region extraction unit 55 by the prediction coefficient input from the coefficient memory 54, and generates a luminance signal Y which is one of the component signals.

Although not shown, the circuits for generating the other color difference signals RY and BY among the component signals have the same configuration. The configuration is the same as the case shown in FIG. 2, and the coefficient stored in the coefficient memory 54 is, in the case shown in FIG.
This is a prediction coefficient for generating the luminance signal Y. When the chrominance signal RY or BY is generated, the prediction coefficient for that is stored.

Next, the operation will be described. VIF3
The region extracting unit 51 extracts a class tap from the composite video signal input from the above. For example, as shown in FIG. 3, the class tap includes five pixels VO, VA to VD in a predetermined field, and a pixel VE corresponding to the target pixel VO one frame (two fields) before, which is a total of six pixels. It is said.

The pattern detecting section 52 performs a predetermined operation on the pixel data of the class tap input from the area extracting section 51 to detect a dot interference component, and detects the class interference based on the size of the dot interference component. The belonging pattern is detected (the details will be described later with reference to FIG. 5). The class code determination unit 53 determines a class corresponding to the pattern detected by the pattern detection unit 52, and outputs a class code corresponding to the class to the coefficient memory 54. The coefficient memory 54 reads out a prediction coefficient corresponding to the class code input from the class code determination unit 53 and outputs it to the prediction calculation unit 56.

The area extracting section 55 converts the composite video signal input from the VIF 3 into, for example, as shown in FIG.
11 neighboring pixels including the target pixel VO, 11 pixels centered on the pixel VE one frame before, and
A total of 23 values of DC offset components are extracted. Therefore, in this case, the coefficient memory 54 has 23 coefficients for one class.

The prediction operation unit 56 performs a product-sum operation on the 23 prediction coefficients input from the coefficient memory 54 with respect to the values of the 23 prediction taps input from the region extraction unit 55 to obtain a pixel of interest. A luminance signal Y corresponding to VO is generated.

The same processing is performed by the class classification adaptive processing circuit 11
This is also performed in a circuit that generates the color difference signals RY and BY. As a result, the luminance signal Y, the color difference signals RY,
A component signal composed of BY is generated and output.

Next, a method of class classification (pattern determination method) in the pattern detecting section 52 will be described. First, a method of classifying from the relationship between upper and lower pixels will be described.

Now, as shown in FIG. 3A, it is assumed that the pixel VA is located on one line of the target pixel VO in a predetermined field (0 field) and the pixel VB is located one line below. At this time, class classification processing is performed by a circuit configuration as shown in FIG.

That is, in the configuration example of FIG. 5, the pixel of interest VO and the pixel VA on one line are added by the adder 21-1 and input to the dot interference component detection circuit 22-1. . Dot interference component detection circuit 22
-1 is a band-pass filter (BPF) 23-1 for extracting a color subcarrier signal (a signal having a frequency fsc of 3.58 MHz) of the data input from the adder 21-1.
And an amplitude detection circuit 24-1 for detecting the amplitude of the output of the BPF 23-1. Amplitude detection circuit 24-1
Further includes an absolute value detection circuit (ABS) 25-1 for detecting the absolute value of the output of the BPF 23-1, and a low-pass filter (LPF) 2 for extracting a predetermined low-frequency component of the output of the ABS 25-1.
6-1.

The adder 21-2 adds the pixel of interest VO and the pixel VB one line below, and generates a dot interference component detection circuit 22.
-2. Like the dot interference component detection circuit 22-1, the dot interference component detection circuit 22-2 includes a BPF 23-2 and an amplitude detection circuit 24-2.
2 and the LPF 26-2.

The magnitude comparison circuit 31-1 is connected to the output of the dot disturbance component detection circuit 22-1 and the dot disturbance component detection circuit 2-1.
The output of 2-2 is compared in magnitude and the result of the comparison is output.

Next, the operation will be described. The adder 21-1 adds the pixel of interest VO and the pixel VA one line above the pixel of interest VO. Since the chroma signals of these two pixels have opposite phases, the value obtained by adding the two pixels is only a luminance signal component. This adder 21
Assuming that the output of -1 is YA, this signal YA has a frequency fsc of the color subcarrier when dot interference (crosstalk of the chroma signal component to the luminance signal component) exists.
(= 3.58 MHz). If there is no dot disturbance, the signal YA does not include this frequency component.

Therefore, this 3.5 is performed by the BPF 23-1.
The frequency component of 8 MHz is extracted, and its absolute value is calculated in the ABS 25-1. The signal Y'A obtained by further extracting the low-frequency component of the output of the ABS 25-1 by the LPF 26-1 is input to the magnitude comparison circuit 31-1.

Similarly, the adder 21-2 adds the pixel of interest VO and the pixel VB one line below, and converts the color subcarrier signal component included in the signal YB obtained as a result of the addition into the BPF 23-2. Is extracted by Then, the extracted color subcarrier signal component is set to ABS2
The signal is converted into an absolute value by 5-2, smoothed by the LPF 26-2, and input to the magnitude comparison circuit 31-1 as a signal Y'B.

For example, if there is a horizontal color edge (uncorrelated portion) between the pixel of interest VO and the pixel VA one line above it, the signal YA has a Y / C separation error. There is a 3.58 MHz dot interfering component. When a color edge exists between the target pixel VO and the pixel VA on one line, on the contrary, there is often no edge between the target pixel VO and the pixel VB one line below. If present, it means that there is a line having a width of one line, and such an extremely thin line image is not generally present in a normal image taken by a video camera or the like. It is.

Therefore, in such a case, the value of the signal Y'A (which contains many dot interference components) is larger than the value of the signal Y'B (which contains almost no dot interference components).

On the other hand, conversely, the target pixel VO, 1
When an edge in the horizontal direction exists between the pixel VB below the line and the pixel VB below the line, there is often no edge between the pixel of interest VO and the pixel VA on one line, so the signal Y ′
B (there are many 3.58 MHz dot interference components) becomes larger than the value of the signal Y'A (the 3.58 MHz frequency has little dot interference components).

The magnitude comparison circuit 31-1 compares the magnitudes of the signal Y'A and the signal Y'B, and determines to which pattern (class) the class tap belongs from the comparison result (class classification processing). Do).

That is, for example, the signal Y'A and the signal Y '
According to the size of B, three classes are classified as follows. N × Y′B <Y′A (1) Y′B / N ≦ Y′A ≦ N × Y′B (2) Y′A <Y′B / N (3) )

Note that N in the above equation is a constant, for example, N = 2.

Alternatively, they can be classified into five classes as follows. N2 × Y′B <Y′A (4) N1 × Y′B <Y′A ≦ N2 × Y′B (5) Y′B / N1 <Y′A ≦ N1 × Y ′ B (6) Y′B / N2 <Y′A ≦ Y′B / N1 (7) Y′A ≦ Y′B / N2 (8)

In the above equation, N1 and N2 are constants, for example, N1 = 2 and N2 = 3.

In the above description, the class is classified based on the vertical relationship between pixels.
Classification is also possible. Now, as shown in FIG. 3A, a pixel on the left side by two pixels of the target pixel VO (one pixel is a pixel sampled at a frequency of 4 fsc) is VC, and a pixel on the right side by two pixels is VD. . FIG. 6 shows a circuit for processing the pixel of interest VO and its left and right pixels VC and VD in the same manner as in FIG. The configuration of FIG. 6 is a circuit basically similar to that of FIG.

That is, the adder 21-3 outputs the target pixel V
O and two pixels VC on the left side are added. Since the chroma signal components of the two pixels have opposite phases, the output of the adder 21-3 is basically a luminance signal component YC. Similarly, the signal YD output by the adder 21-4 adding the pixel of interest VO and the pixel VD on the right by two pixels is also basically a luminance signal component.

As in the case described above, for example, when a color edge exists between the pixel of interest VO and the pixel VC two pixels to the left, the value of the signal YC is larger than the value of the signal YD. Conversely, if there is a color edge between the pixel of interest VO and the pixel VD on the right by two pixels, the signal YD
Becomes larger than the signal YC.

Therefore, as in the case of FIG. 5, FIG.
In this case, the dot interference component of the adder 21-3 is detected by the dot interference component detection circuit 22-3, and the dot interference component of the output of the adder 21-4 is detected by the dot interference component detection circuit 22-3.
4 to detect. Then, by the magnitude comparison circuit 31-2,
The output signal Y'C of the dot interference component detection circuit 22-3 is compared with the output signal Y'D of the dot interference component detection circuit 22-4.

The magnitude comparison circuit 31-2 performs a process of classifying into three classes according to, for example, the following conditions. N × Y′D <Y′C (9) Y′D / N ≦ Y′C ≦ N × Y′D (10) Y′C <Y′D / N (11) )

Further, similarly to the case described above, it is also possible to classify into five classes as follows. N2 × Y′D <Y′C (12) N1 × Y′D <Y′C ≦ N2 × Y′D (13) Y′D / N1 <Y′C ≦ N1 × Y ′ D (14) Y'D / N2 <Y'C ≤ Y'D / N1 (15) Y'C ≤ Y'D / N2 (16)

FIG. 7 shows an example of still another class classification in the pattern detecting section 52. In this example, in addition to the configuration shown in FIGS. 5 and 6, the adder 21-5 adds the pixel of interest VO and the pixel VE corresponding to the pixel of interest one frame (two fields) before. . When there is an uncorrelated pixel in the time direction, that is, when there is motion in the image, a dot disturbing component also occurs in the output signal YE of the adder 21-5. Therefore, the dot interference component of the signal YE is detected by the dot interference component detection circuit 22-5 to obtain the signal Y'E.

The magnitude comparison circuits 31-1 to 31-10 are
The magnitudes of any two outputs of the dot interference component detection circuits 22-1 to 22-5 are compared, and a class classification process is performed according to the comparison result. Each magnitude comparison circuit 31-i
Assuming that each of (i = 1 to 10) performs n class classifications, ten magnitude comparison circuits 31-1 to 31-1
If m combinations of -10 outputs are used and the combination is class-coded, n ^m classifications can be performed.

As described above, the class is classified based on the magnitude of the dot disturbance, and the component signal components are predicted and generated using the prediction coefficients corresponding to the class. Therefore, a component signal with little dot disturbance is generated. be able to.

Next, a method of obtaining a prediction coefficient to be stored in the coefficient memory 54 of FIG. 2 will be described. FIG. 8 shows a configuration example for obtaining such a prediction coefficient. The NTSC encoder 71 receives a component signal including a luminance signal Y and color difference signals RY and BY as teacher signals. The encoder 71 generates an NTSC composite video signal as a student signal from the input component signal, and outputs it to the region extracting unit 72 and the region extracting unit 75. The region extraction unit 72 extracts a class tap from the input composite video signal, and
3 is output. The pattern detection unit 73 detects the input pattern of the class tap, and outputs the detection result to the class code determination unit 74. Class code determination unit 74
Determines the class corresponding to the input pattern, and outputs the class code to the normal equation generating unit 76.

The area extracting section 75 extracts prediction taps from the composite video signal input from the encoder 71 and outputs the extracted taps to the normal equation generating section 76. The above-described region extraction unit 72, pattern detection unit 73, class code determination unit 74, and region extraction unit 75 are the region extraction unit 51, pattern detection unit 52,
It has basically the same configuration and function as the class code determination unit 53 and the area extraction unit 55.

The normal equation generation unit 76 calculates, for each class, pixel data (learning data) of a prediction tap input from the region extraction unit 75 and a teacher for all classes input from the class code determination unit 74. A normal equation is generated from the luminance signal Y of the component signal as a signal and output to the coefficient determination unit 77. When a required number of normal equations are supplied from the normal equation generation section 76, the coefficient determination section 77 solves the normal equations using, for example, the least squares method, and calculates prediction coefficients. The coefficient determining unit 77 supplies the prediction coefficient obtained by the calculation to the memory 78 and stores it.

Next, the operation will be described. The NTSC encoder 71 generates a composite video signal as a student signal from the input component signal as a teacher signal, and outputs the composite video signal to the region extracting unit 72 and the region extracting unit 75. The area extracting unit 72 extracts the class tap shown in FIG. 3 from the input composite video signal, and outputs the extracted class tap to the pattern detecting unit 73. The pattern detecting section 73 obtains the magnitude of the dot disturbance of the class tap according to the same rule as in the pattern detecting section 52 of FIG. 2, detects the class tap pattern from the magnitude, and determines the detection result as the class code Output to the unit 74. The class code determination unit 74 determines a class corresponding to the input pattern, and outputs a class code corresponding to the class to the normal equation generation unit 76.

The area extracting section 75 extracts the prediction tap shown in FIG. 4 from the input composite video signal, and outputs it to the normal equation generating section 76. Normal equation generator 76
Is supplied with the luminance signal Y of the teacher signal as it is. The normal equation generation unit 76 includes the class code determination unit 7
The normal equation in the class input from 4 is generated based on the luminance signal Y and the composite video signal (learning data) of the prediction tap, and the generated normal equation is output to the coefficient determination unit 77. The above processing is performed in response to various input teacher signals, and the coefficient determination unit 77 is supplied with a necessary number of normal equations for each class.

The coefficient determining unit 77 solves a normal equation for each class, obtains 23 prediction coefficients in this case for each class, supplies the prediction coefficients to the memory 78, and stores them.
The prediction coefficients stored in the memory 78 will be stored in the coefficient memory 54 of FIG.

In the above, the case where the prediction coefficient of the luminance signal Y is generated has been described, but the color difference signals RY, B
-Y is obtained in the same manner as in the case shown in FIG.

In the above description, the component video signal is generated from the composite video signal. For example, as shown in FIG. 9, a class classification adaptive processing circuit 11 is formed, and the primary color RGB is output from the composite video signal output from the VIF 3. The signal can be directly generated.

Note that a providing medium for providing a user with a computer program for performing the above-described processing includes:
In addition to recording media such as magnetic disks, CD-ROMs, and solid-state memories, communication media such as networks and satellites can be used.

[0060]

As described above, according to the video signal converter according to the first aspect, the video signal conversion method according to the fifth aspect, and the providing medium according to the sixth aspect, it is possible to correspond to the classified class. Since the baseband video signal is predicted and generated based on the prediction coefficient, the baseband video signal with suppressed Y / C separation error, in particular, dot disturbance, can be generated at a low cost with a simple configuration. It becomes possible. Also,
The circuit scale can be reduced, and the size and cost can be reduced.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration example of a television receiver to which the present invention has been applied.

FIG. 2 is a block diagram showing a configuration example of a class classification adaptive processing circuit 11 of FIG. 1;

FIG. 3 is a diagram illustrating a class tap.

FIG. 4 is a diagram illustrating a prediction tap.

FIG. 5 is a block diagram illustrating a configuration example of a pattern detection unit 52 in FIG. 2;

FIG. 6 is a block diagram illustrating another configuration example of the pattern detection unit 52 in FIG. 2;

FIG. 7 is a block diagram showing still another configuration example of the pattern detection unit 52 of FIG. 2;

FIG. 8 is a block diagram illustrating a configuration example of a circuit that determines a prediction coefficient.

FIG. 9 is a block diagram illustrating a configuration example of another television receiver to which the present invention has been applied.

FIG. 10 is a block diagram illustrating a configuration example of a conventional television receiver.

[Explanation of symbols]

1 antenna, 2 tuners, 3 VIF, 4Y
/ C separation circuit, 5 chroma demodulation circuit, 6 matrix circuit, 7 CRT, 11 class classification adaptive processing circuit,
21-1 to 21-5 adders, 22-1 to 22
-5 dot interference component detection circuits, 23-1 to 23-
5 BPF, 24-1 to 24-5 amplitude detection circuits, 2
5-1 to 25-5 ABS, 26-1 to 26-5 L
PF, 31-1 to 31-10 Large / Small comparison circuit

 ────────────────────────────────────────────────── ─── Continued on the front page (72) Hideo Nakaya, Inventor 6-7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Inside Sony Corporation (72) Inventor Takeharu Nishikata 6-35, Kita-Shinagawa, Shinagawa-ku, Tokyo No. 72 Inside Sony Corporation (72) Inventor Ken Ken Inoue 6-7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Sony Corporation (72) Naoki Kobayashi 6-35, 7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Soni -In-house (72) Inventor Tetsushi Kokubo 6-35, Kita-Shinagawa, Shinagawa-ku, Tokyo Sony Corporation F-term (reference) 5C066 AA03 BA02 CA07 EC13 EC14 EF03 GA01 GA02 GA04 GA05 KC02 KC04 KD02 KD06 KD08 KE01 KE02 KE04 KE07 KE17 KF05 KM12

Claims (6)

[Claims] 1. Classification means for classifying an input composite video signal into classes; storage means for storing prediction coefficients; and baseband video based on the prediction coefficients corresponding to the classes classified by the classification means. A video signal conversion device comprising: a generation unit that predictively generates a signal. 2. The video signal conversion device according to claim 1, wherein the baseband video signal is a component signal or an RGB signal. 3. The method according to claim 2, wherein the classifying unit includes a detecting unit configured to detect a dot interfering component, and a determining unit configured to determine the class based on a size of the dot interfering component detected by the detecting unit. The video signal conversion device according to claim 1. 4. An arithmetic unit for calculating a luminance signal component by adding values of a plurality of pixels; an extracting unit for extracting a color signal component from a calculation result by the arithmetic unit; Amplitude detecting means for detecting the amplitude of the extracted color signal component, wherein the determining means determines the class by comparing the magnitudes of the plurality of color signal components detected by the amplitude detecting means. The video signal conversion device according to claim 3, wherein: 5. A classification step of classifying an input composite video signal, a storage step of storing a prediction coefficient, and a baseband video based on the prediction coefficient corresponding to the class classified in the classification step. And a generating step of predictively generating a signal. 6. A classification step of classifying an input composite video signal into a class, a storage step of storing a prediction coefficient, and a baseband video based on the prediction coefficient corresponding to the class classified in the classification step. A providing medium for providing a computer-readable program for causing a video signal converter to execute a process including a generation step of predictively generating a signal.