JP2008233854A - Image signal processing device, image signal processing method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To achieve such a natural display equivalent to that of a CRT display device as looks as an image displayed by the CRT display device when an image signal is displayed by an FPD display device e.g. of a display type other than that of the CRT display device. <P>SOLUTION: An ABL processing part 33 applies a processing emulated from an ABL (Automatic Beam current Limiter) processing to an image signal, a VM processing part 34 applies a processing emulated from a VM (Velocity Modulation) processing to the processed image signal, and a CRT γ processing part 35 executes gamma correction for the processing image signal. This invention can be applied to the case that an image looking as an image displayed in the CRT is displayed in an LCD. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image signal processing device, an image signal processing method, and a program, and particularly includes, for example, ABL (Automatic Beam current Limiter) processing, VM (Velocity Modulation) processing, and CRT (Cathode Ray Tube) γ processing. By performing FPD (Flat Panel Display) signal processing, the FPD display device, which is an FPD display device, can perform natural display equivalent to the CRT display device, which is a CRT display device. The present invention relates to an image signal processing device, an image signal processing method, and a program.

  FIG. 1 shows an example of a conventional FPD display device (FPD display device) such as an LCD (Liquid Crystal Display).

  The brightness adjustment / contrast adjustment unit 11 adjusts the brightness of the image signal by applying an offset to the input image signal, and adjusts the contrast of the image signal by adjusting the gain. To the unit 12.

  The high image quality processing unit 12 performs high image quality processing represented by DRC (Digital Reality Creation). That is, the image quality improvement processing unit 12 is a processing block for obtaining a high quality image, and performs image signal processing including pixel number conversion on the image signal from the brightness adjustment contrast adjustment unit 11 to obtain γ This is supplied to the correction unit 13.

  Here, DRC is described as class classification adaptation processing in, for example, JP-A-2005-236634 and JP-A-2002-223167.

  The γ correction unit 13 performs a gamma correction process for adjusting the signal level of the dark part by signal processing in addition to the γ characteristic of the original phosphor (CRT light emitting part) because the dark part is difficult to see in the CRT display device. Processing block.

  Here, the LCD also has a processing circuit that adjusts the photoelectric conversion characteristics (transmission characteristics) of the liquid crystal to the γ characteristics of the CRT inside the LCD panel. Therefore, in conventional FPD display devices, γ correction processing is performed in the same way as CRT display devices. It is carried out.

  The γ correction unit 13 performs a gamma correction process on the image signal from the image quality improvement processing unit 12 and supplies the image signal obtained as a result to an LCD (not shown) such as an LCD. Thereby, an image is displayed on the LCD.

  As described above, in the conventional FPD display device, the image signal is directly input to the FPD through the image quality improvement process and the gamma correction process after the contrast and brightness adjustment processes are performed. (Figure 1)

  For this reason, in the FPD display device, the brightness of the input and the display image has a proportional relationship according to gamma, but the display image becomes an image that is too bright or glare compared to the CRT display device.

  Therefore, there is a method to adaptively improve the gradation expression without using a separate ABL circuit in the display device in which the gradation expression ability in the dark part has a panel characteristic lower than that of the CRT (for example, patent) Reference 1).

JP 2005-39817 A

  By the way, as described above, the image displayed on the FPD display device becomes an image that is too bright or glare compared to the CRT display device. Only the image signal processing system that processes only the signal is modified for FPD and installed in the FPD display device, so the CRT display device has a unique response not only in the image signal processing system but also in the drive system itself This is because the system structure of a display device by comprehensive signal processing including characteristics and drive system is not taken into consideration.

  The present invention has been made in view of such a situation, and when an image signal is displayed on a display method other than a CRT display device, for example, an FPD display device, the image appears on the CRT display device. Thus, a natural display equivalent to that of a CRT display device can be performed.

  The image signal processing apparatus or the program according to one aspect of the present invention can be viewed as an image displayed on the CRT display device when the image signal is displayed on a display device other than a CRT (Cathode Ray Tube). An image signal processing device that processes the image signal, an ABL processing unit that applies a process of emulating an ABL (Automatic Beam Current Limiter) process to the image signal, and an image signal processed by the ABL processing unit An image signal processing apparatus comprising: VM processing means for applying processing for emulating VM (Velocity Modulation) processing; and gamma correction means for performing gamma correction on the image signal processed by the VM processing means, Or it is a program which makes a computer function as an image signal processing apparatus.

  According to an image signal processing method of one aspect of the present invention, when an image signal is displayed on a display device other than a CRT (Cathode Ray Tube), the image signal is displayed so that the image signal can be seen on the CRT display device. An image signal processing method of an image signal processing apparatus for processing, wherein an image signal subjected to a process for emulating the ABL process is applied by applying a process for emulating an ABL (Automatic Beam Current Limiter) process to the image signal The image signal processing method includes a step of applying a process for emulating a VM (Velocity Modulation) process to the image signal and performing a gamma correction on the image signal subjected to the process for emulating the VM process.

  In one aspect of the present invention, a process of emulating ABL processing is applied to the image signal, and a process of emulating VM processing is applied to the image signal after the processing. Further, gamma correction is performed on the processed image signal.

  According to one aspect of the present invention, natural display equivalent to that of a CRT display device can be performed.

  Embodiments of the present invention will be described below. Correspondences between the constituent elements of the present invention and the embodiments described in the specification or the drawings are exemplified as follows. This description is intended to confirm that the embodiments supporting the present invention are described in the specification or the drawings. Therefore, even if there is an embodiment which is described in the specification or the drawings but is not described here as an embodiment corresponding to the constituent elements of the present invention, that is not the case. It does not mean that the form does not correspond to the constituent requirements. Conversely, even if an embodiment is described here as corresponding to a configuration requirement, that means that the embodiment does not correspond to a configuration requirement other than the configuration requirement. Not something to do.

An image signal processing apparatus or program according to an aspect of the present invention is provided.
When an image signal is displayed on a display device of a display method other than CRT (Cathode Ray Tube) (for example, an FPD display device having an FPD such as an LCD), the image signal can be seen as an image displayed on the CRT display device. An image signal processing device for processing
ABL processing means (for example, the ABL processing unit 33 in FIG. 2) that applies processing for emulating ABL (Automatic Beam Current Limiter) processing to the image signal;
VM processing means (for example, the VM processing unit 34 in FIG. 2) that applies processing for emulating VM (Velocity Modulation) processing on the image signal processed by the ABL processing means;
An image signal processing device comprising gamma correction means (for example, the CRTγ processing unit 35 in FIG. 2) for performing gamma correction on the image signal processed by the VM processing means, or causing a computer to function as an image signal processing device It is a program.

  In the VM processing unit, a luminance correction unit (for example, a correction unit that corrects an influence of a change in the deflection speed of the electron beam of the CRT display device on the luminance of the image signal processed by the ABL processing unit (for example, The luminance correction unit 210) of FIG. 5 can be provided.

  The VM processing means performs processing for emulating that the electron beam of the CRT display device spreads and collides with the phosphor of the CRT display device for the image signal processed by the ABL processing means. (Erectron Beam) processing means (for example, the EB processing unit 220 in FIG. 5) can be provided.

An image signal processing method according to one aspect of the present invention includes:
An image signal processing method for an image signal processing apparatus that processes an image signal so that the image is displayed on a CRT display device when the image signal is displayed on a display device other than a CRT (Cathode Ray Tube). Yes,
A process of emulating an ABL (Automatic Beam current Limiter) process is applied to the image signal (for example, step S13 in FIG. 4),
A process of emulating a VM (Velocity Modulation) process is applied to an image signal that has been processed to emulate the ABL process (for example, step S14 in FIG. 4),
Gamma correction is performed on the image signal that has been processed to emulate the VM processing (for example, step S15 in FIG. 4).
An image signal processing method including steps.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 2 shows a configuration example of an embodiment of an image signal processing device included in an FPD display device to which the present invention is applied.

  The image signal processing apparatus of FIG. 2 is displayed on a CRT display apparatus when an image signal is displayed on a display apparatus other than a CRT, that is, an FPD display apparatus having an FPD such as an LCD here. Process the image signal so that it looks like an image.

Before describing the image signal processing apparatus of FIG. 2, a CRT display apparatus that displays an image to be displayed by the image signal processing apparatus of FIG. 2, that is, a CRT emulated by the image signal processing apparatus of FIG. The display device will be described.

  FIG. 3 shows a configuration example of a CRT display device.

  In the CRT display device, the brightness adjustment contrast adjustment unit 51 and the image quality improvement processing unit 52 are the same as the brightness adjustment contrast adjustment unit 11 and the image quality improvement processing unit 12 of FIG. The processed image signal is supplied to the gain adjusting unit 53 and the image signal differentiating circuit 60.

  The gain adjustment unit (limiter) 53 limits the signal level of the image signal from the image quality improvement processing unit 52 by an ABL control signal from the ABL control unit 59 described later, and supplies the signal level to the γ correction unit 54. That is, the gain adjustment unit 53 adjusts the gain of the image signal from the image quality improvement processing unit 52 instead of directly limiting the amount of electron beam current of the CRT 56 described later.

  The γ correction unit 54 performs γ correction processing similar to that of the γ correction unit 13 of FIG. 1 on the image signal from the gain adjustment unit 53, and supplies the resulting image signal to the video amplifier 55. To do.

  The video amplifier 55 amplifies the image signal from the γ correction unit 54 and supplies it to the CRT 56 as a CRT drive image signal.

  On the other hand, an FBT (Flyback Transformer) 57 is a transformer for generating a horizontal deflection driving current for horizontal scanning of an electron beam and an anode voltage of a CRT (CRT) 56 in a CRT display device, and its output is It is supplied to the beam current detector 58.

  The beam current detection unit 58 detects the amount of electron beam current necessary for ABL control from the output of the FBT 57 and supplies it to the CRT 56 and the ABL control unit 59.

  The ABL control unit 59 measures the current value of the electron beam from the beam current detection unit 58 and outputs an ABL control signal for ABL control for controlling the signal level of the image signal to the gain adjustment unit 53.

  On the other hand, the image signal differentiating circuit 60 differentiates the image signal from the image quality enhancement processing unit 52 and supplies the differential value of the image signal obtained as a result to the VM drive circuit 61.

  A VM (Velocity Modulation) drive circuit 61 performs VM processing for changing the display luminance even for the same image signal by partially changing the deflection (horizontal deflection) speed of the electron beam in the CRT display device. In the CRT display device, VM processing is performed separately from the main horizontal deflection circuit (consisting of deflection yoke DY, FBT57, horizontal drive circuit (not shown), etc.) and dedicated VM coil (not shown) and VM drive. This is realized using the circuit 61.

  That is, the VM drive circuit 61 generates a VM coil drive signal for driving the VM coil based on the differential value of the image signal from the image signal differentiation circuit 60 and supplies the VM coil drive signal to the CRT 56.

  The CRT 56 includes an electron gun EG, a deflection yoke DY, and the like. In the CRT 56, the electron gun EG emits an electron beam according to the output of the beam current detection unit 58 and the CRT drive image signal from the video amplifier 55, and the electron beam becomes a magnetic field generated by the deflection yoke DY which is a coil. Accordingly, the horizontal and vertical directions are changed (scanned) and collided with the phosphor screen of the CRT 56 to display an image.

  Further, in the CRT 56, the VM coil is driven in accordance with the VM coil drive signal from the VM drive circuit 61, whereby the deflection speed of the electron beam is partially changed, and thereby displayed on the CRT 56, for example. The edge of the image is enhanced.

  As can be seen from FIG. 3, in the CRT display device, VM processing for partially changing the deflection speed and ABL processing (ABL control) for limiting the amount of current of the electron beam are performed in a path other than the path where the image signal is processed, A control signal that affects the image quality of the image displayed on the CRT 56 is created.

  To display images affected by VM processing and ABL processing with FPD, FPD is completely different from CRT and driving method. Therefore, VM processing and ABL processing are performed on the path where image signals are processed. It is necessary to take the form corresponding to the process.

  Therefore, in the image signal processing apparatus of FIG. 2, the image signal is converted in the processing order as shown in FIG. 2, thereby adapting to the FPD driving method and performing the same natural display as the CRT display apparatus. Make it possible.

  That is, in the image signal processing apparatus of FIG. 2, the brightness adjustment contrast adjustment unit 31 and the image quality improvement processing unit 32 perform the image adjustment processing on the image signal with the brightness adjustment contrast adjustment unit 11 of FIG. The same processing as that of each of the units 12 is performed and supplied to the ABL processing unit 33, the full screen brightness average level detection unit 36, and the peak detection differential control value detection unit 37.

  The ABL processing unit 33 obtains the same brightness characteristic as the CRT in the LCD, and the level of the image signal from the high image quality processing unit 32 when the image has a certain level of brightness (luminance and area). ABL emulation processing is performed to limit the above in accordance with control from the ABL control unit 38.

  Here, the ABL emulation process in FIG. 2 is a process for emulating the ABL process in FIG.

  That is, the ABL process performed in the CRT display device is a process that limits the current when the brightness (luminance and its area) exceeds a certain level so that the electron beam (current) does not become excessive in the CRT. The ABL processing unit 33 performs emulation of the ABL processing in FIG.

  In FIG. 2, the ABL processing unit 33 performs a process (ABL emulation process) for limiting the actual display brightness when an attempt is made to display a bright image with a large area by limiting the current of the electron beam in the CRT. As a process for limiting the signal level of the image signal, a non-linear operation process is performed.

  That is, in FIG. 2, the full screen brightness average level detection unit 36 detects the screen brightness and average level based on the image signal from the image quality enhancement processing unit 32, and detects the peak detection differential control value detection unit 37, and This is supplied to the ABL control unit 38. The ABL control unit 38 detects the screen brightness and its area from the screen brightness and average level detection results from the full screen brightness average level detection unit 36, and thereby controls the brightness on the screen. A signal is generated and supplied to the ABL processing unit 33. The ABL processing unit 33 realizes (emulates) ABL processing by performing the above-described non-linear operation on the image signal from the image quality improvement processing unit 32 based on the control signal from the ABL control unit 38.

  The image signal subjected to ABL processing by the ABL processing unit 33 is supplied to the VM processing unit 34.

  The VM processing unit 34 is a processing block for performing processing equivalent to the VM processing in the CRT display device of FIG. 3 on the image signal, and performs emulation of the VM processing performed in the CRT display device of FIG.

  That is, in FIG. 2, the peak detection differential control value detection unit 37 obtains a partial peak signal of the image signal and an edge signal obtained by differentiation of the image signal from the image signal from the image quality improvement processing unit 32. The full screen brightness average level detection unit 36 supplies the screen brightness and average level to the VM control unit 39. The VM control unit 39 partially outputs the image signal based on the partial peak signal of the image signal from the peak detection differentiation control value detection unit 37, the edge signal obtained by the differentiation of the image signal, the brightness of the screen, and the like. The VM control signal corresponding to the VM coil drive signal in the CRT display device is generated and supplied to the VM processing unit 34.

  The VM processing unit 34 partially changes the level of the image signal from the ABL processing unit 33 by the VM control signal generated by the VM control unit 39, that is, partial correction of the image signal, image signal Processes such as edge enhancement and peak enhancement.

  Here, in the CRT display device of FIG. 3, VM processing is performed to compensate for the lack of luminance change at the rise of the signal in the CRT 56. However, the correction is not applied to the image signal itself, but the deflection yoke DY is applied. The luminance is changed as a result by using a certain VM coil and changing the deflection speed (time) of the horizontal deflection peculiar to the CRT 56.

  The VM processing unit 34 calculates a correction value corresponding to a luminance change caused by the VM processing performed in the CRT display device, and performs a calculation process for correcting the image signal using the correction value. Emulation of VM processing.

  The CRT γ processing unit 35 includes a γ correction process including a process performed in a processing circuit (conversion circuit) for obtaining a γ characteristic equivalent to that of a CRT that a conventional LCD panel has in the panel, and a color. In order to perform temperature compensation processing, processing for adjusting the level of each color signal (component signal) is performed.

  Here, the CRTγ processing unit 35 in FIG. 2 is a part that corrects not only the characteristics of the CRT on the same LCD screen but also the electro-optical conversion characteristics necessary for expressing a plurality of display characteristics such as PDP and LED display. In this embodiment, processing necessary for matching the input voltage-transmittance characteristics of the LCD with the electro-luminance characteristics of the CRT is performed.

  That is, in FIG. 2, the display color temperature compensation control unit 40 divides the LCD display screen into a plurality of display areas, and each display area is displayed by a display device having a plurality of different display characteristics. Control to display the display color temperature of the display area that displays an image with the same image quality as the image that would be displayed on the CRT as the color temperature for the CRT in a system that presents an image with the same image quality as the wax image The signal is generated to perform control for adjusting the balance of each color signal (component signal), and is supplied to the CRTγ processing unit 35. The CRTγ processing unit 35 also performs a process of adjusting the balance of each color signal of the image signal from the VM processing unit 34 in accordance with the control signal from the display color temperature compensation control unit 40.

  Since the CRT, LCD, and PDP have different white balance, color temperature, and change in luminance with respect to each other, the display color temperature compensation controller 40 shown in FIG. 2 is required.

  For the processing performed by the CRTγ processing unit 35 in accordance with the control signal from the display color temperature compensation control unit 40, the gradation characteristics of each panel, which has been conventionally processed inside a flat panel such as an LCD, is converted to be equivalent to the CRT. Including the processing performed by the processing circuit, the processing for absorbing the difference in characteristics depending on the display panel is performed.

  Then, the CRTγ processing unit 35 performs the above processing on the image signal from the VM processing unit 34, and then supplies the processed image signal to an LCD (not shown) as an FPD for display.

  As described above, in the image signal processing apparatus of FIG. 2, not only the processing performed in the CRT display device is replaced with the image signal processing but also the processing procedure (the processing of the VM processing section 34 after the processing of the ABL processing section 33). The processing procedure of performing the processing of the CRTγ processing unit 35 after the processing of the VM processing unit 34 is also taken into consideration, so that the LCD display can be more accurately brought close to the image quality of the image displayed on the CRT display device. enable. Therefore, according to the image signal processing apparatus of FIG. 2, an image can be output to the LCD with display characteristics equivalent to those of a CRT.

  Further, according to the image signal processing apparatus of FIG. 2, it is possible to emulate display characteristics due to the difference in characteristics of the CRT itself, and it is possible to switch between different hues and textures on the same LCD. For example, it is possible to easily perform color adjustment and image quality adjustment at the time of transmission by comparing the difference in color development between the EBU phosphor and the general phosphor on the same screen.

  In addition, according to the image signal processing apparatus of FIG. 2, it is possible to easily confirm the difference due to the display characteristics of the LCD and the CRT.

  Furthermore, according to the image signal processing apparatus of FIG. 2, it becomes possible to display an image with the “preferred image quality” in the original sense.

  Further, according to the image signal processing apparatus of FIG. 2, by changing the processing range in the display screen, images displayed on display devices having different characteristics (for example, CRTs with different phosphors, LCDs and CRTs, etc.) Since it becomes possible to see at the same time, it can be easily used for purposes such as comparison and adjustment.

  Next, with reference to the flowchart of FIG. 4, the flow of processing for the image signal by the image signal processing apparatus of FIG. 2 will be described.

  When an image signal is supplied to the brightness adjustment / contrast adjustment unit 31, in step S11, the brightness adjustment / contrast adjustment unit 31 adjusts the brightness of the image signal supplied thereto, and further adjusts the contrast. The image quality enhancement processing unit 32 is supplied, and the process proceeds to step S12.

  In step S12, the image quality improvement processing unit 32 performs image signal processing including pixel number conversion on the image signal from the brightness adjustment contrast adjustment unit 11, and the image signal after the image signal processing is processed. The data is supplied to the ABL processing unit 33, the full screen brightness average level detection unit 36, and the peak detection differential control value detection unit 37, and the process proceeds to step S13.

  Here, the full screen brightness average level detection unit 36 detects the screen brightness and average level based on the image signal from the image quality enhancement processing unit 32, and detects the peak detection differential control value detection unit 37 and the ABL control unit. 38. The ABL control unit 38 generates a control signal for limiting the brightness on the screen based on the screen brightness and the average level detection result from the full screen brightness average level detection unit 36, and the ABL processing unit 33. To supply.

  Further, the peak detection differentiation control value detection unit 37 obtains a partial peak signal of the image signal or an edge signal obtained by differentiation of the image signal from the image signal from the image quality improvement processing unit 32 to obtain the full screen brightness. Along with the brightness and average level of the screen from the average level detection unit 36, it is supplied to the VM control unit 39. The VM control unit 39 uses the VM signal in the CRT display device based on the partial peak signal of the image signal from the peak detection differential control value detection unit 37, the edge signal obtained by the differentiation of the image signal, the brightness of the screen, and the like. A VM control signal corresponding to the coil drive signal is generated and supplied to the VM processing unit 34.

  In step S <b> 33, the ABL processing unit 33 applies a process of emulating ABL processing to the image signal from the image quality improvement processing unit 32.

  That is, the ABL processing unit 33 performs processing for emulating ABL processing (ABL emulation processing) such as limiting the level of the image signal from the image quality enhancement processing unit 32 according to control from the ABL control unit 38, The image signal obtained as a result is supplied to the VM processing unit 34.

  Then, the process proceeds from step S13 to step S14, and the VM processing unit 34 applies a process of emulating the VM process to the image signal from the ABL processing unit 33.

  That is, in step S14, the VM processing unit 34 emulates VM processing such as correcting the luminance of the image signal from the ABL processing unit 33 according to the VM control signal supplied from the VM control unit 39 (VM emulation). Rate processing), the image signal obtained as a result is supplied to the CRTγ processing unit 35, and the process proceeds to step S15.

  In step S <b> 15, the CRTγ processing unit 35 performs γ correction processing on the image signal from the VM processing unit 34, and further, according to the control signal from the display color temperature compensation control unit 40, the image signal from the VM processing unit 34. Color temperature compensation processing for adjusting the balance of each color signal is performed. Then, the CRTγ processing unit 35 supplies an image signal obtained as a result of the color temperature compensation process to an LCD (not shown) as an FPD for display.

  Next, FIG. 5 is a block diagram illustrating a configuration example of the VM processing unit 34 of FIG.

  In FIG. 5, the VM processing unit 34 includes a luminance correction unit 210 and an EB processing unit 220.

  The brightness correction unit 210 corrects the influence of the change in the deflection speed of the horizontal deflection of the electron beam of the CRT display device on the image signal supplied from the ABL processing unit 33 (FIG. 2). Correction processing is performed, and an image signal obtained as a result is supplied to the EB processing unit 220.

  That is, the luminance correction unit 210 includes a VM coefficient generation unit 211 and a calculation unit 212.

  The VM coefficient generator 211 is supplied with a VM control signal from the VM controller 39 (FIG. 2). The VM coefficient generation unit 211 generates a VM coefficient in accordance with the VM control signal from the VM control unit 39 and supplies the VM coefficient to the calculation unit 212.

  The arithmetic unit 212 is supplied with the VM coefficient from the VM coefficient generation unit 211 and the image signal from the ABL processing unit 33 (FIG. 2).

  The calculation unit 212 multiplies the image signal from the ABL processing unit 33 (FIG. 2) by the VM coefficient from the VM coefficient generation unit 211, thereby deflecting the horizontal deflection of the electron beam of the CRT display device for the image signal. Correction for the influence of the change in speed on the luminance is performed, and the corrected image signal is supplied to the EB processing unit 220.

  The EB processing unit 220 targets the image signal from the luminance correction unit 210 (the image signal processed by the ABL processing unit 33 and further processed by the luminance correction unit 210) as a result of the electron beam of the CRT display device being spread. Processing to emulate collision with the phosphor of the display device (EB (Erectron Beam) emulation processing) is performed and supplied to the CRTγ processing unit 35 (FIG. 2).

  As described above, the VM emulation processing performed by the VM processing unit 34 includes the luminance correction processing performed by the luminance correction unit 210 and the EB emulation processing performed by the EB processing unit 220.

  FIG. 6 shows an example of VM coefficients generated by the VM coefficient generator 211 in FIG.

  VM coefficient slows the deflection speed of horizontal deflection (horizontal deflection) in the CRT display device at the position of the pixel of interest (here, the pixel that corrects the brightness by VM processing) by the VM coil drive signal. By equivalently, in order to emulate VM processing that increases the luminance of the target pixel, a plurality of pixels arranged in the horizontal direction around the target pixel are set as luminance correction targets. It is a coefficient that is multiplied by the pixel value (luminance).

  In the VM coefficient generation unit 211, as shown in FIG. 6, the VM coefficient multiplied by the pixel value of the target pixel among the pixels whose luminance is to be corrected is set to a value of 1 or more and is multiplied by other pixels. The VM coefficient is set to a value of 1 or less so that the gain in the calculation unit 212 is 1.

  FIG. 7 shows a method for obtaining the VM coefficient generated by the VM coefficient generator 211 of FIG.

  That is, FIG. 7A shows the waveform of the voltage (deflection voltage) applied to the deflection yoke DY (FIG. 3) of the CRT display device.

  As shown in FIG. 7A, the deflection yoke DY (FIG. 3) is repeatedly applied with a deflection voltage that changes with a constant inclination with the elapse of time t in the horizontal scanning period.

  FIG. 7B shows a VM coil drive signal generated by the VM drive circuit 61 (FIG. 3) of the CRT display device.

  In the CRT display device, the VM coil in the deflection yoke DY (FIG. 3) is driven by the VM coil drive signal of FIG. 7B, and the deflection speed of the electron beam is as shown in FIG. 7C by the magnetic field generated by the VM coil. Partially changed.

  That is, FIG. 7C shows the time change of the horizontal position of the electron beam when the VM coil generates a magnetic field by the VM coil drive signal of FIG. 7B.

  The time variation of the horizontal position of the electron beam (inclination of the graph of FIG. 7C), that is, the deflection speed of the horizontal deflection of the electron beam is the section where the magnetic field is generated by the VM coil generating the magnetic field, etc. Is not constant (changes).

  FIG. 7D shows a differential value of a subtraction value obtained by subtracting the time change of the horizontal position of the electron beam in FIG. 7C from the time change of the horizontal position of the electron beam due to the deflection voltage of FIG. 7A.

  When the horizontal deflection of the electron beam is performed only by the deflection voltage of FIG. 7A, the phosphor of the CRT 56 (FIG. 3) of the CRT display device when the VM coil generates a magnetic field by the VM coil drive signal. The intensity (amount) of the electron beam that collides with the light beam, that is, the luminance (brightness) of the image displayed on the CRT 56 changes as shown in FIG. 7D.

  The VM coefficient generator 211 (FIG. 5) generates a value corresponding to the differential value of FIG. 7D as a VM coefficient.

  It should be noted that the specific value of the VM coefficient, the range of pixels to be multiplied with the VM coefficient (how many pixel values in the horizontal direction around the target pixel are multiplied by the VM coefficient), The pixel value (level) of the pixel to be determined is determined according to the specification of the CRT display device that emulates the display by the image signal processing device of FIG.

  Next, an EB emulation process performed by the EB processing unit 220 in FIG. 5 will be described.

  In the EB emulation process, as described above, a process of emulating that the electron beam of the CRT display device spreads and collides with the phosphor of the CRT 56 (FIG. 3) of the CRT display device is performed.

  That is, if a pixel (subpixel) corresponding to a phosphor to be irradiated with an electron beam is a pixel of interest, the spot shape of the electron beam becomes large when the intensity of the electron beam is large. Thus, not only the phosphor corresponding to the pixel of interest but also the phosphor corresponding to the surrounding pixels impacts the pixel values of the surrounding pixels. In the EB emulation process, a process for emulating the influence is performed.

  FIG. 8 shows the current (beam current) applied to the electron gun that irradiates the electron beam and the diameter (spot size) of the spot formed on the display screen of the CRT by the electron beam irradiated corresponding to the beam current. Shows the relationship.

  FIG. 8 shows the relationship between the beam current and the spot size for two types of CRTs.

  Although the relationship between the beam current and the spot size varies depending on the type of CRT and the setting of the maximum luminance, the spot size increases as the beam current increases. That is, if the luminance is large, the spot size is also large.

  Such a relationship between the beam current and the spot size is described in, for example, Japanese Patent Application Laid-Open No. 2004-39300.

  The CRT display screen is coated with red, green, and blue phosphors (fluorescent substances). The red, green, and blue phosphors are coated with red, green, and blue (for). When the electron beams collide with each other, red, green, and blue light are emitted, thereby displaying an image.

  In addition, the CRT has a color selection mechanism in which an opening through which an electron beam passes is provided so that red, green and blue phosphors are irradiated with the red, green and blue electron beams. Is provided on the display screen.

  FIG. 9 shows a color selection mechanism.

  That is, FIG. 9A shows a shadow mask which is one of color selection mechanisms.

  The shadow mask is provided with a hole as a circular opening, and an electron beam passing through the hole is irradiated to the phosphor.

  In FIG. 9A, a circle with no pattern indicates a hole for irradiating an electron beam to a red phosphor, and a circle with a hatched line irradiates an electron beam on a green phosphor. The black circles indicate the holes for irradiating the blue phosphor with the electron beam.

  FIG. 9B shows an aperture grill which is another one of the color selection mechanisms.

  The aperture grill is provided with a slit as an opening extending in the vertical direction, and the electron beam that has passed through the slit is irradiated onto the phosphor.

  In FIG. 9B, a square without a pattern is a slit for irradiating an electron beam to a red phosphor, and a rectangle with a diagonal line is a slit for irradiating an electron beam to a green phosphor. The black-painted squares indicate the slits for irradiating the blue phosphor with the electron beam.

  As described with reference to FIG. 8, the spot size of the electron beam increases as the luminance increases.

  FIG. 10 shows a spot of an electron beam formed on the color selection mechanism when the luminance is medium, and FIG. 11 shows an electron beam spot formed on the color selection mechanism when the luminance is high. Each spot is schematically shown.

  10A and 11A show electron beam spots formed on the shadow mask when the color selection mechanism is a shadow mask, and FIGS. 10B and 11B show the aperture grille. , The electron beam spot formed on the aperture grille is shown.

  The higher the brightness, the greater the intensity of the central part of the electron beam (spot), and the intensity of the peripheral part of the electron beam is increased in accordance with the intensity of the electron beam. The spot size of the beam spot becomes large. As a result, the electron beam is applied not only to the phosphor corresponding to the pixel of interest (pixel corresponding to the phosphor to be irradiated with the electron beam) but also to the phosphor corresponding to pixels around the pixel of interest.

  FIG. 12 is a cross-sectional view showing a state in which an electron beam is irradiated when an aperture grill is employed as the color selection mechanism.

  That is, FIG. 12A shows a state in which the electron beam is irradiated when the beam current has the first current value, and FIG. 12B shows a second current value in which the beam current is larger than the first current value. It shows how the electron beam is irradiated in the case of.

  In FIG. 12, the pixel corresponding to the green phosphor is the target pixel, and the electron beam when the beam current is the first current value is adjacent to the spot size as shown in FIG. 12A. It falls within the range between the slits, and only the phosphor corresponding to the target pixel is irradiated, and the other phosphors are blocked from being irradiated.

  On the other hand, the electron beam when the beam current is the second current value, as shown in FIG. 12B, the spot size does not fall within the range between adjacent slits, and only the phosphor corresponding to the pixel of interest. In addition, other phosphors are irradiated.

  That is, when the beam current is the second current value, the spot size of the electron beam has a size including other slits in addition to the slits of the phosphor corresponding to the target pixel. The light passes through another slit and is also irradiated to a phosphor other than the phosphor corresponding to the target pixel.

  As shown in FIG. 12B, the beam current when the electron beam passes through a slit other than the phosphor slit corresponding to the pixel of interest is the spot size of the electron beam and the slit width of the slit of the aperture grille. It depends on the relationship.

  In the EB emulation process, as described above, the electron beam is applied not only to the phosphor corresponding to the pixel of interest but also to other phosphors, and the influence on the image is reflected in the image signal. .

  Here, FIG. 13 shows an electron beam intensity distribution approximated by a two-dimensional normal distribution (Gaussian distribution).

  FIG. 14 shows the intensity distribution of the electron beam passing through the slit of the aperture grille among the electron beams of FIG.

  That is, FIG. 14A shows an intensity distribution of an electron beam that passes through the slit of the phosphor corresponding to the target pixel and an electron beam that passes through slits adjacent to the left and right of the slit.

  Most of the electron beam passes through the phosphor slit corresponding to the target pixel, but the remaining part of the electron beam passes to the left of the phosphor slit corresponding to the target pixel and to the right. The display passes through the adjacent right slit, and the display of the pixel corresponding to the phosphor of the left slit and the pixel corresponding to the phosphor of the right slit is affected by the electron beam that has passed therethrough.

  14B shows the intensity distribution of the electron beam that passes through the phosphor slit corresponding to the target pixel in the electron beam intensity distribution shown in FIG. 14A. FIG. 14C shows the left slit. And the intensity distribution of the electron beam passing through the right slit.

  FIG. 15 shows the distribution of the intensity of an electron beam having a higher intensity than that of FIG. 13 and the distribution of the intensity of the electron beam passing through the slit of the aperture grille.

  That is, FIG. 15A shows the distribution of the intensity of an electron beam having a higher intensity than that in FIG.

  The electron beam of FIG. 15A has a larger spot size (intensity or more than a predetermined value) than the electron beam of FIG.

  FIG. 15B shows the intensity distribution of the electron beam passing through the slit of the aperture grille among the electron beams of FIG. 15A.

  In FIG. 15B, compared with the case of FIG. 14, the intensity of the electron beam passing through the left slit and the right slit is large, and accordingly, the pixel corresponding to the phosphor of the left slit and the phosphor of the right slit This has a greater effect on the display with the pixels corresponding to.

  15C shows the intensity distribution of the electron beam passing through the phosphor slit corresponding to the target pixel in the electron beam intensity distribution shown in FIG. 15B, and FIG. 15D shows the left slit. And the intensity distribution of the electron beam passing through the right slit.

  FIG. 16 shows the electron beam intensity distribution shown in FIG. 13 and the electron beam intensity distribution of the electron beam passing through the slit of the shadow mask.

  That is, FIG. 16A shows the same electron beam intensity distribution as FIG.

  FIG. 16B shows the intensity distribution of the electron beam passing through the hole of the shadow mask among the electron beams of FIG. 16A.

  That is, FIG. 16B shows an intensity distribution of an electron beam that passes through a hole of the phosphor corresponding to the target pixel and an electron beam that passes through a hole around the hole (peripheral hole).

  FIG. 16C shows the distribution of the intensity of the electron beam passing through the hole of the phosphor corresponding to the target pixel in the distribution of the intensity of the electron beam shown in FIG. 16B, and FIG. 16D passes through the peripheral hole. The electron beam intensity distribution is shown.

  FIG. 17 shows the distribution of the intensity of an electron beam having a higher intensity than that of FIG. 16, and the distribution of the intensity of the electron beam that passes through the holes of the shadow mask.

  That is, FIG. 17A shows the distribution of the intensity of the electron beam having a higher intensity than that in FIG.

  The electron beam in FIG. 17A has a larger spot size (intensity or greater than a predetermined value) than the electron beam in FIG. 16A.

  FIG. 17B shows the intensity distribution of the electron beam passing through the hole of the shadow mask among the electron beams of FIG. 17A.

  In FIG. 17B, compared with the case of FIG. 16B, the intensity of the electron beam passing through the peripheral hole is larger. Therefore, the pixel corresponding to the phosphor in the peripheral hole is displayed more than in the case of FIG. 16B. It has a big impact.

  FIG. 17C shows the distribution of the intensity of the electron beam that passes through the hole of the phosphor corresponding to the target pixel in the distribution of the intensity of the electron beam shown in FIG. 17B, and FIG. The electron beam intensity distribution is shown.

  In FIG. 13 to FIG. 17, the scale in the height direction representing the intensity of the electron beam is compressed more than the scales in the x and y directions representing the position in order to make it easy to understand the spread of the electron beam spot. .

  By the way, the area of a certain section of the one-dimensional normal distribution (one-dimensional normal distribution) is calculated over the section in which the area of the probability density function f (x) of the expression (1) representing the one-dimensional normal distribution is to be obtained. It can be obtained by integrating.

・・・（１）

... (1)

Here, in Expression (1), μ represents an average value, and σ ² represents dispersion.

  As described above, when the electron beam intensity distribution is approximated by a two-dimensional normal distribution (two-dimensional normal distribution), a certain range of electron beam intensities has a probability of the equation (2) representing the two-dimensional normal distribution. The density function f (x, y) can be obtained by integrating over the range for which the intensity is to be obtained.

・・・（２）

... (2)

Here, in Expression (2), μ _x represents an average value in the x direction, and μ _y represents an average value in the y direction. Also, σ _x ² represents the variance in the x direction, and σ _y ² represents the variance in the x direction. ρ _xy represents a correlation coefficient in the x direction and the y direction (a value obtained by dividing the covariance in the x direction and the y direction by the product of the standard deviation σ _{x in the x} direction and the standard deviation σ _{y in the} y direction).

The average value (average vector) (μ _x , μ _y ) ideally represents the center position (x, y) of the electron beam. For simplicity of explanation, if the center position (x, y) of the electron beam is (0, 0) (origin), the average values μ _x and μ _y are zero.

In the CRT display device, the electron gun, the cathode, and the like are designed so that the electron beam spot is circular, and therefore the correlation coefficient ρ _{xy is set} to zero.

Assuming that the color selection mechanism is an aperture grille, the probability density function f (x, y) of the equation (2) with the average values μ _x and μ _y and the correlation coefficient ρ _xy being 0 is defined as a slit. The intensity (amount) of the electron beam passing through the slit can be obtained by integrating within the range of.

  That is, FIG. 18 is a diagram for explaining the integration for obtaining the intensity of the electron beam passing through the slit.

  FIG. 18A shows an integration interval in the x direction, which is the horizontal direction.

  The intensity of the electron beam that passes through the phosphor slit (target slit) corresponding to the target pixel is in the range of -S / 2 to + S / 2 in the x direction, where S is the slit width of the aperture grill slit. The probability density function f (x, y) can be obtained over a range of.

  The intensity of the electron beam passing through the left slit can be obtained by integrating the probability density function f (x, y) over the slit width of the left slit in the x direction. The intensity of the passing electron beam can be obtained by integrating the probability density function f (x, y) over the slit width of the right slit in the x direction.

  18A and 18C show the integration interval in the y direction, which is the vertical direction.

  As shown in FIG. 18B, the intensity of the electron beam passing through the slit of interest is obtained by integrating the probability density function f (x, y) over the range from −∞ to + ∞ in the y direction. Can do.

  For each of the intensities of the electron beams that pass through the left slit and the right slit, the probability density function f (x, y) is integrated over the range from −∞ to + ∞ in the y direction as shown in FIG. 18C. Can be obtained.

On the other hand, the intensity of the entire electron beam can be obtained by integrating the probability density function f (x, y) over the range from -∞ to + ∞ in both the x and y directions. The value is P ₀ .

Further, the intensity of the electron beam passing through the target slit together represent a P _1, the respective intensities of the electron beams passing through the left and right slits, and is represented as P _L and P _R.

In this case, the display of the pixel of interest, of the intensity P ₀ of the entire electron beam, only the intensity P ₁ is affected by the display of the pixel of interest, the entire electron beam of the intensity P _0, the intensity P _L but affect the display of the pixel (left pixel) corresponding to the phosphor of the left slit, the intensity P _R affects the display of the pixel (right pixel) corresponding to the phosphor of the left slit.

That is, when the intensity P ₀ of the entire electron beam is used as a reference, the display of the target pixel is affected by the electron beam intensity P ₁ / P ₀ , and the electron beam intensity P _L / P ₀ is the left pixel. And the electron beam intensity P _R / P ₀ affects the display of the right pixel.

Therefore, based on the display of the target pixel, the display of the target pixel affects the display of the left pixel by P _L / P ₀ / (P ₁ / P ₀ ), and the display of the right pixel includes P _R / Only P ₀ / (P ₁ / P ₀ ) is affected.

In the EB emulation process, for the left pixel, in order to reflect the influence of the display of the target pixel, the influence of the display of the target pixel P _L / P ₀ / (P ₁ / P ₀ ) is used for the EB emulation process. As the EB coefficient to be used, the pixel value of the left pixel is multiplied, and the resultant multiplication value is added to the (original) pixel value of the left pixel. Further, in the EB emulation processing, the same processing is performed using the influence of the display of the pixels around the left pixel, which affects the display of the left pixel, as an EB coefficient. The pixel value of the left pixel is calculated in consideration of the influence of the electron beam spreading at the time of display and colliding with the phosphor of the left pixel.

  Similarly, for the right pixel, the pixel value of the right pixel is determined in consideration of the influence of the electron beam spreading and colliding with the phosphor of the right pixel when displaying the pixels around the right element.

  Even when the color selection mechanism is a shadow mask, the EB coefficient used for the EB emulation process can be obtained in the same manner as in the case of the aperture grill. However, the integration of the shadow mask is complicated compared to the case of the aperture grill. For the shadow mask, it is easier to obtain the EB coefficient by the Monte Carlo method or the like from the hole position and the hole radius of the shadow mask, instead of using the above-described integration.

As described above, the EB coefficient can theoretically be obtained by calculation, but as shown in FIG. 8, the spot size of the electron beam varies depending on the beam current. Therefore, in order to obtain the EB coefficient, the variances σ _x ² and σ _y ² of the probability density function f (x, y) in the equation (2) that approximates the electron beam intensity distribution are determined for each beam current value. Need to change.

  In the above case, it is assumed that the angle of incidence of the electron beam on the color selection mechanism (aperture grille and shadow mask) is a right angle. The angle incident on the mechanism becomes shallower as the distance from the center of the display screen increases.

  That is, FIG. 19 shows a state where an electron beam is incident on an aperture grill as a color selection mechanism.

  FIG. 19A shows a state where an electron beam is incident on the aperture grill near the center of the display screen.

  As shown in FIG. 19A, near the center of the display screen, the electron beam is perpendicularly incident on the aperture grille.

  FIG. 19B shows a state in which the electron beam is incident on the aperture grill at a position away from the center of the display screen.

  As shown in FIG. 19B, at a position away from the center of the display screen, the electron beam is incident on the aperture grill at an angle inclined from the vertical.

  As shown in FIG. 19B, when the electron beam is incident on the aperture grill at an angle inclined from the vertical, the distribution of the intensity of the electron beam is the shape of the probability density function f (x, y) of the equation (2). Therefore, if the EB coefficient is calculated on the assumption that the electron beam is incident on the aperture grill perpendicularly, the accuracy of the EB coefficient is deteriorated.

  From the above, it is desirable to obtain the EB coefficient not only by calculation but also by experiment.

  Next, the EB emulation process performed by the EB processing unit 220 in FIG. 5 will be further described with reference to FIG. 20 and FIG.

  FIG. 20 shows the pixels and the intensity distribution of the electron beam.

  That is, FIG. 20A shows nine pixels A, B, C, D, F, G, H, and I having a horizontal × vertical of 3 × 3 with the pixel E as the center.

  Now, in FIG. 20A, attention is focused on the pixel E as the target pixel. In addition, the horizontal direction is the x direction, the vertical direction is the y direction, and the positions of the other pixels A to D and F to I are represented on the basis of the position (x, y) of the target pixel E.

  In this case, if the interval between the pixels is 1, the position of the pixel A is (x-1, y-1), the position of the pixel B is (x, y-1), and the position of the pixel C is (x + 1, y-1), the position of pixel D is (x-1, y), the position of pixel F is (x + 1, y), and the position of pixel G is (x-1, y + 1) In addition, the position of the pixel H is (x, y + 1), and the position of the pixel I is (x + 1, y + 1).

  Here, the pixel A is also referred to as a pixel A (x-1, y-1) using its position (x-1, y-1), and the pixel A (x-1, y-1) The value is also referred to as a pixel value A. The same applies to the other pixels B to I.

  20B and 20C schematically show the electron beam intensity distribution when displaying the target pixel E (x, y) in the CRT display device.

  That is, FIG. 20B shows the distribution in the x direction of the intensity of the electron beam when displaying the target pixel E (x, y), and FIG. 20C shows the electron beam when displaying the target pixel E (x, y). This represents the y-direction distribution of intensity.

  The larger the pixel value E of the target pixel E (x, y), the wider the electron beam as shown in FIGS. 20B and 20C, and the other pixels A (x−1, y−1) to D (x -1, y) and F (x + 1, y) through I (x + 1, y + 1) are affected.

  For this reason, the EB processing unit 220 in FIG. 5 uses an electron beam for displaying the target pixel E (x, y) as the other pixels A (x−1, y−1) to D (x−1, y). ) And F (x + 1, y) to I (x + 1, y + 1) are expressed as EB coefficients representing the degree of influence on the display of other pixels A (x-1, y-1) to D ( x-1, y) and F (x + 1, y) to I (x + 1, y + 1) by multiplying the pixel values A to D and F to I by the pixel of interest E (x, y) When the electron beam is displayed, other pixels A (x-1, y-1) to D (x-1, y) and F (x + 1, y) to I (x + 1, y + 1) ) To determine the influence that affects the display of other pixels A (x-1, y-1) to D (x-1, y) and F (x + 1, y) ) To I (x + 1, y + 1) after EB emulation processing is determined.

  FIG. 21 shows that the electron beam when displaying the target pixel E (x, y) is other pixels A (x-1, y-1) to D (x-1, y) and F (x + 1, A configuration example of a circuit for obtaining an influence (hereinafter, appropriately referred to as EB influence) that affects the display of y) to I (x + 1, y + 1) is shown.

  The pixel value A is in the arithmetic unit 242A, the pixel value B is in the arithmetic unit 242B, the pixel value C is in the arithmetic unit 242C, the pixel value D is in the arithmetic unit 242D, the pixel value E is in the EB coefficient generating unit 241, and the pixel value F Is supplied to the calculation unit 242F, the pixel value G is supplied to the calculation unit 242G, the pixel value H is supplied to the calculation unit 242H, and the pixel value I is supplied to the calculation unit 242I.

Based on the pixel value E, the EB coefficient generation unit 241 generates an electron beam for displaying the target pixel E (x, y) from the other pixels A (x−1, y−1) to D (x−1). , y) and F (x + 1, y) to I (x + 1, y + 1), which represent the degree of influence on the display A _EB , B _EB , C _EB , D _EB , F _EB , G _EB , H _EB , and I _EB are generated and supplied to the calculation units 242A, 242B, 242C, 242D, 242F, 242G, 242H, and 242I, respectively.

The arithmetic units 242A through 242D and 242F through 242I are supplied with the pixel values A through D and F through I, and the EB coefficients A _EB through D _EB and F _EB through I _EB from the EB coefficient generator 241. And values A ′ to D ′ and F ′ to I ′ obtained as a result are output as EB influence components.

  Pixel value E is output as it is, and other pixels A (x-1, y-1) to D (x-1, y) and F (x + 1, y) to I (x + 1, y + 1). ) Is added to the EB influence that affects the display of the target pixel E (x, y), and the added value is the EB emulation of the target pixel E (x, y). The pixel value after processing is used.

  FIG. 22 is a block diagram illustrating a configuration example of the EB processing unit 220 in FIG.

  In FIG. 22, the EB processing unit 220 includes an EB function unit 250, and the EB function unit 250 includes delay units 251 to 259, an EB coefficient generation unit 260, and a product-sum operation unit 261.

  For example, as shown in FIG. 20, the EB function unit 250 generates a pixel A (x-1, y) adjacent to the pixel E (x, y) when the electron beam when displaying the pixel E (x, y) is displayed. y-1) to D (x-1, y) and F (x + 1, y) to I (x + 1, y + 1) as affecting the display, i.e. pixel E (x, y ) For pixels A (x-1, y-1) to D (x-1, y) and F (x + 1, y) to I (x + 1) adjacent to the pixel E (x, y). , y + 1), the pixel value after the EB emulation processing of the pixel E (x, y) is obtained on the assumption that there is an EB influence from each.

  That is, the image signal is supplied to the EB function unit 250 from the luminance correction unit 210 (FIG. 5).

  In the EB function unit 250, the pixel values of the pixels constituting the image signal from the luminance correction unit 210 are supplied to the delay units 251, 253, and 258, the EB coefficient generation unit 260, and the product-sum operation unit 261 in the raster scan order. Is done.

  The delay unit 251 delays the pixel value from the luminance correction unit 210 by one line (horizontal line) and supplies the delayed pixel value to the delay unit 252. The delay unit 252 delays the pixel value from the delay unit 251 by one line and supplies it to the delay unit 254 and the product-sum operation unit 261.

  The delay unit 254 delays the pixel value from the delay unit 252 by one pixel, and supplies the delayed pixel value to the delay unit 255 and the product-sum operation unit 261. The delay unit 255 delays the pixel value from the delay unit 254 by one pixel and supplies it to the product-sum operation unit 261.

  The delay unit 253 delays the pixel value from the luminance correction unit 210 by one line and supplies the delayed pixel value to the delay unit 256 and the product-sum operation unit 261. The delay unit 256 delays the pixel value from the delay unit 253 by one pixel, and supplies the delayed pixel value to the delay unit 257 and the product-sum operation unit 261. The delay unit 257 delays the pixel value from the delay unit 256 by one pixel and supplies it to the product-sum operation unit 261.

  The delay unit 258 delays the pixel value from the luminance correction unit 210 by one pixel and supplies the delayed pixel value to the delay unit 259 and the product-sum operation unit 261. The delay unit 259 delays the pixel value from the delay unit 258 by one pixel and supplies it to the product-sum operation unit 261.

  Based on the pixel value from the luminance correction unit 210, the EB coefficient generation unit 260 generates the EB coefficient as described above for calculating the EB influence that the pixel value has on the adjacent pixel value, and performs the product-sum operation. To the unit 261.

  The product-sum operation unit 261 includes a total of eight pixel values including the pixel values from the luminance correction unit 210 and the pixel values from the delay units 252 to 255 and 257 to 259, and the EB coefficient generation unit 260. By multiplying the EB coefficient by the EB coefficient, the EB influence component affected by the pixel value delayed by the delay unit 256 is obtained from the eight pixel values, and the EB influence component is added to the pixel value from the delay unit 256. Thus, the pixel value after the EB emulation processing is obtained and output for the pixel value from the delay unit 256.

  Therefore, for example, if the pixel values A to I shown in FIG. 20 are supplied to the EB function unit 250 in the raster scan order, and now the pixel value I is supplied to the EB function unit 250, the output of the delay unit 255 Is the pixel value A, the output of the delay unit 254 is the pixel value B, the output of the delay unit 252 is the pixel value C, the output of the delay unit 257 is the pixel value D, the output of the delay unit 256 is the pixel value E, The output of the delay unit 253 is supplied to the pixel value F, the output of the delay unit 259 is supplied to the pixel value G, and the output of the delay unit 258 is supplied to the pixel value H.

  Further, the pixel value I supplied to the EB function unit 250 is supplied to the EB coefficient generation unit 260 and the product-sum operation unit 261.

  Since the EB coefficient generation unit 260 is supplied with the pixel values A to H before the pixel value I is supplied, the EB coefficient generation unit 260 determines that each of the pixel values A to I is an adjacent pixel value. An EB coefficient for determining an EB influence component that affects the product is generated and supplied to the product-sum operation unit 261.

  The product-sum operation unit 261 obtains an EB influence that the pixel value E from the delay unit 256 and the pixel values A to D and F to I from the EB coefficient generation unit 260 affect the pixel value E. The pixel values A to D and F to I are multiplied by the EB coefficients for obtaining the EB influences that affect the pixel value E, and added to the pixel value E from the delay unit 256. The added value is output as the pixel value after the EB emulation process for the pixel value E from the delay unit 256.

  Next, FIG. 23 shows another configuration example of the EB processing unit 220 in FIG.

  In the figure, portions corresponding to those in FIG. 22 are denoted by the same reference numerals, and description thereof will be omitted below as appropriate.

  That is, the EB processing unit 220 of FIG. 23 is different from the case of FIG. 22 in that it has the EB function unit 250 and is common to the case of FIG. 22 and further includes selectors 271 and 272.

  In the EB processing unit 220 in FIG. 23, the image signal from the luminance correction unit 210 (FIG. 5) is supplied to the selector 271.

  The selector 271 is also supplied with the image signal from the selector 272.

  The selector 271 selects one of the image signal from the luminance correction unit 210 or the image signal from the selector 272 and supplies the selected signal to the EB function unit 250.

  The selector 272 is supplied with the image signal after the EB emulation processing from the EB function unit 250.

  The selector 272 outputs the image signal from the EB function unit 250 as an image signal after final EB emulation processing or supplies the image signal to the selector 271.

  In the EB processing unit 220 configured as described above, the selector 271 first selects an image signal from the luminance correction unit 210 and supplies the image signal to the EB function unit 250.

  The EB function unit 250 performs EB emulation processing on the image signal from the selector 271 and supplies the image signal to the selector 272.

  The selector 272 supplies the image signal from the EB function unit 250 to the selector 271.

  The selector 271 selects the image signal from the selector 272 and supplies it to the EB function unit 250.

  As described above, in the EB function unit 250, when the EB emulation processing is repeatedly performed a predetermined number of times on the image signal from the luminance correction unit 210, the selector 272 receives the signal from the EB function unit 250. The image signal is output as an image signal after final EB emulation processing.

  As described above, the EB emulation process can be performed recursively.

  In FIG. 22, for simplicity of explanation, the electron beam when displaying the pixel E (x, y) is changed to the pixel A (x−1, y−) adjacent to the pixel E (x, y). 1) to D (x-1, y) and F (x + 1, y) to I (x + 1, y + 1) only affect the display, but the pixel E (x, y The pixel range in which the electron beam affects display is different for each electron beam intensity distribution.

  Next, FIG. 24 shows a configuration example of a portion that performs color temperature compensation processing of the CRTγ processing unit 35 of FIG.

  In FIG. 24, the control unit 281 is supplied with a control signal from the display color temperature compensation control unit 40 (FIG. 2), and the level shift unit 282 is supplied with an image signal from the VM processing unit 34 (FIG. 2). Color signals R (Red), G (Green), and B (Blue) are supplied.

  The control unit 281 controls the level shift unit 282 and the gain adjustment unit 283 based on the color temperature setting value represented by the control signal from the display color temperature compensation control unit 40.

  The level shift unit 282 performs level shift (addition) on the color signals R, G, and B from the VM processing unit 34 according to the control from the control unit 281 (DC bias in the CRT display device), and the result The obtained color signals R, G, B are supplied to the gain adjusting unit 283.

  The gain adjusting unit 283 adjusts the gains of the color signals R, G, and B from the level shift unit 282 according to the control from the control unit 281, and the resulting color signals R, G, and B are subjected to color temperature compensation. Output as processed color signals R, G, B.

  In addition, as a method of color temperature compensation processing, for example, methods described in Japanese Patent Application Laid-Open No. 08-163582 and Japanese Patent Application Laid-Open No. 2002-232905 can be employed.

  FIG. 25 illustrates another configuration example of the VM processing unit 34 in FIG.

  In the figure, portions corresponding to those of the VM processing unit 34 in FIG. 5 are denoted by the same reference numerals, and description thereof will be omitted below as appropriate.

  That is, the VM processing unit 34 in FIG. 25 has the same configuration as the VM processing unit 34 in FIG. 5 except that a luminance correction unit 310 is provided instead of the luminance correction unit 210 (FIG. 5). .

  FIG. 26 illustrates a configuration example of the luminance correction unit 310 of FIG.

  26, the luminance correction unit 310 includes a delay timing adjustment unit 311, a differentiation circuit 312, a threshold processing unit 313, a waveform shaping processing unit 314, and a multiplication circuit 315, for example, Japanese Patent Laid-Open No. 61-167280 ( (Japanese Patent Publication No. 05-84706) and International Publication No. WO00 / 010324 pamphlet, etc., perform luminance correction as emulation of VM processing (electron beam velocity modulation) in a CRT display device.

  That is, the image signal from the ABL processing unit 33 (FIG. 2) is supplied to the luminance correction unit 310, and the image signal is supplied to the delay timing adjustment unit 311 and the differentiation circuit 312.

  The delay timing adjustment unit 311 delays the image signal from the ABL processing unit 33 by a time corresponding to the time required for processing by the differentiation circuit 312, the threshold processing unit 313, and the waveform shaping processing unit 314, and sends it to the multiplication circuit 315. Supply.

  On the other hand, the differentiation circuit 312 first differentiates the image signal from the ABL processing unit 33 to detect an edge portion of the image signal, and obtains a differential value (differential value of the primary differentiation) of the edge portion. , And supplied to the threshold processing unit 313.

  The threshold processing unit 313 compares the absolute value of the differential value from the differentiating circuit 312 with a predetermined threshold value, and supplies only the differential value whose absolute value is larger than the predetermined threshold value to the waveform shaping processing unit 314. The luminance correction is limited to the edge portion where the absolute value of the differential value is equal to or less than a predetermined threshold value.

  Based on the differential value from the threshold processing unit 313, the waveform shaping processing unit 314 calculates a VM coefficient having an average value of 1.0 as a VM coefficient for performing luminance correction by multiplying the pixel value of the edge portion. Supply to circuit 315.

  The multiplication circuit 315 multiplies the pixel value of the edge portion in the image signal supplied from the delay timing adjustment unit 311 by the VM coefficient supplied from the waveform shaping processing unit 314, thereby correcting the luminance of the edge portion. Is supplied to the EB processing unit 220 (FIG. 25).

  Note that the VM coefficient calculated by the waveform shaping processing unit 314 can be adjusted according to the user's operation, for example, so that the brightness correction level of the edge portion matches the user's preference.

  In addition, the threshold processing unit 313 and the waveform shaping processing unit 314 set operating conditions according to the VM control signal supplied from the VM control unit 39 (FIG. 2).

  FIG. 27 shows an example of a VM coefficient calculated by the waveform shaping processing unit 314 and image signals before and after the luminance correction is performed using the VM coefficient.

  That is, FIG. 27A shows a first example of the VM coefficient.

  In FIG. 27A, the VM coefficient multiplied by the edge pixel value (the large pixel value of the large pixel value and the small pixel value constituting the edge) is 1.1, and the edge pixel value The VM coefficient multiplied by each of the pixel values adjacent to the left and right is 0.95.

  FIG. 27B shows a second example of the VM coefficient.

  In FIG. 27B, the VM coefficient multiplied by the edge pixel value is 1.2, and the VM coefficient multiplied by each of the pixel values adjacent to the left of the edge pixel value and further to the left, and the edge pixel value The VM coefficient multiplied by each pixel value adjacent to the right and further to the right is 0.95.

  FIG. 27C shows an image signal before luminance correction is performed.

  In FIG. 27C, an edge is between the third pixel value from the left and the fourth pixel value, and thus the fourth pixel value from the left is the edge pixel value.

  FIG. 27D shows an image signal obtained by performing luminance correction on the image signal of FIG. 27C using the VM coefficient of FIG. 27A.

  In the image signal of FIG. 27D, the fourth pixel value, which is the edge pixel value, is larger than that of the original image signal of FIG. 27C, and the third pixel value and the fifth pixel value from the left. Is small, and as a result, the edges are emphasized.

  FIG. 27E shows an image signal obtained by performing luminance correction on the image signal of FIG. 27C using the VM coefficient of FIG. 27B.

  In the image signal of FIG. 27E, the fourth pixel value, which is the edge pixel value, is larger than the original image signal of FIG. 27C, and the second, third, fifth, and sixth from the left. The second pixel value is smaller, and as a result, the edge is emphasized than in the case of FIG. 27D.

  Note that the VM coefficient in FIG. 27 is merely an example. In FIG. 27, the edge portion that changes from a dark image to a bright image when viewed from the left to the right is shown, but the luminance correction is similarly applied to the edge portion that changes from a bright image to a dark image. Done.

  Next, FIG. 28 shows another configuration example of the luminance correction unit 310 of FIG.

  In FIG. 28, the luminance correction unit 310 includes a tap selection unit 321, a class classification unit 322, a tap coefficient storage unit 326, and a prediction unit 327. For example, Japanese Unexamined Patent Publication No. 07-95591 (Japanese Patent No. 3271101) The luminance correction is performed using the DRC described in 1.

  Here, DRC will be described.

  DRC is a process of converting (mapping) a first image signal into a second image signal, and various signal processes can be performed depending on the definition of the first and second image data.

  That is, for example, if the first image signal is an image signal with a low spatial resolution and the second image signal is an image signal with a high spatial resolution, DRC can create (improve) the spatial resolution to improve the spatial resolution. It can be called processing.

  Further, for example, if the first image signal is a low S / N (Siginal / Noise) image signal and the second image signal is a high S / N image signal, the DRC removes noise. This can be called noise removal processing.

  Further, for example, if the first image signal is an image signal having a predetermined number of pixels (size) and the second image signal is an image signal in which the number of pixels of the first image signal is increased or decreased, DRC can be referred to as resizing processing for resizing (enlarging or reducing) an image.

  Also, for example, if the first image signal is a low time resolution image signal and the second image signal is a high time resolution image signal, DRC creates (improves) time resolution that improves time resolution. It can be called processing.

  Further, for example, the first image signal is a decoded image signal obtained by decoding an image signal encoded in units of blocks such as MPEG (Moving Picture Experts Group) encoding, and the second image signal. Is an image signal before encoding, it can be said that DRC is a distortion removal process for removing various distortions such as block distortion caused by MPEG encoding and decoding.

  In the spatial resolution creation process, when the first image signal, which is an image signal with low spatial resolution, is converted into the second image signal, which is an image signal with high spatial resolution, the second image signal is converted into the second image signal. An image signal having the same number of pixels as one image signal may be used, or an image signal having more pixels than the first image signal may be used. When the second image signal is an image signal having a larger number of pixels than the first image signal, the spatial resolution creation process is a process for improving the spatial resolution and resizing to increase the image size (number of pixels). It is also a process.

  As described above, according to DRC, various signal processes can be realized depending on how the first and second image signals are defined.

  In DRC, a target pixel of interest in the second image signal is selected for a class of tap coefficients and a target pixel obtained by classifying the target pixel into one of a plurality of classes. A pixel value (predicted value) of the target pixel is obtained by a prediction calculation using a plurality of pixels (pixel values thereof) of the first image signal.

  In FIG. 28, the image signal supplied from the ABL processing unit 33 (FIG. 2) to the luminance correction unit 310 of the VM processing unit 34 is supplied to the tap selection unit 321 as the first image signal.

  The tap selection unit 321 uses the image signal obtained by correcting the luminance of the first image signal from the ABL processing unit 33 as the second image signal, and sequentially configures the pixels constituting the second image signal. As the target pixel, some of the pixels (the pixel values) constituting the first image signal used for predicting the target pixel (the pixel value thereof) are selected as prediction taps.

  Specifically, the tap selection unit 321 selects a plurality of pixels of the first image signal that are spatially or temporally close to the temporal and spatial positions of the target pixel as prediction taps.

  Furthermore, the tap selection unit 321 selects some of the pixels constituting the first image signal used for classifying the target pixel into any of a plurality of classes as class taps. . That is, the tap selection unit 321 selects a class tap in the same manner as the tap selection unit 321 selects a prediction tap.

  Note that the prediction tap and the class tap may have the same tap structure (positional relationship with respect to the target pixel) or may have different tap structures.

  The prediction tap obtained by the tap selection unit 321 is supplied to the prediction unit 327, and the class tap obtained by the tap selection unit 321 is supplied to the class classification unit 322.

  The class classification unit 322 includes a class prediction coefficient storage unit 323, a prediction unit 324, and a class determination unit 325, classifies the target pixel based on the class tap from the tap selection unit 321, and sets the class as a result. The corresponding class code is supplied to the tap coefficient storage unit 326.

  Here, details of the class classification by the class classification unit 322 will be described later.

  The tap coefficient storage unit 326 stores a tap coefficient for each class obtained by learning, which will be described later, as a VM coefficient, and further corresponds to the class code supplied from the class classification unit 322 among the stored tap coefficients. The tap coefficient (the tap coefficient of the class represented by the class code supplied from the class classification unit 322) stored in the address to be output is output. This tap coefficient is supplied to the prediction unit 327.

  Here, the tap coefficient corresponds to a coefficient that is multiplied with input data in a so-called tap in the digital filter.

  The prediction unit 327 acquires the prediction tap output from the tap selection unit 321 and the tap coefficient output from the tap coefficient storage unit 326, and uses the prediction tap and the tap coefficient to predict the true value of the target pixel. Predetermined calculation for obtaining is performed. As a result, the prediction unit 327 calculates and outputs the pixel value (predicted value) of the pixel of interest, that is, the pixel value of the pixel constituting the second image signal, that is, the pixel value after luminance correction.

  Note that the class prediction coefficient storage unit 323, the prediction unit 324, and the tap coefficient storage unit 326 constituting the class classification unit 322 operate according to the VM control signal supplied from the VM control unit 39 (FIG. 2), respectively. Set conditions and make necessary selections.

  Next, learning of tap coefficients for each class stored as VM coefficients in the tap coefficient storage unit 326 in FIG. 28 will be described.

  The tap coefficient used for the predetermined prediction calculation of DRC is obtained by learning using a large number of image signals as image signals for learning.

  That is, for example, the image signal before luminance correction is set as the first image signal, and the luminance-corrected image signal obtained by performing luminance correction on the first image signal is used as the second image. In DRC, a prediction tap is selected from the first image signal as a signal, and the pixel value of the target pixel of the second image signal is obtained (predicted) by using the prediction tap and the tap coefficient. )

  If, for example, a linear primary prediction calculation is adopted as the predetermined prediction calculation, the pixel value y of the second image signal is obtained by the following linear primary expression.

・・・（３）

... (3)

However, in Expression (3), x _n is the _nth pixel of the first image signal (hereinafter, appropriately referred to as a pre-correction pixel) that constitutes the prediction tap for the target pixel y of the second image signal. It represents a pixel value, w _n denotes the n-th tap coefficient multiplied with the n-th pre-correction pixel (pixel value). In equation (3), the prediction tap is assumed to be composed of N pre-correction pixels x ₁ , x ₂ ,..., X _N.

  Here, the pixel value y of the target pixel of the second image signal may be obtained by a higher-order expression of the second or higher order, instead of the linear first-order expression shown in the expression (3).

Now, when the true value of the pixel value of the k-th sample of the second image signal is expressed as y _k and the predicted value of the true value y _k obtained by the equation (3) is expressed as y _k ′, the prediction error e _k is expressed by the following equation.

・・・（４）

... (4)

Now, since the predicted value y _k ′ of Expression (4) is obtained according to Expression (3), when y _k ′ of Expression (4) is replaced according to Expression (3), the following expression is obtained.

・・・（５）

... (5)

However, in Expression (5), x _{n, k} represents the n-th pre-correction pixel constituting the prediction tap for the pixel of the k-th sample of the second image signal.

Equation (5) prediction error e _k tap coefficients w _n to 0 (or formula (4)) is, is the optimal to predict the pixels of the second image signal, every second the pixels of the image signal, to determine such tap coefficients w _n is generally difficult.

Therefore, as the standard for indicating that the tap coefficient w _n is optimal, for example, when adopting the method of least squares, optimal tap coefficient w _n, the sum E of square errors expressed by the following formula It can be obtained by minimizing.

・・・（６）

... (6)

However, in Equation (6), K is the pixel y _k of the second image signal and the uncorrected pixels x _{1, k} , x ₂ that constitute the prediction tap for the pixel y _k of the second image signal _{. This} represents the number of samples (total number of learning samples) of _k ,..., xN _{, k} .

The minimum value of the sum E of square errors of Equation (6) (minimum value), as shown in Equation (7), given a material obtained by partially differentiating the sum E with the tap coefficient w _n by w _n to 0.

・・・（７）

... (7)

Therefore, when partial differentiation of above equation (5) by the tap coefficients w _n, the following equation is obtained.

・・・（８）

... (8)

  From the equations (7) and (8), the following equation is obtained.

・・・（９）

... (9)

To e _k of the formula (9), by substituting equation (5), equation (9) can be represented by normal equations shown in Equation (10).

・・・（１０）

... (10)

Normal equation of Equation (10), for example, by using a like sweeping-out method (Gauss-Jordan elimination method) can be solved for the tap coefficient w _n.

The normal equation of Equation (10), by solving for each class, the optimal tap coefficient (here, the tap coefficient that minimizes the sum E of square errors) to w _n, can be found for each class .

As described above, learning for determining the tap coefficient w _n, for example, can be performed by computer (FIG. 31) described later.

Next, a learning process (learning process) for obtaining the tap coefficient w _n performed by the computer will be described with reference to the flowchart of FIG.

  First, in step S21, the computer generates teacher data corresponding to the second image signal and student data corresponding to the first image signal from the learning image signal prepared in advance for learning. The process proceeds to step S22.

  That is, the computer uses the learning image signal as teacher data corresponding to the second image signal to be a teacher (true value) for learning the tap coefficient, and the mapping destination of the mapping as a prediction calculation according to the expression (3). A pixel value, that is, a pixel value after luminance correction is generated.

  Further, the computer generates a pixel value to be converted by mapping as a prediction calculation according to Equation (3) as student data corresponding to the first image signal, which is a student of learning of tap coefficients, from the learning image signal. To do. Here, for example, the computer uses the learning image signal as it is as student data corresponding to the first image signal.

  In step S22, the computer selects one of the teacher data that has not yet been set as the target pixel as the target pixel, and the process proceeds to step S23. In step S23, as with the tap selection unit 321 in FIG. 28, the computer selects a plurality of pixels to be predicted taps from student data and selects a plurality of pixels to be class taps from the student data, and performs processing. Advances to step S24.

  In step S24, the computer classifies the target pixel based on the class tap for the target pixel in the same manner as the class classification unit 322 in FIG. 28, obtains a class code corresponding to the class of the target pixel, and performs processing. Advances to step S25.

  In step S25, the computer performs addition of Expression (10) for the target pixel and the student data constituting the prediction tap selected for the target pixel for the class of the target pixel, and the processing is performed in step S26. Proceed to

That is, the computer uses the prediction tap (student data) x _{n, k} for the class of the pixel of interest, and multiplies (x _{n, k} x _{n ′, k} ) between the student data in the matrix on the left side of equation (10). , An operation corresponding to summation (Σ) is performed.

Further, the computer uses the prediction tap (student data) x _{n, k} and the teacher data y _k for the class of the pixel of interest _, and uses the student data x _{n, k} and the teacher data y _k in the vector on the right side of Equation (10). An operation corresponding to multiplication (x _{n, k} y _k ) and summation (Σ) is performed.

That is, in the class of the target pixel, the computer uses the left-side matrix component (Σx _{n, k} x _{n ′, k} ) and the right-side vector in Equation (10) obtained for the teacher data previously set as the target pixel. Component (Σx _{n, k} y _k ) is stored in its built-in memory (for example, RAM 104 in FIG. 31), and the matrix component (Σx _{n, k} x _{n ′, k} ) or vector component ( Σx _{n, k} y _k ), the corresponding component x _n calculated for the teacher data newly set as the pixel of interest using the teacher data y _{k + 1} and the student data x _{n, k + 1 , k + 1} x _{n ′, k + 1} or x _{n, k + 1} y _{k + 1} is added (addition represented by the summation of equation (10) is performed).

  In step S <b> 26, the computer determines whether there is teacher data that has not yet been set as the pixel of interest. If it is determined in step S26 that there is still teacher data that is not the pixel of interest, the process returns to step S22, and the same processing is repeated thereafter.

If it is determined in step S26 that there is no teacher data that is not a pixel of interest, the process proceeds to step S27, and the computer executes the formula (10) for each class obtained by the processes in steps S22 to S26 so far. By solving the normal equation for each class constituted by the matrix on the left side and the vector on the right side in), the tap coefficient w _n is obtained and output for each class, and the process is terminated.

The tap coefficient storage unit 326 of FIG. 28, the tap coefficient w _n for each class determined as described above is stored as VM coefficients.

  Next, class classification by the class classification unit 322 in FIG. 28 will be described.

  In the class classification unit 322, the class tap for the target pixel from the tap selection unit 321 is supplied to the prediction unit 324 and the class determination unit 325.

  The prediction unit 324 determines the pixel value of one of the plurality of pixels constituting the class tap from the tap selection unit 321, the pixel value of the other pixel, and the class prediction stored in the class prediction coefficient storage unit 323. The prediction is performed using the coefficient, and the predicted value is supplied to the class determination unit 325.

  That is, the class prediction coefficient storage unit 323 stores a class prediction coefficient used for predicting the pixel value of one pixel among a plurality of pixels constituting the class tap for each class.

Specifically, the class tap for the pixel of interest is composed of pixel values of M + 1 pixels, and the prediction unit 324, for example, has pixel values x ₁ , M + 1 of pixels constituting the class tap. Of _{M 2} ,..., x _M , x _{M + 1} , the M + 1-th pixel value x _{M + 1} is used as a prediction target, and the other M pixels x ₁ , x ₂ ,. , x _M is used to predict the M + 1-th pixel value x _{M + 1} to be predicted, the class prediction coefficient storage unit 323, for example, for the class #j, M pixels x ₁ , x ₂ ,..., x _M are stored as _M class prediction coefficients c _{j, 1} , c _{j, 2,.}

In this case, the prediction unit 324, for example, about class #j according to the formula x ′ _{j, M + 1} = x ₁ c _{j, 1} + x ₂ c _{j, 2} +... +, X _M c _{j, M} The prediction value x ′ _{j, M + 1} of the pixel value x _{M + 1} to be predicted is obtained.

For example, if the target pixel is classified into any one of J classes # 1 to #J by class classification, the prediction unit 324 predicts each of classes # 1 to #J. Values x ′ _{1, M + 1} to x ′ _{J, M + 1} are obtained and supplied to the class determining unit 325.

The class determination unit 325 uses the prediction values x ′ _{1, M + 1} to x ′ _{J, M + 1} from the prediction unit 324 as _{the M +} of the class tap prediction target for the target pixel from the tap selection unit 321, respectively. Compared with the _first pixel value (true value) x _{M + 1} , the prediction target M + 1-th pixel value x _M among the predicted values x ′ _{1, M + 1} to x ′ _{J, M + 1} Class #j of class prediction coefficients c _{j, 1} , c _{j, 2} ,..., C _{j, M} used to obtain the predicted value x ′ _{j, M + 1} with the smallest prediction error from ₊₁ Is determined as the class of the pixel of interest, and a class code representing the class #j is supplied to the tap coefficient storage unit 326 (FIG. 28).

Here, the class prediction coefficient c _{j, m} stored in the class prediction coefficient storage unit 323 is obtained by learning.

Learning to obtain the class prediction coefficient c _{j, m} can be performed by, for example, a computer (FIG. 31) described later.

A learning process (learning process) for _{obtaining the} class prediction coefficient c _{j, m} performed by the computer will be described with reference to the flowchart of FIG.

  In step S31, for example, similarly to step S21 in FIG. 29, the computer generates teacher data corresponding to the second image signal and student data corresponding to the first image signal from the learning image signal. Further, in step S31, the computer sequentially selects the teacher data as the pixel of interest, and for each pixel of interest, selects a plurality of pixels as class taps from the student data as in step S23 of FIG. 29. The process proceeds to step S32.

  In step S32, the computer initializes a variable j representing the class to 1, and the process proceeds to step S33.

  In step S33, the computer selects all the class taps obtained in step S31 as learning class taps (learning class taps), and the process proceeds to step S34.

In step S34, the computer, like the case of tap coefficient learning of FIG. 29, formula x ′ _{j, M + 1} = x ₁ c _{j, 1} + x ₂ c _{j, 2} +... +, X _M c _j, is determined according to _M, for the class #j, normal equation which minimizes the prediction error pixel value x _{M + 1} predictive value x _'j of the prediction _target, the _{M + 1,} relative to the true value x _{M + 1} (Normal equation corresponding to Expression (10)) is generated for the learning class tap, and the process proceeds to Step S35.

In step S35, the computer obtains a class prediction coefficient c _{j, m} for class #j by solving the normal equation obtained in step S34 (m = 1, 2,..., M). Proceed to step S36.

  In step S36, the computer determines whether or not the variable j is equal to the total number J of classes. If it is determined that the variable j is not equal, the process proceeds to step S37.

In step S37, the computer increments the variable j by 1, and the process proceeds to step S38, where the class prediction coefficient c _{j, m} obtained in step S35 is used and the learning class tap is set as the target of the prediction target. A prediction error when the pixel x _{M + 1} is predicted is obtained, and the process proceeds to step S39.

  In step S39, the computer selects a learning class tap whose prediction error obtained in step S38 is equal to or greater than a predetermined threshold value as a new learning class tap.

Then, the process returns from step S39 to step S34, and the class prediction coefficient c _{j, m} for class #j is obtained using a new learning class tap in the same manner as described above.

On the other hand, if it is determined in step S36 that the variable j is equal to the total number J of classes, that is, class prediction coefficients c _{1, m} to c _{J, m} are obtained for all J classes # 1 to #J. If so, the process ends.

  As described above, in the image signal processing apparatus of FIG. 2, in consideration of the fact that the CRT display device performs display by illuminating the phosphor with the electron beam, the processing performed when the electron beam is deflected, and the electron Since signal processing is performed in consideration of the influence of the physical shape of the beam and its changes on the display, an image with the same image quality as that displayed on a CRT display device must be displayed on an FPD display device using an LCD. Is possible.

  Further, according to the image signal processing apparatus of FIG. 2, it is possible to emulate display characteristics due to the characteristic difference of the CRT itself, and it is possible to switch between luminance characteristics and texture differences on the same LCD. For example, it is possible to easily perform color adjustment and image quality adjustment at the time of transmission by comparing the difference in color development characteristics between CRT for business use and CRT for general use (general use) on the same screen. Become.

  In addition, according to the image signal processing apparatus of FIG. 2, it is possible to easily confirm the difference due to the display characteristics of the LCD and the CRT.

  Furthermore, according to the image signal processing apparatus of FIG. 2, it becomes possible to display an image with the “preferred image quality” in the original sense.

  In addition, according to the image signal processing apparatus of FIG. 2, by simultaneously changing the processing range in the display screen, display devices having different characteristics (for example, CRT for business use and general use, LCD and CRT, etc.) can be viewed simultaneously. Therefore, it is possible to facilitate use in applications such as comparison and adjustment.

  Next, at least a part of the series of processes described above can be performed by dedicated hardware or can be performed by software. When a series of processing is performed by software, a program constituting the software is installed in a general-purpose computer or the like.

  FIG. 31 shows an example of the configuration of an embodiment of a computer in which a program for executing the series of processes described above is installed.

  The program can be recorded in advance on a hard disk 105 or a ROM 103 as a recording medium built in the computer.

  Alternatively, the program is stored temporarily on a removable recording medium 111 such as a flexible disk, a CD-ROM (Compact Disc Read Only Memory), a MO (Magneto Optical) disk, a DVD (Digital Versatile Disc), a magnetic disk, or a semiconductor memory. It can be stored permanently (recorded). Such a removable recording medium 111 can be provided as so-called package software.

  In addition to installing the program on the computer from the removable recording medium 111 as described above, the program can be wirelessly transferred from the download site to the computer via an artificial satellite for digital satellite broadcasting, LAN (Local Area Network), The program can be transferred to a computer via a network such as the Internet, and the computer can receive the program transferred in this way by the communication unit 108 and install it in the built-in hard disk 105.

  The computer includes a CPU (Central Processing Unit) 102. An input / output interface 110 is connected to the CPU 102 via the bus 101, and the CPU 102 operates an input unit 107 including a keyboard, a mouse, a microphone, and the like by the user via the input / output interface 110. When a command is input as a result, the program stored in a ROM (Read Only Memory) 103 is executed accordingly. Alternatively, the CPU 102 also transfers from a program stored in the hard disk 105, a program transferred from a satellite or a network, received by the communication unit 108 and installed in the hard disk 105, or a removable recording medium 111 attached to the drive 109. The program read and installed in the hard disk 105 is loaded into a RAM (Random Access Memory) 104 and executed. Thus, the CPU 102 performs processing according to the above-described flowchart or processing performed by the configuration of the above-described block diagram. Then, the CPU 102 outputs the processing result from the output unit 106 configured with an LCD (Liquid Crystal Display), a speaker, or the like, for example, via the input / output interface 110, or from the communication unit 108 as necessary. Transmission and further recording on the hard disk 105 are performed.

  Here, in this specification, the processing steps for describing a program for causing a computer to perform various types of processing do not necessarily have to be processed in time series according to the order described in the flowchart, but in parallel or individually. This includes processing to be executed (for example, parallel processing or processing by an object).

  Further, the program may be processed by a single computer, or may be processed in a distributed manner by a plurality of computers. Furthermore, the program may be transferred to a remote computer and executed.

  The embodiment of the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the gist of the present invention.

It is a block diagram which shows the structure of an example of the conventional FPD display apparatus. It is a block diagram which shows the structural example of one Embodiment of the image signal processing apparatus which the FPD display apparatus to which this invention is applied has. It is a block diagram which shows the structural example of a CRT display apparatus. It is a flowchart explaining the process of an image signal processing apparatus. 3 is a block diagram illustrating a configuration example of a VM processing unit 34. FIG. It is a figure which shows the example of VM coefficient. It is a figure explaining the method of calculating | requiring VM coefficient. It is a figure which shows the relationship between beam current and spot size. It is a figure which shows a color identification mechanism. It is a figure which shows the spot of an electron beam. It is a figure which shows the spot of an electron beam. It is sectional drawing which shows a mode that an electron beam is irradiated when an aperture grill is employ | adopted as a color selection mechanism. It is a figure which shows distribution of the intensity | strength of the electron beam approximated by two-dimensional normal distribution. It is a figure which shows distribution of the intensity | strength of the electron beam which passes the slit of an aperture grille. It is a figure which shows the distribution of the intensity | strength of an electron beam, and the distribution of the intensity | strength of the electron beam which passes the slit of an aperture grill among the electron beams. It is a figure which shows the distribution of the intensity | strength of an electron beam, and the distribution of the intensity | strength of the electron beam which passes the slit of a shadow mask among the electron beams. It is a figure which shows the distribution of the intensity | strength of an electron beam, and the distribution of the intensity | strength of the electron beam which passes the slit of a shadow mask among the electron beams. It is a figure explaining the integration which calculates | requires the intensity | strength of the electron beam which passes a slit. It is a figure which shows a mode that an electron beam injects into the aperture grill as a color selection mechanism. It is a figure which shows a pixel and distribution of the intensity | strength of an electron beam. It is a figure which shows the structural example of the circuit which calculates | requires EB influence part. 3 is a block diagram illustrating a configuration example of an EB processing unit 220. FIG. FIG. 10 is a block diagram illustrating another configuration example of the EB processing unit 220. 4 is a block diagram illustrating a configuration example of a portion that performs color temperature compensation processing of a CRTγ processing unit 35. FIG. 10 is a block diagram illustrating another configuration example of the VM processing unit 34. FIG. 3 is a block diagram illustrating a configuration example of a luminance correction unit 310. FIG. It is a figure explaining the process of brightness correction. FIG. 10 is a block diagram illustrating another configuration example of the luminance correction unit 310. It is a flowchart explaining the learning process which calculates | requires the tap coefficient as a VM coefficient. It is a flowchart explaining the learning process which calculates | requires a class prediction coefficient. It is a block diagram which shows the structural example of one embodiment of a computer.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 11 Brightness adjustment contrast adjustment part, 12 High image quality improvement processing part, 13 γ correction part, 31 Brightness adjustment contrast adjustment part, 32 High image quality improvement processing part, 33 ABL processing part, 34 VM processing part, 35 CRTγ processing part, 36 full screen brightness average level detection unit, 37 peak detection differential control value detection unit, 38 ABL control unit, 39 VM control unit, 40 display color temperature compensation control unit, 51 brightness adjustment contrast adjustment unit, 52 image quality enhancement processing Unit, 53 gain adjustment unit, 54 gamma correction unit, 55 video amplifier, 56 CRT, 57 FBT, 58 beam current detection unit, 59 ABL control unit, 60 image signal differentiation circuit, 61 VM drive circuit, 101 bus, 102 CPU, 103 ROM, 104 RAM, 105 hard disk, 106 output unit, 107 input unit, 108 communication unit, 109 drive, 110 input / output interface, 111 removable recording medium, 210 luminance correction unit, 211 VM coefficient generation unit, 212 calculation unit, 220 EB processing unit, 241 EB coefficient generation unit, 242A to 242D, 242F to 242I calculation unit, 251 to 259 delay unit, 260 EB coefficient generation unit, 261 product-sum operation unit, 271 and 272 selector, 281 control unit, 282 level shift unit, 283 gain adjustment unit, 310 brightness correction unit, 311 delay timing adjustment unit, 312 differentiation circuit, 313 threshold processing unit, 314 waveform shaping processing unit, 315 multiplication circuit, 321 tap selection unit, 322 class classification unit, 323 class prediction coefficient storage unit, 324 prediction unit, 325 class determination unit, 326 data Flop coefficient storage unit, 327 prediction unit

Claims (5)

In the image signal processing apparatus that processes the image signal so that the image is displayed on the CRT display device when the image signal is displayed on a display device other than the CRT (Cathode Ray Tube),
ABL processing means for applying processing for emulating ABL (Automatic Beam current Limiter) processing to the image signal;
VM processing means for applying processing for emulating VM (Velocity Modulation) processing on the image signal processed by the ABL processing means;
An image signal processing apparatus comprising: gamma correction means for performing gamma correction on the image signal processed by the VM processing means. The VM processing unit includes a luminance correction unit that corrects the influence of the change in the deflection speed of the electron beam of the CRT display device on the luminance of the image signal processed by the ABL processing unit. The image signal processing apparatus according to claim 1, wherein: The VM processing means performs EB (processing for emulating that the electron beam of the CRT display device spreads and collides with the phosphor of the CRT display device for the image signal processed by the ABL processing means. The image signal processing apparatus according to claim 1, further comprising an Erectron Beam) processing unit. In an image signal processing method of an image signal processing apparatus that processes an image signal so that the image is displayed on a CRT display device when the image signal is displayed on a display device other than a CRT (Cathode Ray Tube) ,
Applying processing to emulate ABL (Automatic Beam current Limiter) processing for the image signal,
Applying the process of emulating VM (Velocity Modulation) processing to the image signal that has been processed to emulate the ABL processing,
An image signal processing method comprising a step of performing gamma correction on an image signal that has been processed to emulate the VM processing. When an image signal is displayed on a display device other than a CRT (Cathode Ray Tube), the computer functions as an image signal processing device that processes the image signal so that the image is displayed on the CRT display device. In the program
ABL processing means for applying processing that emulates ABL (Automatic Beam current Limiter) processing to the image signal;
VM processing means for applying processing emulating VM (Velocity Modulation) processing on the image signal processed by the ABL processing means;
A program for causing a computer to function as gamma correction means for performing gamma correction on an image signal processed by the VM processing means.

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