JP7364250B2 - Video processing device, video processing method, video processing system, and video processing program - Google Patents

Description

The present invention relates to a video processing device, a video processing method, a video processing system, and a video processing program, and more particularly, to a technique for performing video processing on a video signal.

The correspondence between the luminance signal and the video signal is expressed using a dynamic range curve such as a gamma curve. In the dynamic range curve, most of the video signal is allocated to low-luminance signals. A dynamic range curve such as a gamma curve has a characteristic of asymptotic to L=0, where L is the luminance signal.

In order to appropriately perform video processing, it is necessary to perform video processing after converting a video signal into a luminance signal, and then perform inverse conversion to a video signal. In such a case, if the video signal is converted using a curve that asymptotically approaches L=0, there is a problem that the quantization error in the low luminance region becomes large.

Note that Patent Document 1 discloses a technique for appropriately inversely converting a gamma-corrected image in a display device whose luminance luminance characteristic is close to a straight line.

Japanese Patent Application Publication No. 2003-168109

As mentioned above, when video processing is performed, there is a problem in that the quantization error becomes large in low brightness areas.

The present invention was made to solve such problems, and provides a video processing device, a video processing method, a video processing system, and a video processing program that can reduce quantization errors in low brightness areas. The purpose is to provide.

The video processing device according to the present invention converts a video signal into a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal. a conversion unit,
a video processing unit that performs video processing on the luminance signal converted by the first conversion unit;
a second conversion unit that inversely converts the luminance signal subjected to image processing in the video processing unit into a video signal based on the following (Equation 1);
Equipped with

The video processing system according to the present invention includes:
A camera that outputs a video signal,
a video processing device;
Equipped with
The video processing device includes:
Convert the video signal to a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal,
Performing video processing on the converted luminance signal,
The luminance signal subjected to the video processing is inversely converted to a video signal based on the following (Equation 1).

The video processing method according to the present invention includes:
The computer is
Convert the video signal to a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal,
Performing video processing on the converted luminance signal,
The luminance signal subjected to the video processing is inversely converted to a video signal based on the following (Equation 1).

The video processing program according to the present invention includes:
to the computer,
A process of converting the video signal into a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal,
a process of performing video processing on the converted luminance signal;
A process of converting the video subjected to the video processing into a video signal based on the following (Formula 1),
Execute.

According to the present invention, it is possible to provide a video processing device, a video processing system, a video processing method, and a video processing program that can reduce quantization errors in low-luminance regions.

1 is a block diagram showing the configuration of a video processing device according to a first embodiment; FIG. 3 is a graph showing a dynamic range curve used by the video processing device according to the first embodiment. FIG. 2 is a block diagram showing the configuration of a video processing system according to a second embodiment. FIG. 3 is a schematic diagram schematically showing an example of the flow of processing in the video processing device according to the second embodiment. FIG. 2 is a schematic diagram showing a quantization error in a low-luminance region in a video processing device according to a related technique. 7 is a schematic diagram showing a quantization error in a low luminance region in the video processing device according to the second embodiment. FIG.

Embodiment 1
Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the configuration of a video processing device 1 according to the first embodiment. The video processing device 1 includes a first conversion section 11, a video processing section 12, and a second conversion section 13.

The video processing device 1 is a device that performs video processing on a video signal. The video signal may be, for example, an RGB (Red Green Blue) signal or a color difference signal. The relationship between the video signal and the original luminance signal is expressed using a dynamic range curve.

For example, in the SDI (Serial Digital Interface) system, which is mainstream in broadcasting equipment, a video signal is expressed in 10 bits. On the other hand, the dynamic range of the human eye is approximately 80 to 100 dB, which corresponds to a 13 to 17 bit signal. Therefore, if the luminance signal is simply quantized, the low luminance signal will be rounded to almost zero. Therefore, conversion using a dynamic range curve such as a gamma curve is performed.

(Equation 2) represents a dynamic range curve (also referred to as a gamma curve) used in gamma correction, where γ represents a gamma constant. V represents a video signal normalized to [0, 1], and L represents a luminance signal normalized to [0, 1].

Further, (Equation 3) represents a dynamic range curve used in the Hybrid Log-Gamma method, where a, b, and c are constants.

Further, the correspondence relationship between the video signal and the original luminance signal may be expressed using a dynamic range curve shown in (Equation 1). Here, γ is a constant. γ corresponds to the gamma constant used in (Equation 2). Note that, as will be described later, (Equation 1) represents a dynamic range curve used in the first conversion unit 11 and the second conversion unit 13.

Of course, the correspondence between the video signal and the original luminance signal is not limited to (Equation 1), (Equation 2), and (Equation 3). The video processing device 1 can perform video processing on a video signal based on an arbitrary dynamic range curve.

The first conversion unit 11 of the video processing device 1 converts the video signal into a brightness signal based on (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal. . Hereinafter, the process of converting a video signal into a luminance signal may be referred to as conversion, and the process of converting a brightness signal into a video signal may be referred to as inverse conversion.

In order to perform the conversion into a luminance signal, the constant γ needs to be appropriately selected. For example, the constant γ may be set to the same value as the gamma constant for gamma correction. The first conversion unit 11 may convert the video signal into a luminance signal using, for example, a lookup table corresponding to (Equation 1). The first conversion unit does not need to perform conversion after normalizing the video signal.

(Formula 2) and (Formula 3) have the characteristic that they asymptotically approach L=0 as L→0 by performing conversion related to exponentiation. On the other hand, (Equation 1) has a characteristic of asymptotic to V=γ*L as L→0. Therefore, the video processing device 1 can reduce quantization errors in low brightness areas. This point will be explained below with reference to graphs.

The horizontal axis in FIG. 2 represents the magnitude of the normalized luminance signal L. The vertical axis represents the magnitude of the normalized video signal V. A curve 21 shows a dynamic range curve expressed by (Equation 1) with γ=2.4. A straight line 22 indicates a straight line V=γ*L where the curve 21 asymptotically approaches from L→0. Further, a curve 23 indicates a dynamic range curve expressed by (Equation 2).

The curve 23 asymptotically approaches L=0 as L→0. Therefore, when a video signal is converted into a luminance signal using the curve 23, the video signal corresponding to low luminance is distorted (that is, converted to L=0). This increases the quantization error in related video processing methods. The same applies to related technologies using the Hybrid Log-Gamma method and other methods. On the other hand, in the video processing method according to the first embodiment, since the video signal is converted using the curve 21, the quantization error can be reduced.

Note that when the correspondence relationship between the original luminance signal and the video signal is expressed by (Equation 1), the first converter 11 can convert the video signal into the original luminance signal. Therefore, the video processing unit 12, which will be described later, can perform video processing more appropriately. In other cases, the luminance signal converted by the first converter 11 does not completely match the original luminance signal. However, even in such a case, it is possible to perform appropriate video processing using a signal close to the original luminance signal, and it is also possible to reduce the quantization error.

Returning to FIG. 1, the video processing section 12 performs video processing on the luminance signal converted by the first conversion section 11. The video processing unit 12 may perform, for example, a composition process such as chroma key composition, a resolution conversion process, or an I/P (Interlace/Progressive) conversion process. The video processing unit 12 may perform video processing, for example, in response to input from a user operating the video processing device 1.

The second conversion unit 13 inversely converts the luminance signal subjected to image processing by the image processing unit 12 into a video signal based on (Equation 1). Thereby, the second conversion unit 13 can generate a video signal subjected to video processing. The second conversion unit 13 may perform the inverse conversion using, for example, a lookup table corresponding to (Equation 1).

The video processing device 1 according to the first embodiment uses a dynamic range curve having linear characteristics in a low brightness region in video signal conversion (that is, video signal→luminance signal→video signal conversion and inverse conversion). Therefore, the video processing device 1 can reduce the quantization error in the low brightness region.

Note that the video processing device 1 includes a processor, a memory, and a storage device as components not shown. Further, the storage device stores a computer program in which the processing of the video processing method according to the first embodiment is implemented. Then, the processor loads a computer program from the storage device into the memory and executes the computer program. Thereby, the processor realizes the functions of the first conversion section 11, the video processing section 12, and the second conversion section 13.

Alternatively, the first conversion section 11, the video processing section 12, and the second conversion section 13 may each be realized by dedicated hardware. Further, part or all of each component may be realized by a general-purpose or dedicated circuit, a processor, etc., or a combination thereof. These may be composed of a single chip or a plurality of chips connected via a bus. Furthermore, as the processor, a CPU (Central Processing Unit), a GPU (Graphical Processing Unit), an FPGA (Field-Programmable Gate Array), a quantum processor (quantum computer control chip), etc. can be used.

Further, in the case where a part or all of each component of the video processing device 100 is realized by a plurality of information processing devices, circuits, etc., the plurality of information processing devices, circuits, etc. may be centrally arranged, It may also be distributed. For example, information processing devices, circuits, etc. may be realized as a client server system, a cloud computing system, or the like, in which each is connected via a communication network. Further, the functions of the video processing device 1 may be provided in a SaaS (Software as a Service) format.

Embodiment 2
Embodiment 2 is a specific example of Embodiment 1 described above. The video processing device according to the second embodiment performs video processing on a broadcast video signal. Video for broadcasting often requires high quality, and it is particularly desirable to reduce quantization errors in low brightness areas.

FIG. 3 is a block diagram showing the configuration of a video processing system 1000 according to the second embodiment. The video processing system 1000 may be included in a master system that adjusts the transmitted video with high precision. The video processing system 1000 includes a video processing device 100, a camera 200, and a transmitting station 300. The camera 200 captures a video for broadcasting and outputs a video signal to the video processing device 100 via a serial digital interface (SDI). Here, the camera 200 may output a video signal based on (Equation 1), for example. The transmitting station 300 includes electrical equipment for transmitting radio waves based on video signals.

The video processing device 100 is a specific example of the video processing device 1 described above. The video processing device 100 includes an input device 110, a first conversion section 120, a video processing section 130, and a second conversion section 140. The video processing device 100 may be installed, for example, in a master room within a broadcasting station. The input device 110 is hardware for a user to input, and may be, for example, a mouse or a keyboard.

The first converter 120 is a specific example of the first converter 11 described above. The first conversion unit 120 acquires a video signal from the camera 200, and converts the video signal into a luminance signal based on (Equation 1). The video processing unit 130 is a specific example of the video processing unit 12 described above. The video processing unit 130 performs video processing on the luminance signal converted by the first conversion unit 120 based on the input to the input device 110. The second conversion unit 140 is a specific example of the second conversion unit 13 described above. The second conversion unit 140 inversely converts the luminance signal subjected to image processing into a video signal based on (Equation 1). The video processing device 100 may output the inversely converted video signal to the transmitting station 300.

Next, with reference to FIG. 4, the flow of video processing performed by the video processing device 100 will be specifically described. FIG. 4 is a schematic diagram schematically showing the process of combining a background image with a person image. For example, in news programs and the like, it is common practice to combine a caster's video with a background video.

In such a case, the first conversion unit 120 first converts the background video (also referred to as a first video signal) based on (Equation 1) and outputs the luminance signal L1 (step S101). Further, the first conversion unit 120 converts the human image (also referred to as a second video signal) based on (Equation 1) and outputs the luminance signal L2 (step S102). Then, the video processing unit 130 performs a combining process to combine the brightness signal L1 and the brightness signal L2 according to the user's input, and outputs the brightness signal L3, which is a combined video (step S103). Finally, the second conversion unit 140 inversely transforms the luminance signal L3 based on (Equation 1) (step S104). Note that the luminance signals L1, L2, and L3 in FIG. 4 do not need to be normalized signals.

Next, the results of evaluating the magnitude of quantization error will be described with reference to FIGS. 5 and 6. Figure 5 is a schematic diagram showing the magnitude of quantization error when video is converted using (Formula 2), and Figure 6 is a schematic diagram showing the magnitude of quantization error when video is converted using (Formula 1). FIG. Here, the evaluation is performed with the constant γ=2.4 and the accuracy of the video signal and luminance signal as 876.

In order to evaluate the quantization error, we considered a case in which only video transformation and inverse transformation was performed without video processing. In the evaluation, brightness signals and video signals were normalized and calculated using mathematical formulas. However, as described above, in the embodiment, normalization and calculation using formulas may not be performed. Below, signals included in each of video signal space 1, luminance signal space, and video signal space 2 shown in FIGS. 5 and 6 will be explained in order.

First, the original signal Dv1 and the video signal V1 in the video signal space 1 will be explained. The original signal Dv1 is a digital signal representing a video signal. Among the values that the original signal Dv1 can take, the range from 0 to 20 is being considered as a low luminance region. The video signal V1 represents the original signal Dv1 normalized to [0,1].

Next, the luminance signal L in the luminance signal space and the quantized signal Dl (l represents EL) will be explained. The luminance signal L in FIG. 5 represents the video signal V1 converted based on (Equation 2). The luminance signal L in FIG. 6 represents the video signal V1 converted based on (Equation 1). The quantized signal Dl represents the luminance signal L as a digital signal. When (Formula 2) is used, the luminance signal L and quantization signal Dl are all 0, whereas when (Formula 1) is used, the luminance signal L and quantization signal Dl are 0. It turns out that there isn't.

Next, the video signal V2, quantized signal Dv2, and error in the video signal space 2 will be explained. The video signal V2 in FIG. 5 represents a video signal obtained by normalizing the quantized signal Dl and then inversely transforming it based on (Equation 2). The video signal V2 in FIG. 6 represents a video signal obtained by normalizing the quantized signal Dl and then inversely transforming it based on (Equation 1). The quantized signal Dv2 represents the video signal V2 as a digital signal. The error indicates the difference between the original signal Dv1 and the quantized signal Dv2, and represents the quantization error accompanying the conversion and inverse conversion of the video signal. When the related technology is used, as shown in FIG. 5, a quantization error of about 20 at most occurs. On the other hand, when (Equation 1) is used, the error is suppressed to about 1 at most. Therefore, it can be seen that by using the video processing device according to the second embodiment, the quantization error in the low luminance region can be reduced.

In addition, although the above-mentioned embodiment demonstrated as a hardware structure, it is not limited to this. The present disclosure can also realize arbitrary processing by causing the CPU to execute a computer program.

In the examples above, the program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-transitory computer readable medium or a tangible storage medium. By way of example and not limitation, computer readable or tangible storage media may include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD -Includes ROM, digital versatile disc (DVD), Blu-ray disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disc storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, transitory computer-readable or communication media includes electrical, optical, acoustic, or other forms of propagating signals.

Note that the present invention is not limited to the above embodiments, and can be modified as appropriate without departing from the spirit.

1 Video processing device 11 First conversion unit 12 Video processing unit 13 Second conversion unit 100 Video processing device 110 Input device 120 First conversion unit 130 Video processing unit 140 Second conversion unit 200 Camera 300 Transmission station 1000 Video processing system

Claims (9)

A first conversion unit that converts a video signal into a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal;
a video processing unit that performs video processing on the luminance signal converted by the first conversion unit;
a second conversion unit that inversely converts the luminance signal subjected to image processing in the video processing unit into a video signal based on the following (Equation 1);
An image processing device comprising:

The first conversion unit is
Obtaining a video signal based on the above (Formula 1) and converting it into a luminance signal based on the above (Formula 1);
The video processing device according to claim 1. The video signal is a video signal for broadcasting,
The video processing device according to claim 1 or 2. The video processing device outputs the inversely converted video signal to a transmitting station.
The video processing device according to claim 3. The first conversion unit is
Converting the first video signal to a first luminance signal based on the above (Formula 1), converting the second video signal to a second luminance signal based on the above (Formula 1),
The video processing unit includes:
performing video processing to synthesize the first luminance signal and the second luminance signal;
The video processing device according to any one of claims 1 to 4. A camera that outputs a video signal,
a video processing device;
Equipped with
The video processing device includes:
Convert the video signal to a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal,
Performing video processing on the converted luminance signal,
Inversely converting the luminance signal subjected to the video processing into a video signal based on the following (Equation 1),
Video processing system.

The camera is
outputting a video signal based on the above (Formula 1);
The video processing system according to claim 6. The computer is
Convert the video signal to a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal,
Performing video processing on the converted luminance signal,
Inversely converting the luminance signal subjected to the video processing into a video signal based on the following (Equation 1),
Video processing method.

to the computer,
A process of converting the video signal into a brightness signal based on the following (Equation 1), where γ is a constant, L is a normalized brightness signal, and V is a normalized video signal,
a process of performing video processing on the converted luminance signal;
A process of inversely converting the video subjected to the video processing into a video signal based on the following (Equation 1);
A video processing program that runs

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