Video display method, device, video display program

Abstract

Focusing on the fact that factors such as the brightness, display area, and display shape of still images also affect the surface temperature of the display panel (and thus the degree of burn-in), this invention provides a video display method and apparatus that can more effectively reduce burn-in. [Solution] This video display method divides a frame corresponding to an input video signal into multiple areas, detects a still image area, calculates the gradation value of the still image area, determines adjacent areas for each gradation (above a certain gradation) as the same group, changes the weighting of coefficients according to the area and / or shape of the grouped areas, and controls the level of the video signal displayed on the display image using the weighted coefficients.

Description

Technical Field

[0001] The present invention relates to a video display method, apparatus, and video display program.

Background Art

[0002] In an organic EL display, when the same image (for example, a still image such as a logo mark, a telop, an image representing time, etc.) is displayed in the same area of the screen for a long time, the deterioration of the organic material in the area where the still image has been displayed for a long time progresses. As a result, when another image is displayed in the area where the still image has been displayed for a long time, a phenomenon occurs in which the still image that has been displayed until then appears as a shadow or an afterimage. This phenomenon is so-called "burn-in", and various burn-in reduction methods have been applied conventionally.

[0003] As a method for reducing burn-in, for example, there is a method of detecting an area where a still image is displayed for a long time and reducing the luminance of this area. In this method, for example, a screen of 2048 (= 64 × 32) pixels is divided into a plurality of areas, and the average luminance of each area is detected. Then, an area where the average luminance between frames does not change for a long time is detected, and this area is specified as a still image area. Next, when the still image in this still image area continues and the luminance is high, control is performed to reduce the luminance of the image.

[0004] The control method of the display device of this mechanism determines this as a still image when an image such as a logo mark or a telop is displayed, and performs control for reducing burn-in.

[0005] Also, it is known from Patent Document 1 that burn-in occurs more rapidly as the temperature of the pixels of the display is higher, and there is also a control device that incorporates temperature information as a factor for determining burn-in reduction.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

[0007] As mentioned above, OLED displays require control devices to reduce burn-in, but there is a demand for more effective and efficient image display methods.

[0008] Therefore, in this embodiment, we focus on the fact that (a) the degree of burn-in tends to increase as the panel surface temperature rises, and (b) factors such as the brightness of the still image, the display area of ​​the still image, and the display shape of the still image also affect the panel surface temperature (and thus the degree of burn-in), and aim to provide a video display method, apparatus, and video display program that can more effectively reduce burn-in. [Means for solving the problem]

[0009] According to one embodiment, a video display method is provided which divides a frame corresponding to an input video signal into a plurality of blocks, detects still image blocks before and after the time axis of the frame, calculates the grayscale value of the still image block, distributes it into a predetermined range, groups adjacent still image blocks for each range, changes the weighting of coefficients according to at least the area of ​​the grouped area, and controls the level of the displayed video signal using the weighted coefficients. [Brief explanation of the drawing]

[0010] [Figure 1] Figure 1 is an explanatory diagram illustrating the configuration of the video display device according to this embodiment. [Figure 2] Figure 2 is an explanatory diagram illustrating an example of the basic concept for realizing this embodiment. [Figure 3] Figure 3 is an explanatory diagram illustrating a further example of the basic concept for realizing this embodiment. [Figure 4A]Figure 4A is a schematic diagram illustrating the signal processing by the frame splitter in the video display device shown in Figure 1. [Figure 4B] Figure 4B is a schematic diagram illustrating the signal processing status of the still image block detector in the signal processing of the video display device shown in Figure 1. [Figure 4C] Figure 4C is a schematic diagram illustrating an example of how the grayscale value calculation and grouping unit in the signal processing of the video display device shown in Figure 1 detects the grayscale value range and then groups the values ​​according to that range. [Figure 5A] Figure 5A is an explanatory diagram showing multiple still image areas formed by still image blocks, and each area shows the number of blocks (area) within that area. [Figure 5B] Figure 5B is an explanatory diagram that shows multiple areas within the still image area of ​​Figure 5A where blocks with a grayscale value of 50% or higher exist, as well as the number of blocks (area) within each area. [Figure 5C] Figure 5C is an explanatory diagram that shows multiple areas within the still image area of ​​Figure 5A or Figure 5B where blocks with a grayscale value of 75% or higher exist, and also shows the number of blocks (area) within each area. [Figure 5D] Figure 5D is an explanatory diagram showing an example of securing a square area, as indicated by the thick dotted line, within each area (the same applies to Figure 5B) where blocks with a grayscale value of 50% or more exist. [Figure 5E] Figure 5E is an explanatory diagram showing the state in which, as in Figure 5D, the areas that can be secured in each square area 731, 732, 734, 735, 736, and 737 are moved while additional squares are placed on top of them, and a number representing the side length of the square is assigned to each block where a square can be secured. [Figure 5F] Figure 5F is an explanatory diagram illustrating an example of how the coefficient calculator generates coefficients. [Modes for carrying out the invention]

[0011] The embodiments will be described below with reference to the drawings. <Example configuration of the embodiment> Figure 1 shows an example configuration of the video display device and video display method of the present invention. The video signal input circuit 101 receives video signals from a tuner that receives broadcast waves (not shown) and a communication device for connecting to the internet, and transmits the video signals to the time adjuster 102 and the splitter SA2 provided in the control device 200. The time adjuster 102 adjusts the timing so that the timing at which the control device 200 processes the frame to be displayed, calculates a coefficient for brightness correction, and transmits the calculated coefficient to the video brightness correction circuit 103 matches the timing at which the frame to be displayed transmitted from the video signal input circuit 101 is transmitted to the video brightness correction circuit 103.

[0012] The video brightness correction circuit 103 controls the brightness included in the video signal of the still image area where still images such as logos and text overlays are displayed, in response to coefficients transmitted from the coefficient calculator SA7, which will be described below. The video signal output from this video brightness correction circuit 103 is input to the organic EL display 104.

[0013] The control device 200 has a frame splitter SA2 that divides a frame into a plurality of blocks, and a still image block detector SA3 that detects whether the image within each block is stationary or nearly stationary. Furthermore, it has a gradation value calculator / grouping unit SA4. This gradation value calculator / grouping unit SA4 can detect the gradation values of the still image blocks respectively, and perform grouping by sorting the still image blocks for each gradation value range, for example, above a predetermined gradation value. The grouping information is transmitted to the area calculator SA6. The area calculator SA5 calculates the area of each grouped still image area in its own way, which is expressed by the number of blocks (to be described later by referring to FIGS. 5A, 5B, and 5C). The area information of the area calculator SA5 is transmitted to the coefficient calculator SA7 and the shape detector SA6. The shape detector SA6 has received the grouping information obtained by grouping blocks above a predetermined gradation value range and the previous area information. Then, in each grouped block area, the shape detector SA6, for example, fits a square block and adopts the number of blocks on one side of the square as the shape information. Furthermore, it uses its own technology by fitting a square block, shifting the square to fit, or reducing the size of the square to fit (for details, refer to FIGS. 5D and 5F and will be described later).

[0014] Hereinafter, the functions and operations of each part will be further described with reference to the image diagrams.

[0015] As shown in FIG. 4A, the frame splitter SA2 divides one frame 700 into a plurality of blocks. The number of divisions is such that if the number of horizontal and vertical pixels is X and Y respectively, Number of horizontal divisions = (number of horizontal pixels X / integer X1) Number of vertical divisions = (number of vertical pixels Y / integer Y1) where X1 and Y1 can be arbitrarily set according to the design. It is desirable to select X1 and Y1 so that one block approaches a square.

[0016] The still image block detector SA3 detects still image blocks using the frames divided into a plurality of blocks output from the frame divider SA2. For example, at a predetermined time t, the still image block detector SA3 compares the luminance of corresponding blocks between the blocks of the frame output from the frame divider SA2 at time t and the blocks of the frame output from the frame divider SA2 at time t-1 which is a time earlier than the predetermined time t.

[0017] If, as a result of comparing the luminance of corresponding blocks, the difference in luminance is within a predetermined value (for example, 10%, but can be changed depending on design, etc. and is not limited to this), the still image block detector SA3 determines that the block is a still image block. When it is determined that the block is a still image block, still image block identification information is assigned to the block determined to be a still image (block information or block address, etc.). As another method for detecting still images, there is also a method of using the output of a motion detector to determine an image area (block) with no motion as a still image. Also, in a video display device that already has a motion detector, there is also a method of using the output of the existing detector.

[0018] The gradation value calculation / grouping unit SA4 calculates the gradation value of each still image block and distributes each block to a predetermined range based on the calculated gradation value (for example, see FIG. 4C). That is, for each range, adjacent still image blocks in the same range are grouped.

[0019] The ranges for distribution are, for example 75% or more (for example, high gradation value) (still image block with reference numeral 701 in FIG. 4C), 50% or more (for example, medium gradation value) (still image block with reference numeral 702 in FIG. 4C), It is conceivable to define a range of 0% or more (for example, low gradation value) (the still image block labeled 703 in Figure 4C) ("%" represents the ratio of white to black colors in that block; the more white there is, the higher the ratio, and the more black there is, the lower the ratio). The gradation value range is determined by checking if the detected gradation value is 75% or higher. If it is 75% or higher, it is determined to be high gradation value. If it is not 75% or higher, it is checked if the gradation value is 50% or higher. If it is determined to be 50% or higher, it is determined to be medium gradation value, and if it is determined to be less than 50%, it is determined to be low gradation value. These high, medium, and low gradation values ​​will be referred to as gradation value range information. Figure 4C shows how still image blocks are divided into ranges according to their gradation values.

[0020] As described above, the grayscale value calculation and grouping device SA4 calculates the grayscale value of each block that is a still image by referring to the block information that has been determined to be a still image block, and performs grouping according to the range of grayscale values.

[0021] There are several ways to divide and group data based on its grayscale value range. Several methods are described below.

[0022] <Explanation of a method for efficiently detecting the range of grayscale values> For example, as shown in Figure 4C, 75% or more (e.g., high gradation value) (still image block labeled 701 in Figure 4C), 50% or more (e.g., medium gradation value) (still image block labeled 702 in Figure 4C), The system will assign values ​​of 0% or higher (for example, low grayscale values) (the still image block labeled 703 in Figure 4C).

[0023] In this case, first, the detection of blocks with low grayscale values ​​(corresponding to the detection of still image blocks (Figure 5A)) is confirmed. Next, block detection within the grayscale values ​​is performed while referring to the information of the still image blocks in Figure 5A (e.g., block address, block grayscale value information). Then, block detection with high grayscale values ​​is performed while referring to the information of the blocks within the grayscale values ​​(e.g., block address, block grayscale value).

[0024] Processing in the order of detecting blocks with low tonal values, blocks with medium tonal values, and blocks with high tonal values ​​yields efficient processing as follows: Specifically, grouping is performed to create groups with tonal values ​​of 50% or higher (including groups with tonal values ​​of 75% or higher), and then groups with tonal values ​​of 75% or higher. This reduces the number of blocks whose tonal value range needs to be checked as the number of sorting iterations increases, making it more efficient. However, the method for sorting the tonal value range is not limited to this approach.

[0025] For example, as explained below, group identification may be performed by scanning the blocks of the still image area shown in Figure 5A, starting from the top left block of the frame, through each block in the first row, each block in the second row, ..., each block in the bottom row, and the final block in the bottom right of the frame (this may also be called a method of grouping multiple grayscale value ranges with a single frame scan).

[0026] Another grouping method involves detecting groups 701 (high gradation value), 702 (medium gradation value), and 703 (low gradation value) by repeatedly scanning at different timings (this could also be called a method of grouping multiple gradation value ranges by scanning multiple frames).

[0027] <Explanation of how to group multiple grayscale value ranges using a single frame scan> The still image block detector SA3 detects the area of ​​the still image block shown in Figure 4B and provides still image block information that allows for the identification of the still image block to the grayscale value calculation and grouping unit SA4.

[0028] The SA4 grayscale value calculator and grouper scans the blocks to the left in order, starting from the first block in the upper left corner of the first row of the frame, and determines the grayscale value and its range for each block. If the range for each block is determined, it identifies the grayscale value range as attribute information for each block and adds the grayscale value identification information to the block information.

[0029] After determining the grayscale value range for the first row of blocks, the grayscale value range for the second row of blocks is determined. In this manner, the grayscale value range for the second row, the third row, ..., and so on, up to the last row of the frame, is determined.

[0030] The gradation value calculation and grouping device SA4 determines the gradation value range for each block and adds gradation value identification information based on the range information as attribute information to the block identification information of each block. As a result, as shown in Figure 4C, information identifying groups 701, 702, and 703 can be obtained.

[0031] <Explanation of the method for grouping multiple grayscale value ranges using multiple frame scans> <Formation of group 701 of blocks with high grayscale values ​​by the first scan> For example, as shown in Figure 4C, the grayscale value calculation and grouping unit SA4 detects the grayscale value range of block B(1,1) (address (X,Y)=(1,1)) on the left side of the screen (which may also be called a frame). If the grayscale value of block B(1,1) is in the high grayscale value range, then block B(1,1) is identified as group 701 of high grayscale values. Next, the grayscale value range of block B(2,1) (address (X,Y)=(2,1)), which is adjacent to the right of block B(1,1), is detected. If the grayscale value of block B(2,1) (address (X,Y)=(2,1)) is detected as being in the high grayscale value range, then block B(2,1) is also identified as group 701 of high grayscale values ​​by the grayscale value calculation and grouping unit SA4.

[0032] In this way, the grayscale value calculation and grouping unit SA4 detects the grayscale value range of the block to its right and groups (identifies) the blocks according to their grayscale value ranges, continuing this process up to the block located at the far right of the screen.

[0033] The gradation value calculation and grouping device SA4 detects the gradation value range up to block B(X,Y) located at the right edge of the screen (X,Y varies depending on the screen size, number of pixels, number of blocks, etc.). Then it detects the gradation value range of block B(1,2) (address (X,Y)=(1,2)), which is the second from the top of the screen and located at the left edge. For example, if block B(1,2) is in the high gradation value range, it identifies block B(1,2) as group 701 of the high gradation value group.

[0034] Subsequently, the range of grayscale values ​​is successively detected for each block located in the second row from the top of the screen, identifying blocks with high grayscale values, and identifying these blocks as group 701. Once the detection of blocks with high grayscale value ranges for all blocks in the second row is complete, the detection of high grayscale value ranges for all blocks in the third row is performed. In this way, blocks with high grayscale value ranges are detected for all blocks in the bottom row of the screen, making it possible to identify the block group with high grayscale values ​​as group 701. This 701, etc., may be called, for example, grayscale value range identification information (or group identification information).

[0035] If the range of the gradation value of the still image block being judged is lower than the range of the gradation value of the still image blocks judged up to that point (e.g., medium gradation value (group 702), low gradation value (group 703)), grouping will be performed using the same method as described above.

[0036] <Formation of group 702 of blocks in the grayscale value by the second scan> Suppose the gradation value calculation and grouping unit SA4 has started grouping block 702, which consists of blocks with a gradation value of 50% or higher (medium gradation value). Since the gradation value calculation and grouping unit SA4 has already grouped group 701, which has a high gradation value, it starts by detecting the gradation value range of a block that has not yet been grouped, for example, block B(1,8) (address (X,Y)=(1,8)). When it detects that block B(1,8) has a medium gradation value, it identifies block B(1,8) as belonging to group 702. Next, it detects the gradation value range of the block B(1,9) to its right. In the example shown in the figure, block B(1,9) also has a medium gradation value, so it identifies block B(1,9) as belonging to group 702 as well.

[0037] Subsequently, similar to the process used to generate group 701, the range of grayscale values ​​for each block in the first row, the second row, ..., and the last row is detected, and group 702 is formed within the grayscale values. In this case, since the blocks of group 701 are already grouped, grayscale values ​​are not detected for these blocks to improve processing efficiency.

[0038] <Formation of group 703 of blocks with low grayscale values ​​by the third scan> When forming group 703 of blocks with low gradation values, group 703 is formed in the same manner as when forming group 701 of blocks with high gradation values ​​and group 702 of blocks with medium gradation values.

[0039] <Explanation of the process for determining isolated tone value ranges when grouping tone value ranges> Let's further explain the process for determining the range of grayscale values. In blocks to which still image block information is attached, there may be cases where the detected range of grayscale values ​​differs between adjacent blocks. In this case, it is determined whether the block with a different range of grayscale values ​​is adjacent to a block with the same range of grayscale values. For example, block (3,5) in Figure 4C is adjacent to block B (3,4), which has the same range of grayscale values, so it is determined to belong to group 701 of the same grayscale value range. However, if they are not adjacent (for example, block B (4,7) in Figure 4C (address (X,Y=(4,7)) is determined to belong to a different range of grayscale values), it is determined to belong to a different group of grayscale values. By performing this process, the grayscale value calculation and grouping unit SA4 can detect still image areas for each range as shown in Figures 5A to 5C.

[0040] As described above, there may be multiple grouped areas. That is, in the example in Figure 4C, there are multiple instances of group 701 within a single frame 700, and there are also multiple instances of groups 702 and 703 within a single frame 700.

[0041] The grayscale value calculation and grouping unit SA4 transmits the grayscale value range information (high, medium, or low information) of each grouped block, along with the group information to which each block belongs, to the area calculator SA5.

[0042] <Explanation regarding area information generated by the area calculator SA5> The area calculator SA5 utilizes the group information to which each block belongs and the grayscale value range information (high, medium, or low) for each block. The area calculator SA5 can then calculate the area of ​​the grouped areas based on the grayscale value range. For example, the number of blocks within each area may be used as the area information for that area.

[0043] Figure 5A shows still image blocks with a grayscale value greater than 0% (including high, medium, and low grayscale values). The figure shows an example where still image areas exist in three locations within the frame (areas A, B, and C). It also shows that the area information for area A is 204, the area information for area B is 122, and the area information for area C is 60; these numbers represent the number of blocks.

[0044] Figure 5B shows an example of a composite area, which combines the area with a medium grayscale value and the area with a high grayscale value. In this example, the composite area is distributed across multiple locations, and the numbers indicated for each area represent the number of blocks, i.e., area information.

[0045] Figure 5C shows an example of an area with only high grayscale values. In this example, there are multiple areas with high grayscale values, and the numbers indicated for each area represent the number of blocks, i.e., area information.

[0046] Another method for detecting and grouping gradation values ​​involves preparing the same number of gradation value range detection circuits (detection circuits for low, medium, and high gradation values) in parallel, and obtaining group information for all groups simultaneously.

[0047] As described above, the area information used to indicate area is based on the number of blocks in the block area, which is grouped according to the range of grayscale values.

[0048] The area calculator SA5 then transmits the area information shown in Figures 5A, 5B, and 5C above to the coefficient calculator SA7 and the shape detector SA6 as supplementary information to the block identification information.

[0049] <Shape detection for each area using shape detector A6> The shape detector SA6 refers to the area information transmitted from the area detector SA5 and acquires shape information for each area with a grayscale value greater than a predetermined grayscale value. In this case, it finds the area that forms the largest square in each area and acquires information on the number of blocks on one side that make up this square. Furthermore, the shape detector SA6 sets the area that forms the next smallest square and acquires information on the number of blocks on one side that make up this square as shape information.

[0050] As described above, the shape detector SA6 acquires shape information for each area with a grayscale value greater than a predetermined grayscale value. That is, in each area, it acquires information on the number of blocks on one side of the largest square that can be secured there. If there is still area remaining, it shifts the square or gradually reduces the size of the square, and if it is reduced, it calculates the number of blocks on one side of the smaller square. Note that the shape is not limited to a square; other shapes (pentagon, hexagon, etc.) are also acceptable.

[0051] Figure 5D illustrates the process by which the shape detector SA6 detects the shape of a still image area formed by blocks with grayscale values ​​greater than, for example, 50% (see Figure 5B). Figure 5E shows an example where, after detecting a square, the number of blocks on one side of this square is assigned to each block as shape information. In this way, the number of blocks on one side of the square is used as part of the calculation elements in the coefficient calculator SA7 to determine the coefficient that controls the brightness of the corresponding block. A more specific example of shape detection will be explained in more detail later. The shape detector SA6 transmits the acquired square area information to the coefficient calculator SA7.

[0052] The coefficient calculator SA7 includes a memory unit (not shown) that stores coefficients for controlling the brightness of the video signal of the video brightness correction circuit 103. These coefficients are determined, for example, based on the area information of the still image area and the shape for each grayscale value greater than a predetermined grayscale value calculated by the shape detector SA6. This operation will be explained later in Figure 5F. The coefficients may also be determined based on either the area information of the still image area or the shape of the still image area. The determined coefficients are transmitted to the video brightness correction circuit 103 as a control signal.

[0053] Figure 5F shows an example of calculating the weighting coefficient for a single block using the coefficient calculator SA7. The coefficient calculator SA7 is pre-configured with conversion tables 910 for weighting coefficients based on grayscale range, 911 for weighting coefficients based on area, and 912 for weighting coefficients based on shape. For each grayscale range, the coefficients are multiplied according to the conversion tables based on the area and shape of the actual still image area, and the largest weighting coefficient is ultimately applied. The conversion tables for weighting coefficients based on grayscale, area, and shape are best determined by temperature evaluation.

[0054] In the conversion table 910 for weighting coefficients based on grayscale range, When the gradation range is 0% or more and less than 50%, the coefficient is 1. When the gradation range is 50% or more and less than 75%, the coefficient is 5. When the grayscale range is 75% or higher, set the coefficient to 15.

[0055] In the conversion table 911 for weighting coefficients by area, When the number of blocks is 1, the coefficient is 1. When the number of blocks is between 2 and 9, the coefficient is 2. When the number of blocks is between 10 and 29...the coefficient is 4. When the number of blocks is between 30 and 49...the coefficient is 6. When the number of blocks is between 50 and 99...the coefficient is 7. For 100 blocks, set the coefficient to 8.

[0056] In the shape-based weighting coefficient conversion table 912, When the number of sides is 1, the coefficient is 1; when the number of sides is 2, the coefficient is 2; when the number of sides is 3, the coefficient is 3. When the number of sides is 4, the coefficient is 4; when the number of sides is 5, the coefficient is 5; when the number of sides is 6, the coefficient is 6. When the number of sides is 7, the coefficient is 7; when the number of sides is 8, the coefficient is... 8. When the number is 9, the coefficient is 9. When the number of sides is 10, set the coefficient to 10.

[0057] In the above configuration, a switch SA8 for further correcting the coefficient may be provided. For example, considering that an increase in panel surface temperature leads to degradation of the organic EL element, the operating environment of the organic EL display 104 may also be taken into consideration. For example, if a sensor that detects ambient brightness, which is commonly used in televisions, is provided, the coefficient may be corrected using the information from this sensor. Also, if the television is connected to the internet, date, temperature, and time information may be obtained from the internet to determine what season it is, what the temperature is, whether it is daytime or nighttime, and the switch SA8 may correct the coefficient accordingly. Furthermore, if the television is equipped with a temperature sensor, the switch SA8 may correct the coefficient using either the information from this temperature sensor or by communicating via the network and using the information from a temperature sensor provided by another device.

[0058] <Characteristic shape detection method using the SA6 shape detector> The characteristic method for obtaining weighting coefficients using the shape detector SA6 described above will be explained. Figure 5E shows how, for each square area 731, 732, 734, 735, 736, and 737 obtained in Figure 5D, numbers representing the side lengths of the squares are assigned to each block that can form a square even when the squares are overlapping. When the largest possible square can be formed with 5 vertical blocks and 5 horizontal blocks (see section labeled 731 in Figure 5D), 5 is written for each block. Similarly, when the number of vertical blocks is 4 and the number of horizontal blocks is 4 (see section of square area 736 in Figure 5D), 4 is written for each block. However, when a 5x5 block square and a 4x4 block square overlap, the 5x5 block square (see section of square area 731 in Figure 5D) takes priority (the larger area takes priority), and the 5x5 square is assigned first (see section labeled area 810 in Figure 5E), with only the overflowing blocks being assigned 4 (see section labeled area 811 in Figure 5E). The above describes an example of obtaining shape information for the areas 810 and 811 in Figure 5E, but shape information can be obtained for other block areas using a similar shape detection method. In the frame of Figure 5E, the area on the right labeled "3,3,1", the area in the lower right labeled "3,4,2", and the area in the lower left labeled "4,2,1" can have their shape information obtained using the same procedure as for obtaining the shape information for areas 810 and 811.

[0059] As described above, the coefficient information for weighting in each still image area is determined by the coefficient calculator AS7 using the gradation value of each still image area, the area information for each gradation value range of the still image area divided using the gradation value, and the shape information of the still image area. In the video brightness correction circuit 103 (see Figure 1), a reduction process of the video signal is performed based on the coefficient information. Here, the brightness of each block in each area is controlled block by block, as explained in Figure 5F.

[0060] As described above, the shape information indicating the shape of the grouped areas can be said to utilize the number of blocks that form one side of a predetermined shape (for example, a square) that corresponds to the block area that is clustered within a range of a predetermined grayscale value or higher.

[0061] <Explanation of the rationale for focusing on the area, shape, etc., of the same group area> Figures 2 and 3 are shown to illustrate the basic reason why this embodiment includes an area calculator SA5 and a shape detector SA6.

[0062] Figure 2 shows three display panels 301, 302, and 303. A small square image 311 is displayed in the center of the left display panel 301 in the figure, a large square image 312 is displayed in the center of the middle display panel 302 in the figure, and a horizontally elongated rectangular image 313 is displayed in the center of the right display panel 302 in the figure.

[0063] Here, the small square image 311, the large square image 312, and the rectangular image 313 are all assumed to have the same brightness. Also, the large square image 312 and the rectangular image 313 are assumed to have the same area.

[0064] With the above settings, comparing the panel surface temperatures of the small square image 311, the large square image 312, and the rectangular image 313 after a certain period of time yielded the following results. Expressed as large, medium, and small, Large square image 312... Panel surface temperature Large Rectangular image 313... Panel surface temperature: Medium Small square image 311... Panel surface temperature small.

[0065] Based on the results above, it can be seen that even with the same brightness, there are differences in panel surface temperature in still image areas due to differences in area and shape. This means that even if multiple still image areas such as logos have the same brightness, the degree of element degradation (the progression of burn-in) will differ between still image areas with different areas and shapes.

[0066] Therefore, in this embodiment, the coefficient calculator SA7 shown in Figure 1 weights the coefficients that control the brightness (grayscale value) of the video signal (signal of the still image area) passing through the video brightness correction circuit 103. In this case, the coefficient calculator SA7 adjusts the weighting according to the grayscale value of the still image area and at least the combination of area or shape.

[0067] Figure 3 shows an example of the basic concept when the weighting of the coefficients differs depending on the shape and area of ​​the still image area.

[0068] Let's assume the display panel is divided into 7x7 blocks. We will explain this using columns for the vertical direction and rows for the horizontal direction. In the diagram, the first vertical column shows weighting information by area, the second column shows weighting information by shape, and the third column shows an example of the final weighted coefficients that take both area and shape into consideration.

[0069] The first column shows the difference in area, so we will explain the first column first. In example 441 of the first column, the block within the still image area is 1 block (= area 1), and this area of ​​1 is used as a reference value for weighting. In example 442, the same group area within the still image area is 4 blocks horizontally and 4 blocks vertically (= area 16), and this area of ​​16 is used as a reference value for weighting. In example 443, the same group area within the still image area is 5 blocks horizontally and 3 blocks vertically (= area 15), and this area of ​​15 is used as a reference value for weighting.

[0070] The second column shows the differences in shape and explains the second column. Example 451 in the second column is a small square, and the number of edges in this area, which is 1, is used as a reference value for weighting. Example 452 is a large square, and the number of blocks on the edges in this area, which is 4, is used as a reference value for weighting. Example 453 is a rectangle, but a square is reserved as shown by the thick line, and the number of blocks on the edges of that square, which is 3, is used as a reference value for weighting. This is because, as explained in Figure 2, the panel surface temperature has a strong influence on the square portion, so the square portion is used. In that case, for Example 453, the number of blocks on the edges, which is 3, is used as a reference value for weighting.

[0071] The shape information described above may be used directly as weighting information.

[0072] Next, the third column shows the final weighted coefficients for each example, based on a combination of area and shape information. In examples 441 and 451, the coefficient 1 is obtained by multiplying the number of blocks in the area (1) by the number of blocks in one side of the square (1). In examples 442 and 452, the coefficient 64 is obtained by multiplying the number of area blocks (16) by the number of blocks on one side of the square (4). In examples 443 and 453, the coefficient 45 is obtained by multiplying the number of blocks in the area (15) by the number of blocks on one side of the square (3).

[0073] As shown in Figure 1, the coefficient calculator SA7 provides the above coefficients to the video brightness correction circuit 103 as control elements for the video signal level of each block. In this case, for example, the larger the value of the coefficient, the lower the video signal level will be.

[0074] In the above explanation, both area-based and shape-based weighting were used, but the effects of this embodiment can be obtained by using only one of them, i.e., area-based weighting alone, or shape-based weighting alone.

[0075] Furthermore, in order to perform the data processing described above, the control device 200 is provided with a random access memory (RAM) for forming and temporarily storing the various types of information explained in Figures 5A-5F. Of course, the program for executing the above operations of the control device 200 (i.e., the video display program) is also stored in the memory. The RAM also manages, for example, block address data, still image area data (Figure 5A) which is a group of blocks, grayscale identification data (Figures 5B, 5C) which identifies blocks within the still image area by grayscale, and area identification data (Figure 5E) which identifies blocks by area. Of course, there is also a program memory that stores the program for constructing the above types of data.

[0076] The above-described embodiment can be used not only in television systems using organic EL displays, but also in electronic devices such as smartphones and personal computers.

[0077] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. Furthermore, even if each component of a claim is expressed by dividing it, by combining multiple components, or by combining them, it remains within the scope of the present invention. Multiple embodiments may also be combined, and embodiments composed of such combinations also fall within the scope of the invention. In addition, the drawings may schematically represent the width, thickness, shape, etc., of each part compared to the actual embodiment in order to make the explanation clearer. [Explanation of Symbols]

[0078] 101...Video signal input circuit, 102...Time adjuster, 103...Video brightness correction circuit, 104...Organic EL display, SA1...Video signal capture unit, SA2...Frame splitter, SA3...Still image block detector, SA4...Gradation value calculator / grouper, SA5...Area calculator, SA6...Shape detector, SA7...Coefficient calculator, SA8...Switcher.

Claims

1. The frame corresponding to the input video signal is divided into multiple blocks. A still image block is detected between the time axis of the aforementioned frame, The grayscale values ​​of the aforementioned still image blocks are calculated, allocated to predetermined ranges, and adjacent still image blocks are grouped together within each range. The weighting of the coefficients is changed according to the area of ​​the grouped area, A video display method that controls the level of the displayed video signal using the weighted coefficients.

2. The frame corresponding to the input video signal is divided into multiple blocks. A still image block is detected between the time axis of the aforementioned frame, The grayscale values ​​of the aforementioned still image blocks are calculated, allocated to predetermined ranges, and adjacent still image blocks are grouped together within each range. The weighting of the coefficients is changed according to the shape of the grouped area. A video display method that controls the level of the displayed video signal using the weighted coefficients.

3. Furthermore, the video display method according to claim 1 or 2 uses a coefficient switcher, and multiple ranges of coefficients are provided as the coefficients, and the multiple ranges of coefficients can be switched.

4. The video display method according to claim 1 or 2, wherein controlling the level of the video signal means controlling the brightness level or controlling the RGB signal.

5. A divider that divides the frame corresponding to the input video signal into multiple blocks, A detector that detects still image blocks between the time axis of the aforementioned frame, A still image area calculator calculates the grayscale value of the aforementioned still image block, assigns it to a predetermined range, and groups adjacent still image blocks within each range. An area calculator that changes the weighting of coefficients according to the area of ​​the grouped area, A video display device comprising: a coefficient calculator that controls the level of the displayed video signal using the weighted coefficients; and

6. A divider that divides the frame corresponding to the input video signal into multiple blocks, A detector that detects still image blocks between the time axis of the aforementioned frame, A still image area calculator calculates the grayscale value of the aforementioned still image block, assigns it to a predetermined range, and groups adjacent still image blocks within each range. A shape detector that changes the weighting of coefficients according to the shape of the grouped area, A video display device comprising: a coefficient calculator that controls the level of the displayed video signal using the weighted coefficients; and

7. The video display device according to claim 5 or 6, wherein the coefficient calculator for controlling the level of the video signal controls the brightness level or controls the RGB signal.

8. A video display program that outputs a control signal to a video brightness correction circuit to reduce the level of the video signal in the still image area, The frame corresponding to the input video is divided into multiple blocks, A still image block is detected between the time axis of the aforementioned frame, The grayscale values ​​of the aforementioned still image blocks are calculated, allocated to predetermined ranges, and adjacent still image blocks are grouped together within each range. The weighting of the coefficients is changed according to the area of ​​the grouped area, The weighted coefficients control the level of the displayed video signal. A program for displaying video.

9. A video display program that outputs a control signal to a video brightness correction circuit to reduce the level of the video signal in the still image area, The frame corresponding to the input video signal is divided into multiple blocks. A still image block is detected between the time axis of the aforementioned frame, The grayscale values ​​of the aforementioned still image blocks are calculated, allocated to predetermined ranges, and adjacent still image blocks are grouped together within each range. The weighting of the coefficients is changed according to the shape of the grouped area. The weighted coefficients control the level of the displayed video signal. A program for displaying video.

10. The video display program according to claim 8 or 9, wherein controlling the level of the video signal means controlling the brightness level or controlling the RGB signal.

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