Data scanning method and apparatus, electronic device, storage medium and program product

Abstract

A data scanning method and apparatus, an electronic device, a storage medium and a program product. The data scanning method comprises: acquiring a first sub-field of a data frame to be displayed and a transient brightness of the first sub-field (S1101); adjusting the number of sub-fields for the first sub-field to obtain at least one third sub-field, a scanning weight of the first sub-field being greater than or equal to that of the third sub-field (S1102); adjusting the transient brightness of the first sub-field to obtain a transient brightness of the third sub-field (S1103); determining a scanning duration of the third sub-field on the basis of the transient brightness of the third sub-field, a scanning duration of the first sub-field being greater than or equal to the scanning duration of the third sub-field (S1104); arranging a scanning order of a second sub-field and the third sub-field to obtain a target sub-field scanning order (S1105); and scanning the second sub-field and a plurality of third sub-fields on the basis of the target sub-field scanning order, the scanning weights and the scanning durations (S1106). According to the data scanning method, the dynamic false contour phenomenon is weakened while the motion blur phenomenon is improved, enhancing the image display quality.

Description

Data scanning method, device, electronic device, storage medium and program product

[0001] Cross-references

[0002] This application claims priority to the Chinese patent application filed on January 31, 2024, with application number "202410138668.6" and invention name "Data scanning method, device, electronic device, storage medium and program product", all contents of which are incorporated by reference into this application. Technical Field

[0003] The present application belongs to the field of display technology, and in particular relates to a data scanning method, device, electronic device, storage medium and program product. Background Art

[0004] Silicon-based microdisplays have garnered widespread attention in the display industry due to their advantages, including high resolution, high contrast, and low power consumption. Excellent display quality is a key performance metric for silicon-based microdisplays. However, due to the human eye's visual response, digitally driven silicon-based microdisplays suffer from dynamic false contouring.

[0005] The dynamic false contour reduction method in the related art can reduce the dynamic false contour phenomenon, but this method will also increase the motion blur phenomenon, thereby reducing the quality of image display.

[0006] Summary of the Invention

[0007] The embodiments of the present application provide a data scanning method, device, electronic device, storage medium and program product, which can improve the motion blur phenomenon while reducing the dynamic false contour phenomenon, thereby improving the quality of image display.

[0008] In a first aspect, an embodiment of the present application provides a data scanning method, which includes: obtaining a first subfield of a data frame to be displayed and the transient brightness of the first subfield; the data frame to be displayed includes a first subfield and a second subfield; adjusting the number of subfields of the first subfield to obtain at least one third subfield, and the scanning weight of the first subfield is greater than or equal to the scanning weight of the third subfield; adjusting the transient brightness of the first subfield to obtain the transient brightness of the third subfield; determining the scanning time of the third subfield based on the transient brightness of the third subfield, wherein the scanning time of the first subfield is greater than or equal to the scanning time of the third subfield; arranging the scanning order of the second subfield and the third subfield to obtain the target subfield scanning order; scanning the second subfield and at least one third subfield according to the target subfield scanning order, scanning weight and scanning time.

[0009] In the second aspect, an embodiment of the present application provides a data scanning device, which includes: a subfield acquisition module, used to acquire the first subfield of the data frame to be displayed and the transient brightness of the first subfield; the data frame to be displayed includes the first subfield and the second subfield; a subfield adjustment module, used to adjust the number of subfields of the first subfield to obtain at least one third subfield, and the scanning weight of the first subfield is greater than or equal to the scanning weight of the third subfield; a brightness adjustment module, used to adjust the transient brightness of the first subfield to obtain the transient brightness of the third subfield; a duration determination module, used to determine the scanning duration of the third subfield based on the transient brightness of the third subfield, wherein the scanning duration of the first subfield is greater than or equal to the scanning duration of the third subfield; a sorting module, used to arrange the scanning order of the second subfield and the third subfield to obtain the target subfield scanning order; a scanning module, used to scan the second subfield and at least one third subfield according to the target subfield scanning order, scanning weight and scanning duration.

[0010] In a third aspect, an embodiment of the present application provides an electronic device comprising: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the data scanning method as described in the first aspect is implemented.

[0011] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the data scanning method as described in the first aspect is implemented.

[0012] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the data scanning method as described in the first aspect.

[0013] It can be seen from the above content that in an embodiment of the present application, the first subfield with a larger scanning weight in the data frame to be displayed is divided into a third subfield with a smaller scanning weight, and the scanning time of the third subfield is adjusted by adjusting the transient brightness of the subfield, so that when there are multiple third subfields, the scanning time of the third subfield is not longer than the scanning time of the first subfield, and shortening the scanning time of the subfield can reduce the motion blur phenomenon of the subfield.

[0014] In addition, in the embodiment of the present application, the subfield scanning order of the multiple subfields included in the data frame to be displayed is adjusted so that the multiple data frames can compensate each other to reduce the dynamic false contour phenomenon.

[0015] It can be seen that the solution provided by the embodiment of the present application not only improves the motion blur phenomenon, but also reduces the dynamic false contour phenomenon, thereby improving the quality of image display. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] FIG1 is a schematic diagram showing the principle of a dynamic false contour phenomenon generated by a digitally driven display screen when the display is fixed;

[0018] FIG2 is a diagram showing the dynamic integration result of pixel brightness when the human eye moves from grayscale 127 to grayscale 128;

[0019] FIG3 is a diagram showing the dynamic integration result of pixel brightness when the human eye moves from grayscale 128 to grayscale 127;

[0020] FIG4 is a diagram showing the result of quantizing the integral brightness of image pixels during eye tracking;

[0021] FIG5 is a schematic diagram showing the light and dark stripes produced when the human eye tracks pixels on a display as the head moves to the left;

[0022] FIG6 is a schematic diagram showing the light and dark stripes produced when the human eye tracks pixels on a display as the head moves to the right;

[0023] FIG7 is a schematic diagram of light and dark stripes generated when the display moves with the head to the left but the human eye does not track pixels;

[0024] FIG8 is a schematic diagram showing the light and dark stripes produced when the display moves rightward with the head but the human eye tracks pixels;

[0025] FIG9 is a schematic structural diagram of a light-emitting device in a digital drive according to an embodiment of the present application;

[0026] FIG10 is a schematic structural diagram of a light-emitting device in a digital drive according to an embodiment of the present application;

[0027] FIG11 is a flow chart of a data scanning method according to an embodiment of the present application;

[0028] FIG12( a ) is a schematic diagram showing the generation of bright and dark stripes when the head moves to the left, according to one embodiment of the present application;

[0029] FIG12( b ) is a schematic diagram showing the generation of bright and dark stripes when the head moves to the right, according to one embodiment of the present application;

[0030] FIG13 is a schematic diagram of sub-field changes when i=0, N=1, and t≥T under 12 sub-fields provided by an embodiment of the present application;

[0031] FIG14 is a schematic diagram of the optimization effect of bright and dark stripes when i=0, N=1, and t≥T under 12 sub-fields provided by one embodiment of the present application;

[0032] FIG15 is a measured diagram of sub-field distribution under 12 sub-fields, i=0, N=1, t≥T, provided by one embodiment of the present application;

[0033] FIG16 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 12 sub-fields provided by an embodiment of the present application;

[0034] FIG17 is a schematic diagram of the optimization effect of bright and dark stripes under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0035] FIG18 is a measured diagram of sub-field distribution under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0036] FIG19 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 12 sub-fields provided by one embodiment of the present application;

[0037] FIG20 is a schematic diagram of the optimization effect of bright and dark stripes under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0038] FIG21 is a measured diagram of sub-field distribution under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0039] FIG22 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 12 sub-fields provided by an embodiment of the present application;

[0040] FIG23 is a schematic diagram of the optimization effect of bright and dark stripes under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0041] FIG24 is a measured diagram of sub-field distribution under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0042] FIG25( a ) is a schematic diagram showing the generation of bright and dark stripes when the head moves to the left, according to one embodiment of the present application;

[0043] FIG25( b ) is a schematic diagram showing the generation of bright and dark stripes when the head moves to the right, according to one embodiment of the present application;

[0044] FIG26 is a schematic diagram of sub-field changes when i=0, N=1, and t≥T under 14 sub-fields provided by one embodiment of the present application;

[0045] FIG27 is a schematic diagram of the optimization effect of bright and dark stripes when i=0, N=1, and t≥T under 14 sub-fields provided by one embodiment of the present application;

[0046] FIG28 is a measured diagram of sub-field distribution under 14 sub-fields, i=0, N=1, t≥T, provided by one embodiment of the present application;

[0047] FIG29 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 14 sub-fields provided by an embodiment of the present application;

[0048] FIG30 is a schematic diagram of the optimization effect of bright and dark stripes under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0049] FIG31 is a measured diagram of sub-field distribution under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0050] FIG32 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 14 sub-fields provided by an embodiment of the present application;

[0051] FIG33 is a schematic diagram of the optimization effect of bright and dark stripes under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0052] FIG34 is a measured diagram of sub-field distribution under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0053] FIG35 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 14 sub-fields provided by one embodiment of the present application;

[0054] FIG36 is a schematic diagram of the optimization effect of bright and dark stripes under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0055] FIG37 is a measured diagram of sub-field distribution under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0056] FIG38( a ) is a schematic diagram showing the generation of light and dark stripes when the head moves to the left, according to one embodiment of the present application;

[0057] FIG38( b ) is a schematic diagram showing the generation of bright and dark stripes when the head moves to the right, according to one embodiment of the present application;

[0058] FIG39 is a schematic diagram of sub-field changes when i=0, N=1, and t≥T under 16 sub-fields provided by one embodiment of the present application;

[0059] FIG40 is a schematic diagram of the optimization effect of bright and dark stripes under 16 sub-fields, i=0, N=1, and t≥T, provided by one embodiment of the present application;

[0060] FIG41 is a measured diagram of sub-field distribution under 16 sub-fields, i=0, N=1, t≥T, provided by one embodiment of the present application;

[0061] FIG42 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 16 sub-fields provided by one embodiment of the present application;

[0062] FIG43 is a schematic diagram of the optimization effect of bright and dark stripes under 16 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0063] FIG44 is a measured diagram of sub-field distribution under 16 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0064] FIG45 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 16 sub-fields provided by one embodiment of the present application;

[0065] FIG46 is a schematic diagram of the optimization effect of bright and dark stripes under 16 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0066] FIG47 is a measured diagram of sub-field distribution under 16 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0067] FIG48 is a schematic diagram of sub-field changes when i=4, N=1, 2, 4, 8, and 3.2t≥T under 16 sub-fields provided by one embodiment of the present application;

[0068] FIG49 is a schematic diagram of the optimization effect of bright and dark stripes under 16 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0069] FIG50 is a measured diagram of sub-field distribution under 16 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, provided by one embodiment of the present application;

[0070] FIG51 is a diagram showing the optimization effect of light and dark stripes on 12-bit data provided by one embodiment of the present application;

[0071] FIG52 is a diagram showing the optimization effect of light and dark stripes on 14-bit data provided by one embodiment of the present application;

[0072] FIG53 is a diagram showing the optimization effect of light and dark stripes on 16-bit data provided by one embodiment of the present application;

[0073] FIG54 is a schematic structural diagram of a data scanning device provided by another embodiment of the present application;

[0074] Figure 55 is a structural diagram of an electronic device provided by another embodiment of the present application. DETAILED DESCRIPTION

[0075] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0076] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the elements defined by the phrase "comprising..." do not exclude the presence of other identical elements in the process, method, article, or device comprising the elements.

[0077] For ease of understanding, before explaining the solution provided in this application, the relevant technologies involved in the solution provided in this application are first explained.

[0078] In the display industry, silicon-based microdisplay technology not only achieves higher pixel density and system integration by integrating more display units per unit area thanks to the mature CMOS (Complementary Metal-Oxide-Semiconductor) process, but also offers the advantages of high resolution, high contrast, and low power consumption. Therefore, silicon-based microdisplay technology is currently a focus of industry attention. A good display effect is an important factor in measuring display performance. Due to the human eye's visual response process, digitally driven silicon-based microdisplays are subject to the dynamic false contour phenomenon. Eliminating the impact of this dynamic false contour phenomenon on display quality is one of the issues that needs to be addressed.

[0079] Because the human eye's perception of external light brightness is energy-accumulating, there is a slight delay between the moment the light appears and the moment the eye begins to perceive the brightness, and again between the moment the light disappears and the moment the eye no longer perceives the brightness. These delays are known as the visual delay effect and the persistence of vision effect. Depending on the color and brightness of the light, as well as individual differences between people, these delays typically range from 50ms to 200ms. The visual delay effect and the persistence of vision effect together represent the visual response process of the human eye. Due to the existence of the visual response process, the process by which the human eye perceives the brightness of an image is usually represented as a dynamic integration of the brightness of the image pixels.

[0080] Figure 1 shows the principle diagram of the dynamic false contour phenomenon in the traditional display industry, where the display is fixed and the digital drive display produces a dynamic false contour phenomenon. In Figure 1, the horizontal axis is the pixel position, that is, the position of the pixel on the display. In Figure 1, X1, X2, X3, X4, X5, X6, X7, and X8 respectively represent the positions of the eight pixels on the display; the vertical axis is time, T frame Indicates the time it takes for the display to display one frame of an image. Furthermore, taking 256 grayscale levels as an example, a frame of an image is divided into eight subfields, and the scanning weight sequence for each subfield is 128:64:32:16:8:4:2:1. It should be noted that in the various example diagrams shown in this application, a gray subfield represents an unlit subfield, and a white subfield represents a lit subfield.

[0081] In Figure 1, the left half represents 127-level grayscale pixels, and the right half represents 128-level grayscale pixels. The oblique arrows indicate the eye's tracking trajectory of the pixels in this frame. Figure 1 shows six eye tracking trajectories: A, B, B2, C, C2, and D. For trajectory A, the eye's perception of brightness remains at 127-level grayscale. For trajectory B, the eye's tracking trajectory moves from 127 to 128. Due to the visual response process, the eye integrates the brightness of multiple pixels along the moving trajectory, increasing the perceived brightness to 255 levels, represented as bright streaks. Similarly, when the eye moves in the opposite direction from position X5, dark streaks are also produced, as shown in trajectory C. For trajectory D, the eye's perception of brightness remains at 128-level grayscale.

[0082] Figures 2 and 3 show the results of the human eye quantizing the integrated brightness of image pixels. Figure 2 shows the dynamic integrated brightness of pixels when the eye moves from a grayscale of 127 to a grayscale of 128, and Figure 3 shows the dynamic integrated brightness of pixels when the eye moves from a grayscale of 128 to a grayscale of 127. In Figures 2 and 3, a frame of image is divided into eight subfields, and the scanning weights and encoding of each subfield are shown in Figures 2 and 3. In Figure 2, when the eye tracks from a grayscale region of 127 to a grayscale region of 128, the maximum integrated brightness appears as grayscale 255, i.e., a bright streak. In Figure 3, when the eye tracks in the reverse direction from a grayscale region of 128 to a grayscale region of 127, the minimum integrated brightness appears as grayscale 0, i.e., a dark streak. Figure 4 shows the results of the quantized integrated brightness of image pixels when the eye tracks. In Figure 4, curve L1 represents the change in the integrated brightness when a bright streak is generated, and curve L2 represents the change in the integrated brightness when a dark streak is generated.

[0083] The above is an explanation of the dynamic false contour phenomenon that occurs when the display is fixed.

[0084] In near-eye display environments, such as AR (Augmented Reality) and VR (Virtual Reality), the display moves synchronously with the human head. Therefore, based on head movement and eye tracking, it can be divided into the following situations:

[0085] 1) Keep your head still and track your eyes;

[0086] 2) The head does not move, and the human eye does not track;

[0087] 3) Head movement and eye tracking;

[0088] 4) The head moves, but the eyes do not track.

[0089] For the above situation 1), similar to the phenomenon in the traditional display industry, the process of generating dynamic false contours is shown in FIG1 , and the cause is the same as the principle shown in FIG2 and FIG3 .

[0090] For case 2), since neither the display nor the human eye moves, no dynamic false contour phenomenon occurs.

[0091] For case 3), as shown in Figures 5 and 6, Figure 5 shows a schematic diagram of the light and dark stripes generated when the display moves to the left with the head and the human eye tracks the pixels, and Figure 6 shows a schematic diagram of the light and dark stripes generated when the display moves to the right with the head and the human eye tracks the pixels. In Figures 5 and 6, when the display moves to the left or right with the head, the human eye will track from the 127-level grayscale area to the 128-level grayscale area during the tracking process, thereby generating light stripes, as shown in track B in Figures 5 and 6. The reason for this is similar to the principle shown in Figure 2. Similarly, when the human eye tracks in the opposite direction, dark stripes will be generated, as shown in track A in Figures 5 and 6. The reason for this is similar to the principle shown in Figure 3. In Figures 5 and 6, the slope of the pixel point is related to the speed of the head movement.

[0092] For case 4), as shown in Figures 7 and 8, Figure 7 shows a schematic diagram of light and dark stripes generated when the display moves to the left with the head but the human eye does not track the pixels, and Figure 8 shows a schematic diagram of light and dark stripes generated when the display moves to the right with the head but the human eye tracks the pixels. In Figures 7 and 8, when the display moves to the left or right with the head and the human eye does not track, the dynamic false contour phenomenon will still occur. In Figure 7, although the human eye does not move, the display moves to the left with the head, causing the different subfields of the pixel points to shift to the left in physical space, causing the human eye to passively move from the 127-level grayscale area to the 128-level grayscale area, which in turn causes the generation of light stripes. In addition, the duration of this process is much longer than the process of active tracking by the human eye, so the duration of the light stripes is also longer. This is a phenomenon that does not occur in the traditional display industry when the display is fixed. The reason for the generation of light stripes is similar to the principle shown in Figure 2. Similarly, in FIG8 , as the head moves to the right, the display causes the human eye to passively move from the 128-level grayscale area to the 127-level grayscale area, thus generating dark stripes. The reason for the generation of dark stripes is similar to the principle shown in FIG3 .

[0093] In summary, the most significant difference between near-eye display environments (including AR / VR) and traditional display environments (where the display is stationary) is that when the display moves with the head but the eye doesn't track it, a new phenomenon called dynamic false contouring is introduced, and this phenomenon is more pronounced due to its longer duration. On the other hand, methods that effectively mitigate dynamic false contouring in traditional display environments with stationary displays can actually enhance motion blur in near-eye display environments (including AR / VR), thereby further weakening the image quality.

[0094] The occurrence of motion blur is proportional to the time the frame is illuminated. Typically, a frame consists of multiple subfields, and each subfield has its own weight. Generally speaking, the subfield weight is related to both transient brightness and luminous time. In the structural diagrams of the luminous device in the digital drive shown in Figures 9 and 10, the transient brightness can be changed by changing the VP voltage or VCOM voltage across the luminous material. If the frequency of the voltage change is in subfield units, the transient brightness of each subfield can be changed. When the subfield weight does not change, increasing the transient brightness of the subfield can shorten the luminous time of the subfield, that is, reducing the motion blur phenomenon in near-eye display environments (including AR / VR and other environments). In addition, adjusting the scanning order of the subfields in the data frame so that the subfield scanning order of two adjacent data frames is different can effectively reduce the dynamic false contour phenomenon.

[0095] It should be noted that the VP adjustable range is limited in the structure of Figure 9 because the MOS transistor is between VP and the light-emitting material. In contrast, in the structure of Figure 10, the VP voltage can be increased to above +10V because it is not limited by the maximum load voltage of the MOS transistor.

[0096] Based on the above principles, in a near-eye display environment (including AR / VR and other environments), in order to improve the impact of dynamic false contouring on the display effect without exacerbating the motion blur phenomenon, the embodiments of the present application provide a data scanning method, device, electronic device, storage medium, and program product. The data scanning method proposed in the embodiments of the present application can be applied to digitally driven display devices that have dynamic false contouring, such as liquid crystal displays (LCDs), digitally driven light-emitting diode (LED) displays, and organic light-emitting diode (OLED) displays. Of course, other displays are also possible, and the present application is not limited thereto.

[0097] The following first introduces the data scanning method provided in the embodiment of the present application.

[0098] FIG11 is a flow chart of a data scanning method provided by an embodiment of the present application. As shown in FIG11 , the method includes the following steps:

[0099] Step S1101 , obtaining a first subfield of a data frame to be displayed and the transient brightness of the first subfield.

[0100] In step S1101, the data frame to be displayed includes multiple subfields. In an embodiment of the present application, the data frame to be displayed includes a first subfield and a second subfield, wherein the first subfield is a subfield with a higher subfield weight (i.e., a subfield weight value), and the second subfield is a subfield other than the first subfield in the data frame to be displayed.

[0101] Furthermore, in step S1101, after determining the first subfield from the multiple subfields included in the data frame to be displayed, brightness data of the first subfield can be obtained. The brightness data includes at least the brightness of the first subfield and the transient brightness. The brightness of the first subfield is obtained by integrating the transient brightness of the first subfield at each moment within the scanning time corresponding to the first subfield. The transient brightness of the first subfield can be determined from the brightness data of the first subfield.

[0102] In an embodiment of the present application, the subfield weight is related to the transient brightness and luminous time of the subfield. Therefore, after the subfield weight is determined, that is, when the subfield weight is determined, increasing the transient brightness of the subfield can shorten the luminous time of the subfield to reduce the motion blur phenomenon in the near-eye display environment.

[0103] Step S1102: adjusting the number of subfields of the first subfield to obtain at least one third subfield.

[0104] In step S1102, at least one third subfield can be obtained by scanning the first subfield at least once, wherein the number of times the first subfield is scanned is the number of subfields in the third subfield. For example, if the first subfield with a subfield weight of 128 is scanned four times, four third subfields can be obtained.

[0105] It should be noted that the scenario in which the number of third subfields is 1 is a special scenario for adjusting the number of subfields of the first subfield. In this scenario, the number of third subfields is the same as that of the first subfield, and the third subfield is also the first subfield. The scanning weight, transient brightness, scanning time, etc. of the third subfield are the same as those of the first subfield.

[0106] In addition, it should be noted that in the embodiment of the present application, when there are multiple first subfields, for the same data frame, after the first subfield is determined, each first subfield is scanned the same number of times to obtain multiple third subfields corresponding to each first subfield.

[0107] In addition, in step S1102, the scanning weight of the first subfield is greater than or equal to the scanning weight of the third subfield. When the number of third subfields is 1, the scanning weight of the third subfield is the scanning weight of the first subfield, that is, the scanning weight of the first subfield is equal to the scanning weight of the third subfield; and when the number of third subfields is multiple, the scanning weight of the first subfield is greater than the scanning weight of the third subfield. In this scenario, through step S1102, the subfield with a higher subfield weight can be converted into multiple subfields with a lower subfield weight.

[0108] Step S1103 , adjusting the transient brightness of the first subfield to obtain the transient brightness of the third subfield.

[0109] In step S1103 , as can be seen from FIG. 9 and FIG. 10 , by changing the VP voltage or the VCOM voltage, the luminous brightness of the light-emitting device can be adjusted, thereby adjusting the transient brightness of the sub-field.

[0110] It should be noted that in the scenario where the number of third subfields is 1, the transient brightness of the third subfield is the transient brightness of the first subfield, that is, in the scenario where the number of third subfields is 1, that is, in the scenario where the first subfield is not split, there is no need to adjust the transient brightness of the subfield.

[0111] When there are multiple third subfields, increasing the transient brightness of the first subfield to determine the transient brightness of the third subfield can shorten the scanning time of the third subfield. Furthermore, the subfield weight is related to the transient brightness and luminous time of the subfield. Therefore, after the subfield weight is determined, that is, when the subfield weight is determined, increasing the transient brightness of the subfield can shorten the luminous time of the subfield. As can be seen from step S1103, the transient brightness of the third subfield is higher than that of the first subfield. This shortens the scanning time of the third subfield compared to the first subfield, thereby reducing motion blur in near-eye display environments.

[0112] Step S1104 : determining the scanning duration of the third subfield based on the transient brightness of the third subfield.

[0113] In step S1104, since the subfield weight is related to the transient brightness and luminous time of the subfield, after determining the subfield weight and transient brightness of the third subfield, the luminous time of the third subfield, that is, the scanning duration of the third subfield, can be determined. In this embodiment of the present application, the scanning duration of the first subfield is greater than or equal to the scanning duration of the third subfield. Specifically, in a scenario where the first subfield is not split into subfields, the scanning duration of the first subfield is equal to the scanning duration of the third subfield; in a scenario where the first subfield is split into multiple third subfields, the scanning duration of the first subfield is greater than the scanning duration of the third subfield.

[0114] As can be seen from step S1103, in the scenario where the first subfield is split into multiple third subfields, the transient brightness of the third subfield is increased compared to the first subfield, thereby shortening the scanning time of the third subfield, thereby reducing motion blur in the near-eye display environment. In contrast, in the scenario where the first subfield is not split into subfields, the transient brightness of the subfields is not increased, the scanning time is not increased, and thus the motion blur in the near-eye display environment is not increased. Combined with subsequent steps, the dynamic false contour phenomenon can be reduced without increasing motion blur, thereby improving image display quality.

[0115] Step S1105 , arranging the scanning order of the second subfield and the third subfield to obtain a target subfield scanning order.

[0116] In step S1105, the scanning order of the second subfield and the third subfield can be sorted according to a pre-set subfield sorting rule; in addition, the scanning order of the second subfield and the third subfield can also be sorted according to the subfield scanning order of the previous data frame of the data frame to be displayed. In this scenario, the target subfield scanning order can be different from the subfield scanning order of the previous data frame of the data frame to be displayed, that is, in an embodiment of the present application, the subfield scanning order of two adjacent data frames to be displayed can be made different, so that multiple data frames can compensate for each other to reduce the dynamic false contour phenomenon.

[0117] Step S1106 : Scan the second subfield and at least one third subfield according to the target subfield scanning sequence, scanning weight, and scanning duration.

[0118] It should be noted that after step S1101 to step S1105, the data frame to be displayed includes the second subfield and the third subfield. After determining the target subfield scanning order of the data frame to be displayed, the second subfield and the third subfield contained in the data frame to be displayed can be scanned according to the target subfield scanning order. During the subfield scanning process, for different subfields, the scanning data corresponding to the subfield (including at least the scanning weight, transient brightness and scanning duration) is used to perform subfield scanning. For example, when scanning the second subfield, the scanning weight, transient brightness and scanning duration of the second subfield are used for scanning; when scanning the third subfield, the scanning weight, transient brightness and scanning duration of the third subfield are used for scanning.

[0119] Based on the scheme defined by the above steps S1101 to S1106, it can be known that in an embodiment of the present application, by dividing the first subfield with a larger scanning weight in the data frame to be displayed into multiple third subfields with smaller scanning weights, and adjusting the scanning time of the third subfield by adjusting the transient brightness of the subfield, when the number of third subfields is multiple, the scanning time of the third subfield is not longer than the scanning time of the first subfield, and shortening the scanning time of the subfield can reduce the motion blur phenomenon of the subfield.

[0120] In addition, in the embodiment of the present application, the subfield scanning order of the multiple subfields included in the data frame to be displayed is adjusted so that the multiple data frames can compensate each other to reduce the dynamic false contour phenomenon.

[0121] It can be seen that the solution provided by the embodiment of the present application not only improves the motion blur phenomenon, but also reduces the dynamic false contour phenomenon, thereby improving the quality of image display.

[0122] The data scanning method proposed in the embodiment of the present application is explained in detail below.

[0123] The following explanation is given by taking the splitting of the first subfield into a plurality of third subfields as an example.

[0124] A data frame to be displayed can typically be divided into multiple subfields, each with a different scan weight. To mitigate the dynamic false contour phenomenon, in an embodiment of the present application, the subfield with high bits (i.e., high scan weight) that has a greater impact on the dynamic false contour phenomenon is split into multiple smaller subfields, thereby overcoming the aforementioned drawbacks. Prior to this, the subfield with high bits (i.e., high scan weight) must be determined (i.e., the first subfield).

[0125] Specifically, after obtaining scanning weights of multiple subfields included in the data frame to be displayed, a subfield having a scanning weight greater than a preset weight threshold is determined from the multiple subfields to obtain a first subfield and its transient brightness.

[0126] In one example, the weight threshold can be determined by the developer based on actual experience and actual needs. The developer can set the number of bits corresponding to the weight threshold, and then the display device calculates the weight threshold based on the number of bits. In the embodiment of the present application, if the number of bits of the subfield is i, the scanning weight of the subfield is 2 i .

[0127] As an example, when a data frame includes 8 subfields, if the number of subfield bits corresponding to the weight threshold is 5, and the weight threshold is 32, the display device will scan the subfield with a weight greater than 32 as the first subfield, and obtain the transient brightness of the subfield with a scanning weight greater than 32.

[0128] Furthermore, after determining the first subfield, the display device scans the first subfield multiple times to obtain multiple third subfields, where the number of times the display device scans the first subfield is the number of subfields in the third subfield. That is, by scanning the first subfield multiple times, the number of subfields corresponding to the first subfield becomes an integer multiple of the original number.

[0129] Furthermore, when there are multiple third subfields, the display device calculates the ratio of the scanning weight of the first subfield to the number of subfields in the third subfield to obtain the scanning weight of the third subfield. That is, the scanning weight of the first subfield is an integer multiple of the scanning weight of the third subfield. For example, when the number of subfields in the third subfield is M, the scanning weight of each third subfield is the same, which is a multiple of the scanning weight of the first subfield.

[0130] By splitting a subfield with a higher scanning weight into multiple subfields with lower scanning weights, the influence of the dynamic false contour phenomenon on the image display effect can be effectively improved, thereby improving the quality of image display.

[0131] Since increasing the transient brightness of the subfield can shorten the scanning time of the subfield and thus reduce the motion blur phenomenon, in an embodiment of the present application, after splitting the first subfield into multiple third subfields, after adjusting the number of subfields of the first subfield to obtain multiple third subfields, the transient brightness of the first subfield is increased, and the increased brightness is used as the transient brightness of the third subfield.

[0132] Specifically, the display device adjusts the first voltage of the first subfield to the second voltage according to the correlation between the transient brightness and the subfield voltage to increase the transient brightness of the first subfield and obtain the transient brightness of the third subfield.

[0133] In the above embodiment, the voltage of the subfield can be the voltage difference between the VP voltage and the VCOM voltage in Figure 9. By adjusting the voltage difference between VP and VCOM, the transient brightness of the subfield can be adjusted, and increasing the voltage difference between VP and VCOM can increase the transient brightness of the subfield.

[0134] Furthermore, after the transient brightness of the third subfield is determined, the scanning duration of the third subfield may be determined based on the transient brightness of the third subfield.

[0135] Specifically, the display device calculates the ratio of the transient brightness of the first subfield to the transient brightness of the third subfield to obtain a transient brightness ratio. At the same time, it calculates the ratio of the scanning weight of the first subfield to the scanning weight of the third subfield to obtain a weight ratio; then, it calculates the product of the transient brightness ratio and the weight ratio to obtain a target ratio; finally, based on the scanning time of the first subfield and the target ratio, it determines the scanning time of the third subfield.

[0136] In one example, the ratio of the transient brightness of the first subfield to the transient brightness of the second and third subfields is set to N, the ratio of the scanning weight of the first subfield to the scanning weight of the third subfield is set to M, the scanning time of the first subfield is T1, and the scanning time of the third subfield is set to

[0137] It should be noted that the motion blur phenomenon can be reduced by shortening the scanning time of the data frame to be displayed. Based on this, in an embodiment of the present application, the upper screen clock of the subfield can also be adjusted to further shorten the scanning time of the data frame to be displayed.

[0138] Specifically, the display device calculates the product of the scanning weight of the first subfield and the initial on-screen clock corresponding to the first subfield to obtain the scanning duration of the first subfield; then, the initial on-screen clock is adjusted to obtain the target on-screen clock; then, the ratio of the scanning weight of the first subfield to the target ratio is calculated to obtain the target weight; finally, the product of the target weight and the target on-screen clock is calculated to obtain the scanning duration of the third subfield.

[0139] In the above embodiment, the initial upper screen clock is the unit scanning duration of the subfield. For each subfield, the corresponding scanning duration is the product of the upper screen clock and the scanning weight. Therefore, in the embodiment of the present application, the upper screen clock can represent the scanning duration of the subfield with a scanning weight of 1.

[0140] It should be noted that after the upper screen clock is modified, the scanning durations of all subfields included in the data frame to be displayed are changed, thereby shortening the scanning duration of the data frame to be displayed.

[0141] In order to avoid the motion blur phenomenon, the total scanning time of a data frame after the on-screen clock is modified needs to be less than or equal to the total scanning time of a data frame before the on-screen clock is modified. That is, the initial on-screen clock and the target on-screen clock need to satisfy the following formula: m1*t≥m2*T

[0142] In the above formula, t is the scanning duration of the subfield with a scanning weight of 1 before the upper screen clock is modified, that is, t is the initial upper screen clock; T is the scanning duration of the subfield with a scanning weight of 1 after the upper screen clock is modified, that is, T is the target upper screen clock; m1 is the cumulative sum of the scanning weights of all subfields contained in the data frame before the upper screen clock is modified; m2 is the cumulative sum of the scanning weights of all subfields contained in the data frame after the upper screen clock is modified; m1*t is the total scanning duration of a data frame before the upper screen clock is modified; m2*T is the total scanning duration of a data frame after the upper screen clock is modified.

[0143] It should be noted that, since the scanning time of a data frame before the upper screen clock is modified is less than the scanning time of a data frame after the upper screen clock is modified, that is, there is a time difference between the scanning time of the data frame before and after the upper screen clock is modified, therefore, in actual applications, it is necessary to insert a black frame in the data frame after the upper screen clock is modified.

[0144] Specifically, first, obtain the first scanning duration of the data frame to be displayed before the initial upper screen clock is adjusted, and the second scanning duration of the data frame to be displayed after the initial upper screen clock is adjusted; then insert a preset number of black frames into the data frame to be displayed, so that the difference between the first scanning duration and the second scanning duration is the scanning duration of the preset number of black frames.

[0145] As an example, when the display duration of the black frame is fixed, in the process of inserting the black frame into the data frame to be displayed, the number of black frames (i.e., the preset number) can be determined based on the time difference between the two scanning durations and the display duration of each black frame. The preset number of black frames can be inserted into the end part of the data frame to be displayed, or at least one target subfield can be determined from the second subfield and the third subfield included in the data frame to be displayed, and the preset number of black frames can be evenly or unevenly inserted and exited into the end part of at least one target subfield.

[0146] As another example, the display duration of the black frame may not be fixed. In this scenario, the display device may combine the black frames according to the display duration of each black frame to determine black frames with different display durations to be inserted into the data frame to be displayed, and insert the selected black frames into the end part of the data frame to be displayed, or determine at least one target subfield from the second subfield and the third subfield contained in the data frame to be displayed, and evenly or unevenly move the selected black frames into and out of the end part of at least one target subfield.

[0147] In the process of arranging the scanning order of the second subfield and the third subfield, a reverse sorting method may be used to determine the target subfield scanning order of the data frame to be displayed.

[0148] Specifically, after obtaining the subfield scanning order of the previous data frame of the data frame to be displayed, the scanning order of the second subfield and the third subfield is arranged in the reverse order of the subfield scanning order of the previous data frame to obtain the target subfield scanning order. That is, the target subfield scanning order of the data frame to be displayed can be obtained by reversely sorting the subfield scanning order of the previous data frame of the data frame to be displayed.

[0149] In another solution, the target subfield scanning order of the data frame to be displayed can also be determined by shifting. Specifically, after obtaining the initial subfield scanning order of the second subfield and the plurality of third subfields, the sequence of the second subfield and the plurality of third subfields in the initial subfield scanning order is shifted according to a preset shift direction and shift amount to obtain the target subfield scanning order.

[0150] In addition, the above two schemes can be combined to determine the target subfield scanning order. For example, the subfield scanning order of the data frame to be displayed can be shifted, and the shifted subfield scanning order can be reversely sorted to obtain the target subfield scanning order; or the subfield scanning order of the data frame to be displayed can be reversely sorted first, and then the reversely sorted subfield scanning order can be shifted to obtain the target subfield scanning order.

[0151] The following diagrams illustrate several examples of rearranging the subfields contained in a data frame in the above manner, and describe in detail the optimization effect on the dynamic false contour phenomenon in combination with head movement in near-eye display environments (including AR / VR environments) and scenarios where the human eye does not track.

[0152] In the first example, when 12 subfields are used to represent 4096 levels of grayscale, the process of generating light and dark stripes is shown in Figure 12, where Figure 12(a) is a schematic diagram of the generation of light and dark stripes when the head moves to the left, and Figure 12(b) is a schematic diagram of the generation of light and dark stripes when the head moves to the right. A, B, and C represent the tracking trajectories of the human eye.

[0153] As an example, Figure 13 shows a schematic diagram of subfield changes when 12 subfields are used, i = 0, N = 1, and t ≥ T. As shown in Figure 13, in this scenario, the subfield voltage value and the subfield scanning duration (i.e., the scanning time in Figure 13) do not change; only the scanning order of the subfields is shifted. Figure 14 shows a schematic diagram of the optimization effect of bright and dark stripes when 12 subfields are used, i = 0, N = 1, and t ≥ T. Figure 15 shows a measured diagram of the subfield distribution when 12 subfields are used, i = 0, N = 1, and t ≥ T, where the numbers 0-11 represent the scanning order of the subfields.

[0154] As an example, Figure 16 shows a schematic diagram of subfield changes when 12 subfields are used, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 16, in this scenario, the upper 4-bit subfield is split, and each upper subfield is divided into 4 small subfields. The scanning weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is reduced to 1 / 2, 4, or 8 times the original value. The corresponding subfield scanning duration is reduced to 1 / 4, 1 / 8, 1 / 16, and 1 / 32 of the original value. Figure 17 shows a schematic diagram of the optimization effect of bright and dark stripes when 12 subfields are used, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. Figure 18 shows a measured diagram of the subfield distribution when 12 subfields are used, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. The numbers 0-23 represent the scanning order of the subfields.

[0155] As an example, to further improve the impact of dynamic false contours on display effects, in the data frame following the data frame to be displayed, the subfield scan weights, corresponding voltage values, and scan durations are inverted, and this cycle repeats. Figure 19 shows a schematic diagram of subfield changes when there are 12 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 19, in this scenario, the upper 4-bit subfields are split, and each upper subfield is split into 4 small subfields. The scan weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is 1, 2, 4, or 8 times the original value. The corresponding subfield scan duration is reduced to 1 / 4, 1 / 8, 1 / 16, or 1 / 32 of the original value. The scan order, scan weight, voltage value, and scan duration of the data frame to be displayed are then inverted to obtain the scan data (including the scan order, scan weight, voltage value, and scan duration) of the next data frame. Figure 20 shows a schematic diagram of the optimization effect of bright and dark stripes when 12 sub-fields, i = 4, N = 1, 2, 4, 8, and 3.2t≥T. Figure 21 shows a measured diagram of the sub-field distribution when 12 sub-fields, i = 4, N = 1, 2, 4, 8, and 3.2t≥T, where the numbers 0-23 represent the scanning order of the sub-fields.

[0156] As an example, to further improve the impact of the dynamic false contour phenomenon on the display effect, the scanning order of the data frame to be displayed and the next data frame is rearranged, and this cycle is repeated. Figure 22 shows a schematic diagram of subfield changes under 12 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 22, in this scenario, the upper 4-bit subfield is split, and each upper subfield is split into 4 small subfields. The scanning weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is changed to 1 / 2, 4, or 8 times the original. The corresponding subfield scanning time is changed to 1 / 4, 1 / 8, 1 / 16, or 1 / 32 of the original. Then, the scanning order, scanning weight, voltage value, and scanning time of the data frame to be displayed are shifted to obtain the scanning data of the next data frame (including scanning order, scanning weight, voltage value, and scanning time). Figure 23 shows a schematic diagram of the optimization effect of bright and dark stripes under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T. Figure 24 shows a measured diagram of the sub-field distribution under 12 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, where the numbers 0-23 represent the scanning order of the sub-fields.

[0157] In the second example, when 14 subfields are used to represent 16384 levels of grayscale, the process of generating light and dark stripes is shown in Figure 25, where Figure 25(a) is a schematic diagram of the generation of light and dark stripes when the head moves to the left, and Figure 25(b) is a schematic diagram of the generation of light and dark stripes when the head moves to the right. A, B, and C represent the tracking trajectories of the human eye.

[0158] As an example, Figure 26 shows a schematic diagram of subfield changes when 14 subfields are used, i = 0, N = 1, and t ≥ T. As shown in Figure 26, in this scenario, the subfield voltage value and the subfield scanning duration (i.e., the scanning time in Figure 26) do not change; only the scanning order of the subfields is shifted. Figure 27 shows a schematic diagram of the optimization effect of bright and dark stripes when 14 subfields are used, i = 0, N = 1, and t ≥ T. Figure 28 shows a measured diagram of the subfield distribution when 14 subfields are used, i = 0, N = 1, and t ≥ T, where the numbers 0-13 represent the scanning order of the subfields.

[0159] As an example, Figure 29 shows a schematic diagram of subfield changes when there are 14 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 29, in this scenario, the upper 4-bit subfield is split, and each upper subfield is split into 4 small subfields. The scanning weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is reduced to 1 / 2, 4, and 8 times the original value. The corresponding subfield scanning duration is reduced to 1 / 4, 1 / 8, 1 / 16, and 1 / 32 of the original value. Figure 30 shows a schematic diagram of the optimization effect of bright and dark stripes when there are 14 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. Figure 31 shows a measured diagram of the subfield distribution when there are 14 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. The numbers 0-25 represent the scanning order of the subfields.

[0160] As an example, to further improve the impact of dynamic false contours on display effects, in the data frame following the data frame to be displayed, the subfield scan weights, corresponding voltage values, and scan durations are inverted, and this cycle repeats. Figure 32 shows a schematic diagram of subfield changes when there are 14 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 32, in this scenario, the upper 4-bit subfields are split, and each upper subfield is split into 4 small subfields. The scan weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is 1, 2, 4, or 8 times the original value. The corresponding subfield scan duration is reduced to 1 / 4, 1 / 8, 1 / 16, or 1 / 32 of the original value. Then, the scan order, scan weight, voltage value, and scan duration of the data frame to be displayed are inverted to obtain the scan data (including the scan order, scan weight, voltage value, and scan duration) of the next data frame. Figure 33 shows a schematic diagram of the optimization effect of bright and dark stripes under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T. Figure 34 shows a measured diagram of the sub-field distribution under 14 sub-fields, i=4, N=1, 2, 4, 8, and 3.2t≥T, where the numbers 0-25 represent the scanning order of the sub-fields.

[0161] As an example, to further improve the impact of the dynamic false contour phenomenon on the display effect, the scanning order of the data frame to be displayed and the next data frame is rearranged, and this cycle is repeated. Figure 35 shows a schematic diagram of subfield changes under 14 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 35, in this scenario, the upper 4-bit subfield is split, and each upper subfield is split into 4 small subfields. The scanning weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is changed to 1 / 2, 4, or 8 times the original. The corresponding subfield scanning time is changed to 1 / 4, 1 / 8, 1 / 16, or 1 / 32 of the original. Then, the scanning order, scanning weight, voltage value, and scanning time of the data frame to be displayed are shifted to obtain the scanning data of the next data frame (including scanning order, scanning weight, voltage value, and scanning time). Figure 36 shows a schematic diagram of the optimization effect of bright and dark stripes when 14 sub-fields are present, i=4, N=1, 2, 4, 8, and 3.2t≥T. Figure 37 shows a measured diagram of the sub-field distribution when 14 sub-fields are present, i=4, N=1, 2, 4, 8, and 3.2t≥T, where the numbers 0-25 represent the scanning order of the sub-fields.

[0162] In the second example, when 16 subfields are used to represent 65536 levels of grayscale, the process of generating light and dark stripes is shown in Figure 38, where Figure 38(a) is a schematic diagram of the generation of light and dark stripes when the head moves to the left, and Figure 38(b) is a schematic diagram of the generation of light and dark stripes when the head moves to the right. A, B, and C represent the tracking trajectories of the human eye.

[0163] As an example, Figure 39 shows a schematic diagram of subfield changes when 16 subfields are used, i = 0, N = 1, and t ≥ T. As shown in Figure 39, in this scenario, the subfield voltage value and the subfield scanning duration (i.e., the scanning time in Figure 39) do not change; only the scanning order of the subfields is shifted. Figure 40 shows a schematic diagram of the optimization effect of bright and dark stripes when 16 subfields are used, i = 0, N = 1, and t ≥ T. Figure 41 shows a measured diagram of the subfield distribution when 16 subfields are used, i = 0, N = 1, and t ≥ T, where the numbers 0-15 represent the scanning order of the subfields.

[0164] As an example, Figure 42 shows a schematic diagram of subfield changes when 16 subfields are used, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 42, in this scenario, the upper 4-bit subfield is split, and each upper subfield is divided into 4 small subfields. The scanning weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is reduced to 1 / 2, 4, or 8 times the original value. The corresponding subfield scanning duration is reduced to 1 / 4, 1 / 8, 1 / 16, and 1 / 32 of the original value. Figure 43 shows a schematic diagram of the optimization effect of bright and dark stripes when 16 subfields are used, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. Figure 44 shows a measured diagram of the subfield distribution when 16 subfields are used, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. The numbers 0-27 represent the scanning order of the subfields.

[0165] As an example, to further improve the impact of dynamic false contours on display quality, in the data frame following the data frame to be displayed, the subfield scan weights, corresponding voltage values, and scan durations are inverted, and this cycle repeats. Figure 45 shows a schematic diagram of subfield changes when 16 subfields are present, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 45, in this scenario, the upper 4-bit subfields are split, each of which is divided into four small subfields. The scan weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is 1, 2, 4, or 8 times the original value. The corresponding subfield scan duration is reduced to 1 / 4, 1 / 8, 1 / 16, or 1 / 32 of the original value. The scan order, scan weight, voltage value, and scan duration of the data frame to be displayed are then inverted to obtain the scan data (including the scan order, scan weight, voltage value, and scan duration) of the next data frame. Figure 46 shows a schematic diagram of the optimization effect of bright and dark stripes when 16 sub-fields are present, i=4, N=1, 2, 4, 8, and 3.2t≥T. Figure 47 shows a measured diagram of the sub-field distribution when 16 sub-fields are present, i=4, N=1, 2, 4, 8, and 3.2t≥T, where the numbers 0-27 represent the scanning order of the sub-fields.

[0166] As an example, to further improve the impact of dynamic false contours on display effects, the scanning order of the data frame to be displayed and the next data frame is rearranged, and this cycle repeats. Figure 48 shows a schematic diagram of subfield changes under 16 subfields, i = 4, N = 1, 2, 4, 8, and 3.2t ≥ T. As shown in Figure 48, in this scenario, the upper 4-bit subfield is split, and each upper subfield is split into 4 small subfields. The scanning weight (i.e., subfield weight) of each small subfield is 1 / 4 of the original subfield weight, and the voltage value is changed to 1 / 2, 4, or 8 times the original. The corresponding subfield scanning time is changed to 1 / 4, 1 / 8, 1 / 16, or 1 / 32 of the original. Then, the scanning order, scanning weight, voltage value, and scanning time of the data frame to be displayed are shifted to obtain the scanning data of the next data frame (including scanning order, scanning weight, voltage value, and scanning time). Figure 49 shows a schematic diagram of the optimization effect of bright and dark stripes when 16 sub-fields are present, i=4, N=1, 2, 4, 8, and 3.2t≥T. Figure 50 shows a measured diagram of the sub-field distribution when 16 sub-fields are present, i=4, N=1, 2, 4, 8, and 3.2t≥T, where the numbers 0-27 represent the scanning order of the sub-fields.

[0167] In summary, Figures 51, 52, and 53 show the optimization effects of light and dark stripes for 12-bit data, 14-bit data, and 16-bit data, respectively. For 12-subfield, 14-subfield, and 16-subfield data, the following schemes are proposed: Scheme 1 (i.e., i=0, N=1, t≥T), Scheme 2 (i.e., N=1, 2.4, 8, 3.2t≥T, where the subfields are not shifted), Scheme 3 (i.e., N=1, 2.4, 8, 3.2t≥T, where the subfields are reversed), and Scheme 4 (i.e., N=1, 2.4, 8, 3.2t≥T, where the scanning order is rearranged) all effectively improve the impact of dynamic false contouring on the display effect. Further explanation: the scheme developed according to the principles proposed in this application can effectively reduce the dynamic false contouring phenomenon in digitally driven silicon-based displays.

[0168] An embodiment of the present application also provides a data scanning device, as shown in Figure 54, the device 5400 includes: a subfield acquisition module 5401, a subfield adjustment module 5402, a brightness adjustment module 5403, a duration determination module 5404, a sorting module 5405 and a scanning module 5406.

[0169] The subfield acquisition module 5401 is used to acquire the first subfield of the data frame to be displayed and the transient brightness of the first subfield; the data frame to be displayed includes the first subfield and the second subfield;

[0170] a subfield adjustment module 5402 configured to adjust the number of subfields of the first subfield to obtain at least one third subfield, wherein the scanning weight of the first subfield is greater than or equal to the scanning weight of the third subfield;

[0171] The brightness adjustment module 5403 is used to adjust the transient brightness of the first subfield to obtain the transient brightness of the third subfield;

[0172] a duration determining module 5404, configured to determine a scan duration of the third subfield based on the transient brightness of the third subfield, wherein the scan duration of the first subfield is greater than or equal to the scan duration of the third subfield;

[0173] The sorting module 5405 is used to arrange the scanning order of the second subfield and the third subfield to obtain the target subfield scanning order;

[0174] The scanning module 5406 is configured to scan the second subfield and at least one third subfield according to the target subfield scanning sequence, scanning weight, and scanning duration.

[0175] In one example, the subfield acquisition module is specifically used to obtain the scanning weights of multiple subfields contained in the data frame to be displayed; determine the subfield whose scanning weight is greater than a preset weight threshold from the multiple subfields, and obtain the first subfield and the transient brightness of the first subfield.

[0176] In one example, the data scanning device further includes: a weight calculation module, configured to calculate a ratio of the scanning weight of the first subfield to the number of subfields in the third subfield to obtain the scanning weight of the third subfield.

[0177] In one example, the brightness adjustment module is specifically used to adjust the first voltage of the first subfield to the second voltage according to the correlation between the transient brightness and the subfield voltage when there are multiple third subfields, so as to increase the transient brightness of the first subfield and obtain the transient brightness of the third subfield.

[0178] In one example, the duration determination module includes: a first calculation module, a second calculation module, a third calculation module, and a first determination module. The first calculation module is configured to calculate the ratio of the transient brightness of the subfield to the transient brightness of the third subfield to obtain a transient brightness ratio; the second calculation module is configured to calculate the ratio of the scan weight of the first subfield to the scan weight of the third subfield to obtain a weight ratio; the third calculation module is configured to calculate the product of the transient brightness ratio and the weight ratio to obtain a target ratio; and the first determination module is configured to determine the scan duration of the third subfield based on the scan duration of the first subfield and the target ratio.

[0179] In one example, the first determination module is specifically used to calculate the product of the scanning weight of the first subfield and the initial on-screen clock corresponding to the first subfield to obtain the scanning time of the first subfield, wherein the initial on-screen clock is the unit scanning time of the subfield; adjust the initial on-screen clock to obtain the target on-screen clock; calculate the ratio of the scanning weight of the first subfield to the target ratio to obtain the target weight; calculate the product of the target weight and the target on-screen clock to obtain the scanning time of the third subfield.

[0180] In one example, the data scanning device also includes: a black frame insertion module, used to obtain a first scanning duration of the data frame to be displayed before the initial upper screen clock is adjusted, and a second scanning duration of the data frame to be displayed after the initial upper screen clock is adjusted; inserting a preset number of black frames into the data frame to be displayed so that the difference between the first scanning duration and the second scanning duration is the scanning duration of the preset number of black frames.

[0181] In one example, the sorting module is specifically used to obtain the subfield scanning order of the previous data frame of the data frame to be displayed; arrange the scanning order of the second subfield and the third subfield in the reverse order of the subfield scanning order of the previous data frame to obtain the target subfield scanning order.

[0182] In one example, the sorting module is specifically used to obtain the initial subfield scanning order of the second subfield and multiple third subfields; shift the order of the second subfield and multiple third subfields in the initial subfield scanning order according to a preset shift direction and shift quantity to obtain the target subfield scanning order.

[0183] The data scanning device provided in the embodiment of the present application can implement each process implemented in the aforementioned method embodiment. To avoid repetition, they will not be described here.

[0184] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0185] Figure 55 shows a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application.

[0186] The electronic device may include a processor 5501 and a memory 5502 storing computer program instructions.

[0187] Specifically, the processor 5501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0188] Memory 5502 may include a large capacity memory for data or instructions. By way of example and not limitation, memory 5502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 5502 may include removable or non-removable (or fixed) media. Where appropriate, memory 5502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, memory 5502 is a non-volatile solid-state memory.

[0189] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0190] The processor 5501 implements any one of the data scanning methods in the above embodiments by reading and executing computer program instructions stored in the memory 5502 .

[0191] In one example, the electronic device may further include a communication interface 5503 and a bus 5510. As shown in FIG55 , the processor 5501, the memory 5502, and the communication interface 5503 are connected via the bus 5510 and communicate with each other.

[0192] The communication interface 5503 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0193] Bus 5510 includes hardware, software or both, couples the parts of electronic equipment to each other.For example, and not limitation, bus may include accelerated graphics port (AGP) or other graphics buses, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 5510 may include one or more buses. Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0194] In addition, in conjunction with the data scanning method in the above embodiments, the present application can provide a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the data scanning methods in the above embodiments is implemented.

[0195] In addition, in combination with the data scanning method in the above embodiments, the present application can provide a computer program product to implement the data scanning method. When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device executes any one of the data scanning methods in the above embodiments.

[0196] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0197] The functional modules shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in unit, a function card or the like. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0198] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0199] The above reference is made to the flowcharts and / or block diagrams of the data scanning method, device, electronic device, storage medium and program product according to the embodiments of the present disclosure. Various aspects of the present disclosure are described. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by special-purpose hardware that performs the specified function or action, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0200] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A data scanning method, characterized in that: include: Acquire a first subfield of a data frame to be displayed and a transient brightness of the first subfield; the data frame to be displayed includes the first subfield and the second subfield; Adjusting the number of subfields of the first subfield to obtain at least one third subfield, wherein a scanning weight of the first subfield is greater than or equal to a scanning weight of the third subfield; adjusting the transient brightness of the first subfield to obtain the transient brightness of the third subfield; determining a scanning duration of the third subfield based on the transient brightness of the third subfield, wherein the scanning duration of the first subfield is greater than or equal to the scanning duration of the third subfield; Arranging the scanning order of the second subfield and the third subfield to obtain a target subfield scanning order; The second subfield and at least one of the third subfields are scanned according to the target subfield scanning sequence, scanning weight and scanning duration.

2. The method according to claim 1, characterized in that Acquiring a first subfield of a data frame to be displayed and a transient brightness of the first subfield includes: Obtaining scanning weights of a plurality of subfields included in the data frame to be displayed; A subfield having a scan weight greater than a preset weight threshold is determined from the multiple subfields to obtain the first subfield and the transient brightness of the first subfield.

3. The method according to claim 2, characterized in that After adjusting the number of subfields of the first subfield to obtain at least one third subfield, the method further includes: The ratio of the scanning weight of the first subfield to the number of subfields in the third subfield is calculated to obtain the scanning weight of the third subfield.

4. The method according to claim 1, wherein In a case where there are multiple third subfields, adjusting the transient brightness of the first subfield to obtain the transient brightness of the third subfield includes: According to the correlation between transient brightness and subfield voltage, the first voltage of the first subfield is adjusted to a second voltage to increase the transient brightness of the first subfield and obtain the transient brightness of the third subfield.

5. The method according to claim 4, characterized in that Determining a scanning duration of the third subfield based on the transient brightness of the third subfield includes: calculating a ratio of the transient brightness of the first subfield to the transient brightness of the third subfield to obtain a transient brightness ratio; calculating a ratio of a scan weight of the first subfield to a scan weight of the third subfield to obtain a weight ratio; Calculating the product of the instantaneous brightness ratio and the weight ratio to obtain a target ratio; The scanning duration of the third subfield is determined based on the scanning duration of the first subfield and the target ratio.

6. The method according to claim 5, characterized in that Determining the scanning duration of the third subfield based on the scanning duration of the first subfield and the target ratio includes: Calculating the product of the scanning weight of the first subfield and the initial on-screen clock corresponding to the first subfield to obtain the scanning duration of the first subfield, wherein the initial on-screen clock is a unit scanning duration of the subfield; Adjusting the initial on-screen clock to obtain a target on-screen clock; calculating a ratio of the scanning weight of the first subfield to the target ratio to obtain a target weight; The product of the target weight and the target on-screen clock is calculated to obtain the scanning duration of the third subfield.

7. The method according to claim 6, characterized in that After scanning the second subfield and at least one of the third subfields according to the target subfield scanning order, scanning weight, and scanning duration, the method further includes: Acquire a first scanning duration of the data frame to be displayed before the initial on-screen clock is adjusted, and a second scanning duration of the data frame to be displayed after the initial on-screen clock is adjusted; A preset number of black frames are inserted into the data frame to be displayed, so that the difference between the first scanning time length and the second scanning time length is the scanning time length of the preset number of black frames.

8. The method according to claim 1, characterized in that Arranging the scanning order of the second subfield and the third subfield to obtain a target subfield scanning order includes: Obtaining a subfield scanning order of a previous data frame of the data frame to be displayed; The scanning order of the second subfield and the third subfield is arranged in the reverse order of the subfield scanning order of the previous data frame to obtain the target subfield scanning order.

9. The method according to claim 1, characterized in that Arranging the scanning order of the second subfield and the third subfield to obtain a target subfield scanning order includes: Acquire an initial subfield scanning order of the second subfield and a plurality of the third subfields; The second subfield and the plurality of third subfields are shifted in order in the initial subfield scanning sequence according to a preset shift direction and shift quantity to obtain the target subfield scanning sequence.

10. A data scanning device, characterized in that: include: A subfield acquisition module, configured to acquire a first subfield of a data frame to be displayed and a transient brightness of the first subfield; the data frame to be displayed includes the first subfield and the second subfield; a subfield adjustment module, configured to adjust the number of subfields of the first subfield to obtain at least one third subfield, wherein a scanning weight of the first subfield is greater than or equal to a scanning weight of the third subfield; a brightness adjustment module, configured to adjust the transient brightness of the first subfield to obtain the transient brightness of the third subfield; a duration determining module, configured to determine a scanning duration of the third subfield based on the transient brightness of the third subfield, wherein the scanning duration of the first subfield is greater than or equal to the scanning duration of the third subfield; a sorting module, configured to arrange a scanning order of the second subfield and the third subfield to obtain a target subfield scanning order; A scanning module is configured to scan the second subfield and at least one of the third subfields according to the target subfield scanning sequence, scanning weight, and scanning duration.

11. An electronic device, characterized in that: The electronic device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the data scanning method according to any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium, characterized in that Computer program instructions are stored on the computer-readable storage medium, and when the computer program instructions are executed by the processor, the data scanning method according to any one of claims 1 to 9 is implemented.

13. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the data scanning method according to any one of claims 1 to 9.

Images