Image generation method and electronic equipment

Abstract

The invention provides an image generation method, which comprises the steps of determining a plurality of regions based on depth information of each pixel in an initial three-dimensional image, the depth information representing a relative distance of a scene point corresponding to the pixel in the initial three-dimensional image relative to a display plane; obtaining sight distance data in real time, wherein the sight distance data represents a relative position relationship between a user and a display plane at at least two time points; predicting a relative motion track of the user relative to the display plane according to the sight distance data; and according to the sight distance data and the relative motion track, adjusting image parameters of at least part of the plurality of regions to generate a target three-dimensional image.

Description

Technical Field

[0001] This disclosure relates to the field of image processing, and more specifically, to an image generation method and electronic device. Background Technology

[0002] With the continuous advancement of 3D display technology, enhancing the immersiveness and viewing comfort of stereoscopic images has become a key focus in the industry. 3D image display solutions typically render images based on a preset, fixed optimal viewing distance, or simply make global adjustments to display parameters based on instantaneous static detection of the observer's current position. When the observer moves forward or backward relative to the screen, or when the distance changes, the display device struggles to respond in advance based on the movement trajectory, easily leading to problems such as depth perception distortion, delayed image adjustment, and visual fatigue, making it difficult to meet the high-quality display requirements of dynamic viewing scenarios. Summary of the Invention

[0003] In view of this, the present disclosure provides an image generation method and an electronic device.

[0004] One aspect of this disclosure provides an image generation method, comprising: determining multiple regions based on depth information of each pixel in an initial three-dimensional image, wherein the depth information represents the relative distance of scene points corresponding to pixels in the initial three-dimensional image relative to a display plane; acquiring viewing distance data in real time, wherein the viewing distance data represents the relative positional relationship between a user and the display plane at at least two time points; predicting the relative motion trajectory of the user relative to the display plane based on the viewing distance data; and adjusting image parameters of at least some regions in the multiple regions based on the viewing distance data and the relative motion trajectory to generate a target three-dimensional image.

[0005] According to embodiments of this disclosure, image parameters include brightness parameters and / or parallax parameters, whereby the parallax parameter characterizes the pixel offset between a pixel and the user's eyes. Adjusting image parameters in at least a portion of multiple regions includes: adjusting the brightness parameters and / or parallax parameters in at least a portion of multiple regions based on viewing distance data and relative motion trajectories.

[0006] According to embodiments of this disclosure, multiple regions are determined, including: defining a first region as the region formed by pixels whose relative distance, represented by depth information, is less than a first distance threshold; defining a second region as the region formed by pixels whose relative distance, represented by depth information, is less than or equal to a second distance threshold and greater than or equal to the first distance threshold; and defining a third region as the region formed by pixels whose relative distance, represented by depth information, is greater than the second distance threshold.

[0007] According to embodiments of this disclosure, the viewing distance data includes first data, which characterizes the relative distance between the midpoint of the user's eyes and the display plane. Adjusting image parameters of at least some regions in a plurality of regions includes: increasing the brightness parameter of the first region and / or decreasing the brightness parameter of the third region in response to the first data being less than a third distance threshold; and / or decreasing the difference between the brightness parameter of the first region and the brightness parameter of the third region in response to the first data being greater than or equal to the third distance threshold.

[0008] According to embodiments of this disclosure, the viewing distance data further includes second data, which characterizes the deflection angle of the user's binoculars' line of sight relative to the normal direction of the display plane. Adjusting image parameters in at least some regions of multiple regions includes: determining the offset correction amount for each pixel based on the first data and the second data; and adjusting the parallax parameters corresponding to each region based on the offset correction amount.

[0009] According to embodiments of this disclosure, the image parameters include brightness parameters, and the method further includes: adjusting the brightness parameter of a first region to a first brightness parameter, wherein the first brightness parameter is less than or equal to a first brightness threshold; and / or adjusting the brightness parameter of a second region to a second brightness parameter, wherein the second brightness parameter is greater than or equal to a second brightness threshold; wherein the first brightness parameter is greater than the second brightness parameter, and the first brightness threshold is greater than the second brightness threshold.

[0010] According to embodiments of this disclosure, the image parameters include pulse signal parameters, which characterize the flicker frequency of the corresponding display point of a pixel on the display plane. The method further includes: adjusting the pulse signal parameters of the first region to a first pulse signal parameter; and / or adjusting the pulse signal parameters of the third region to a second pulse signal parameter; wherein the first pulse signal parameter is greater than the second pulse signal parameter.

[0011] According to embodiments of this disclosure, adjusting image parameters in at least some regions of a plurality of regions includes: determining the target image parameters to be adjusted; and gradually changing the target image parameters along consecutive frames based on the image parameters currently corresponding to the initial three-dimensional image until the target image parameters are reached.

[0012] According to embodiments of this disclosure, the image generation method further includes: determining at least one target region based on the position of pixels in each region and the depth information corresponding to each region, wherein the center of the target region is determined based on the position of the pixels and the radius of the target region is determined based on the depth information of each region; and blurring the image parameters of the region corresponding to the target range so that at the boundary of each region, the image parameters corresponding to each pixel gradually change along the position of the pixel.

[0013] Another aspect of this disclosure provides an image generation apparatus, comprising: a first determining module, configured to determine multiple regions based on depth information of each pixel in an initial three-dimensional image, wherein the depth information characterizes the relative distance between scene points corresponding to pixels in the initial three-dimensional image and a display plane; a first acquiring module, configured to acquire viewing distance data in real time, wherein the viewing distance data characterizes the relative positional relationship between a user and the display plane at at least two time points; a first predicting module, configured to predict the relative motion trajectory of the user relative to the display plane based on the viewing distance data; and a first adjusting module, configured to adjust image parameters of at least some regions in the multiple regions based on the viewing distance data and the relative motion trajectory, to generate a target three-dimensional image.

[0014] Another aspect of this disclosure provides an electronic device, including: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform at least one of the following operations: determining multiple regions based on depth information of pixels in an initial three-dimensional image, the depth information representing the relative distance of scene points corresponding to pixels in the initial three-dimensional image relative to a display plane; acquiring viewing distance data in real time, the viewing distance data representing the relative positional relationship between a user and the display plane at at least two time points; predicting the relative motion trajectory of the user relative to the display plane based on the viewing distance data; and adjusting image parameters of at least some regions in the multiple regions based on the viewing distance data and the relative motion trajectory to generate a target three-dimensional image.

[0015] Another aspect of this disclosure provides a computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform an image generation method according to any of the foregoing embodiments.

[0016] Another aspect of this disclosure provides a computer program product, including a computer program / instructions, characterized in that the computer program / instructions, when executed by a processor, implement the operation of the image generation method of any of the foregoing embodiments. Attached Figure Description

[0017] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0018] Figure 1 A flowchart illustrating an image generation method according to an embodiment of the present disclosure is shown schematically;

[0019] Figure 2 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically;

[0020] Figure 3A flowchart illustrating the determination of multiple regions in an image generation method according to an embodiment of the present disclosure is shown schematically.

[0021] Figure 4 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically;

[0022] Figure 5 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically;

[0023] Figure 6 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically;

[0024] Figure 7 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically;

[0025] Figure 8 A flowchart illustrating the adjustment of image parameters in an image generation method according to an embodiment of the present disclosure is shown schematically.

[0026] Figure 9 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically;

[0027] Figure 10 A block diagram schematically illustrates an image generation apparatus according to an embodiment of the present disclosure; and

[0028] Figure 11 A block diagram of an electronic device suitable for implementing the methods described above, according to embodiments of the present disclosure, is illustrated schematically. Detailed Implementation

[0029] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0030] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0031] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0032] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0033] In the embodiments disclosed herein, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.

[0034] Embodiments of this disclosure provide an image generation method, comprising: determining multiple regions based on depth information of each pixel in an initial three-dimensional image, wherein the depth information represents the relative distance of scene points corresponding to pixels in the initial three-dimensional image relative to a display plane; acquiring viewing distance data in real time, wherein the viewing distance data represents the relative positional relationship between a user and a display plane at at least two time points; predicting the relative motion trajectory of the user relative to the display plane based on the viewing distance data; and adjusting image parameters of at least some regions in the multiple regions based on the viewing distance data and the relative motion trajectory to generate a target three-dimensional image.

[0035] Figure 1 A flowchart illustrating an image generation method according to an embodiment of the present disclosure is shown schematically.

[0036] like Figure 1 As shown, the image generation method may include at least operations S110 to S140.

[0037] In operation S110, multiple regions are determined based on the depth information of each pixel in the initial 3D image. The depth information represents the relative distance between the scene point corresponding to a pixel in the initial 3D image and the display plane. The initial 3D image can be image data containing depth channels, or a video frame with spatial depth information generated using binocular parallax algorithms and light field rendering techniques. The magnitude of the depth information reflects the distance of objects in the virtual scene from the display screen plane. For example, the image can be divided into foreground and background regions based on the histogram distribution of depth values; alternatively, image recognition algorithms can be used to extract the main display object in the image as one independent region, and the remaining parts as another region.

[0038] During operation S120, viewing distance data is acquired in real time. This data represents the relative positional relationship between the user and the display plane at at least two points in time. The viewing distance data may include the straight-line distance from the center of the user's eyes to the center of the display screen, or the coordinates of the user's head in a three-dimensional spatial coordinate system. Acquiring data at at least two points in time is to form a time series for analyzing the user's dynamic behavior. Sensors integrated into the display device can periodically collect data on the user's facial features or eye positions at a preset sampling frequency, and the relative distance between the user and the display plane at each moment can be calculated geometrically.

[0039] For example, an infrared eye-tracking sensor can be used to collect the change in the distance between the user's pupils every tens of milliseconds, thereby inferring the distance between the user and the screen; or, a depth camera can be used to directly measure the vertical distance between the user's face and the screen, and record a time-stamped distance sequence.

[0040] In operation S130, the relative motion trajectory of the user relative to the display plane is predicted based on the viewing distance data. The relative motion trajectory can refer to the trend of the user's position change over a short period of time in the future, including the direction of movement (e.g., moving closer or further away) and the speed of movement. The relative motion trajectory can be obtained by inputting the collected historical viewing distance data sequence into a motion prediction algorithm or neural network model, based on the slope or acceleration of the position data change.

[0041] Specific algorithms can also be used to predict the relative motion trajectory of a user relative to the display plane. For example, based on the gradually decreasing trend of distance data from multiple recent consecutive time points, it can be predicted that the user is approaching the display plane at a specific speed; or, by processing historical location data through a Kalman filter algorithm, the motion vector of the user within a specific time range in the future can be predicted.

[0042] In operation S140, based on viewing distance data and relative motion trajectory, image parameters of at least some areas in multiple regions are adjusted to generate a target 3D image. Image parameters may include, but are not limited to, various indicators affecting image display effects, such as brightness, contrast, color saturation, or parallax offset used to construct a sense of depth. The adjustment process is based on the user's real-time position and motion trends, differentially controlling the display characteristics of different depth regions.

[0043] Based on the predicted user location, a preset parameter mapping relationship can be found, or the target parameter values ​​that each area should match can be determined through real-time calculation formulas, and the image data or display drive signals can be modified accordingly. For example, when it is predicted that a user is rapidly approaching, the grayscale value or gain coefficient of pixels in a specific area can be adjusted in advance; or, based on the change in the distance between the user and the screen, the parallax parameters of different areas can be scaled in real time to generate a stereoscopic image adapted to the current viewing distance.

[0044] According to embodiments of this disclosure, by integrating depth information into partitioning and using a motion trajectory-based prediction mechanism, the image display parameters can be adaptively compensated in advance when the user moves relative to the screen. This avoids the limitations of single-dimensional adjustment, effectively alleviates the problem of discontinuous visual experience caused by system response lag, and enables the three-dimensional display effect to smoothly transition with the user's dynamic position changes, significantly improving the immersion and comfort of viewing.

[0045] Figure 2 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically.

[0046] like Figure 2 As shown, based on the aforementioned embodiments, the image parameters include brightness parameters and / or parallax parameters. The parallax parameters characterize the pixel offset between the user's eyes and the pixel offset between the two eyes. Operation S140 may include operation S210.

[0047] In operation S210, based on viewing distance data and relative motion trajectory, the brightness parameters and / or parallax parameters of at least some areas in multiple regions are adjusted. The brightness parameters may refer to the digital gain, grayscale level, or backlight drive level that controls the luminous intensity of the display pixels; the parallax parameters refer to the relative displacement value that the left-eye view and the right-eye view need to generate in the horizontal direction in order to construct depth information in the observer's eyes, and this value determines the position of the virtual object in terms of perceived depth.

[0048] Adjusting brightness and / or parallax parameters can dynamically change the brightness output intensity of different areas based on the predicted user motion state to match the visual sensitivity of the human eye at different viewing distances; or, based on the dynamic changes in viewing distance, the binocular parallax geometric model can be reconstructed in real time to calculate the pixel offset adapted to the current viewing distance and angle, and perform geometric correction on the stereo image.

[0049] For example, when viewing distance data and motion trajectory indicate that the user is rapidly approaching the display plane, the brightness gain of the image is adjusted synchronously to prevent excessive brightness and glare, and the parallax parameters are recalculated at the same time to prevent visual fatigue caused by excessive depth perception; or, the parallax parameters are simply adjusted based on changes in the user's position to maintain the three-dimensional accuracy of the object's shape.

[0050] According to the embodiments of this disclosure, by dynamically adjusting the two core dimensions that affect the three-dimensional experience—brightness and parallax—based on motion trends, the shortcomings of focusing only on a single dimension or adjusting only based on static position are avoided. This ensures that the stereoscopic image remains true to its geometric structure and conforms to the natural perception law of the human eye in terms of light and shadow intensity as the user moves, thereby improving the immersion and comfort when watching dynamically.

[0051] Figure 3 A flowchart illustrating the determination of multiple regions in an image generation method according to an embodiment of the present disclosure is shown schematically.

[0052] like Figure 3 As shown, based on the aforementioned embodiments, operation S110 may include operations S310 to S330.

[0053] In operation S310, the region comprised of pixels whose relative distance, as represented by depth information, is less than a first distance threshold is designated as the first region. The first distance threshold can be a preset depth reference value used to define the area in the image that is visually closest to the observer. The first region spatially corresponds to the foreground portion of a 3D scene, or a set of objects that appear to "go out of screen" in a stereoscopic display. Pixels meeting the condition can be marked as the first region mask by comparing their depth grayscale value or Z-axis coordinate value with the first distance threshold. For example, in a depth map with depth values ​​from 0 to 255, setting the first distance threshold to 80, the set of pixels with depth values ​​less than 80 is designated as the first region; alternatively, pixels whose distance from the negative parallax direction of the display plane exceeds a specific number of centimeters can be included in the first region.

[0054] In operation S320, the region comprised of pixels whose relative distance, represented by depth information, is less than or equal to a second distance threshold and greater than or equal to a first distance threshold, is designated as the second region. The second distance threshold, being greater than the first distance threshold, is used to define intermediate transition levels of scene depth. The second region typically corresponds to the midground of a 3D scene, or a set of objects near the display plane with low parallax. A depth value range between the foreground and background can be selected, and pixels falling within this range are identified as the second region. For example, setting the second distance threshold to 180, the set of pixels with depth values ​​between 80 and 180 is classified as the second region; or, pixels within a certain range near zero parallax on the display plane are assigned to the second region.

[0055] In operation S330, the region comprised of pixels whose relative distance, represented by depth information, exceeds a second distance threshold is designated as the third region. Spatially, the third region typically corresponds to the background or distant portion of a 3D scene. These pixels represent scene points that are visually furthest from the observer, or those that create a "deep" effect. The remaining pixels with depth values ​​exceeding the second distance threshold can be grouped together to form a background layer. For example, the set of pixels with a depth value greater than 180 is designated as the third region.

[0056] According to the embodiments of this disclosure, by setting multi-level distance thresholds, the continuously changing depth information is discretized into independent regions with clear spatial hierarchy attributes such as foreground, midground, and background. This breaks through the limitation of relying solely on two-dimensional planar position to divide regions, providing an accurate spatial mapping basis for subsequent realization of depth-based differentiated display control, and helping to construct a three-dimensional image with a stronger sense of hierarchy and more in line with real physical laws.

[0057] Figure 4 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically.

[0058] like Figure 4 As shown, based on the aforementioned embodiments, the viewing distance data includes first data, which represents the relative distance between the midpoint of the user's eyes and the display plane. Specifically, the first data can refer to the physical distance value of the center point of the line connecting the user's eyebrows or eyes in a direction perpendicular to the display screen. This distance value can be obtained directly through the ranging function of a depth camera, or it can be calculated in reverse based on the pixel spacing of the interpupillary distance on the image sensor combined with the principle of perspective.

[0059] Operation S140 may include operation S410 and / or operation S420.

[0060] In operation S410, in response to the first data being less than the third distance threshold, the brightness parameter of the first area is increased, and / or the brightness parameter of the third area is decreased. The third distance threshold is the dividing point between near-field viewing mode and far-field viewing mode, for example, 1 meter. When the user is within the near-field range, the human eye is more sensitive to depth information. At this time, by increasing the contrast between the foreground and background, the visual sense of three-dimensionality can be artificially enhanced, simulating the "out-of-screen" effect.

[0061] Increasing the brightness parameters of the first area and / or decreasing the brightness parameters of the third area can increase the driving current of the backlight zone corresponding to the first area (foreground), making its brightness higher than the standard value, while decreasing the brightness of the third area (background), making it darker than the standard value, thus creating a "spotlight"-like visual focusing effect. For example, when the user is detected to be less than 1 meter away from the screen, the brightness gain of the first area (foreground) is increased by 30%, while the brightness gain of the third area (background) is decreased by 20%, to highlight the main subject.

[0062] When operating S420, in response to the first data being greater than or equal to the third distance threshold, the difference between the brightness parameters of the first region and the third region is reduced. When the user is in the far field, the human eye's depth perception is relatively weakened, and excessive contrast between light and dark can disrupt the overall sense of the image. Therefore, it is necessary to reduce the brightness difference between the foreground and background to make the brightness distribution of the image more uniform, thereby enhancing the immersiveness and blending of the overall scene.

[0063] Reducing the difference between the brightness parameters of the first and third regions allows the brightness parameters of each region to be adjusted to be close to the global average brightness or the standard brightness reference value, thus reducing the visual disjointedness caused by artificially enhanced contrast. For example, when the user is at least 1 meter away from the screen, adjusting the brightness gain of both the first and third regions to within ±10% of the reference value makes the brightness transition between the foreground and background more natural.

[0064] According to embodiments of this disclosure, by establishing a dynamic mapping relationship between viewing distance and regional brightness distribution, it is possible to simulate the visual psychological characteristics of the human eye at different viewing distances. When viewing at close range, the contrast between light and dark is enhanced to strengthen the stereoscopic impact, and when viewing at a distance, the brightness is balanced to improve the integrity and immersion of the scene.

[0065] Figure 5 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically.

[0066] like Figure 5As shown, based on the aforementioned embodiment, the viewing distance data also includes second data, which characterizes the angle of deflection of the user's binocular gaze direction relative to the normal direction of the display plane. The offset correction amount refers to the pixel-level compensation value that needs to be applied to the original image parallax to eliminate visual geometric distortion caused by the tilt of the viewing angle. The second data typically includes the user's yaw angle or pitch angle, reflecting the degree to which the user's gaze deviates from the screen's center normal.

[0067] Operation S140 may include operations S510 to S520.

[0068] In operation S510, the offset correction amount for each pixel is determined based on the first data and the second data. By constructing a mathematical model that includes the geometric relationship between viewing distance, viewing angle, and parallax, the required parallax compensation value under the current viewing state can be calculated in real time, ensuring that the imaging position of the virtual object on the retina does not undergo erroneous depth drift due to changes in the viewing angle.

[0069] For example, the pixel-level disparity correction ΔP is calculated using the following formula:

[0070] ΔP=k*α*D

[0071] Where k is a preset correction coefficient (e.g., 0.02), α is the user's viewing angle offset angle (second data), and D is the relative distance between the user and the display plane (first data).

[0072] When operating the S520, the disparity parameters for each region are adjusted based on the offset correction. This adjustment involves superimposing the calculated offset correction onto the original left and right eye image disparity data, essentially performing real-time geometric correction on the 3D image to change the relative separation of the left and right eye views in the horizontal direction. A uniform correction can be applied to all pixels on the screen, or a weighted correction can be applied based on different depth regions. The updated disparity parameters then drive the rendering engine to regenerate the left and right eye disparity images. For example, adding the calculated ΔP to the original disparity parameters dynamically stretches or compresses the distance between the left and right eye images when the user's yaw angle exceeds a specific angle (e.g., 15 degrees), preventing image misalignment.

[0073] According to the embodiments of this disclosure, by introducing a dynamic parallax correction mechanism that combines viewing distance and viewing angle, the problem of depth distortion and object deformation that easily occur when the user deviates from the preset viewing angle in the directional backlight technology is solved, ensuring that the user can still obtain a 3D display effect with correct geometric relationships and no visual distortion when moving or viewing from the side.

[0074] Figure 6 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically.

[0075] like Figure 6 As shown, based on the aforementioned embodiments, the image parameters include brightness parameters, and the image generation method may include operations S610 and / or S620.

[0076] In operation S610, the brightness parameter of the first area is adjusted to a first brightness parameter, which is less than or equal to a first brightness threshold. The first brightness parameter characterizes the high brightness level, high grayscale value, or high backlight drive level used to drive the corresponding area pixels in the display screen. The first brightness threshold can be the maximum peak brightness supported by the display device hardware, or a safe brightness upper limit set to prevent glare to the human eye. The display brightness of the area can be increased by increasing the drive current of the corresponding partition in the micro-LED backlight array or increasing its light emission duty cycle, thereby creating a prominent foreground effect visually, while simultaneously limiting it to not exceed the physical limits of the hardware or the limits of human eye comfort.

[0077] For example, in a screen that supports high dynamic range display, the first brightness threshold is set to 1000 nits, and the backlight zone brightness corresponding to the first area is set to a high brightness mode between 800 nits and 1000 nits.

[0078] In operation S620, the brightness parameter of the second area is adjusted to a second brightness parameter, which is greater than or equal to a second brightness threshold. The first brightness parameter is greater than the second brightness parameter, and the first brightness threshold is greater than the second brightness threshold. The second brightness parameter represents the relatively low brightness level or base brightness value used to drive the corresponding area pixels on the display screen. The second brightness threshold can be the minimum brightness limit to ensure image details are visible, avoiding loss of detail in dark areas or blackouts due to excessively low brightness. The backlight brightness of non-prime areas (such as mid-ground or background) can be reduced to create a significant contrast with the high-brightness first area, utilizing the visual psychology principle of "near bright, far dark" to enhance the depth of the image, while ensuring that the brightness of this area does not fall below the minimum standard required to maintain basic display quality.

[0079] For example, the second brightness threshold is set to 200 nits, and the brightness of the backlight zone corresponding to the second area is set to a low brightness mode between 200 nits and 400 nits to ensure that the background area is still clearly visible even though it is dark.

[0080] According to the embodiments of this disclosure, by implementing differentiated brightness threshold control for different depth areas, and utilizing the display characteristics of high dynamic range, a light and shadow effect with a bright foreground and a deep background (or midground) is constructed at the physical level. This not only restores the lighting logic of the real scene, but also overcomes the problem of insufficient sense of layering caused by uniform brightness in 3D display by significantly enhancing the contrast between the foreground and non-foreground areas, thereby improving the overall stereoscopic perception experience.

[0081] Figure 7 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically.

[0082] like Figure 7 As shown, based on the aforementioned embodiments, the image parameters include pulse signal parameters, which characterize the flicker frequency of the corresponding display point on the display plane. Specifically, the pulse signal parameters can refer to the frequency of the pulse width modulation (PWM) signal used to control the brightness adjustment of the backlight unit. This parameter determines the switching rate of the display light source per unit time, directly related to the persistence of vision effect of the human eye and its ability to capture dynamic images.

[0083] The image generation method may also include operation S710, and / or operation S720.

[0084] When operating the S710, adjust the pulse signal parameters of the first region to the first pulse signal parameters. The first pulse signal parameters are typically set to a higher frequency value. The first region, as the foreground or main subject area that the user is focusing on, often contains fast-moving objects. Using high-frequency drive helps improve the dynamic contrast of the image and reduces motion blur or ghosting caused by visual persistence. For example, setting the PWM dimming frequency corresponding to the first region to 2000 Hz or higher enhances the edge sharpness and three-dimensional texture of foreground objects.

[0085] When operating the S720, adjust the pulse signal parameters of the third region to match the second pulse signal parameters. The first pulse signal parameter is greater than the second pulse signal parameter. The second pulse signal parameter is set to a relatively low frequency value. Since the third region serves as a background or non-focused area, the human eye has lower requirements for detail resolution. Using a lower frequency can accommodate the flicker sensitivity of the human eye in peripheral vision, improving viewing comfort. The backlight zones corresponding to the background area can be configured to a standard frequency or low-frequency mode to differentiate them from the high-frequency mode of the foreground. For example, setting the PWM dimming frequency corresponding to the third region to 480 Hz can reduce visual fatigue while maintaining background image display.

[0086] According to the embodiments of this disclosure, by applying differentiated pulse modulation strategies to different depth regions in a single frame image, fine-grained management at the display driving level is achieved. High-frequency modulation is used in the foreground region that the user is most concerned with to ensure excellent dynamic image quality and contrast, while low-frequency modulation is used in the background region to take into account viewing comfort. Thus, while improving the overall three-dimensional display effect, it effectively solves the problem that a single frequency drive cannot simultaneously meet the requirements of high dynamic response and visual comfort.

[0087] Figure 8A flowchart illustrating the adjustment of image parameters in an image generation method according to an embodiment of the present disclosure is shown schematically.

[0088] like Figure 8 As shown, based on the aforementioned embodiments, operation S140 may include operations S810 to S820.

[0089] In operation S810, the target image parameters to be adjusted are determined. The target image parameters refer to the ideal display values ​​calculated using the aforementioned depth-backlight mapping model or parallax correction formula, based on the latest user viewing distance, viewing angle, or position data. These values ​​represent the theoretically optimal final brightness level or parallax setting that the display device should achieve to best match the user's current state. For example, when a user's viewing distance is detected to rapidly change from far to near, the target brightness parameter for the foreground area is determined to be 1.3 times the current reference value based on preset logic.

[0090] During operation of S820, based on the image parameters corresponding to the current initial 3D image, the parameters gradually change towards the target image parameters along consecutive frames until the target image parameters are reached. Gradual change towards the target image parameters along consecutive frames means smoothing the parameter change process in the time dimension (such as linear interpolation), so that the parameter values ​​gradually approach the target values ​​at certain step sizes within the refresh cycle of multiple frames, rather than causing a step-like abrupt change within a single frame.

[0091] A dynamic interpolation algorithm can be introduced, setting an interpolation rate coefficient between 0 and 1. Based on the difference between the actual parameter value and the target parameter value in the previous frame, the increment to be applied in the current frame is calculated. The specific calculation logic can be expressed as: L t =L t−1 +β*(Lt arget -L t-1 ); where L t L is the parameter value for the current frame. t-1 Here are the parameter values ​​from the previous frame, β is the interpolation rate, and L is the value of L. target The target image parameters are determined for operation S810.

[0092] For example, by setting the interpolation rate β to 0.2, 20% of the difference between the current actual brightness and the target brightness is added to the current brightness during each frame rendering, so that the screen brightness transitions smoothly during user movement and avoids flickering.

[0093] According to the embodiments of this disclosure, by introducing a time-based gradation mechanism during the image parameter adjustment process, the drastic changes in image parameters (such as brightness or parallax) caused by rapid changes in user position or viewing angle are effectively avoided, eliminating visual flicker and abruptness during image switching, ensuring the continuity and stability of the three-dimensional display effect during dynamic adjustment, and enabling the human eye to naturally adapt to changes in image depth and brightness.

[0094] Figure 9 Another flowchart of an image generation method according to an embodiment of the present disclosure is illustrated schematically.

[0095] like Figure 9 As shown, based on the aforementioned embodiments, the image generation method may further include operations S910 to S920.

[0096] In operation S910, at least one target region is determined based on the pixel positions and corresponding depth information of each region. The center of the target region is determined by the pixel positions, and its radius is determined by the depth information of each region. The target region can be understood as the spatial neighborhood involved in parametric smoothing of a specific pixel or partition, or the coverage area of ​​the filter kernel used to perform convolution operations. The size of this range determines the width of the parametric transition band. The depth difference between different regions can be used as the calculation basis; the larger the depth difference, the greater the spatial distance between them, and the larger the target region radius (i.e., blur radius) needs to be set for a natural visual transition; conversely, a smaller depth difference results in a smaller radius.

[0097] For example, for pixels at the boundary between the foreground and background regions, calculate the difference in their average depth using the formula r=0.5*|D 前景 -D 背景 | Calculate the dynamic blur radius r, and define the target region with the current pixel as the center and r as the radius, where D 前景 D represents the depth value of the foreground region. 背景 This represents the depth value of the background area.

[0098] In operation S920, the image parameters of the region corresponding to the target area are blurred so that the image parameters corresponding to each pixel gradually change along the pixel position at the boundary of each region. Blur processing can refer to using a specific mathematical model (such as a Gaussian distribution model) to perform weighted averaging or convolution operations on the image parameters (such as the brightness gain matrix or disparity map) within the target region, in order to eliminate abrupt changes in parameters at the region boundaries. For example, spatial filtering can be performed on the two-dimensional distribution map of brightness or disparity parameters, so that the originally distinct parameter boundaries are transformed into a transition zone with continuously changing values. Specifically, for example, using the calculated dynamic blur radius, Gaussian blur processing is performed on the brightness gain matrix of the backlight zone, so that the brightness of the foreground bright area and the background dark area shows a gradual decrease at the boundary, rather than a cliff drop.

[0099] According to embodiments of this disclosure, by introducing an edge blending mechanism based on dynamic radius adjustment of depth difference, the "halo" effect or brightness discontinuity that is easily generated when processing the boundaries of different depth areas in zone dimming technology is effectively solved. This parameter gradient processing in the spatial dimension allows the foreground object and the background environment to blend naturally in terms of light and shadow, eliminating visual interference caused by sudden changes in brightness or parallax, and further improving the realism and comfort of 3D display.

[0100] Figure 10 A block diagram of an image generation apparatus according to an embodiment of the present disclosure is shown schematically.

[0101] like Figure 10 As shown, the image generation device 1000 may include a first determining module 1010, a first acquiring module 1020, a first predicting module 1030, and a first adjusting module 1040.

[0102] The first determining module 1010 is used to determine multiple regions based on the depth information of each pixel in the initial three-dimensional image. The depth information represents the relative distance between the scene point corresponding to the pixel in the initial three-dimensional image and the display plane. In some embodiments, the first determining module 1010 can be used to perform operation S110 in the image generation method described above, which will not be elaborated here.

[0103] The first acquisition module 1020 is used to acquire viewing distance data in real time. The viewing distance data represents the relative positional relationship between the user and the display plane at at least two points in time. In some embodiments, the first acquisition module 1020 can be used to perform operation S120 in the image generation method described above, which will not be elaborated here.

[0104] The first prediction module 1030 is used to predict the relative motion trajectory of the user relative to the display plane based on the viewing distance data. In some embodiments, the first prediction module 1030 may be used to perform operation S130 in the image generation method described above, which will not be elaborated here.

[0105] The first adjustment module 1040 is used to adjust the image parameters of at least some regions in multiple regions according to the viewing distance data and the relative motion trajectory, so as to generate a target three-dimensional image. In some embodiments, the first adjustment module 1040 can be used to perform operation S140 in the image generation method described above, which will not be elaborated here.

[0106] According to embodiments of this disclosure, the image parameters include brightness parameters and / or parallax parameters, whereby the parallax parameters characterize the pixel offset between a pixel and the user's eyes, and the first adjustment module may include a second adjustment module.

[0107] The second adjustment module is used to adjust the brightness parameters and / or parallax parameters of at least some regions in multiple regions based on viewing distance data and relative motion trajectories. In some embodiments, the second adjustment module can be used to perform operation S210 in the image generation method described above, which will not be elaborated here.

[0108] According to embodiments of this disclosure, the first determining module may include a first region division module, a second region division module, and a third region division module.

[0109] The first region segmentation module is used to define the region formed by pixels whose relative distance, as represented by depth information, is less than a first distance threshold as the first region. In some embodiments, the first region segmentation module can be used to perform operation S310 in the image generation method described above, which will not be elaborated here.

[0110] The second region segmentation module is used to define the region formed by pixels whose relative distance, represented by depth information, is less than or equal to a second distance threshold and greater than or equal to a first distance threshold as the second region. In some embodiments, the second region segmentation module can be used to perform operation S320 in the image generation method described above, which will not be elaborated here.

[0111] The third region segmentation module is used to define the region formed by pixels whose relative distance, as represented by depth information, is greater than a second distance threshold as the third region. In some embodiments, the third region segmentation module can be used to perform operation S330 in the image generation method described above, which will not be elaborated here.

[0112] According to embodiments of this disclosure, the viewing distance data includes first data, which represents the relative distance between the midpoint of the user's eyes and the display plane, and the first adjustment module may include a third adjustment module and / or a fourth adjustment module.

[0113] The third adjustment module is used to increase the brightness parameter of the first region and / or decrease the brightness parameter of the third region in response to the first data being less than the third distance threshold. In some embodiments, the third adjustment module may be used to perform operation S410 in the image generation method described above, which will not be elaborated here.

[0114] The fourth adjustment module is used to reduce the difference between the brightness parameters of the first region and the brightness parameters of the third region in response to the first data being greater than or equal to the third distance threshold. In some embodiments, the fourth adjustment module can be used to perform operation S420 in the image generation method described above, which will not be elaborated here.

[0115] According to an embodiment of this disclosure, the viewing distance data further includes second data, which represents the deflection angle of the user's binoculars' line of sight relative to the normal direction of the display plane. The first adjustment module may include a second determining module and a fifth adjustment module.

[0116] The second determining module is used to determine the offset correction amount of each pixel based on the first data and the second data. In some embodiments, the second determining module can be used to perform operation S510 in the image generation method described above, which will not be elaborated here.

[0117] The fifth adjustment module is used to adjust the disparity parameters corresponding to each region based on the offset correction amount. In some embodiments, the fifth adjustment module can be used to perform operation S520 in the image generation method described above, which will not be elaborated here.

[0118] According to embodiments of this disclosure, the image parameters include brightness parameters, and the image generation apparatus may further include a sixth adjustment module and / or a seventh adjustment module.

[0119] The sixth adjustment module is used to adjust the brightness parameter of the first region to a first brightness parameter, wherein the first brightness parameter is less than or equal to a first brightness threshold. In some embodiments, the sixth adjustment module can be used to perform operation S610 in the image generation method described above, which will not be elaborated here.

[0120] The seventh adjustment module is used to adjust the brightness parameter of the second region to a second brightness parameter, which is greater than or equal to a second brightness threshold. The first brightness parameter is greater than the second brightness parameter, and the first brightness threshold is greater than the second brightness threshold. In some embodiments, the seventh adjustment module can be used to perform operation S620 in the image generation method described above, which will not be elaborated upon here.

[0121] According to embodiments of this disclosure, the image parameters include pulse signal parameters, which characterize the flicker frequency of the corresponding display point of the pixel on the display plane. The image generation device may further include an eighth adjustment module and / or a ninth adjustment module.

[0122] The eighth adjustment module is used to adjust the pulse signal parameters of the first region to the first pulse signal parameters. In some embodiments, the eighth adjustment module can be used to perform operation S710 in the image generation method described above, which will not be elaborated here.

[0123] The ninth adjustment module is used to adjust the pulse signal parameters of the third region to the second pulse signal parameters, wherein the first pulse signal parameters are greater than the second pulse signal parameters. In some embodiments, the ninth adjustment module can be used to perform operation S720 in the image generation method described above, which will not be elaborated here.

[0124] According to embodiments of this disclosure, the first adjustment module may include a third determining module and a gradation module.

[0125] The third determining module is used to determine the target image parameters corresponding to the adjustment. In some embodiments, the third determining module can be used to perform operation S810 in the image generation method described above, which will not be elaborated here.

[0126] The gradient module is used to gradually transition from the initial 3D image to the target image parameters along consecutive frames, based on the image parameters currently corresponding to the initial 3D image, until the target image parameters are reached. In some embodiments, the gradient module can be used to perform operation S820 in the image generation method described above, which will not be elaborated here.

[0127] According to embodiments of this disclosure, the image generation apparatus may further include a fourth determining module and a blur processing module.

[0128] The fourth determining module is used to determine at least one target region based on the position of pixels in each region and the corresponding depth information of each region. The center of the target region is determined based on the pixel position, and the radius of the target region is determined based on the depth information of each region. In some embodiments, the fourth determining module can be used to perform operation S910 in the image generation method described above, which will not be elaborated upon here.

[0129] The blurring module is used to blur the image parameters of the region corresponding to the target range, so that at the boundaries of each region, the image parameters corresponding to each pixel gradually change along the pixel position. In some embodiments, the blurring module can be used to perform operation S920 in the image generation method described above, which will not be elaborated here.

[0130] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-a-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0131] For example, any and more of the first determining module 1010, the first acquiring module 1020, the first predicting module 1030, the first adjusting module 1040, and the preset module 1050 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least some of the functions of one or more of these modules / units / subunits can be combined with at least some of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the first determining module 1010, the first acquiring module 1020, the first predicting module 1030, the first adjusting module 1040, and the preset 5 modules 1050 can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or any other reasonable means of integrating or packaging circuits, or implemented in hardware or firmware, or in any one of software, hardware, and firmware implementations, or in a suitable combination of any of these. Alternatively, at least one of the first determining module 1010, the first acquiring module 1020, the first predicting module 1030, the first adjusting module 1040, and the preset 5 modules 1050 can be at least partially implemented as computer program modules, which can perform corresponding functions when the computer program module is run.

[0132] It should be noted that the data processing system part in the embodiments of this disclosure corresponds to the data processing method part in the embodiments of this disclosure. The specific description of the data processing system part is referred to in the data processing method part, and will not be repeated here.

[0133] Figure 11 A block diagram of an electronic device suitable for implementing the methods described above, according to embodiments of the present disclosure, is illustrated schematically. Figure 11 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0134] like Figure 11 As shown, an electronic device 1100 according to an embodiment of the present disclosure includes a processor 1101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1102 or a program loaded from a storage portion 1108 into a random access memory (RAM) 1103. The processor 1101 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1101 may also include onboard memory for caching purposes. The processor 1101 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0135] RAM 1103 stores various programs and data required for the operation of electronic device 1100. Processor 1101, ROM 1102, and RAM 1103 are interconnected via bus 1104. Processor 1101 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 1102 and / or RAM 1103. It should be noted that the programs may also be stored in one or more memories other than ROM 1102 and RAM 1103. Processor 1101 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0136] According to embodiments of this disclosure, the electronic device 1100 may further include an input / output (I / O) interface 1105, which is also connected to a bus 1104. The electronic device 1100 may also include one or more of the following components connected to the input / output (I / O) interface 1105: an input section 1106 including a keyboard, mouse, etc.; an output section 1107 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1108 including a hard disk, etc.; and a communication section 1109 including a network interface card such as a LAN card, modem, etc. The communication section 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the input / output (I / O) interface 1105 as needed. A removable medium 1111, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1110 as needed so that computer programs read from it can be installed into the storage section 1108 as needed.

[0137] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1109, and / or installed from removable medium 1111. When the computer program is executed by processor 1101, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0138] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0139] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0140] For example, according to embodiments of this disclosure, a computer-readable storage medium may include one or more memories other than the ROM 1102 and / or RAM 1103 described above and / or ROM 1102 and RAM 1103.

[0141] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the image generation method provided in the embodiments of this disclosure.

[0142] When the computer program is executed by the processor 1101, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0143] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices or magnetic storage devices. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via communication section 1109, and / or installed from removable medium 1111. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof. According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code may be executed entirely on a user computing device, partially on a user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing devices can be connected to user computing devices via any type of network, including local area networks (LANs) or wide area networks (WANs), or they can be connected to external computing devices (e.g., via the Internet using an Internet service provider).

[0144] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0145] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An image generation method, comprising: Based on the depth information of each pixel in the initial 3D image, multiple regions are determined, wherein the depth information represents the relative distance of the scene point corresponding to the pixel in the initial 3D image with respect to the display plane; View distance data is acquired in real time, and the view distance data represents the relative positional relationship between the user and the display plane at at least two points in time; Based on the viewing distance data, predict the relative motion trajectory of the user relative to the display plane; Based on the viewing distance data and the relative motion trajectory, the image parameters of at least some regions in the plurality of regions are adjusted to generate a target three-dimensional image.

2. The method according to claim 1, wherein the image parameters include brightness parameters and / or parallax parameters, the parallax parameters characterizing the pixel offset relative to the user's eyes. The adjustment of image parameters in at least some of the plurality of regions includes: Based on the viewing distance data and the relative motion trajectory, adjust the brightness parameters and / or parallax parameters of at least some areas in the plurality of regions.

3. The method according to claim 1 or 2, wherein determining the plurality of regions includes: The region formed by pixels whose relative distance, as represented by the depth information, is less than a first distance threshold is defined as the first region. The region formed by pixels whose relative distance, as represented by the depth information, is less than or equal to the second distance threshold and greater than or equal to the first distance threshold, is defined as the second region. The region formed by pixels whose relative distance, as represented by the depth information, is greater than the second distance threshold is designated as the third region.

4. The method according to claim 3, wherein the viewing distance data includes first data, the first data representing the relative distance between the midpoint of the user's eyes and the display plane, and adjusting the image parameters of at least some regions in the plurality of regions includes: In response to the first data being less than a third distance threshold, the brightness parameter of the first region is increased, and / or the brightness parameter of the third region is decreased; And / or, in response to the first data being greater than or equal to a third distance threshold, reduce the difference between the brightness parameters of the first region and the brightness parameters of the third region.

5. The method according to claim 4, wherein the viewing distance data further comprises second data, the second data representing the deflection angle of the user's binocular gaze direction relative to the normal direction of the display plane. The adjustment of image parameters in at least some of the plurality of regions includes: The offset correction amount for each pixel is determined based on the first data and the second data; The disparity parameters corresponding to each region are adjusted based on the offset correction amount.

6. The method according to claim 3, wherein the image parameters include brightness parameters, and the method further includes: Adjust the brightness parameter of the first region to a first brightness parameter, wherein the first brightness parameter is less than or equal to a first brightness threshold; And / or, adjust the brightness parameter of the second region to a second brightness parameter, wherein the second brightness parameter is greater than or equal to a second brightness threshold; Wherein, the first brightness parameter is greater than the second brightness parameter, and the first brightness threshold is greater than the second brightness threshold.

7. The method according to claim 3, wherein the image parameters include pulse signal parameters, the pulse signal parameters characterizing the flicker frequency of the display point corresponding to the pixel on the display plane. The method further includes: Adjust the pulse signal parameters of the first region to the first pulse signal parameters; And / or, adjust the pulse signal parameters of the third region to the second pulse signal parameters; Wherein, the parameter of the first pulse signal is greater than the parameter of the second pulse signal.

8. The method according to claim 1, wherein adjusting the image parameters of at least some regions in the plurality of regions comprises: Determine the target image parameters corresponding to the adjustment; Based on the image parameters corresponding to the current initial 3D image, the parameters gradually change along consecutive frames towards the target image parameters until the target image parameters are reached.

9. The method according to claim 1, further comprising: Based on the position of the pixels in each region and the depth information corresponding to each region, at least one target region is determined, wherein the center of the target region is determined according to the position of the pixels, and the radius of the target region is determined according to the depth information of each region; The image parameters of the region corresponding to the target range are blurred so that at the boundary of each region, the image parameters corresponding to each pixel gradually change along the position of the pixel.

10. An electronic device, comprising: At least one processor; as well as The memory connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform at least one of the following operations: determining multiple regions based on depth information of each pixel in an initial three-dimensional image, wherein the depth information characterizes the relative distance of the scene point corresponding to the pixel in the initial three-dimensional image relative to the display plane; Real-time viewing distance data is acquired, which represents the relative positional relationship between the user and the display plane at at least two time points; based on the viewing distance data, the relative motion trajectory of the user relative to the display plane is predicted; based on the viewing distance data and the relative motion trajectory, the image parameters of at least some regions in the plurality of regions are adjusted to generate a target three-dimensional image.

Images