Image distortion pre-correction method and device based on MEMS galvanometer laser scanning

Abstract

The application discloses a kind of image distortion pre-correction method and device based on MEMS galvanometer laser scanning, the scanning speed of sinusoidal wave scanning by MEMS galvanometer is calculated the pixel density of image;The luminance positive gain of image is calculated by pixel density;Cumulative scanning length mapping is established based on cumulative scanning length method;Inverse function is obtained by interpolation calculation of cumulative scanning length mapping, to obtain reverse position correction mapping;The reciprocal of luminance positive gain is calculated as reverse luminance correction gain;Image is preprocessed based on reverse position correction mapping and reverse luminance correction gain.The application does not need to modify MEMS galvanometer driving mode and hardware architecture, simultaneously consider the spatial position distortion and luminance non-uniform distortion caused by sinusoidal wave scanning of MEMS galvanometer laser scanning, by the joint application of reverse position correction mapping and reverse luminance correction gain, image is preprocessed, and position distortion and luminance distortion are simultaneously eliminated at one time.

Description

Technical Field

[0001] This invention relates to the field of laser scanning display technology, and in particular to an image distortion pre-correction method and apparatus based on MEMS galvanometer laser scanning. Background Technology

[0002] Laser scanning beam (LSB) systems are a display technology that uses MEMS (microelectromechanical systems) mirrors to drive a laser beam for two-dimensional scanning to form an image. This technology offers advantages such as a wide color gamut, high contrast, and small size, and is widely used in AR / VR head-up displays, automotive HUDs, and micro-projections.

[0003] In existing MEMS laser scanning display systems, X-axis (horizontal) scanning is achieved by MEMS mirrors driven by a sine wave. MEMS mirrors operate in mechanical resonance mode, offering advantages such as low power consumption, large scanning angle, and stable frequency, making them the core scanning device in LSB systems. However, an inherent problem with sine wave driving is the spatial non-uniformity of its scanning speed, and the resulting distortion is a recognized technical challenge in LSB systems.

[0004] This leads to two serious distortion problems: (1) Positional distortion (spatial compression / stretching) When the sine wave is near its peak (edge ​​region), the scanning speed is slow and the spatial distance the laser beam moves per unit time is small, causing multiple output pixels to be mapped to the same area of ​​the input image, resulting in pixel stacking and spatial compression in the X-axis direction.

[0005] When the sine wave crosses zero (the central region), the scanning speed is fast and the spatial distance is large, resulting in sparse pixels and spatial stretching.

[0006] (2) Brightness distortion (uneven brightness) Because the scanning speed is slower and the laser dwell time is longer in the edge regions, the laser energy density per unit area is higher, making the edges brighter than the center. Conversely, the faster scanning speed and shorter dwell time in the center regions result in the center being darker.

[0007] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0008] In view of the shortcomings of the prior art, the purpose of this invention is to provide an image distortion pre-correction method and device based on MEMS galvanometer laser scanning, so as to solve the problem that the sinusoidal wave drive in the X-axis direction of the existing MEMS laser scanning display system cannot simultaneously solve the problems of position distortion and brightness distortion.

[0009] The technical solution of the present invention is as follows: In a first aspect, the present invention provides an image distortion pre-correction method based on MEMS galvanometer laser scanning, comprising: The scanning speed is calculated based on the time derivative of the mirror deflection angle during MEMS galvanometer sinusoidal scanning. The pixel density of the original image is calculated based on the scanning speed; Calculate the positive brightness gain of the original image based on the pixel density; Establish a cumulative scan length mapping based on the cumulative scan length method; Interpolate the cumulative scan length mapping to obtain the inverse function, obtain the inverse position correction mapping, and calculate the reciprocal of the positive brightness gain as the inverse brightness correction gain. Image preprocessing is performed based on inverse position correction mapping and inverse brightness correction gain, and the corrected image is output.

[0010] A further provision of the present invention is that the image preprocessing based on reverse position correction mapping and reverse brightness correction gain specifically includes: for each frame of input image, row-by-row position correction remapping and pixel-by-pixel brightness correction.

[0011] A further provision of the present invention, wherein calculating the pixel density of an image from the scanning speed specifically includes: taking the absolute value of the scanning speed and normalizing it to obtain a normalized scanning speed; wherein the pixel density is inversely proportional to the normalized scanning speed.

[0012] In a further embodiment of the present invention, the interpolation calculation includes linear interpolation, bilinear interpolation, bicubic interpolation, or Lanczos interpolation.

[0013] In a further embodiment of the present invention, the data of reverse position correction mapping and reverse brightness correction gain can be calculated online, or calculated and stored offline in ASIC / FPGA / embedded processor.

[0014] A further provision of the present invention is that establishing the cumulative scan length mapping based on the cumulative scan length method specifically includes: establishing a mapping relationship between the position of each pixel in the output image and the corresponding normalized sampling position of the input original image.

[0015] A further provision of the present invention, which calculates the positive luminance gain of an image from the pixel density, specifically includes the following relationship: the positive luminance gain is related to the pixel density as follows: ; Where α is the brightness gain model offset parameter, β is the brightness gain model scaling parameter, and G[i] is the positive brightness gain of the i-th pixel in the original image. Let be the pixel density of the i-th pixel in the original image.

[0016] Secondly, the present invention provides a pre-correction device for implementing the above-described image distortion pre-correction method based on MEMS galvanometer laser scanning, comprising: a pre-calculation module, a position remapping module, a brightness correction module, and a control module; the pre-calculation module is used to calculate the scanning speed based on the time derivative of the galvanometer deflection angle of the MEMS galvanometer sinusoidal scanning; calculate the pixel density of the original image based on the scanning speed; calculate the positive brightness gain of the original image based on the pixel density; establish a cumulative scanning length mapping based on the cumulative scanning length method, and calculate the reciprocal of the positive brightness gain as the inverse brightness correction gain; the position remapping module is used to perform interpolation remapping on the input image based on the cumulative scanning length mapping to obtain the inverse position correction mapping; the brightness correction module is used to perform pixel-by-pixel brightness adjustment on the position-remapped image based on the inverse brightness correction gain; the control module is used to control the pre-calculation module, the position remapping module, and the brightness correction module to process the image and output the corrected image.

[0017] A further embodiment of the present invention includes a storage module for storing the reverse position correction mapping and the reverse brightness correction gain.

[0018] In a further embodiment of the present invention, when an embedded processor is used, the pre-correction device can be used as a software module for display driving and executed before the frame buffer is output.

[0019] The image distortion pre-correction method and device based on MEMS galvanometer laser scanning provided by the present invention have the following beneficial effects: The present invention does not require modification of the MEMS galvanometer driving method and hardware architecture, and simultaneously considers the spatial position distortion and brightness non-uniform distortion caused by the sinusoidal scanning of MEMS galvanometer laser scanning. By combining the application of reverse position correction mapping and reverse brightness correction gain, the image is pre-processed, and position distortion and brightness distortion are eliminated at the same time. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0021] Figure 1 This is a flowchart of an image distortion pre-correction method in one embodiment of the present invention.

[0022] Figure 2 This is a schematic diagram of the sinusoidal scanning speed and pixel density distribution of the pre-correction method in one embodiment of the present invention.

[0023] Figure 3 This is a nonlinear mapping relationship between the output position of the pre-correction method and the sampling position of the original image in one embodiment of the present invention.

[0024] Figure 4 This is a schematic diagram of the brightness distortion and correction curves of the pre-correction method in one embodiment of the present invention.

[0025] Figure 5 This is a schematic diagram of a MEMS galvanometer laser scanning system according to one embodiment of the present invention.

[0026] Figure 6 This is a schematic diagram of a pre-correction device using an ASIC / FPGA in one embodiment of the present invention. Detailed Implementation

[0027] This invention provides an image distortion pre-correction method and apparatus based on MEMS galvanometer laser scanning. To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0028] In the implementation methods and claims, unless otherwise specified in the text, the terms "a," "an," "the," and "the" may also include plural forms. If the embodiments of the present invention involve descriptions of "first," "second," etc., such descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features.

[0029] It should be further understood that the term "comprising" as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when an element is referred to as "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements present. Furthermore, "connected" or "coupled" as used herein can include wireless connections or wireless coupling. The term "and / or" as used herein includes all or any unit and all combinations of one or more associated listed items.

[0030] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0031] Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0032] The existing solutions for X-axis sinusoidal scanning non-uniformity are as follows: Option 1: Non-uniform pixel clock The non-uniformly spaced pixel clock signals are generated based on the sine wave scanning angle position, so that the pixels are evenly distributed in space.

[0033] Limitations: This method only adjusts the time domain at the pixel clock level, solving the positional distortion problem but failing to address the brightness distortion problem. Furthermore, non-uniform pixel clocks require the laser to output pixels of varying durations at different time intervals, placing high demands on the timing control precision of the laser driver circuit and necessitating a dedicated clock generation circuit, thus increasing hardware complexity.

[0034] Option 2: Pixel row removal Excess pixel rows are removed directly from the scanning edge region (the slow-moving region), so that the remaining pixels are spatially approximately uniformly distributed.

[0035] Limitations: Removing pixels means discarding valuable image information, leading to a decrease in resolution at edges. This is a compromise, sacrificing edge image quality for near-uniformity. Furthermore, this method also fails to address brightness distortion.

[0036] Option 3: Laser Power Modulation The laser's output power is adjusted in real time according to the scanning speed. The power is increased when the scanning speed is fast (center) and decreased when the scanning speed is slow (edge) to compensate for uneven brightness.

[0037] Limitations: This method only addresses brightness distortion, not positional distortion. It requires a high-speed laser drive circuit to adjust power in real-time with the scanning position, placing high demands on the laser's response speed and the drive circuit's bandwidth, thus increasing system cost. Furthermore, the linearity and accuracy of power modulation are limited by the laser's nonlinear response characteristics.

[0038] Option 4: Pre-shaping drive signal By superimposing a predistortion component on the sinusoidal drive signal, the actual motion trajectory of the galvanometer deviates from the ideal sine wave and becomes closer to a linear scan.

[0039] Limitations: Changing the drive signal means the galvanometer no longer operates in pure resonance, leading to a reduced scanning angle and increased power consumption. Furthermore, precise design of the pre-shaping drive signal requires an accurate galvanometer dynamics model; the resonance characteristics of different individual galvanometers vary, limiting its versatility. This method also struggles to simultaneously achieve both position and brightness correction.

[0040] Please refer to the instruction manual appendix. Figure 1 This invention provides a preferred embodiment of an image distortion pre-correction method based on MEMS galvanometer laser scanning, comprising: calculating the scanning speed based on the time derivative of the galvanometer deflection angle during MEMS galvanometer sinusoidal scanning; calculating the pixel density of the original image based on the scanning speed; calculating the positive brightness gain of the original image based on the pixel density; establishing a cumulative scanning length mapping based on a cumulative scanning length method; interpolating the cumulative scanning length mapping to obtain an inverse function, thereby obtaining a reverse position correction mapping, and calculating the reciprocal of the positive brightness gain as the reverse brightness correction gain; preprocessing the image based on the reverse position correction mapping and the reverse brightness correction gain, and outputting the corrected image.

[0041] This invention presents an image distortion pre-correction method based on MEMS galvanometer laser scanning. It utilizes the scanning speed of a sinusoidal wave scan to calculate the scanning length at each pixel position (inversely proportional to the speed), and then establishes a precise output-input position mapping through an accumulated scanning length method. The inverse function of this mapping yields the inverse position correction mapping, and the reciprocal of the positive brightness gain is calculated as the inverse brightness correction gain. This method has clear physical meaning, high computational accuracy, and does not rely on approximation formulas. Simultaneously, it considers the spatial position distortion and brightness non-uniformity distortion caused by the sinusoidal scanning of MEMS galvanometer laser scanning. Through the combined application of the inverse position correction mapping and the inverse brightness correction gain, the image is pre-processed, eliminating both position and brightness distortions simultaneously in one step.

[0042] In some embodiments, the interpolation calculation can employ linear interpolation, bilinear interpolation, bicubic interpolation, or Lanczos interpolation. The data for the inverse position correction mapping and inverse brightness correction gain can be calculated online, or calculated and stored offline in an ASIC (Application-Specific Integrated Circuit) / FPGA (Field-Programmable Gate Array) / embedded processor. Alternatively, the inverse function and brightness gain can be calculated in real-time in an FPGA using the CORDIC (Coordinate Rotation Digital Computer) algorithm or Taylor expansion, instead of pre-calculating and storing the correction data. CORDIC is an abbreviation for Coordinate Rotation Digital Computer.

[0043] No correction is required when the Y-axis uses uniform linear scanning. If the Y-axis also uses sinusoidal wave driving or has nonlinearity, the reverse position correction mapping and reverse brightness correction gain of the Y-axis can be calculated using the same cumulative scan length method as the X-axis, so as to achieve two-dimensional joint correction.

[0044] In this embodiment of the invention, the relationship between the positive gain of brightness and the pixel density is as follows: ; Where α is the brightness gain model offset parameter, β is the brightness gain model scaling parameter, determined through measurement system calibration, and G[i] is the positive brightness gain of the i-th pixel in the original image. Let be the pixel density of the i-th pixel in the original image.

[0045] The process of solving for α and β is as follows: Input a full-screen uniform grayscale image into the measurement system, acquire the actual projected output using a luminance meter or camera, and measure the luminance value at each pixel position; using the luminance at the center position as a reference, calculate the measured gain at each position. , This represents the measured brightness value of the i-th pixel position after the actual projection output is captured by a luminance meter or camera (how bright that position is when actually projected onto the screen). This represents the brightness value with the center position brightness as a reference (i.e., the measured brightness of the center pixel); then the measured gain is compared with the known pixel density. α and β can be solved by performing linear least squares fitting. The calibration process can be completed during the production stage, and the results are written to the device's non-volatile memory and automatically loaded upon power-on.

[0046] The present invention also provides a preferred embodiment of an image distortion pre-correction method based on MEMS galvanometer laser scanning, specifically as follows: The method includes: Step 1: Calculate the scan trajectory parameters.

[0047] Given the X-axis scanning frequency fx and the image width W, the X-axis scanning period is angular frequency is The total time for unidirectional scanning is T / 2, and the cutting time at each end is... The effective scanning time is T / 2-2t1. The time cropping ratio affects the degree of distortion and effective resolution.

[0048] W pixels are evenly distributed over the effective scanning time to obtain the time point sequence t[i] (i=0,1,...,W-1) for each pixel, which ranges from [-T / 4+t1,T / 4-t1].

[0049] Step 2: Calculate the scanning speed and pixel density, such as Figure 2 As shown.

[0050] In an LSB system, X-axis (horizontal) scanning is typically achieved by a MEMS galvanometer driven by a sine wave, with the galvanometer deflection angle satisfying the following: ; Where A is the maximum deflection amplitude, fx is the scanning frequency, and t is the scanning time.

[0051] The scanning speed is the derivative of position with respect to time: ; Where ω = 2πfx.

[0052] Take the absolute value of the scan speed and normalize it: ; Pixel density is inversely proportional to scanning speed: ; Where ε is a small constant to prevent division by zero. The density is normalized to [0,1]: .

[0053] Step 3: Establish a cumulative scan length mapping, such as Figure 3 As shown.

[0054] This is one of the key aspects of this invention. For sinusoidal scanning, the laser beam's movement speed in space is uneven, resulting in varying spatial lengths covered within the same time interval. By calculating the cumulative scan length, a precise mapping relationship between the output pixel position and the input pixel position can be established.

[0055] The scan length corresponding to each pixel position is inversely proportional to the scan speed: .

[0056] Where L0 is the reference length. The cumulative scan length is: .

[0057] Normalize to [0,1] as the sampling location: .

[0058] in This indicates the normalized sampling position of the input image corresponding to the output position i.

[0059] The physical meaning of this mapping is: the edge region has a slow speed and a large L[i], which causes multiple consecutive output pixels to be mapped to similar input positions, i.e., the edges are compressed; the center region has a fast speed and a small L[i], which causes the input position to change rapidly, i.e., the center is stretched.

[0060] Step 4: Calculate the reverse position correction mapping.

[0061] This is the core correction step of the present invention. The corrected mapping is obtained by inverting the function of the forward mapping.

[0062] Assume equal-interval output positions Correcting the sampling position by adjusting the positive mapping curve By performing linear interpolation and obtaining the inverse function, we get: .

[0063] `linspace` is an abbreviation for Linearly Spaced. Its function is to generate an arithmetic sequence (i.e., equally spaced values) within a specified interval. The `linspace` function automatically calculates the precise values ​​for all points within the specified interval, specifying the start and end points, and the number of intervals to be divided into. That is, `linspace(start, stop, num)`, where `start` represents the starting value (inclusive), `stop` represents the ending value (inclusive), and `num` represents the number of equally spaced points to generate.

[0064] The meaning of the correction mapping: At position i in the corrected image, a pixel should be sampled from position corr_x[i] in the original image. In this way, after the positive distortion caused by MEMS scanning, the pre-stretched part in the corrected image is compressed back to the correct position.

[0065] Step 5: Calculate the brightness correction gain, such as Figure 4 As shown.

[0066] Positive brightness gain is determined by pixel density: .

[0067] α and β are the parameters of the brightness gain model, which can be determined through calibration in a practical system.

[0068] The reverse correction gain is the reciprocal of the forward gain: .

[0069] Step 6: Generate correction data.

[0070] The position correction map and brightness correction gain are stored as correction data for use in the real-time preprocessing stage: ; .

[0071] The storage format of the above correction data depends on the implementation platform: in ASIC / FPGA, it can be stored as a lookup table in the form of on-chip ROM / BRAM, and the bit width is selected according to the accuracy requirements; in embedded processor, it can be stored as an array or a floating-point table.

[0072] By utilizing the scanning speed of a sinusoidal wave scan, the scan length at each pixel position (inversely proportional to the speed) is calculated. Then, a precise output-input position mapping is established through normalization of the accumulated scan lengths. The position-corrected LUT is obtained by inverting the function of this mapping. Compared with existing technologies, the method of this invention has higher computational accuracy.

[0073] The following parameters in the method of this invention can be configured according to the actual characteristics of the MEMS galvanometer: (1) X-axis scanning frequency: Different galvanometer models have different X-axis scanning frequencies.

[0074] (2) Time cutting ratio: The time clipping ratio affects the degree of distortion and effective resolution.

[0075] (3) Maximum deflection angle of the galvanometer: .

[0076] (4) Luminance gain model offset parameter: α.

[0077] (5) Luminance gain model scaling parameter: β.

[0078] In actual processing, these parameters can be determined through a calibration process. The calibrated LUT can be stored in non-volatile memory and loaded into the preprocessing module upon power-on. During production, standard test patterns (such as uniform grayscale or grid patterns) are used to acquire output images through the actual MEMS system, automatically calculating the actual correction curve and programming the LUT. This can compensate for process differences between individual galvanometers. Correction accuracy and image quality can also be improved by: increasing the effective bit depth of the laser (e.g., from 8 bits to 10 bits) to increase the dynamic range of brightness correction; or using an intermediate precision higher than the display bit depth in preprocessing (e.g., internal 12-bit processing with 10-bit output).

[0079] The image preprocessing method (real-time processing step) in this embodiment preprocesses each frame of the input image according to the following steps: Step 1: Line-by-line position correction and remapping.

[0080] For each row of the image (y=0,1,...,H-1), for each output position i=0,1,...,W-1: Obtain the source coordinates by looking up a table: .

[0081] The original image is sampled using bilinear interpolation to obtain the corrected pixel values.

[0082] Step 2: Pixel-by-pixel brightness correction.

[0083] For each pixel [y][i] after position remapping: Obtain the correction gain by looking up a table: ; Multiply the pixel value by the correction gain: ; If the product exceeds the maximum value that the pixel bit depth can represent (e.g., 255 in an 8-bit system), it is clamped to that maximum value; if it is lower than 0, it is clamped to 0. That is, after multiplying by the gain, if the value exceeds the maximum value, it is clamped to the maximum value; if it is lower than 0, it is clamped to 0; intermediate values ​​remain unchanged.

[0084] Step 3: Output the corrected image to the laser scanning system.

[0085] When the X-axis uses alternating forward and reverse scanning (odd rows from left to right, even rows from right to left), two sets of position correction LUTs (forward and reverse) are required, and the LUT to be used is selected based on the parity of the row number.

[0086] In some embodiments, where image preprocessing is implemented using an FPGA or ASIC, the system mainly includes: LUT storage module: Uses on-chip BRAM / ROM to store position correction LUTs and brightness correction LUTs. The bit width is selected according to the accuracy requirements (e.g., the position LUT uses 16-bit fixed point and the brightness LUT uses 12-bit fixed point).

[0087] Row caching module: Caches image data of the current row and adjacent rows for bilinear interpolation.

[0088] Location remapping module: based on The source coordinates are obtained by looking up the table, and bilinear interpolation is performed.

[0089] Brightness correction module: based on Look up the table and perform multiplication on the remapped pixel values.

[0090] Pipeline control: The above modules operate in a pipeline manner, outputting one correction pixel per clock cycle.

[0091] Timing flow: Input pixel stream → LUT lookup (1 cycle) → Line buffer read (1 cycle) → Bilinear interpolation (2 cycles) → Luminance multiplication (1 cycle) → Output. The total delay is approximately 5-6 clock cycles. Figure 6 As shown.

[0092] In some embodiments, when implemented using embedded software, preprocessing is performed in software on an embedded processor such as an ARM / MCU: The system calculates the LUT (or loads a pre-calculated LUT from an external source) during system initialization; position remapping and brightness correction are performed line by line as each frame of image arrives; interpolation and multiplication operations are accelerated using SIMD instructions (such as NEON); and the processed image is transferred to the laser scanning controller via DMA.

[0093] It can also be implemented through a hybrid hardware and software approach: LUT lookup and brightness multiplication are implemented in the FPGA, while the interpolation calculation for position remapping is performed by the embedded CPU, balancing flexibility and performance.

[0094] The method of this invention can pre-calculate and store the correction curve as correction data, enabling real-time preprocessing in ASIC / FPGA / embedded processors with extremely low computational complexity (table lookup or array indexing + one multiplication) without increasing display latency. This method requires no modification to the MEMS driver hardware and is implemented entirely within the image data path.

[0095] In some embodiments, the continuous position correction curve and brightness correction curve can also be approximated by piecewise linear functions to reduce LUT storage space. For example, the correction curve for W pixels in an entire row is stored as K breakpoints (K<<W), and intermediate values are obtained through linear interpolation. This is particularly valuable in embedded systems with limited storage resources.

[0096] For RGB three-color lasers, if the response characteristics of the three-color lasers are different, an independent brightness correction LUT can be calculated for each color channel, while the position correction LUT is shared by all three channels.

[0097] In the embodiments of the present invention, a pre-correction apparatus for the image distortion pre-correction method based on MEMS galvanometer laser scanning is further provided, including: a pre-calculation module, a position remapping module, a brightness correction module, and a control module; the pre-calculation module is configured to calculate the scanning speed according to the time derivative of the galvanometer deflection angle of the MEMS galvanometer in sine wave scanning; calculate the pixel density of the original image from the scanning speed; calculate the forward brightness gain of the original image from the pixel density; establish a cumulative scanning length mapping based on the cumulative scanning length method, and calculate the reciprocal of the forward brightness gain as the reverse brightness correction gain; the position remapping module is configured to perform interpolation remapping on the input image according to the cumulative scanning length mapping to obtain a reverse position correction mapping; the brightness correction module is configured to perform pixel-by-pixel brightness adjustment on the position-remapped image according to the reverse brightness correction gain; the control module is configured to control the pre-calculation module, the position remapping module, and the brightness correction module to process the image, and output the corrected image.

[0098] The pre-correction apparatus of the present invention uses the scanning speed of sine wave scanning to calculate the scanning length (inversely proportional to the speed) at each pixel position, and then establishes an accurate output-input position mapping through the cumulative scanning length method. The inverse function of this mapping is taken to obtain the reverse position correction mapping, and the reciprocal of the forward brightness gain is calculated as the reverse brightness correction gain. This method has a clear physical meaning, high calculation accuracy, does not rely on approximate formulas, and does not require modification of the MEMS galvanometer driving mode and hardware architecture, while eliminating both spatial position distortion and brightness non-uniformity distortion caused by sine wave scanning.

[0099] In the embodiments of the present invention, the pre-correction apparatus further includes a storage module, configured to store the reverse position correction mapping and the reverse brightness correction gain, such as Figure 5 shown in the following.

[0100] The pre-correction apparatus of the present invention should be placed at the end of the Image Signal Processing (ISP) pipeline, before the laser scanning controller. The specific integration position depends on the system architecture: In FPGA solutions, the preprocessing module serves as a processing stage of the ISP pipeline; when using an embedded processor, the pre-correction device can be used as a software module for the display driver, executed before the frame buffer is output.

[0101] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for image distortion pre-correction based on MEMS galvanometer laser scanning, characterized in that, include: The scanning speed is calculated based on the time derivative of the mirror deflection angle during MEMS galvanometer sinusoidal scanning. The pixel density of the original image is calculated based on the scanning speed; Calculate the positive brightness gain of the original image based on the pixel density; Establish a cumulative scan length mapping based on the cumulative scan length method; Interpolate the cumulative scan length mapping to obtain the inverse function, obtain the inverse position correction mapping, and calculate the reciprocal of the positive brightness gain as the inverse brightness correction gain. Image preprocessing is performed based on inverse position correction mapping and inverse brightness correction gain, and the corrected image is output.

2. The image distortion pre-correction method based on MEMS galvanometer laser scanning according to claim 1, characterized in that, The image preprocessing based on inverse position correction mapping and inverse brightness correction gain specifically includes: For each frame of the input image, perform line-by-line position correction and remapping, and pixel-by-pixel brightness correction.

3. The image distortion pre-correction method based on MEMS galvanometer laser scanning according to claim 1, characterized in that, Calculating the pixel density of an image from the scanning speed specifically includes: The absolute value of the scanning speed is taken and normalized to obtain the normalized scanning speed; The pixel density is inversely proportional to the normalized scan speed.

4. The image distortion pre-correction method based on MEMS galvanometer laser scanning according to claim 1, characterized in that, The interpolation calculation includes linear interpolation, bilinear interpolation, bicubic interpolation, or Lanczos interpolation.

5. The image distortion pre-correction method based on MEMS galvanometer laser scanning according to claim 1, characterized in that, The data for reverse position correction mapping and reverse brightness correction gain can be calculated online or calculated and stored offline in ASIC / FPGA / embedded processor.

6. The image distortion pre-correction method based on MEMS galvanometer laser scanning according to claim 1, characterized in that, The establishment of the cumulative scan length mapping based on the cumulative scan length method specifically includes: Establish a mapping relationship between the pixel positions of the output image and the corresponding normalized sampling positions of the input original image.

7. The image distortion pre-correction method based on MEMS galvanometer laser scanning according to claim 1, characterized in that, Calculating the positive brightness gain of an image from the pixel density specifically includes: The relationship between the positive brightness gain and the pixel density is as follows: ； Where α is the brightness gain model offset parameter, β is the brightness gain model scaling parameter, and G[i] is the positive brightness gain of the i-th pixel in the original image. Let be the pixel density of the i-th pixel in the original image.

8. A pre-correction device for implementing the image distortion pre-correction method based on MEMS galvanometer laser scanning as described in any one of claims 1-7, characterized in that, include: The module consists of a pre-calculation module, a position remapping module, a brightness correction module, and a control module. The pre-calculation module is used to calculate the scanning speed based on the time derivative of the mirror deflection angle of the MEMS mirror sinusoidal scanning; calculate the pixel density of the original image based on the scanning speed; calculate the positive brightness gain of the original image based on the pixel density; establish a cumulative scanning length mapping based on the cumulative scanning length method, and calculate the reciprocal of the positive brightness gain as the inverse brightness correction gain. The position remapping module is used to perform interpolation remapping on the input image based on the cumulative scan length mapping to obtain the inverse position correction mapping; The brightness correction module is used to perform pixel-by-pixel brightness adjustment on the position-remapped image based on the inverse brightness correction gain; The control module is used to control the pre-calculation module, the position remapping module and the brightness correction module to process the image and output the corrected image.

9. The pre-correction device according to claim 8, characterized in that, It also includes a storage module for storing the reverse position correction map and the reverse brightness correction gain.

10. The pre-correction device according to claim 8, characterized in that, When an embedded processor is used, the pre-correction device can be used as a software module for the display driver and executed before the frame buffer is output.

Images