WO2021218603A1 - 图像处理方法及投影系统 - Google Patents

图像处理方法及投影系统 Download PDF

Info

Publication number
WO2021218603A1
WO2021218603A1 PCT/CN2021/086420 CN2021086420W WO2021218603A1 WO 2021218603 A1 WO2021218603 A1 WO 2021218603A1 CN 2021086420 W CN2021086420 W CN 2021086420W WO 2021218603 A1 WO2021218603 A1 WO 2021218603A1
Authority
WO
WIPO (PCT)
Prior art keywords
image
brightness
ambient light
image processing
dark field
Prior art date
Application number
PCT/CN2021/086420
Other languages
English (en)
French (fr)
Inventor
赵鹏
许擎栋
Original Assignee
深圳光峰科技股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳光峰科技股份有限公司 filed Critical 深圳光峰科技股份有限公司
Publication of WO2021218603A1 publication Critical patent/WO2021218603A1/zh

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H04N9/3182—Colour adjustment, e.g. white balance, shading or gamut
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H04N9/3185—Geometric adjustment, e.g. keystone or convergence

Definitions

  • This application relates to the field of projection technology, and in particular to an image processing method and projection system.
  • High dynamic range (HDR) display images and videos have high contrast and peak brightness, and the dark and bright areas of the image contain rich grayscale information, which can greatly improve the display effect of the picture and bring better to the audience. Movie viewing experience.
  • HDR High dynamic range
  • Tone Mapping tone mapping
  • Tone Mapping algorithm that is, tone mapping algorithm, for the convenience of description, hereinafter referred to as TM algorithm
  • TM algorithm is a mapping relationship that acts on the source image, and maps the color space of the image accordingly, thereby mapping the source image with high dynamic contrast to low dynamic Contrast target image.
  • This application mainly provides an image processing method that can automatically optimize the brightness distribution of the screen according to the ambient light field to improve the visual perception of the projected screen.
  • the present application provides an image processing method for processing a source image to obtain a target image, and the target image is superimposed with ambient light to output a display image; including: obtaining a dark field of the source image The contrast of the area; determine the contrast of the dark field area of the display image according to the contrast of the dark field area of the source image; obtain the ambient light brightness in the display area; according to the contrast of the dark field area of the display image and the ambient light brightness Calculate the brightness threshold of the dark field area of the target image; select the tone mapping algorithm by looking up the table according to the brightness threshold of the dark field area of the target image and the dark field area of the source image; select the tone mapping algorithm according to the selected tone mapping algorithm
  • the source image is subjected to image processing.
  • the present application provides a projection system, including an ambient light detection module, an image processing module, and an image projection module; the ambient light detection module is arranged beside the image projection module and is used to monitor the environment in the display area. Light brightness is detected; the image processing module uses the above-mentioned image processing method to process the source image according to the ambient light brightness detected by the ambient light detection module to form a target image; the image projection module is used to convert the The target image processed and output by the image processing module is projected into the display area.
  • the beneficial effect of the present application is that the image processing method and projection system in the embodiments of the present application can select an appropriate TM algorithm to process the image according to the ambient light brightness of the display area, so as to make the displayed image projected to the display area dark after processing.
  • the field contrast is improved, the brightness distribution of the displayed image is optimized, and the visual perception effect of the projection display is improved.
  • FIG. 1 is a block diagram of the image processing method in this application.
  • FIG. 2 is a flowchart of an image processing method in Embodiment 1 of the present application.
  • Fig. 3a is a schematic diagram of the distribution of the target image and the ambient light in the third embodiment of the present application.
  • 3b is a schematic diagram of the brightness distribution of the target image before and after the image brightness is subtracted in the third embodiment of the present application;
  • Figure 4 is the expected output, the voltage-brightness curve displayed by the system and the projector
  • Figure 5 shows the expected output, the voltage-brightness curve displayed by the system and the projector under the action of ambient light.
  • Figure 1 shows the relationship between the source image, target image, and display image of this application.
  • the relationship between the three involved in the method is first explained clearly. Specifically, the source image is processed by the TM algorithm to obtain the target image, and the target image is superimposed on the ambient light in the display area to form a display Image, the display image is displayed in the display area, that is, the image viewed by the human eye is the display image.
  • FIG. 2 is a flowchart of the image processing method in Embodiment 1 of this application.
  • the image processing method includes:
  • the contrast of the dark field area of the source image can be directly carried in the source image data information, and the step of obtaining the contrast of the dark field area of the source image is to directly read the information.
  • C 0 of the source image contrast or dark field region is proportional to the source image to determine the presence of global contrast, the contrast C 0 can obtain the dark field image of the source region in the case where the source image is known by the ratio of the global contrast of the determination.
  • the dark field area contrast C 0 I t /I min .
  • 20% of the light source brightness is used as the brightness threshold I t of the dark field area of the source image
  • the minimum brightness value I min of the dark field area is the minimum brightness value of the source image, or an appropriate value is selected according to the actual situation. As the minimum brightness I min in the dark field area.
  • the contrast C 2 of the dark field area of the displayed image is equal to the contrast C 0 of the dark field area of the source image, that is, it is ensured that the contrast of the dark field area of the source image will not decrease after the source image is processed by the TM algorithm and superimposed with ambient light.
  • the contrast C 2 of the dark field area of the displayed image is equal to the contrast of the dark field area of the source image processed by the preset TM algorithm, that is, to ensure that the image processed by the preset TM algorithm is superimposed
  • the contrast of the dark field area will not decrease after ambient light.
  • the specific parameters of the preset TM algorithm can be determined according to the actual situation.
  • the image may be reasonable certainty that the global contrast of the image source according to the contrast of dark field region C 0 consider the dark field display image contrast C 2 region, an image is displayed dark field region C 2 and the source image contrast darkfield
  • the regional contrast C 0 is related to the global contrast of the displayed image.
  • the ratio of the contrast C 2 of the dark field area of the displayed image to the contrast C 0 of the dark field area of the source image is a preset value, and the preset value may be equal to 1, or may be a value less than or greater than 1. Set it according to actual needs.
  • the contrast C 2 of the dark field area of the display image is determined according to the contrast of the dark field area of the source image and the preset conditions.
  • the ambient light brightness in the display area includes the light brightness distribution information of the ambient light in the display area.
  • the minimum brightness value of the ambient light in the display area can be selected as the ambient light brightness, or the brightness of the ambient light in the display area can be selected The average value of is used as the ambient light brightness.
  • the additional ambient light on different frames of the image may be different when the image is displayed. Therefore, the ambient light brightness can be obtained separately when each frame of image is displayed. This method obtains the most accurate ambient light brightness and the best image processing effect. However, because each frame of image obtains the ambient light brightness, the performance requirements of the device are also required. Higher.
  • the ambient light brightness can be acquired once at intervals of a certain number of image frames, or the ambient light brightness can be acquired in the key frame of the image display, which can be selected as required.
  • the white field of the ambient light is photographed by a camera to obtain a digital image, and then corresponding calculations are performed according to the RGB value of the digital image, so as to obtain the brightness of the ambient light.
  • the brightness threshold of the dark field area of the target image is I t1
  • the minimum brightness of the dark field area is I t1min
  • the brightness threshold of the dark field area of the displayed image is I t2
  • the minimum brightness of the dark field area is I t2min , according to step S2
  • a preset method can be adopted to determine that the ambient light brightness in the display area is I B.
  • the tone mapping algorithm is selected by the look-up table method
  • the brightness threshold I t1 of the dark field area of the target image has been calculated in step S4 , and the brightness threshold I t of the dark field area of the source image is also known—in one embodiment, 20% of the light source brightness is used as the source image dark
  • the brightness threshold of the field area so the corresponding TM algorithm can be selected by the look-up table method.
  • the target image is a dark field region luminance threshold TM algorithm corresponding form
  • the source image is a dark field region luminance threshold value I t can be Determine the corresponding TM algorithm according to the pre-established table.
  • selecting a TM algorithm includes selecting different TM algorithms, or selecting different parameters in a certain TM algorithm.
  • TM algorithms actually use different mapping relationships.
  • TM algorithms include global methods and local methods.
  • the global method maps all pixels of the image uniformly. Commonly used are logarithmic processing, exponential processing, statistical processing, and histogram Processing, etc.; the local method uses different strategies to process each pixel according to the neighborhood information of the pixel, which can more effectively process the details of different brightness areas.
  • the main local methods are spatial non-uniform transformation and photography tonal reconstruction.
  • steps S1-S5 in this embodiment can be applied to each picture frame, that is, the corresponding TM algorithm is selected for each picture frame, and then each picture frame is imaged according to the selected TM algorithm. deal with.
  • the inventive concept of the embodiments of this application is: first determine the contrast of the dark field area of the display image that needs to be reached, and then combine the contrast of the dark field area of the display image and the brightness of the ambient light to calculate the corresponding brightness threshold of the dark field area of the target image. Finally, according to the brightness threshold of the dark field area of the target image and the brightness threshold of the dark field area of the source image, the TM algorithm for processing the source image into the target image can be determined by the look-up table method, so that the determined TM algorithm can be used under the specific ambient light. The TM algorithm processes the source image to ensure that the image processed by the TM algorithm can not only be displayed on a low-contrast device, but also that the dark details of the displayed image will not be lost too much.
  • the ultimate goal of the image processing method provided by the embodiments of the application is to enable the contrast of the dark field area of the displayed image to reach a preset value, so as to avoid the excessive decrease in the dark field contrast of the displayed image superimposed with ambient light after the TM algorithm. A serious problem of the loss of details in the shadows.
  • Using the image processing method of the embodiments of the present application can improve the contrast of the dark field area of the displayed image, so that the details of the dark part can be displayed more fully. Although part of the global contrast is sacrificed, the displayed image after superimposing the ambient light can obtain a better image display. Effect.
  • the first embodiment When the ambient light is not uniform, the first embodiment only uses a reasonable method to create a uniform ambient light and determine its ambient light intensity. Therefore, the first embodiment has a better technical effect when applied to a scene with uniform ambient light than when applied to a scene with uneven ambient light.
  • this embodiment provides an image processing method when the ambient light is unevenly distributed in the display area.
  • the image processing method further includes determining whether the ambient light is unevenly distributed in the display area.
  • the display area is divided according to the brightness of the ambient light, and then the display area is divided according to the brightness of the ambient light.
  • Each partition selects the corresponding TM algorithm, and performs image processing on the image of each partition respectively.
  • the ambient light brightness of each partition is a unique value
  • the TM algorithm of the partition can be determined according to the unique value
  • the ambient light brightness change is not a discrete brightness distribution
  • the display area whose ambient light brightness changes within the preset brightness interval can be used as the ambient light brightness unchanged and can be selected separately TM
  • the algorithm processes the partition of the image.
  • the minimum value of the ambient light brightness in the partition can be used as the ambient light brightness of the partition, or the maximum value of the ambient light brightness in the partition can be used as the ambient light brightness of the partition.
  • the average value of the ambient light brightness in the partition can be used as the ambient light brightness of the partition. Since the entire display area has been partitioned according to the ambient light brightness distribution, when setting a sufficiently small preset brightness interval, select the ambient light brightness The minimum, maximum, or average value is not much different as the ambient light brightness of the partition.
  • the image processing method in the second embodiment can be applied to each frame in the source image, that is, when each frame of image is displayed, the display partition is performed according to the brightness distribution of the ambient light.
  • the image processing method in the second embodiment can also be applied to the key frames in the source image, that is, the display area is partitioned according to the brightness distribution of the ambient light when the key image frame is displayed, and when other image frames are displayed
  • the ambient light brightness is simulated as a uniform distribution for image processing. Based on the same logic, it is also possible to select one or several frames at intervals of a certain number of frames to adopt the image processing method in the second embodiment.
  • this embodiment recognizes and partitions the brightness distribution of the ambient light, which can obtain the information of the ambient light more accurately, and process the image more finely, so as to obtain a better display effect. Display image.
  • this embodiment further includes determining whether there is a situation in which the brightness of the target image formed after the TM algorithm processing is lower than the brightness of the ambient light.
  • Figure 3a there is a situation where the brightness of some areas in the target image is less than the brightness of the ambient light
  • curve 1 is the brightness distribution of the displayed image formed by superimposing the brightness of the ambient light on the target image in Figure 3a
  • curve 2 is the brightness distribution of the display image formed after the target image in FIG. 3a is processed by the image processing algorithm in this embodiment.
  • the image processing algorithm in this embodiment includes: judging whether there is a situation in which the brightness of the target image formed after the TM algorithm is less than the brightness of the ambient light;
  • the minimum brightness as shown in Figure 3a, the brightness subtraction amount is the minimum brightness of the target image. After the brightness is subtracted, without affecting the normal display of the original image, the impact of ambient light on the target image is reduced, which can improve the dark field area of the displayed image (the target image after the brightness subtraction is superimposed on the ambient light) Contrast to improve the display effect of the displayed image.
  • the overall brightness of the target image is subtracted from the brightness of the ambient light, that is, the influence of the ambient light on the image display can be eliminated at this time.
  • this is an ideal situation. Under normal circumstances, there will be no images in which the minimum brightness of the target image is greater than the brightness of the ambient light.
  • FIG. 3a and the above text description all take the case where the ambient light brightness distribution is uniform as an example for description. Of course, the ambient light brightness distribution can also be uneven.
  • the minimum brightness value of the ambient light in the display area can be obtained and compared with the minimum brightness value of the target image. If the minimum brightness value of the target image Less than the minimum brightness value of the ambient light, then the brightness of the target image will be subtracted from the minimum brightness value of the target image. If the minimum brightness of the target image is greater than the minimum brightness value of the ambient light, then the brightness of the target image will be subtracted from the ambient light as a whole The minimum brightness value. In summary, when the brightness distribution of the ambient light is uneven, the overall brightness of the target image is subtracted from the smaller of the minimum brightness value of the ambient light and the minimum brightness value of the target image.
  • the minimum brightness value of the target image or the ambient light brightness before subtracting the minimum brightness value of the target image or the ambient light brightness, it also includes calculating the brightness distribution of the target image according to the RGB value of the target image, and then determining the minimum brightness of the target image according to the brightness distribution of the target image; and, After subtracting the minimum brightness value of the target image or the ambient light brightness, it also includes calculating the new RGB value of the image according to the current brightness of the target image, so as to ensure that the target image is displayed without distortion after subtracting the corresponding brightness.
  • corresponding brightness subtraction processing is performed on the target image according to the brightness distribution of the ambient light, so that a better image display effect can be obtained.
  • images are represented by three-channel RGB values.
  • the color gamut standard of general display devices is sRGB.
  • sRGB The color gamut standard of general display devices
  • the conversion relationship between RGB space and XYZ space is shown in the following (2), and the common DCI-P3 color gamut conversion relationship is shown in formula (3).
  • the Y calculated according to the conversion relationship is the brightness information, and the x and y obtained according to (4) represent chroma and saturation, forming color coordinates.
  • the processing of image brightness only needs to undergo color coordinate conversion, subtract the Y component, and then output the processed RGB value through the inverse operation of the matrix in (2).
  • the image processing methods involved in the first embodiment to the third embodiment are all applicable to a projector with a processor equipped with a smart chip and capable of intelligently processing images.
  • the inventive concept in the above-mentioned embodiments of this application can be used to adjust the system gamma correction curve of the projector without a smart chip, so as to achieve better The image display effect. This part is explained below:
  • the projector has a relationship curve between input voltage and output brightness due to its image output characteristics.
  • the normal situation is shown in Figure 4. Since the input image is converted by the camera's analog-to-digital conversion, the brightness distribution presents a linear distribution, while the voltage-brightness output curve of a general projector does not follow a linear distribution, so it is displayed as a display curve 1 by the projector.
  • the projection output of the projector is expected to output the brightness distribution curve 2 of the image, which often needs to be reversed gamma correction. Therefore, the gamma correction curve 3 is generally set in the projector system, and the display curve 1 is corrected by the gamma correction curve 3 to obtain the desired image Brightness distribution curve 2.
  • the embodiment of the present application mainly describes how to set the gamma correction curve under the effect of ambient light.
  • the gamma correction curve 3 of the projector corrects the input image, but the final output image brightness distribution is curve 21 due to the effect of ambient light. Therefore, a new gamma correction curve 3 needs to be set according to the ambient light brightness and projector parameters, so that the gamma correction curve 3 can also correct the input image to curve 2 under the action of the ambient light.
  • the corresponding gamma correction curve 3 can be obtained by looking up the table.
  • the actual output image brightness under ambient light has a certain increase relative to the display curve 2.
  • the corresponding parameters between the actual output image curve 21 and the display curve 2 are calculated, so as to correct the gamma correction curve 3 accordingly, so as to obtain the desired display image curve 2.
  • the corresponding tone mapping algorithm is first obtained according to the ambient light information and the source image information, and then the gamma correction curve 3 is obtained according to the tone mapping algorithm. Specifically, a correspondence table between the tone mapping algorithm and the gamma correction curve is established in advance. After the tone mapping algorithm is selected using the methods in the first to third embodiments described above, the corresponding gamma correction curve is obtained by the look-up table method, and the gamma correction curve is used to correct the input image.
  • the solution in this embodiment is applied to a projection scene with ambient light.
  • image correction can be performed by acquiring a new gamma correction curve. It can be applied to projectors that cannot perform image processing in real time. Obtain a better image display effect.
  • this embodiment has better technical effects in a uniform ambient light field, but in a non-uniform light field, it is necessary to obtain a simulated uniform ambient light field brightness value through calculation, and then according to the ambient light field The brightness value corrects the gamma correction curve 3 accordingly. Although the technical effect cannot be obtained under uniform ambient light, it can also improve the display effect of the image to a certain extent.
  • the present application also provides a computer-readable storage medium with a computer program stored on the storage medium, and when the computer program is executed by a processor, the above-mentioned image processing method is implemented.
  • the present application also provides a projection device, including a memory and a processor; the memory is used to store a computer program; the processor is used to implement the above-mentioned image processing method when the computer program is executed.
  • the application also provides a projection system, including the above-mentioned projection device and ambient light detection module; the projection device further includes an image projection module; Perform detection; the processor uses the above-mentioned image processing method to process the source image according to the ambient light brightness detected by the ambient light detection module to form the target image; the image projection module is used to project the target image processed and output by the image processing module to the display within the area.
  • the ambient light detection module is a camera.
  • the ambient light detection module can be installed on the projection device, or in another location, or the existing camera of a mobile terminal such as a mobile phone can be used.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Geometry (AREA)
  • Controls And Circuits For Display Device (AREA)
  • Image Processing (AREA)

Abstract

本申请公开了一种图像处理方法，用于对源图像进行处理，以获得目标图像，所述目标图像叠加环境光后输出显示图像；包括：获取源图像暗场区域的对比度；根据所述源图像暗场区域的对比度确定所述显示图像暗场区域的对比度；获取显示区域内的环境光亮度；根据所述显示图像暗场区域的对比度及所述环境光亮度计算出所述目标图像暗场区域的亮度阈值；根据所述目标图像暗场区域的亮度阈值及源图像暗场区域亮度阈值通过查表法选取色调映射算法；根据所述选取的色调映射算法对所述源图像进行图像处理。本申请提供的图像处理方法可根据环境光场自动优化图像亮度分布，提高了投影画面视觉观感。

Description

图像处理方法及投影系统 技术领域
本申请涉及投影技术领域，特别是涉及一种图像处理方法及投影系统。
背景技术
高动态范围(HDR)显示图像和视频因具有较高的对比度和峰值亮度、图像的暗区和亮区均含有丰富的灰阶信息从而能大大提高画面的显示效果，给观众带来较好的观影体验。
但是，目前HDR的显示设备相对较少，仅在特定的场景，如影院中会采用，更多的场景需要将HDR显示内容投放到SDR甚至LDR设备上进行显示。为了提升HDR显示内容在SDR/LDR设备上的显示效果，会对显示内容进行Tone Mapping(色调映射)。Tone Mapping算法(即色调映射算法，为方便描述，以下简称TM算法)是作用于源图像上的映射关系，对图像的色彩空间进行相应的映射，从而将高动态对比度的源图像映射为低动态对比度的目标图像。
现有技术中，针对源图像通常只采用一种TM算法进行图像映射处理，往往不能兼顾图像亮部和暗部的显示细节。而且，也未考虑环境光对图像处理的影响，在环境光较强时，投影画面的暗部细节损失严重，当环境较弱时，在暗部细节充分展示的情况下，投影画面的亮区显示可能刺眼。
发明内容
本申请主要提供一种图像处理方法，可根据环境光场自动优化画面亮度分布以提高投影画面视觉观感。
为解决上述技术问题，一方面，本申请提供一种图像处理方法，用于对源图像进行处理，以获得目标图像，所述目标图像叠加环境光后输出显示图像；包括：获取源图像暗场区域的对比度；根据所述源图像暗场区域的对比度确定所述显示图像暗场区域的对比度；获取显示区域内的环境光亮度；根据所述显示图像暗场区域的对比度及所述环境光亮度计算出所述目标图像暗场区域的亮度阈值；根据所述目标图像暗场区域的亮度阈值及源图像暗场区域亮度阈值通过查表法选取色调映射算法；根据所述选取的色调映射算法对所述源图像进行图像处理。
另一方面，本申请提供一种投影系统，包括环境光检测模块、图像处理模块、图像投射模块；所述环境光检测模块设置在所述图像投射模块旁侧，用于对显示区域内的环境光亮度进行检测；所述图像处理模块根据所述环境光检测模块检测到的环境光亮度、采用上述的图像处理方法对源图像进行处理，形成目标图像；所述图像投射模块用于将所述图像处理模块处理输出的目标图像投射到显示区域内。
本申请的有益效果是：采用本申请实施例中的图像处理方法及投影系统可根据显示区域的环境光亮度选择合适的TM算法对图像进行处理，从而使得处理后投射到显示区域的显示图像暗场对比度提高、优化了显示图像的画面亮度分布，提高了投影显示的视觉观感效果。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得 其他的附图，其中：
图1是本申请中图像处理方法的框图；
图2是本申请实施例一中图像处理方法的流程图；
图3a是本申请实施例三中目标图像与环境光的分布示意图；
图3b是经本申请实施例三中图像亮度减除前后目标图像亮度分布示意图；
图4是期望输出、系统及投影仪显示的电压-亮度曲线；
图5是环境光作用下期望输出、系统及投影仪显示的电压-亮度曲线。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本申请的一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
在本文中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本申请的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其他实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本文所描述的实施例可以与其他实施例相结合。
请参考图1，其中所示为本申请源图像、目标图像、显示图像三者的关系图。为了便于后续对图像处理方法进行描述，先将方法中涉及到的此三者的关系说明清楚，具体地，源图像经过TM算法处理后得到目标图像，目标图像叠加显示区域的环境光后形成显示图像，显示图像在显示区域进行显示，即人眼观看到的图像为显示图像。
实施例一
请参考图2，为本申请实施例一中图像处理方法的流程图。
该图像处理方法包括：
S1：获取源图像暗场区域的对比度C 0；
需要说明的是，在此步骤中源图像暗场区域的对比度可以直接携带在源图像数据信息中，所述获取源图像暗场区域的对比度的步骤为直接读取该信息即可。或者源图像暗场区域的对比度C 0为源图像全局对比度存在确定的比例关系，在获知源图像全局对比度的情况下可根据该确定的比例关系获取源图像暗场区域的对比度C 0。
或者，需要通过具体计算获取源图像暗场区域的对比度C 0，假设源图像暗场区域的亮度分布在区间(I min，I t)之间，其暗场区域对比度C 0＝I t/I min。在一种实施方式中，以光源亮度的20％作为源图像暗场区域的亮度阈值I t，暗场区域的亮度最小值I min为源图像的最小亮度值，或者根据实际情况选取合适的值作为暗场区域的亮度最小值I min。
S2：根据所述源图像暗场区域的对比度C 0确定所述显示图像暗场区域的对比度C 2；
在一种实施方式中，显示图像暗场区域的对比度C 2等于源图像暗场区域的对比度C 0，即确保源图像在经过TM算法处理、叠加环境光后暗场区域的对比度不会降低。
在另一种实施方式中，显示图像暗场区域的对比度C 2等于源图像经预设TM算法处理后的图像暗场区域的对比度，即保证经过经该预设TM算法处理后的图像在叠加环境光后暗场区域的对比度不会降低。可根据实际情况确定该预设TM算法的具体参数。
在又一实施方式中，可根据源图像暗场区域对比度C 0综合考虑显示 图像的全局对比度后合理确定显示图像暗场区域对比度C 2，即显示图像暗场区域对比度C 2与源图像暗场区域对比度C 0及显示图像的全局对比度相关。
在其他实施方式中，显示图像暗场区域对比度C 2与源图像暗场区域对比度C 0的比值为一预设值，该预设值可以等于1，也可以为小于1或大于1的数值，根据实际需要进行设定即可。
总之，在本步骤中根据源图像暗场区域的对比度及预设的条件确定显示图像暗场区域的对比度C 2。
S3：获取显示区域内的环境光亮度；
显示区域内的环境光亮度包括环境光在显示区域内的光亮度分布信息。
需要说明的是，在本实施例中，当环境光在显示区域的亮度为非均匀时，可以选取环境光在显示区域内的最小亮度值作为环境光亮度，也可以选择环境光在显示区域亮度的平均值作为环境光亮度。
另外，由于外部环境光可能会随着时间变化，图像显示时不同帧图像上附加的环境光可能不同。因此，可以在显示每一帧图像时分别获取环境光亮度，这种做法获得的环境光亮度最准确，图像处理效果也最好，但是因为每帧图像都获取环境光亮度对设备的性能要求也较高。
在另一种实施方式中，可以间隔一定数量的图像帧获取一次环境光亮度，也可以在图像显示的关键帧时获取环境光亮度，可根据需要进行选择。
具体地，在一种实施方式中，通过摄像头对环境光白场进行拍摄，得到数字图像，然后根据该数字图像的RGB值进行相应计算，从而获取环境光亮度。
S4：根据显示图像暗场区域的对比度C 2及环境光亮度计算出目标图像暗场区域的亮度阈值I t1；
设目标图像暗场区域的亮度阈值为I t1，暗场区域的亮度最小值为I t1min，显示图像暗场区域的亮度阈值为I t2，暗场区域的亮度最小值为I t2min，根据步骤S2已经获知显示图像暗场区域的对比度C2＝I t2/I t2min。
根据步骤S3已经获取显示区域内的环境光亮度，采取预设的方法可以确定显示区域内的环境光亮度为I B。
由于显示图像是目标图像叠加环境光后形成的，且I min1<<I B，因此有：
Figure PCTCN2021086420-appb-000001
在该公式中，C 2及I B均已知，因此，可求出目标图像暗场区域的亮度阈值I t1。
S5：根据目标图像暗场区域的亮度阈值及源图像暗场区域亮度阈值通过查表法选取色调映射算法；
由于在步骤S4中已经计算出目标图像暗场区域的亮度阈值I t1，而源图像暗场区域亮度阈值I t也是已知的—在一种实施方式中以光源亮度的20％作为源图像暗场区域的亮度阈值，因此可以通过查表法选取相应的TM算法。
具体地，预先存储一个源图像、目标图像暗场区域亮度阈值与TM算法对应的表格，在计算出目标图像暗场区域的亮度阈值I t1后，根据源图像暗场区域亮度阈值I t即可根据预先建立的表格确定相应的TM算法。
需要说明的是，选取TM算法包括选取不同的TM算法，或者在某一种TM算法中选取不同的参数。
不同的TM算法实际上是采用不同的映射关系，TM算法包括全局 方法和局部方法，其中全局方法对图像的所有像素统一进行映射处理，常用的有对数处理、指数处理、统计处理、直方图处理等；局部方法根据像素点的邻域信息对每个像素采用不同的策略进行处理，能够更有效地处理不同亮度区域的细节。但相对全局方法，局部的方法参数更多，面临的运算选择更多，如基于不同的像素需要针对性的分析其像素邻域的情况，图像处理的效果提升但牺牲了运算效率。主要的局部方法有空间非均匀变换、摄影学色调重构。
S6：根据选取的TM算法对源图像进行图像处理。
需要说明的是，本实施例中上述步骤S1-S5可以应用于每个图帧，即针对每个图帧选取相应的TM算法，然后根据选取的TM算法分别相应地对每个图帧进行图像处理。
也可以将本实施例上述步骤S1-S5应用于图像中的关键帧，即对图像显示作用较大的图帧，仅针对关键帧选取TM算法，然后将该TM算法应用于该关键帧附近的其他图帧，保证图像中的所有图帧均经过TM算法的处理后能在非HDR设备上进行显示。
本申请实施例的发明构思为：首先确定需要到达的显示图像暗场区域的对比度，然后结合显示图像暗场区域的对比度与环境光亮度可以反向计算出对应的目标图像暗场区域的亮度阈值，最后根据目标图像暗场区域的亮度阈值及源图像暗场区域的亮度阈值通过查表法即可确定将源图像处理为目标图像的TM算法，从而在该特定的环境光下采用确定好的TM算法对源图像进行处理能够保证经TM算法处理后的图像不仅能够在低对比度的设备上进行显示，而且能够保证显示图像暗部细节不会出现较多丢失的现象。
本申请实施例提供的图像处理方法的最终目的是为了使得显示图像暗场区域的对比度能达到预设值，以避免在经过TM算法后叠加环境 光的显示图像暗场对比度降低过多而导致的暗部细节丢失严重的问题。
采用本申请实施例的图像处理方法能够提高显示图像暗场区域的对比度，从而使暗部细节显示更充分，虽然牺牲了部分全局对比度，但是能使得叠加环境光后的显示图像获得更好的图像显示效果。
实施例二
在环境光不均匀时，实施例一仅通过合理的方法拟制出均匀的环境光，确定其环境光强度。因此，实施例一应用于环境光均匀的场景中比应用于环境光不均匀的场景具有更好的技术效果。
针对实施例一不能较好地适用于环境光不均匀场景的问题，本实施例提供一种环境光在显示区域分布不均匀时的图像处理方法。
该图像处理方法，在实施例一的基础上进一步包括，判断环境光在显示区域分布是否不均匀，当环境光在显示区域分布不均匀时，根据环境光亮度对显示区域进行分区，然后针对每个分区选择相应的TM算法，分别对每个分区的图像进行图像处理。
需要说明的是，每个分区的环境光亮度为一个唯一值，根据该唯一值可以确定该分区的TM算法。
另外，当环境光的亮度在显示区域上的最大值与最小值之间的差值超过预设值时判定环境光在显示区域分布不均匀。
由于环境光亮度变化不是离散的亮度分布，因此，在根据环境光亮度分布对显示区域进行分区时，可将环境光亮度变化在预设亮度区间的显示区域作为环境光亮度不变可单独选择TM算法对图像进行处理的分区，此时可将该分区内环境光亮度的最小值作为该分区的环境光亮度，也可将该分区内环境光亮度的最大值作为该分区的环境光亮度，也可以将该分区内环境光亮度的平均值作为该分区的环境光亮度，由于已经根 据环境光亮度分布将整个显示区域进行分区，在设定足够小的预设亮度区间时，选取环境光亮度的最小值、最大值或平均值作为分区的环境光亮度并无太大差别。
另外，实施例二中的图像处理方法可以应用于源图像中的每个图帧，即在显示每一帧图像时均根据环境光亮度分布进行显示分区。为了加快运算速率，也可以将实施例二中的图像处理方法应用于源图像中的关键帧，即在显示关键图帧时才根据环境光的亮度分布对显示区域进行分区，显示其他图帧时将环境光亮度拟制为均匀分布进行图像处理。基于相同的逻辑，也可以间隔一定数量的图帧选择某一个或几个图帧采用实施例二中的图像处理方法。
相比于实施例一，本实施例对环境光的亮度分布进行识别并进行分区，可以更为精确地获取到环境光的信息，对图像进行更为精细的处理，从而获得具有更佳显示效果的显示图像。
实施例三
本实施例在实施例一或实施例二的基础上，还包括判断经过TM算法处理后形成的目标图像中是否存在亮度小于环境光亮度的情形。如图3a所示为目标图像中存在部分区域的亮度小于环境光亮度的情形，如图3b，其中曲线①为图3a中的目标图像叠加环境光亮度后形成的显示图像的亮度分布，其中曲线②为图3a中的目标图像经本实施例中的图像处理算法处理后形成的显示图像亮度分布。
具体地，本实施例中的图像处理算法包括：判断经过TM算法处理后形成的目标图像中是否存在亮度小于环境光亮度的情形，若存在，则将目标图像的亮度整体减除目标图像中的最小亮度，如图3a中所示，亮度减除量为目标图像的最小亮度。经过亮度减除后，在不影响原图像正常显示的情况下，降低了环境光对目标图像的影响，从而可以提高显示 图像(经过亮度减除的目标图像叠加环境光后的图像)暗场区域的对比度，提高显示图像的显示效果。
进一步地，在本实施例中，若经过判断目标图像中不存在亮度小于环境光亮度的情形，即目标图像的亮度均大于环境光的亮度，此时为了降低环境光对图像显示效果的影响可将目标图像的亮度整体减除环境光的亮度，即此时可将环境光对图像显示的影响消除。当然这是一种理想情况，一般情况下不会出现目标图像的最小亮度还大于环境光亮度的图像。
需要说明的是，图3a以及上述文字说明均以环境光亮度分布均匀的情况为例进行说明。当然环境光亮度分布也可以是不均匀的，此时，为了保证图像显示不失真，可以获取环境光在显示区域的最小亮度值与目标图像的最小亮度值进行比较，若目标图像的最小亮度值小于环境光的最小亮度值，则将目标图像的亮度整体减除目标图像的最小亮度值，若目标图像的最小亮度值大于环境光的最小亮度值，则将目标图像的亮度整体减除环境光的最小亮度值。总结之，当环境光亮度分布不均匀时，将目标图像的亮度整体减除环境光最小亮度值与目标图像最小亮度值中的较小者。
本实施例中，在减除目标图像最小亮度值或环境光亮度之前还包括根据目标图像的RGB值计算出目标图像的亮度分布，然后根据目标图像的亮度分布确定目标图像最小亮度；以及，在减除目标图像最小亮度值或环境光亮度之后还包括根据目标图像当前亮度计算出图像新的RGB值，以保证目标图像在减除相应亮度后显示不失真。
本实施例中根据环境光的亮度分布对目标图像进行相应的亮度减除处理，可以得到更好的图像显示效果。
由于本申请实施例中均涉及亮度计算的问题，以下简要说明根据 RGB值计算图像亮度的方法及根据变化后的亮度反推出RGB值的方法：
一般图像均由三通道的RGB值表示，一般显示设备的色域标准为sRGB，通过计算RGB图像对应的XYZ值，可以获取图像的亮度分布即Y的分布。RGB空间与XYZ空间的转换关系如下(2)所示，常见的DCI-P3色域转换关系如公式(3)所示。根据转换关系计算出的Y为亮度信息，而根据(4)所示得到的x，y则代表色度和饱和度，形成色坐标。对于图像亮度的处理只需经过色坐标转换后，减除Y分量，然后通过(2)中矩阵的逆运算将处理后的RGB值输出即可。
Figure PCTCN2021086420-appb-000002
Figure PCTCN2021086420-appb-000003
Figure PCTCN2021086420-appb-000004
实施例一至实施例三中所涉及的图像处理方法均适用于处理器搭载有智能芯片，可对图像进行智能处理的投影仪。
而对于处理器未搭载智能芯片的投影仪虽然不能直接对图像进行处理，但可以采用本申请上述实施例中的发明构思对未搭载智能芯片投影仪的系统gamma校正曲线进行调整，从而实现更好的图像显示效果。下面对此部分进行说明：
投影仪由于其图像输出特征，存在一个输入电压和输出亮度的关系曲线，常规情况如图4所示。由于输入的图像通过摄像机的模拟-数字 转换，亮度的分布呈现线性分布，而一般投影仪的电压-亮度输出曲线并不按照线性分布，从而通过投影仪显示为显示曲线1，为了保证图像能经投影仪投影输出期望图像亮度分布曲线2，常常需要进行反向gamma矫正，因此投影仪的系统中一般设置有gamma校正曲线3，通过gamma校正曲线3对显示曲线1进行矫正，从而得到期望图像的亮度分布曲线2，。
关于设置gamma校正曲线3，现有技术中已有较多方案。本申请实施例主要对存在环境光的作用下如何设置gamma校正曲线进行说明。
如图5所示，假设期望输出的图像亮度分布为曲线2，而由于环境光的作用，实际输出的光亮度会存在一定的抬升形成曲线21，因此需要建立特定的优化策略，对抬升后的曲线21进行处理。优化策略有很多形式，常用的方法是通过均方误差最小化对问题进行优化。
为了实现输出的图像亮度分布为曲线2，投影仪的gamma校正曲线3对输入的图像进行矫正，但由于环境光的作用最后输出的图像亮度分布为曲线21。因此需要根据环境光亮度及投影仪参数设置新的gamma校正曲线3，以使得在环境光的作用下gamma校正曲线3也能将输入图像矫正为曲线2。
根据输入的图像信号通过查表的方式可以获得对应的gamma校正曲线3。但是，如图7所示，在环境光下实际输出的图像亮度相对显示曲线2有一定抬升。本申请实施例通过计算实际输出图像曲线21与显示曲线2之间的对应参数，从而对gamma校正曲线3进行相应修正，从而获得期望显示图像曲线2。
具体的，在本实施例中先根据环境光信息及源图像信息获取相应的色调映射算法，然后根据色调映射算法获取gamma校正曲线3。具体地， 预先建立色调映射算法与gamma校正曲线的对应表。采用上述实施例一至实施例三的方法选取色调映射算法后，通过查表法获取对应的gamma校正曲线，采用gamma校正曲线对输入的图像进行矫正。
本实施例中的方案应用于存在环境光的投影场景，在环境光场均匀或者近似均匀的情况下，可以通过获取新的gamma校正曲线进行图像矫正，应用于不能实时进行图像处理的投影仪能够获得较好的图像显示效果。
需要说明的是，本实施例在均匀环境光场下具有较佳的技术效果，而在非均匀光场下，需要先通过计算获得一个模拟的均匀环境光场亮度值，然后根据该环境光场亮度值对gamma校正曲线3进行相应修正，虽然不能获得均匀环境光下那样好的技术效果，但也能对图像的显示效果进行一定程度的改善。
本申请还提供一种计算机可读存储介质，存储介质上存储有计算机程序，当计算机程序被处理器执行时，实现上述的图像处理方法。
本申请还提供一种投影装置，包括存储器和处理器；存储器，用于存储计算机程序；处理器，用于当执行计算机程序时，实现上述的图像处理方法。
本申请还提供一种投影系统，包括上述的投影装置、环境光检测模块；投影装置还包括图像投射模块；环境光检测模块设置在图像投射模块旁侧，用于对显示区域内的环境光亮度进行检测；处理器根据环境光检测模块检测到的环境光亮度、采用上述的图像处理方法对源图像进行处理，形成目标图像；图像投射模块用于将图像处理模块处理输出的目标图像投射到显示区域内。
在一种实施方式中，环境光检测模块为摄像头。
需要说明的是，环境光检测模块可以设置在投影装置上，也可以设 置在其他位置，或者采用手机等移动终端现有的摄像头。
以上所述仅为本申请的实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (14)

  1. 一种图像处理方法，用于对源图像进行处理，以获得目标图像，所述目标图像叠加环境光后输出显示图像；其特征在于，包括：
    获取源图像暗场区域的对比度；
    根据所述源图像暗场区域的对比度确定所述显示图像暗场区域的对比度；
    获取显示区域内的环境光亮度；
    根据所述显示图像暗场区域的对比度及所述环境光亮度计算出所述目标图像暗场区域的亮度阈值；
    根据所述目标图像暗场区域的亮度阈值及源图像暗场区域亮度阈值通过查表选取色调映射算法；
    根据所述选取的色调映射算法对所述源图像进行图像处理。
  2. 如权利要求1所述的图像处理方法，其特征在于，所述获取显示区域内的环境光亮度后还包括：
    当环境光亮度在显示区域分布不均匀时，根据所述环境光亮度对所述显示区域进行分区；
    针对每个分区选择相应的色调映射算法；
    根据选取的色调映射算法对相应分区的图像进行图像处理。
  3. 如权利要求2所述的图像处理方法，其特征在于，所述根据环境光亮度对显示区域进行分区包括：将环境光亮度变化在预设亮度区间的显示区域作为一个分区。
  4. 如权利要求3所述的图像处理方法，其特征在于，所述根据环境光亮度对显示区域进行分区包括：在显示关键图帧时根据环境光的亮度对显示区域进行分区；或者间隔预设数量的图帧根据环境光的亮度对 显示区域进行分区。
  5. 如权利要求1所述的图像处理方法，其特征在于，所述环境光亮度的分布均匀时，所述图像处理方法还包括判断所述目标图像的最小亮度是否小于所述环境光亮度，若是，则将所述目标图像亮度整体减除所述目标图像的最小亮度值。
  6. 如权利要求5所述的图像处理方法，其特征在于，若所述目标图像的最小亮度大于所述环境光亮度，则将所述目标图像亮度整体减除环境光亮度。
  7. 如权利要求1所述的图像处理方法，其特征在于，所述环境光亮度分布不均匀时，所述图像处理方法还包括，将目标图像的亮度整体减除环境光最小亮度值与目标图像最小亮度值中的较小者。
  8. 如权利要求1所述的图像处理方法，其特征在于，所述计算源图像暗场区域的对比度包括：以光源亮度的20％作为所述源图像暗场区域的亮度阈值来计算所述源图像暗场区域的对比度。
  9. 如权利要求1所述的图像处理方法，其特征在于，所述获取显示区域内的环境光信息包括通过摄像头对环境白场进行拍摄后，得到数字图像，根据所述数字图像的RGB值计算获取环境光信息。
  10. 如权利要求1-9任一项所述的图像处理方法，其特征在于，所述根据色调映射算法对源图像进行处理的步骤包括：
    针对源图像的每个图帧或关键帧，选取相应的色调映射算法；
    根据选取的色调映射算法对图帧进行图像处理。
  11. 如权利要求1所述的图像处理方法，其特征在于，所述根据色调映射算法对源图像进行处理的步骤包括：
    根据所述选取的色调映射算法通过查表法获得Gamma校正曲线；
    根据所述Gamma校正曲线对源图像进行图像处理。
  12. 一种计算机可读存储介质，其特征在于，所述存储介质上存储有计算机程序，当所述计算机程序被处理器执行时，实现如权利要求1-11任一项所述的图像处理方法。
  13. 一种投影装置，其特征在于，包括存储器和处理器；所述存储器，用于存储计算机程序；所述处理器，用于当执行所述计算机程序时，实现如权利要求1-11任一项所述的图像处理方法。
  14. 一种投影系统，其特征在于，包括如权利要求13所述的投影装置、环境光检测模块；所述投影装置还包括图像投射模块；
    所述环境光检测模块设置在所述图像投射模块旁侧，用于对显示区域内的环境光亮度进行检测；
    所述处理器根据所述环境光检测模块检测到的环境光亮度、采用如权利要求1-11任一项所述的图像处理方法对源图像进行处理，形成目标图像；
    所述图像投射模块用于将所述图像处理模块处理输出的目标图像投射到显示区域内。
PCT/CN2021/086420 2020-04-28 2021-04-12 图像处理方法及投影系统 WO2021218603A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202010348014.8A CN113573032A (zh) 2020-04-28 2020-04-28 图像处理方法及投影系统
CN202010348014.8 2020-04-28

Publications (1)

Publication Number Publication Date
WO2021218603A1 true WO2021218603A1 (zh) 2021-11-04

Family

ID=78158008

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/086420 WO2021218603A1 (zh) 2020-04-28 2021-04-12 图像处理方法及投影系统

Country Status (2)

Country Link
CN (1) CN113573032A (zh)
WO (1) WO2021218603A1 (zh)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114532919A (zh) * 2022-01-26 2022-05-27 深圳市杉川机器人有限公司 多模态目标检测方法、装置、扫地机及存储介质
CN114822444A (zh) * 2022-05-13 2022-07-29 深圳创维－Rgb电子有限公司 兼容显示方法、装置、设备及可读存储介质
CN114998207A (zh) * 2022-04-28 2022-09-02 南通升祥盈纺织品有限公司 基于图像处理的棉织品丝光处理方法

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115547226B (zh) * 2022-10-17 2023-09-08 深圳市安立信电子有限公司 医用显示器的亮度自检及预警方法、装置及电子设备
CN116256936A (zh) * 2023-03-27 2023-06-13 广东远合工程科技有限公司 一种亮度控制方法、装置、电子设备和存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102651136A (zh) * 2011-02-28 2012-08-29 国际商业机器公司 图像的颜色映射方法及装置
CN108090879A (zh) * 2017-12-12 2018-05-29 上海顺久电子科技有限公司 一种对输入的高动态范围图像进行处理的方法和显示设备
CN108510557A (zh) * 2018-04-09 2018-09-07 湖南国科微电子股份有限公司 图像色调映射方法及装置
CN109410126A (zh) * 2017-08-30 2019-03-01 中山大学 一种细节增强与亮度自适应的高动态范围图像的色调映射方法
US20190228511A1 (en) * 2016-08-04 2019-07-25 Intel Corporation Tone-mapping high dynamic range images
WO2020016999A1 (ja) * 2018-07-19 2020-01-23 Ｎｅｃディスプレイソリューションズ株式会社 プロジェクタ、スタック表示システム、映像表示方法およびプログラム

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102651136A (zh) * 2011-02-28 2012-08-29 国际商业机器公司 图像的颜色映射方法及装置
US20190228511A1 (en) * 2016-08-04 2019-07-25 Intel Corporation Tone-mapping high dynamic range images
CN109410126A (zh) * 2017-08-30 2019-03-01 中山大学 一种细节增强与亮度自适应的高动态范围图像的色调映射方法
CN108090879A (zh) * 2017-12-12 2018-05-29 上海顺久电子科技有限公司 一种对输入的高动态范围图像进行处理的方法和显示设备
CN108510557A (zh) * 2018-04-09 2018-09-07 湖南国科微电子股份有限公司 图像色调映射方法及装置
WO2020016999A1 (ja) * 2018-07-19 2020-01-23 Ｎｅｃディスプレイソリューションズ株式会社 プロジェクタ、スタック表示システム、映像表示方法およびプログラム

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114532919A (zh) * 2022-01-26 2022-05-27 深圳市杉川机器人有限公司 多模态目标检测方法、装置、扫地机及存储介质
CN114998207A (zh) * 2022-04-28 2022-09-02 南通升祥盈纺织品有限公司 基于图像处理的棉织品丝光处理方法
CN114998207B (zh) * 2022-04-28 2024-05-14 汕头市鼎泰丰实业有限公司 基于图像处理的棉织品丝光处理方法
CN114822444A (zh) * 2022-05-13 2022-07-29 深圳创维－Rgb电子有限公司 兼容显示方法、装置、设备及可读存储介质
CN114822444B (zh) * 2022-05-13 2024-05-07 深圳创维－Rgb电子有限公司 兼容显示方法、装置、设备及可读存储介质

Also Published As

Publication number Publication date
CN113573032A (zh) 2021-10-29

Similar Documents

Publication Publication Date Title
WO2021218603A1 (zh) 图像处理方法及投影系统
US11375128B2 (en) Method for obtaining exposure compensation values of high dynamic range image, terminal device and non-transitory computer-readable storage medium
US8072507B2 (en) Method and system of generating high dynamic range image corresponding to specific scene
CN112752023B (zh) 一种图像调整方法、装置、电子设备及存储介质
CN109801240B (zh) 一种图像增强方法以及图像增强装置
WO2018176925A1 (zh) Hdr图像的生成方法及装置
US8577142B2 (en) Image processing device, image processing method and program with improved image contrast
US10565742B1 (en) Image processing method and apparatus
US8902328B2 (en) Method of selecting a subset from an image set for generating high dynamic range image
US20210158488A1 (en) Image edge processing method, electronic device, and computer readable storage medium
CN105407296B (zh) 实时视频增强方法和装置
WO2022116989A1 (zh) 图像处理方法、装置、设备和存储介质
CN108009997B (zh) 一种调整图像对比度的方法及装置
US8605106B2 (en) Projector and color improvement method of the projector
JP2005353069A (ja) 彩度適応的な映像向上装置およびその方法
US20180061029A1 (en) Image processing apparatus, imaging apparatus, image processing method, and storage medium storing image processing program of image processing apparatus
CN112669758A (zh) 显示屏校正方法、装置、系统和计算机可读存储介质
CN112351195A (zh) 图像处理方法、装置和电子系统
TW201801042A (zh) 影像中飽和像素之檢測方法
JP5327766B2 (ja) デジタル画像における記憶色の修正
WO2022158010A1 (ja) 画像処理方法
US20210192742A1 (en) Method and system for image correction
CN113709438B (zh) 一种图像的白平衡校正方法、装置、存储介质及设备
CN114125408A (zh) 图像处理方法及装置、终端和可读存储介质
CN108711176B (zh) 全景鱼眼相机的增益值确定、成像的颜色调整方法及装置、终端、鱼眼相机

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21796123

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21796123

Country of ref document: EP

Kind code of ref document: A1