Projection device

Abstract

The invention provides an image correction method, comprising the following steps: (1) obtaining a color card comprising a plurality of color blocks, each color block having a preset color standard; (2) placing the image acquisition device and the color card in a selected use environment; (3) capturing RGB (Red, Green, Blue) numerical values of each color block of the color card by using a system of an image capturing device, and converting the RGB numerical values into HSV (Hue, Saturation and Value) numerical values; (4) comparing the preset color standard of each color block with the HSV value of each color block to determine the difference degree among the H value, the S value and the V value of the preset color standard and the HSV value; and (5) automatically adjusting the HSV value set by the image acquisition device according to the preset color standard and the difference degree of each color block.

Description

Technical Field

[0001] The present invention relates to the field of image correction, and in particular to a method for performing image correction using a color card. Background Art

[0002] The dramatic increase in demand for remote work and teaching has driven the development of online conferencing and instant sharing technologies. However, this communication method presents a significant problem: color distortion, a common issue in video conferencing. This color distortion primarily stems from the image quality of video cameras and the limitations of display devices, such as in home office environments with multiple or complex light sources.

[0003] Typical color reproduction techniques utilize the camera's built-in automatic white balance function. This function analyzes the image to detect the current ambient color temperature and applies predefined white balance parameters to adjust color performance. However, this method has two significant drawbacks. The first drawback is that the predefined white balance parameters may not achieve optimal adjustment due to misjudgment of color temperature detection. The second drawback is that because the white balance function applies a full color shift to the entire image, it can easily create a filter-like effect, resulting in a shift in overall hue.

[0004] To address the aforementioned color distortion issue, color calibration can be performed using color charts. However, commercially available color charts are designed for use by professional camera developers and are not suitable for end consumers to perform camera calibration themselves. Furthermore, these charts cannot achieve optimal display effects under various lighting conditions. Furthermore, when photographing people, the accuracy of commercially available color charts in detecting skin tones under different lighting conditions still leaves room for improvement.

[0005] In view of the above problems, it is necessary to propose an image correction method that allows end consumers to use color charts and solve technical problems existing in the prior art, such as color distortion, without using the automatic white balance function of the camera. Summary of the Invention

[0006] The object of the present invention is to provide a new image correction method that can reduce the distortion effect of ambient light sources on images, so as to better restore the true color of objects under multiple light sources or complex light sources.

[0007] To achieve the above object, the present invention provides an image correction method, comprising the following steps:

[0008] Obtain a color card, the color card comprising a plurality of color blocks, each of the color blocks having a preset color standard;

[0009] Place the image capture device and the color card in the selected usage environment;

[0010] A system using the image capture device to capture the RGB value of each color block of the color card and convert the RGB value into an HSV value;

[0011] Comparing a preset color standard for each color block with the HSV value corresponding to each color block to determine the degree of difference between the preset color standard and the H value, S value, and V value of the HSV value, where the H value represents hue, the S value represents saturation, and the V value represents brightness; and

[0012] Automatically adjusting the HSV value set by the image capture device according to the preset color standard of each color block and the degree of difference;

[0013] The plurality of color blocks include a second group for adjusting the portrait mode, and the second group includes a first skin color block, a second skin color block, and a third skin color block.

[0014] Preferably, the plurality of color blocks further include a first group for adjusting the hue and saturation of an image, and the color saturation of each color block in the first group is 45-70%.

[0015] Preferably, the plurality of color blocks further include a third group for adjusting the grayscale of an image, and the grayscale value of each color block in the third group is 32-235.

[0016] Preferably, the L value of the first skin color is 50-70, the a value is 7-12, and the b value is 10-26, and / or the L value of the second skin color is 50-70, the a value is 6-11, and the b value is 7-19, and / or the L value of the third skin color is 40-60, the a value is 7-16, and the b value is 9-38; wherein the L value is the brightness value, the a value is the green-red value, and the b value is the blue-yellow value.

[0017] Preferably, the preset color standard corresponds to the RGB value, HSV value or Lab value presented by the color card under a standard light source environment.

[0018] Preferably, when using the system of the image capture device to capture the RGB values ​​of each color block of the color card, the system of the image capture device does not capture images of other objects, and the RGB values ​​of each color block are captured simultaneously.

[0019] Preferably, the step of automatically adjusting the HSV value set by the image capture device is based on a binary search algorithm or an optimal parameter step adjustment method.

[0020] Preferably, the plurality of color blocks include a first group for adjusting image hue and saturation, a second group for adjusting a portrait mode, and a third group for adjusting image grayscale;

[0021] The step of automatically adjusting the HSV value set by the image capture device specifically includes: adjusting the H value of the HSV value set by the image capture device based on the preset color standard and the degree of difference between the color blocks in the first group and the second group; and / or adjusting the V value of the HSV value set by the image capture device based on the preset color standard and the degree of difference between the color blocks in the third group.

[0022] Preferably, before using the system of the image capture device to capture the RGB value of each color block of the color card, the step further includes: adjusting the weight of at least a second group of the plurality of color blocks according to whether the image capture device is in a people shooting mode or an object shooting mode.

[0023] Preferably, the step of automatically adjusting the HSV value set by the image capture device includes automatically adjusting the V value, H value, and S value in sequence, or automatically adjusting the V value, H value, S value, and V value in sequence.

[0024] Compared to existing technologies, the present invention utilizes a color chart containing multiple color patches. The image capture device and the color chart are placed in a selected usage environment. The system then determines the degree of difference between the preset color standard for each color patch and the HSV values ​​of each color patch acquired by the image capture device's system. Based on the preset color standard and the degree of difference, the HSV values ​​set by the image capture device are automatically adjusted, thereby adjusting the image captured by the image capture device to more closely resemble what is observed by the naked eye. This effectively reduces the effects of ambient light on image distortion, allowing for better reproduction of the true color of objects under multiple or complex lighting conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 FIG. 4 is a flow chart of an image correction method according to an embodiment of the present invention.

[0026] Figure 2 This is a color chart for image calibration according to an embodiment of the present invention.

[0027] Figure 3 is a flow chart of an image correction method according to another embodiment of the present invention.

[0028] Figure 4 This is a table of experimental data after image correction according to an embodiment of the present invention.

[0029] Figure 5 FIG. 4 is a diagram showing the result of image correction according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to provide a further understanding of the purpose, structure, features, and functions of the present invention, the present invention is described in detail below with reference to the embodiments.

[0031] Certain terms are used throughout the specification and claims to refer to specific components. Those skilled in the art will understand that manufacturers may use different terms to refer to the same component. This specification and claims do not distinguish components by name, but rather by their functional differences. Throughout the specification and claims, the term "including" is open-ended and should be interpreted as meaning "including, but not limited to."

[0032] Figure 1 FIG. 1 is a flow chart of an image correction method according to an embodiment of the present invention. Figure 1 The flowchart shown provides an image correction method, particularly a correction method for a single image or continuous images captured by a network camera (or video lens), comprising at least the following steps: (1) Step 102, obtaining a color card including a plurality of color blocks, each having a preset color standard; (2) Step 104, placing the image capture device and the color card in a selected use environment; (3) Step 106, using the system of the image capture device to capture the RGB values ​​of each color block of the color card and converting the RGB values ​​into HSV values ​​(hue, saturation, value); (4) Step 108, comparing the preset color standard of each color block with the HSV value of each color block to determine the degree of difference in H value (hue), S value (saturation), and V value (brightness) between the preset color standard and the HSV value; and (5) Step 110, automatically adjusting the HSV value set by the image capture device based on the preset color standard of each color block and the degree of difference. The above steps (1) to (5) are further described below.

[0033] According to one embodiment, the image correction method of the present application can be used to correct images generated during remote video teaching or video conferencing. Therefore, the images are primarily indoor scenes (e.g., classrooms or offices) rather than outdoor scenes (e.g., street scenes or natural landscapes). Compared to outdoor scenes, indoor scenes typically exhibit more black, white, and gray tones, less sky blue or earth green, and often contain human figures (e.g., faces) with skin tones.

[0034] For step 102, a color card including a plurality of color blocks is obtained, and each color block has a preset color standard. According to one embodiment, the color card is, for example, Figure 2A color card 200 for image correction is shown. Here, the color card 200 is essentially equivalent to a color checker. The color card 200 can be composed of a series of standardized color blocks 211 to 264, which represent the colors commonly seen by people under natural or artificial light sources. Each color block in the color card 200 typically includes colors of varying brightness and saturation, ranging from black, white, and gray to various colors (such as red, blue, and green). Using the color card 200 for color balancing can help ensure that images captured by the camera maintain color consistency and accuracy under different ambient light sources.

[0035] According to one embodiment, color blocks 211-264 comprise a first group 202 for adjusting image hue and saturation. For example, first group 202 comprises twelve color blocks 221-224, 231, 234, 241, 244, and 251-254 located within a closed circular region. The primary six primary colors and six color blocks are selected from the six primary color axes of the sRGB (standard Red, Green, and Blue) color space. The remaining six color blocks are located midway between the xy color coordinates of two adjacent primary colors in the sRGB color space. This ensures that the color blocks cover most of the color axes in the color space, achieving optimal image hue correction.

[0036] According to another embodiment, the color saturation (S value) of each color block in the first group 202 is 45-70%, and the brightness (V value, or brightness B) is 50-100%. Since the color saturation of each color block in the first group 202 is 45-70%, when performing subsequent image calibration, the original image captured by the camera is prevented from being oversaturated, which would affect parameter adjustment and thus prevent color distortion in the adjusted image.

[0037] According to one embodiment, color blocks 211-264 comprise a second group 204 for adjusting portrait mode. For example, when the image captured by the image capture device includes a person's image, and the person's image includes exposed skin, the color blocks in second group 204 can adjust the hue and saturation of the person's image. Second group 204 includes at least a first region 204A and a second region 204B, located at opposite edges of color card 200, and includes a first skin color block, a second skin color block, a third skin color block, and an orange color block. These multiple color blocks correspond to, for example, color blocks 212, 213, 262, and 263, respectively. Using the CIELab color space as the judgment standard, the first skin color, the second skin color, and the third skin color correspond to different skin tones, such as Japanese, Caucasian, and African skin tones, and have different Lab values, where the L value represents lightness, the a value represents green-red, and the b value represents blue-yellow. For example, the first skin tone is Japanese, with an L value of 50-70, an a value of 7-12, and a b value of 10-26; and / or the second skin tone is Caucasian, with an L value of 50-70, an a value of 6-11, and a b value of 7-19; and / or the third skin tone is African, with an L value of 40-60, an a value of 7-16, and a b value of 9-38. The above values ​​for the first, second, and third skin tones are summarized in Table 1 below. Because color chart 200 includes color patches for three different skin tones, it can accommodate images of people with various skin tones, achieving better calibration results.

[0038] Table 1

[0039] color L a b Japanese 50～70 7～12 10～26 Caucasians 50～70 6～11 7～19 African 40～60 7～16 9～38

[0040] According to one embodiment, color patches 211-264 comprise a third group 206 for adjusting image grayscale. Third group 206 includes a first region 206A and a second region 206B. First region 206A is located at the center of color card 200 and includes color patches 232, 233, 242, and 243. Second region 206B is located at the four corners of color card 200 and includes color patches 211, 214, 261, and 264. The grayscale values ​​of each color patch in third group 206 range from 32 to 235, including, for example, black, white, and gray. The colors of the color patches in third group 206 differ from those in first group 202 and second group 204. Because third group 206 is located at the center and corners of color card 200, rather than forming a closed ring, the adverse effects of center- or spot-metering can be avoided during subsequent image correction.

[0041] In step (1) 102, refer to Figure 2Each color block has a preset color standard. The preset color standard can be the RGB values ​​of each color block in the color card 200 under a standard light source (such as D50 or D65), or a manually set RGB value. Depending on different needs, the preset color standard is not limited to RGB values ​​and can also be HSV values ​​or Lab values, depending on actual needs.

[0042] Next, refer to Figure 1 and Figure 2 , execute (2) step 104 to place the image capture device and the color card 200 in a selected use environment. According to one embodiment of the present invention, the image capture device is, for example, a webcam (or video lens), which is used to capture a single image or continuous images, and transmit the image to a receiving end via a network signal (such as a wired network signal or a wireless network signal), so that the image can be displayed via at least one display. The "selected use environment" referred to here refers to an environment with a selected single light source or multiple light sources, and the image capture device will subsequently operate in an environment that is the same as or similar to the selected use environment. The light source of the "selected use environment" may include a standard light source and / or a non-standard light source. In one embodiment, the light source of the "selected use environment" is a non-standard light source. In one embodiment, the light source of the "selected use environment" is different from the light source used to perform image calibration on the image capture device when the image capture device is manufactured.

[0043] Next, refer to Figure 1 and Figure 2 , execute (3) step 106, use the system of the image capture device to capture the RGB value of each color block of the color card 200, and convert the RGB value into an HSV value. According to one embodiment of the present invention, the system of the image capture device includes hardware (such as an image sensor and a memory) and software (such as a digital signal processing software), and the software of the image capture device can be operated remotely (or in the cloud), and is not limited to the location of the hardware of the image capture device. The image sensor in the image capture device can be arranged in an array, and it can capture the optical image of each color block and convert it into a digital image. The digital image of each color block can be calculated by the digital signal processing software in the image capture device to obtain the RGB value (i.e., R value, G value, B value) of each color block, and then convert it into an HSV value (i.e., H value, S value, V value).

[0044] Since the color card 200 is placed in a selected usage environment, and the light source of the selected usage environment may be non-standard, the RGB value and HSV value of each color block captured at this time may be different from the preset color standard of each color block.

[0045] According to one embodiment of the present invention, in step 106, when capturing the RGB values ​​of each color block of the color card 200, the image capture device system does not capture images of other objects. For example, the image capture device system does not capture a human figure or parts of a human body (e.g., teeth, tongue, nose, etc.), but only captures the images of the color blocks of the color card 200.

[0046] According to one embodiment of the present invention, in step 106, when capturing the RGB values ​​of each color block on the color card 200, the RGB values ​​of each color block are captured simultaneously. In other words, the image capture device system does not capture the RGB values ​​of each color block sequentially, but rather simultaneously. This allows the RGB values ​​of all color blocks to be mapped to a single selected usage environment, rather than to multiple selected usage environments.

[0047] Next, step (4) 108 is performed to compare the preset color standard of each color block with the HSV value of each color block to determine the degree of difference in H value, S value, and V value between the preset color standard and the HSV value. According to one embodiment of the present invention, the preset color standard of each color block is already built into the system of the image capture device, and step 108 can be performed by running the digital signal processing software in the image capture device.

[0048] Next, step (5) 110 is executed to automatically adjust the HSV values ​​set by the image capture device based on the preset color standards and the degree of difference of each color block. According to one embodiment of the present invention, the HSV values ​​set by the image capture device can be automatically adjusted by digital signal processing software in the image capture device according to a binary search algorithm or a best parameter step adjustment method to obtain the adjusted HSV values. In particular, if the binary search algorithm is used for the correction operation, the adjusted HSV values ​​can be obtained more quickly.

[0049] According to one embodiment of the present invention, the V value, H value, and S value can be automatically adjusted in sequence based on the preset color standard and degree of difference of each color block. In another embodiment, the V value, H value, S value, and V value can be automatically adjusted in sequence based on the preset color standard and degree of difference of each color block to further enhance the brightness correction effect.

[0050] According to one embodiment of the present invention, when adjusting the H value in step 110, a correction calculation is performed based on the color blocks 212, 213, 221-224, 231, 234, 241, 244, 251-254, 262, and 263 in the first group 202 and the second group 204. In another embodiment, when adjusting the H value in step 110, a correction calculation is performed based on the color blocks in the first group 202 and the second group 204, rather than based on the color blocks 211, 214, 232, 233, 242, 243, 261, and 264 in the third group 206. The color blocks in the third group 206 are primarily used to adjust the grayscale of the image. The preset color standard (e.g., HSV value) of these color blocks is located at or near the center of the HSV color space. A slight change in their position in the color space will result in a significant change in their corresponding H value. Therefore, when adjusting the H value in step 110, if the correction operation is performed simultaneously based on the color blocks in the first group 202, the second group 204, and the third group 206, the standard deviation of the H value of the corrected image will have a larger variation. In contrast, if the correction operation is performed only based on the color blocks in the first group 202 and the second group 204, but not based on the color blocks in the third group 206, the standard deviation of the H value of the corrected image will have a smaller variation.

[0051] According to one embodiment of the present invention, when adjusting the V value in step 110, the color blocks in the third group 206 are used as the basis. In one embodiment, when adjusting the V value in step 110, the color blocks 211, 214, 232, 233, 242, 243, 261, and 264 in the third group 206 are used as the basis, rather than the color blocks 212, 213, 221-224, 231, 234, 241, 244, 251-254, 262, and 263 in the first group 202 and the second group 204. This allows for better brightness correction.

[0052] Afterwards, the image captured by the image capturing device can be adjusted according to the adjusted HSV value, so that the adjusted image is closer to the image observed by the naked eye.

[0053] Figure 3 FIG. 1 is a flow chart of an image correction method according to another embodiment of the present invention. Figure 3The flowchart shown in FIG. 1 provides an image correction method, comprising at least the following steps: (1) step 302, executing a correction process; (2) step 304, placing a first image capture device and a color card in a selected use environment; (3) step 306, starting a correction process, aligning the color card through a window and a preset pane of the first image capture device; (4) step 308, determining the weight of each color block value according to a person shooting mode or an object shooting mode; (5) step 310, capturing the RGB value of each color block of the color card in the selected use environment according to a system using the first image capture device, and After converting the signal to the HSV color space, the brightness (V value) is optimized; (6) Step 312, according to this system, the RGB values ​​of each color block of the color card under the selected use environment are captured, and after converting the signal to the HSV color space, the hue (H value) is optimized; (7) Step 314, according to this system, the RGB values ​​of each color block of the color card under the selected use environment are captured, and after converting the signal to the HSV color space, the saturation (S value) is optimized; (8) Step 316, based on the result presented by the current adjusted image, it is determined whether to optimize the brightness (V value) again.

[0054] In step 304 , the first image capturing device is, for example, a camera.

[0055] In step 306, 24 closed, separated geometric shapes appear in the camera's display window. These geometric shapes are the default window panes. The user must adjust the camera's alignment and angle so that the 24 geometric shapes in the display window are located within the 24 color blocks on the color card. In subsequent steps, the camera will capture the image of the color block corresponding to each geometric shape.

[0056] In step 308 , if the image is taken in the portrait mode, the weight value of the second group 204 for adjusting the portrait mode is increased by 2 to 6 times to make the skin color closer to the real color.

[0057] In step 310 , it is necessary to compare the difference between the preset color standard and the V value in order to optimize the brightness (V value).

[0058] In step 312, it is necessary to compare the difference between the preset color standard and the H value in order to optimize the hue (H value).

[0059] In step 314 , the difference between the preset color standard and the S value must be compared to optimize the saturation (S value).

[0060] In another embodiment, steps 302 to 308 are performed first. Then, in addition to adjusting brightness, hue, and saturation, the UVC parameters set by the first image capture device may be adjusted using contrast, sharpness, gain, gamma, exposure, or a 2D lookup table.

[0061] In one embodiment, after executing steps 302-308, the HSV values ​​set by the first image capture device are adjusted to user-defined HSV values. This allows users to perform image calibration based on their personal needs. In another embodiment, the HSV values ​​of each color block captured by the first image capture device from a color chart are used as target values ​​(first stage). These target values ​​are then used to calibrate the HSV values ​​set by another image capture device (e.g., a second image capture device) (second stage). In the first stage, the first image capture device and the color chart are placed in a selected usage environment. The calibration process is then initiated, and the window and preset pane of the first image capture device are aligned with the color chart. The first image capture device's system then captures the RGB values ​​of each color block of the color chart in the selected usage environment and converts the signals to the HSV color space. The calibration process is then performed on the second image capture device. In the second stage, the second image capture device is first placed in the selected usage environment. The weighting of the color block values ​​is then determined based on whether the image capture mode is set to capture people or objects. The second image capture system obtains the HSV values ​​of each color block of the color chart captured by the first image capture system under the selected usage environment to optimize brightness (V value), hue (H value), and saturation (S value). Based on the results of the current adjusted image, it determines whether to optimize brightness (V value) again.

[0062] Figure 4 This is an experimental data table after image correction according to an embodiment of the present invention. Figure 4 As shown, the above flowchart can be implemented, with the target image as the expected target, to calibrate the image before calibration. After automatically adjusting the V value, H value, S value, and V value in sequence, the H difference (dH), S difference (dS), and V difference (dV) of the image will be reduced from the original 10.77, 7.31, and 19.48 to 5.17, 2.63, and 3.64, respectively, and the color difference value calculated by the dE2000 formula will be reduced from the original 14.81 to 4.00. According to Figure 4 The experimental results shown confirm that by implementing the above embodiments of the present application, the color distortion of the image can indeed be reduced.

[0063] Figure 5 This is the result of image correction according to one embodiment of the present invention. Figure 5As shown, images are captured under six environmental conditions 501 to 506, and the captured images are corrected to obtain corrected images. The corrected images are then visually inspected. After visual inspection, the color distortion of each corrected image is lower than that of the original image. Among them, environmental conditions 501 to 506 correspond to light sources LED4200K, CFL (Compact Fluorescent Lamp) 6500K, CFL2700K, CFL5400K, LED3000K, and LED5500K, respectively. It can be seen that the image correction method of the present invention can effectively reduce the distortion effect of ambient light sources on the image, thereby better restoring the true color of the object under multiple light sources or complex light sources.

[0064] The present invention has been described with reference to the above embodiments. However, the above embodiments are merely exemplary embodiments of the present invention. It should be noted that the disclosed embodiments do not limit the scope of the present invention. On the contrary, modifications and improvements that do not depart from the spirit and scope of the present invention are intended to be protected by the present invention.

Claims

1. An image correction method, characterized in that: The following steps are involved: Obtain a color card, the color card comprising a plurality of color blocks, each of the color blocks having a preset color standard; Place the image capture device and the color card in the selected usage environment; A system using the image capture device to capture the RGB value of each color block of the color card and convert the RGB value into an HSV value; Comparing a preset color standard for each color block with the HSV value corresponding to each color block to determine the degree of difference between the preset color standard and the H value, S value, and V value of the HSV value, where the H value represents hue, the S value represents saturation, and the V value represents brightness; and Automatically adjusting the HSV value set by the image capture device according to the preset color standard of each color block and the degree of difference; The plurality of color blocks include a second group for adjusting the portrait mode, and the second group includes a first skin color block, a second skin color block, and a third skin color block.

2. The image correction method according to claim 1, wherein: The plurality of color blocks further include a first group for adjusting the hue and saturation of an image. The color saturation of each color block in the first group is 45-70%.

3. The image correction method according to claim 1, wherein: The plurality of color blocks further include a third group for adjusting the grayscale of an image. The grayscale value of each color block in the third group is 32-235.

4. The image correction method according to claim 1, wherein: The first skin color has an L value of 50-70, an a value of 7-12, and a b value of 10-26, and / or the second skin color has an L value of 50-70, an a value of 6-11, and a b value of 7-19, and / or the third skin color has an L value of 40-60, an a value of 7-16, and a b value of 9-38; wherein the L value is a brightness value, the a value is a green-red value, and the b value is a blue-yellow value.

5. The image correction method according to claim 1, wherein: The preset color standard corresponds to the RGB value, HSV value or Lab value presented by the color card under a standard light source environment.

6. The image correction method according to claim 1, wherein: When using the system of the image capture device to capture the RGB values ​​of each color block of the color card, the system of the image capture device will not capture images of other objects, and the RGB values ​​of each color block will be captured simultaneously.

7. The image correction method according to claim 1, wherein: When the HSV value set by the image capture device is automatically adjusted, a binary search algorithm or an optimal parameter step adjustment method is used.

8. The image correction method according to claim 1, wherein: The plurality of color blocks include a first group for adjusting image hue and saturation, a second group for adjusting a portrait mode, and a third group for adjusting image grayscale; The step of automatically adjusting the HSV value set by the image capture device specifically includes: adjusting the H value of the HSV value set by the image capture device based on the preset color standard and the degree of difference between the color blocks in the first group and the second group; and / or adjusting the V value of the HSV value set by the image capture device based on the preset color standard and the degree of difference between the color blocks in the third group.

9. The image correction method according to claim 1, wherein: Before using the system of the image capture device to capture the RGB value of each color block of the color card, the step further includes: adjusting the weight of at least a second group of the plurality of color blocks according to whether the image capture device is in a people shooting mode or an object shooting mode.

10. The image correction method according to claim 1, wherein: The step of automatically adjusting the HSV value set by the image capture device includes automatically adjusting the V value, the H value, and the S value in sequence, or automatically adjusting the V value, the H value, the S value, and the V value in sequence.

Images