CN108616700B - Image processing method and device, electronic equipment and computer readable storage medium - Google Patents

Abstract

The application relates to an image processing method and device, an electronic device and a computer readable storage medium. The method comprises the following steps: the method comprises the steps of obtaining at least two brightening central points in an image to be processed, establishing a light effect model according to the brightening central points, wherein the light effect model is a model simulating light intensity change, and performing light ray adding effect processing on the image to be processed according to the light effect model. Because a plurality of brightening central points of the image to be processed can be obtained to establish the light effect model, the light ray adding effect is carried out on the image to be processed according to the light effect model, and the light ray processing effect can be improved.

Description

Image processing method and apparatus, electronic device, computer-readable storage medium

technical field

The present application relates to the field of computer technology, and in particular, to an image processing method and apparatus, an electronic device, and a computer-readable storage medium.

Background technique

With the development of computer technology, image processing methods have become more and more abundant. During the shooting process, people can adjust the light brightness of the object to be shot by moving the focus point and the metering point, and can also select the highlight point in the shot image for lighting. The effect is added, so as to highlight the outline of the object to be photographed and achieve a better shooting effect.

However, the traditional image processing method has the problem of poor effect of adding light.

SUMMARY OF THE INVENTION

Embodiments of the present application provide an image processing method and apparatus, an electronic device, and a computer-readable storage medium, which can improve the effect of adding light.

An image processing method, comprising:

Obtain at least two brightening center points in the image to be processed;

A light effect model is established according to the brightening center point, and the light effect model is a model for simulating changes in light intensity;

The processing of adding a light effect is performed on the to-be-processed image according to the light effect model.

An image processing device, comprising:

an acquisition module, used to acquire at least two highlight center points in the image to be processed;

a model establishment module for establishing a light effect model according to the brightening center point, where the light effect model is a model for simulating changes in light intensity;

A processing module, configured to perform processing of adding light effects to the to-be-processed image according to the light effect model.

An electronic device includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the following steps:

Obtain at least two brightening center points in the image to be processed;

A light effect model is established according to the brightening center point, and the light effect model is a model for simulating changes in light intensity;

The processing of adding a light effect is performed on the to-be-processed image according to the light effect model.

A computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

Obtain at least two brightening center points in the image to be processed;

A light effect model is established according to the brightening center point, and the light effect model is a model for simulating changes in light intensity;

The processing of adding a light effect is performed on the to-be-processed image according to the light effect model.

The above-mentioned image processing method and device, electronic equipment, and computer-readable storage medium can obtain at least two brightening center points in the image to be processed, establish a light effect model according to the brightening center points, and add light to the image to be processed according to the light effect model. The processing of effects, the light effect model is a model that simulates changes in light intensity. Since a plurality of brightening center points of the image to be processed can be acquired to establish a light effect model, and the processing of adding light effects to the image to be processed is performed according to the light effect model, the light processing effect can be improved.

Description of drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort.

1 is a schematic diagram of the internal structure of an electronic device in one embodiment;

2 is a flowchart of an image processing method in one embodiment;

3 is a flowchart of an image processing method in another embodiment;

4 is a flowchart of an image processing method in yet another embodiment;

5 is a flow chart of establishing a light effect model in one embodiment;

6 is a schematic diagram of a light effect model in one embodiment;

7 is a flowchart of an image processing method in one embodiment;

8 is a structural block diagram of an image processing apparatus in one embodiment;

FIG. 9 is a schematic diagram of an image processing circuit in one embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, a first client may be referred to as a second client, and similarly, a second client may be referred to as a first client, without departing from the scope of this application. Both the first client and the second client are clients, but they are not the same client.

FIG. 1 is a schematic diagram of the internal structure of an electronic device in one embodiment. As shown in FIG. 1, the electronic device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor is used to provide computing and control capabilities to support the operation of the entire electronic device. The memory is used to store data, programs, etc., and at least one computer program is stored in the memory, and the computer program can be executed by the processor to implement the wireless network communication method applicable to the electronic device provided in the embodiments of the present application. The memory may include non-volatile storage media and internal memory. The nonvolatile storage medium stores an operating system and a computer program. The computer program can be executed by the processor to implement an image processing method provided by the following embodiments. Internal memory provides a cached execution environment for operating system computer programs in non-volatile storage media. The network interface can be an Ethernet card or a wireless network card, etc., and is used to communicate with external electronic devices. The electronic device may be a mobile phone, a tablet computer, a personal digital assistant or a wearable device, and the like.

FIG. 2 is a flowchart of an image processing method in one embodiment. The image processing method in this embodiment is described by taking the electronic device running in FIG. 1 as an example. As shown in FIG. 2 , the image processing method includes steps 202 to 206 .

Step 202: Acquire at least two highlight center points in the image to be processed.

The image to be processed is an image composed of multiple pixels and needs to be processed by adding light effects. The image to be processed may be an image collected by the electronic device in real time through a camera, or may be an image stored locally on the electronic device, or an image downloaded by the electronic device from a network. Lighting effects can be natural light, stage light, film light, contour light, etc. After the light source emits light, the light will spread around the light source, and the intensity of the light will decrease as the distance from the light source increases. The highlight center point is the pixel point corresponding to the center of the light source. The number of highlighting center points may be 2, 3, 4, 5, etc., but is not limited to this.

The electronic device can acquire the to-be-processed image and display the to-be-processed image. The electronic device may identify the image to be processed, determine at least two highlight center points according to the object in the image to be processed, or obtain at least two highlight center points selected by the user according to the displayed image to be processed.

Step 204 , establishing a light effect model according to the brightening center point, where the light effect model is a model for simulating changes in light intensity.

The light effect model refers to the model that adds light effects to the image to be processed. The light effect model can simulate the curve of the intensity change of the light emitted by the light source. A light effect model is established based on the brightening center point, that is, a model in which the brightening center point is used as a light source to simulate the change of light intensity at the location of each pixel point. The electronic device performs processing of adding light effects to the image to be processed according to the light effect model, which may include performing brightening processing on the image to be processed, changing the color of the image to be processed, and the like. The light effect reference model may be pre-stored in the electronic device, and the light effect reference model may be a model in which any reference pixel in the image is the light source. After the highlighting center point is obtained, the displacement of the highlighting center point relative to the reference pixel point can be obtained, and the light effect model corresponding to the highlighting center point can be obtained after displacing the light effect reference model.

For example, a light effect reference model may be pre-stored in the electronic device as P(x, y), and the light effect reference model takes the reference pixel point whose coordinates are (0, 0) as the model of the light source. Assuming that the selected highlighting center point is (x ₀ , y ₀ ), then the displacement of the highlighting center point relative to the reference pixel point is (-x ₀ , -y ₀ ), then the improvement obtained according to the displacement The light effect model corresponding to the bright center point is P(xx ₀ , yy ₀ ). In the obtained light effect model P(xx ₀ , yy ₀ ), it is the light effect model with the brightening center point (x ₀ , y ₀ ) as the light source.

The electronic device can acquire the environmental parameters of the image to be processed, and determine the light effect parameters in the light effect model according to the environmental parameters. Optionally, the light effect parameters may include color adjustment parameters, brightness enhancement coefficients, and the like. The color adjustment parameters can be used to adjust the color of the added light effect. The color adjustment parameters can include color conversion matrix, color saturation, etc., where the color conversion matrix can be used to adjust the color value of the pixel, and the saturation refers to the vividness of the color. degree. The color saturation can be used to adjust the color saturation of the pixels, and the brightness enhancement factor can be used to adjust the intensity of the added light effect.

In one embodiment, the electronic device may determine color adjustment parameters in the light effect model according to the collected color temperature. Optionally, the electronic device may preset color adjustment parameters corresponding to different color temperatures, and after collecting the color temperature of the image to be processed, may directly obtain the color adjustment parameters corresponding to the collected color temperature. Color adjustment parameters change the hue and color saturation of the light effect added to the image being processed. The electronic device may select the added light effect type according to the color temperature, and the light effect type may include a sunset light effect, a cloudy sky effect, a stage light effect, etc., but is not limited thereto. Different color adjustment parameters can be set in different light effect types. For example, the sunset light effect can set the color adjustment parameters of warm tones, and increase the value of the pixels in the R and G channels in the image to be processed, so that the light added to the image to be processed can be adjusted. The effect is yellowish, reddish, and cloudy. You can set the color adjustment parameters of the cool tone, increase the value of the pixel in the B channel of the image to be processed, and make the light effect added to the image to be processed bluish, gray, etc., but not limited to this.

The electronic device may construct a corresponding light effect model according to the acquired at least two brightening center points, and the number of the light effect models corresponds to the number of the brightening center points one-to-one.

Step 206 , adding light effects to the image to be processed according to the light effect model.

The electronic device performs processing of adding light effects to the image to be processed according to the light effect model, and can adjust the color values of the pixels in the image to be processed, and can also perform brightening processing on the image to be processed. Specifically, the electronic device may acquire pixel enhancement coefficients corresponding to each pixel in the image to be processed according to the light effect model, and perform processing of adding light effects to the pixel points according to the pixel enhancement coefficient. The pixel enhancement coefficient of a pixel point may be the pixel enhancement coefficient corresponding to the pixel point in the light effect model established by the brightening center point closest to the pixel point, or it may be at least two corresponding to the pixel point in at least two light effect models in the image. Weighted superposition of pixel enhancement coefficients. The electronic device may perform the processing of adding light effects to the image to be processed by superimposing or multiplying the pixel enhancement coefficients on the image to be processed.

For example, assuming that the image to be processed is H ₀ (x, y) and the light effect model is P(x, y), the image to be processed H(x, y) after the processing of adding light effects by superposition can be expressed as It is H(x,y)=(1+P(x,y))H ₀ (x,y), and the image to be processed after adding light effect processing by product can be expressed as H(x,y) =P(x,y)H ₀ (x,y). It can be understood that the processing of adding light effects can also be implemented in other ways, which are not limited here.

The image processing method provided by the embodiment of the present application can obtain at least two brightening center points in the image to be processed, establish a light effect model simulating light intensity changes according to the brightening center points, The image is processed to add light effects. At least two brightening center points of the to-be-processed image can be acquired to establish at least two corresponding light effect models, and the light-added effect can be improved by performing the processing of adding light effects to the to-be-processed image according to the establishment of the at least two light effect models.

As shown in FIG. 3 , in one embodiment, the provided image processing method further includes steps 302 to 306 . in:

Step 302: Obtain a target area of the image to be processed, where the target area is the area of the object to be photographed.

The electronic device can identify the area of the photographed object in the image to be processed. Specifically, the electronic device may obtain the focus point position of the image to be processed to determine the area of the object to be photographed, and may also use an image feature extraction method to determine the area of the object to be photographed. Specifically, the image features of the image to be processed include color features, texture features, shape features, spatial relationship features, etc. The image feature extraction method may be a histogram method, a geometric parameter method, a boundary feature method, etc., but is not limited thereto. The number of highlight center points in the target area may be 1, 2, 3, etc., but not limited thereto. After the electronic device determines the area of the object to be photographed in the image to be processed, that is, the target area, it acquires at least one highlight center point in the target area. In one embodiment, the target area may also be another area where the main light effect needs to be added.

Step 304, processing the first light effect on the highlight center point in the target area.

Step 306 , processing a second light effect on the brightening center point outside the target area, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect.

The highlight center point outside the target area refers to at least one highlight center point obtained by the electronic device from other areas outside the target area in the image to be processed after determining the target area. The brightness enhancement coefficient can be related to the distribution amplitude in the light effect model. The larger the brightness enhancement coefficient is, the larger the distribution amplitude can be, and the greater the intensity of the added light effect; The less powerful the effect.

The processing by the electronic device to perform the first light effect on the highlight center point in the target area means that the electronic device determines the corresponding highlight center point in the target area according to the highlight center point in the target area and the brightness enhancement coefficient of the first light effect. The light effect model is obtained, thereby obtaining the pixel enhancement coefficient corresponding to the pixel point in the light effect model, and performing the processing of adding the first light effect to the pixel point in the target area according to the pixel enhancement coefficient. The processing method of the electronic device performing the second light effect on the brightening center point outside the target area is similar to the processing method of performing the first light effect on the target area, and details are not described herein again.

Since the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect, after the electronic device completes the processing of the first light effect and the second light effect of the image to be processed, the target area in the image to be processed can be highlighted , so that the outline of the object to be photographed is better highlighted and the effect of adding light is improved.

As shown in FIG. 4 , an image processing method provided in an embodiment further includes steps 402 to 408 . in:

Step 402: Determine the face region of the image to be processed.

The electronic device can perform face detection on the image to be processed, and determine whether the image to be processed contains a human face, and if so, can determine the face area of the image to be processed. The electronic device can extract image features of the image to be processed, and analyze the image features through a preset face detection model to determine whether the image to be processed contains a human face. In one embodiment, the face detection model may be a decision-making model constructed in advance through machine learning. When constructing the face detection model, a large number of sample images may be obtained. The sample images include face images and unmanned images. Whether each sample image contains a face, mark the sample image, use the marked sample image as the input of the face detection model, and train through machine learning to obtain the face detection model.

Step 404, processing the first light effect on the highlight center point in the face area.

The processing of the first light effect by the electronic device on the brightening center point in the face area means that the electronic device obtains the brightening center point in the face area, and establishes the first light effect according to the brightening center point in the face area and the parameters of the first light effect. For the light effect model, the pixel enhancement coefficients corresponding to the pixels in the face area are obtained according to the light effect model, and the processing of adding the first light effect is performed on the face area. The parameters of the light effect include brightness enhancement coefficients, color adjustment parameters, and the like. The electronic device may acquire at least one highlight center point of the face area. Specifically, the number of highlighted center points can be related to the proportion of the face area in the image to be processed. The smaller the number of highlighted center points for the area.

Step 406: Obtain a portrait region corresponding to the human face region in the image to be processed.

After the electronic device detects the face area in the image to be processed, it can acquire the portrait area in the image to be processed according to the face area and depth information. The portrait and the human face are usually on the same vertical plane, and the values of the depth information from the portrait to the image acquisition device and the depth information from the human face to the image acquisition device are in the same range. Therefore, after obtaining the face area, the depth information corresponding to the face area can be obtained from the depth map obtained by the electronic device, and then the depth information corresponding to the portrait area can be obtained according to the depth information corresponding to the face area, and then The depth information can be obtained to obtain the portrait area in the image to be processed. It can be understood that, other methods may also be used to obtain the portrait area, which is not limited in this embodiment. For example, the portrait region can also be obtained by methods such as artificial intelligence and region growing method.

Step 408 , processing the portrait area with a second light effect, where the luminance enhancement coefficient of the second light effect is lower than the luminance enhancement coefficient of the first light effect.

After the electronic device determines the portrait area according to the face area in the image to be processed, it can obtain at least one brightening center point of the portrait area, and establish a light effect model according to the brightening center point of the portrait area and the parameters of the second light effect. The light effect model obtains the pixel enhancement coefficients corresponding to the pixels in the portrait area, and performs processing of adding a second light effect to the portrait area. Optionally, the electronic device may acquire multiple face areas and multiple portrait areas in the image to be processed, perform the first lighting effect processing on the multiple face areas, perform the second lighting effect processing on the multiple portrait areas, and perform the second lighting effect processing on the multiple portrait areas. The brightness enhancement coefficient of the light effect is lower than the brightness enhancement coefficient of the first light effect.

The electronic device performs the processing of the first light effect and the second light effect on the face area and the portrait area respectively, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect, which can highlight the portrait in the image to be processed, The effect of adding light to the face in the image to be processed is stronger, so that the outline of the person in the image to be processed is better highlighted, and the added light effect is better.

In one embodiment, an image processing method is provided in which a light effect model is established according to the highlight center point, as shown in FIG. 5 , including steps 502 to 506 . in:

Step 502, obtaining a two-dimensional Gaussian distribution function.

Specifically, the light effect model can be constructed according to a two-dimensional Gaussian distribution function. First obtain the two-dimensional Gaussian distribution function as follows:

The above function is a two-dimensional Gaussian distribution function with (0, 0) as the maximum point, where (x, y) represents the pixel point in the image to be processed; P(x, y) represents the pixel point for brightening processing The pixel enhancement coefficient at time; d is the standard deviation, the brightness enhancement coefficient can affect the size of d, the larger the brightness enhancement coefficient, the smaller the d can be, and the smaller the brightness enhancement coefficient, the larger the d can be. In the light effect model, the pixels at different positions of the image to be processed have different pixel enhancement coefficients. The pixel points that are closer to the maximum point have stronger pixel enhancement coefficients, and the pixels that are farther from the maximum point are , the smaller the pixel enhancement coefficient is.

Step 504: Determine the distribution amplitude according to the luminance enhancement coefficient.

Step 506 , taking the highlight center point as the maximum point of the two-dimensional Gaussian distribution function, and constructing a light effect model according to the maximum point and the distribution amplitude.

In this embodiment, the light effect model is a two-dimensional Gaussian distribution function, and the electronic device can determine the maximum value point of the light effect model according to the position of the brightening center point, and determine the distribution amplitude according to the brightness enhancement coefficient. The maximum value point of the light effect model can be used to determine the position of the light effect model, and the electronic device can use the highlight center point as the maximum value point of the light effect model. The distribution amplitude of the light effect model can be used to describe the shape of the two-dimensional Gaussian distribution function. When the brightness enhancement coefficient is larger, the shape of the light effect model can be more "skinny and taller", and when the brightness enhancement coefficient is smaller, the shape of the light effect model can be more "thin".

The electronic device establishes a light effect model according to the brightening center point, that is, displaces the two-dimensional Gaussian distribution function, and moves the maximum point of the two-dimensional Gaussian distribution function to the position of the brightening center point to obtain the light effect model. Assuming that the position of the highlight center point is (x ₀ , y ₀ ), the resulting light effect model can be expressed as:

In the obtained light effect model, the highlight center point (x ₀ , y ₀ ) is the maximum value point, that is, the pixel enhancement coefficient P _o (x, y) obtained at the highlight center point (x ₀ , y ₀ ) maximum.

FIG. 6 is a schematic diagram of a light effect model in one embodiment. As shown in FIG. 6 , the resolution of the image to be processed in the light effect model is 50*50, and the coordinate value of the highlight center point 602 is (25, 25). It can be seen that the pixel enhancement coefficient corresponding to the highlight center point 602 is the largest, and the pixel enhancement coefficients corresponding to other pixel points in the image to be processed decrease as the distance from the highlight center point 602 increases. The farther the distance is, the smaller the corresponding pixel enhancement coefficient is.

In one embodiment, an image processing method is provided, further comprising: determining a brightness enhancement coefficient in the optical model according to brightness information of the image to be processed, where the brightness enhancement coefficient is used to adjust the intensity of light intensity changes in the light effect model.

The electronic device may set a standard brightness threshold, where the standard brightness threshold is used to represent an ideal ratio of the brightness value of the object to be photographed to the brightness value of the image to be processed. When the brightness value of the photographed object and the brightness value of the image to be processed reach an ideal ratio, it can be determined that there is a relatively ideal effect. After the electronic device collects the brightness information of the image to be processed, it can determine whether the ratio of the brightness value of the object to be photographed to the brightness value of the image to be processed is smaller than the standard brightness threshold. When the ratio is greater than the standard brightness threshold, the processing of adding light effects to the image to be processed may not be performed. When the ratio is smaller than the standard brightness threshold, the brightness enhancement coefficient in the optical model can be determined according to the ratio. The brightness enhancement coefficient in the optical model is negatively correlated with this ratio. When the ratio of the brightness value of the object to be photographed to the brightness value of the image to be processed is small, the brightness enhancement coefficient increases. When the ratio of the brightness value to is larger, the brightness enhancement coefficient decreases. The brightness enhancement coefficient can also be adjusted according to the brightness value of the image to be processed, etc., which is not limited here.

As shown in FIG. 7 , in one embodiment, the provided image processing method further includes steps 702 to 704 . in:

Step 702: Obtain pixel enhancement coefficients corresponding to each pixel in the image to be processed according to the light effect model.

It can be understood that the image to be processed is a two-dimensional pixel matrix, and a coordinate system can be established with the pixel at the bottom left corner of the image to be processed as the origin, and the pixels in the image to be processed can be represented by a two-dimensional coordinate. According to the above light effect model, the pixel enhancement coefficient of each pixel in the image to be processed can be obtained, and the coordinates corresponding to each pixel can be directly brought into the above light effect model to obtain the pixel enhancement coefficient of the pixel. The electronic device can obtain the pixel enhancement coefficient of the pixel point in the optical model established by the brightening center point closest to the pixel point as the pixel enhancement coefficient corresponding to the pixel point, or obtain the pixel point in at least two light effect models in the image to be processed. The at least two pixel enhancement coefficients are weighted to obtain the pixel enhancement coefficients corresponding to the pixel points.

Step 704: Perform processing of adding light effects to the pixel points according to the pixel enhancement coefficients corresponding to the pixel points.

The electronic device adds light effects to the pixels according to the pixel enhancement coefficients corresponding to the pixels. It can add light effects to all pixels in the image to be processed, and can also add light effects to the target area. Add light effects to the face area and the portrait area. Areas other than the portrait area or the target area in the image to be processed may not be processed, or may be weakened.

In one embodiment, an image processing method is provided, further comprising: when there are multiple pixel enhancement coefficients at a pixel point, weighting the multiple pixel enhancement coefficients of the pixel point to obtain the pixel enhancement coefficient corresponding to the pixel point, and according to the pixel point The corresponding pixel enhancement coefficients process the pixel points.

Specifically, the electronic device may use the average value of all pixel enhancement coefficients of the pixel as the pixel enhancement coefficient corresponding to the pixel, or it may be the area where the pixel is located in the image to be processed. The average value of the multiple pixel enhancement coefficients of the pixel points in the light effect model established by the brightening center point is taken as the pixel enhancement coefficient corresponding to the pixel point, and the largest pixel enhancement coefficient among the multiple pixel enhancement coefficients of the pixel point can also be taken as the pixel point. The pixel enhancement coefficient corresponding to the point, and the weighting manner of the pixel enhancement coefficient may be various, which is not limited here. The area where the pixel points are located may be a target area, an area outside the target area, a face area, a portrait area, and the like.

The electronic device may add light effect processing to the pixel points according to the pixel enhancement coefficients corresponding to the pixel points obtained by weighting. Therefore, the photographed object in the to-be-processed image is more prominent, and the effect of light processing is improved.

In one embodiment, an image processing method is provided, and the specific steps for realizing the method are as follows:

First, the electronic device may acquire at least two highlight center points in the image to be processed. The image to be processed is an image composed of multiple pixels and needs to be processed by adding light effects. The image to be processed may be an image captured by the electronic device in real time through a camera, or may be an image stored locally on the electronic device. Lighting effects can be natural light, stage light, film light, contour light, etc. The highlight center point is the pixel point corresponding to the center of the light source. The electronic device can acquire the to-be-processed image and display the to-be-processed image. The electronic device may identify the image to be processed, determine at least two highlight center points according to the object in the image to be processed, or obtain at least two highlight center points selected by the user according to the displayed image to be processed.

Next, the electronic device establishes a light effect model according to the brightening center point, and the light effect model is a model that simulates changes in light intensity. The light effect model refers to the model that adds light effects to the image to be processed. The light effect model can simulate the curve of the intensity change of the light emitted by the light source. A light effect model is established based on the brightening center point, that is, a model in which the brightening center point is used as a light source to simulate the change of light intensity at the location of each pixel point. The electronic device performs processing of adding light effects to the image to be processed according to the light effect model, which may include performing brightening processing on the image to be processed, changing the color of the image to be processed, and the like. The light effect reference model may be pre-stored in the electronic device, and the light effect reference model may be a model in which any reference pixel in the image is the light source. After the highlighting center point is obtained, the displacement of the highlighting center point relative to the reference pixel point can be obtained, and the light effect model corresponding to the highlighting center point can be obtained after displacing the light effect reference model.

Optionally, the electronic device obtains a two-dimensional Gaussian distribution function, determines the distribution amplitude according to the brightness enhancement coefficient, takes the brightening center point as the maximum value point of the two-dimensional Gaussian distribution function, and constructs a light effect model according to the maximum value point and the distribution amplitude. . The light effect model is a two-dimensional Gaussian distribution function, and the electronic device can determine the maximum value point of the light effect model according to the position of the brightening center point, and determine the distribution amplitude according to the brightness enhancement coefficient. The maximum value point of the light effect model can be used to determine the position of the light effect model, and the electronic device can use the highlight center point as the maximum value point of the light effect model. The distribution amplitude of the light effect model can be used to describe the shape of the two-dimensional Gaussian distribution function. The electronic device establishes a light effect model according to the brightening center point, that is, displaces the above-mentioned two-dimensional Gaussian distribution function, and moves the maximum point of the two-dimensional Gaussian distribution function to the position of the brightening center point to obtain the light effect model.

Optionally, a brightness enhancement coefficient in the light effect model is determined according to the brightness information of the image to be processed, and the brightness enhancement coefficient is used to adjust the intensity of light intensity changes in the light effect model. The electronic device may set a standard brightness threshold, where the standard brightness threshold is used to represent an ideal ratio of the brightness value of the object to be photographed to the brightness value of the image to be processed. When the ratio of the brightness value of the photographed object to the brightness value of the image to be processed is smaller than the standard brightness threshold, the brightness enhancement coefficient in the optical model can be determined according to the ratio. The brightness enhancement coefficient in the optical model is negatively correlated with this ratio. When the ratio of the brightness value of the object to be photographed to the brightness value of the image to be processed is small, the brightness enhancement coefficient increases. When the ratio of the brightness value to is larger, the brightness enhancement coefficient decreases. The brightness enhancement coefficient can also be adjusted according to the brightness value of the image to be processed, etc., which is not limited here.

Next, the electronic device performs processing of adding light effects to the image to be processed according to the light effect model. The electronic device performs processing of adding light effects to the image to be processed according to the light effect model, and can adjust the color values of the pixels in the image to be processed, and can also perform brightening processing on the image to be processed. Specifically, the electronic device may acquire pixel enhancement coefficients corresponding to each pixel in the image to be processed according to the light effect model, and perform processing of adding light effects to the pixel points according to the pixel enhancement coefficient. The electronic device may perform the processing of adding light effects to the image to be processed by superimposing or multiplying the pixel enhancement coefficients on the image to be processed.

Optionally, the electronic device obtains the target area of the image to be processed, where the target area is the area of the object to be photographed, and performs the first light effect processing on the brightening center point in the target area, and performs the first light effect processing on the brightening center point outside the target area. In the processing of the second light effect, the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect. The electronic device can identify the area of the photographed object in the image to be processed. After the electronic device determines the area of the object to be photographed in the image to be processed, that is, the target area, it acquires at least one highlight center point in the target area. The processing by the electronic device to perform the first light effect on the highlight center point in the target area means that the electronic device determines the corresponding highlight center point in the target area according to the highlight center point in the target area and the brightness enhancement coefficient of the first light effect. The light effect model is obtained, thereby obtaining the pixel enhancement coefficient corresponding to the pixel point in the light effect model, and performing the processing of adding the first light effect to the pixel point in the target area according to the pixel enhancement coefficient. The processing method of the electronic device performing the second light effect on the brightening center point outside the target area is similar to the processing method of performing the first light effect on the target area. Since the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect, after the electronic device completes the processing of the first light effect and the second light effect of the image to be processed, the target area in the image to be processed can be highlighted , so that the outline of the object to be photographed is better highlighted and the effect of adding light is improved.

Optionally, the electronic device determines the face area of the image to be processed, performs the processing of the first light effect on the brightening center point in the face area, obtains the portrait area corresponding to the face area in the image to be processed, and performs the processing on the portrait area. The middle brightening center point is processed for the second light effect, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect. The electronic device can perform face detection on the image to be processed, and determine whether the image to be processed contains a human face, and if so, can determine the face area of the image to be processed. After the electronic device detects the face area in the image to be processed, it can acquire the portrait area in the image to be processed according to the face area and depth information. The electronic device performs the processing of the first light effect and the second light effect on the face area and the portrait area respectively, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect, which can highlight the portrait in the image to be processed, The effect of adding light to the face in the image to be processed is stronger, so that the outline of the person in the image to be processed is better highlighted, and the added light effect is better.

Optionally, the electronic device obtains pixel enhancement coefficients corresponding to each pixel in the to-be-processed image according to the light effect model, and performs processing of adding light effects to the pixel according to the pixel enhancement coefficient corresponding to the pixel. The image to be processed is a two-dimensional pixel matrix, and a coordinate system can be established with the pixel at the bottom left corner of the image to be processed as the origin, and the pixels in the image to be processed can be represented by a two-dimensional coordinate. According to the above light effect model, the pixel enhancement coefficient of each pixel in the image to be processed can be obtained, and the coordinates corresponding to each pixel can be directly brought into the above light effect model to obtain the pixel enhancement coefficient of the pixel. The electronic device adds light effects to the pixels according to the pixel enhancement coefficients corresponding to the pixels. It can add light effects to all pixels in the image to be processed, and can also add light effects to the target area. Add light effects to the face area and the portrait area.

Optionally, when the pixel point has multiple pixel enhancement coefficients, the electronic device weights the multiple pixel enhancement coefficients of the pixel point to obtain the pixel enhancement coefficient corresponding to the pixel point. The pixel points are processed by pixel enhancement coefficients. The electronic device weights multiple pixel enhancement coefficients of a pixel point, which may be the average value of all pixel enhancement coefficients of the pixel point as the pixel enhancement coefficient corresponding to the pixel point, or it may be to brighten the area where the pixel point is located in the image to be processed. The average value of the multiple pixel enhancement coefficients of the pixel points in the light effect model established by the center point is used as the pixel enhancement coefficient corresponding to the pixel point, and the largest pixel enhancement coefficient among the multiple pixel enhancement coefficients of the pixel point can also be used as the corresponding pixel point. The pixel enhancement coefficient, the weighting manner of the pixel enhancement coefficient can be in various ways, which is not limited here.

It should be understood that although the various steps in the flowcharts of FIGS. 2-5 and 7 are shown in sequence according to the arrows, these steps are not necessarily executed in the sequence shown by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in FIGS. 2-5 and 7 may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. These sub-steps are not necessarily completed at the same time. Alternatively, the order of execution of the stages is not necessarily sequential, but may be performed alternately or alternately with other steps or sub-steps of other steps or at least a portion of a stage.

FIG. 8 is a structural block diagram of an image processing apparatus according to an embodiment. As shown in FIG. 8 , the apparatus includes an acquisition module 820, a model establishment module 840 and a processing module 860, wherein:

The acquiring module 820 is configured to acquire at least two highlight center points in the image to be processed.

The model establishment model 840 is used to establish a light effect model according to the brightening center point, and the light effect model is a model for simulating changes in light intensity.

The processing module 860 is configured to perform processing of adding light effects to the image to be processed according to the light effect model.

In one embodiment, the processing module 860 may also be used to obtain a target area of the image to be processed, where the target area is the area of the object to be photographed; perform the first light effect processing on the highlight center point of the target area, The second light effect is processed at the brightening center point, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect.

In one embodiment, the processing module 860 may also be used to determine the face area of the image to be processed, perform the first light effect processing on the highlighted center point in the face area, and obtain the image to be processed that matches the face of the human face. In the portrait area corresponding to the area, a second light effect is processed on the brightening center point in the portrait area, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect.

In one embodiment, the model building module 840 may be further configured to determine a brightness enhancement coefficient in the light effect model according to the brightness information of the image to be processed, where the brightness enhancement coefficient is used to adjust the intensity of light intensity changes in the light effect model.

In one embodiment, the model building module 840 can also be used to obtain a two-dimensional Gaussian distribution function, determine the distribution amplitude according to the brightness enhancement coefficient, and use the highlight center point as the maximum value point of the two-dimensional Gaussian distribution function, according to the maximum value Point and distribution amplitude to build a light effect model.

In one embodiment, the processing module 860 may be further configured to obtain pixel enhancement coefficients corresponding to each pixel in the image to be processed according to the light effect model, and perform processing of adding light effects to the pixels according to the pixel enhancement coefficients corresponding to the pixels.

In one embodiment, the processing module 860 may also be configured to, when there are multiple pixel enhancement coefficients at the pixel point, weight the multiple pixel enhancement coefficients of the pixel point to obtain the pixel enhancement coefficient corresponding to the pixel point. The pixel enhancement coefficient of the pixel is processed.

The division of each module in the above image processing apparatus is only for illustration. In other embodiments, the image processing apparatus may be divided into different modules as required to complete all or part of the functions of the above image processing apparatus.

For the specific limitation of the image processing apparatus, reference may be made to the limitation of the image processing method above, which will not be repeated here. Each module in the above-mentioned image processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

The implementation of each module in the image processing apparatus provided in the embodiments of the present application may be in the form of a computer program. The computer program can be run on a terminal or server. The program modules constituted by the computer program can be stored in the memory of the terminal or the server. When the computer program is executed by the processor, the steps of the methods described in the embodiments of the present application are implemented.

Embodiments of the present application also provide a computer-readable storage medium. One or more non-volatile computer-readable storage media containing computer-executable instructions, when executed by one or more processors, cause the processors to perform the steps of an image processing method.

A computer program product containing instructions, when run on a computer, causes the computer to perform an image processing method.

The embodiments of the present application also provide an electronic device. The above electronic device includes an image processing circuit, and the image processing circuit may be implemented by hardware and/or software components, and may include various processing units that define an ISP (Image Signal Processing, image signal processing) pipeline. FIG. 9 is a schematic diagram of an image processing circuit in one embodiment. As shown in FIG. 9 , for the convenience of description, only various aspects of the image processing technology related to the embodiments of the present application are shown.

As shown in FIG. 9 , the image processing circuit includes an ISP processor 940 and a control logic 950 . Image data captured by imaging device 910 is first processed by ISP processor 940 , which analyzes the image data to capture image statistics that can be used to determine and/or control one or more parameters of imaging device 910 . Imaging device 910 may include a camera having one or more lenses 912 and an image sensor 914 . Image sensor 914 may include an array of color filters (eg, Bayer filters), image sensor 914 may obtain light intensity and wavelength information captured with each imaging pixel of image sensor 914 and provide a set of raw materials that may be processed by ISP processor 940. image data. The sensor 920 (eg, a gyroscope) may provide the acquired image processing parameters (eg, anti-shake parameters) to the ISP processor 940 based on the sensor 920 interface type. The sensor 920 interface may utilize a SMIA (Standard Mobile Imaging Architecture) interface, other serial or parallel camera interfaces, or a combination of the above interfaces.

In addition, image sensor 914 may also send raw image data to sensor 920, which may provide raw image data to ISP processor 940 based on the sensor 920 interface type, or sensor 920 may store the raw image data in image memory 930.

The ISP processor 940 processes raw image data pixel by pixel in various formats. For example, each image pixel may have a bit depth of 8, 10, 12, or 14 bits, and the ISP processor 940 may perform one or more image processing operations on the raw image data, collecting statistical information about the image data. Among them, the image processing operations can be performed with the same or different bit depth precision.

ISP processor 940 may also receive image data from image memory 930 . For example, the sensor 920 interface sends the raw image data to the image memory 930, and the raw image data in the image memory 930 is provided to the ISP processor 940 for processing. The image memory 930 may be a part of a memory device, a storage device, or an independent dedicated memory in an electronic device, and may include a DMA (Direct Memory Access, direct memory access) feature.

When receiving raw image data from the image sensor 914 interface or from the sensor 920 interface or from the image memory 930, the ISP processor 940 may perform one or more image processing operations, such as temporal filtering. The processed image data may be sent to image memory 930 for additional processing before being displayed. The ISP processor 940 receives processed data from the image memory 930 and performs image data processing in the original domain and in the RGB and YCbCr color spaces on the processed data. The image data processed by the ISP processor 940 may be output to the display 970 for viewing by the user and/or further processed by a graphics engine or a GPU (Graphics Processing Unit, graphics processor). In addition, the output of the ISP processor 940 may also be sent to the image memory 930 , and the display 970 may read image data from the image memory 930 . In one embodiment, image memory 930 may be configured to implement one or more frame buffers. In addition, the output of ISP processor 940 may be sent to encoder/decoder 960 for encoding/decoding image data. The encoded image data can be saved and decompressed prior to display on the display 970 device. The encoder/decoder 960 may be implemented by a CPU or GPU or a co-processor.

Statistics determined by the ISP processor 940 may be sent to the control logic 950 unit. For example, the statistics may include image sensor 914 statistics such as auto exposure, auto white balance, auto focus, flicker detection, black level compensation, lens 912 shading correction, and the like. Control logic 950 may include a processor and/or microcontroller executing one or more routines (eg, firmware) that may determine control parameters and ISP processing of imaging device 910 based on received statistics control parameters of the controller 940. For example, imaging device 910 control parameters may include sensor 920 control parameters (eg, gain, integration time for exposure control, stabilization parameters, etc.), camera flash control parameters, lens 912 control parameters (eg, focal length for focusing or zooming), or these combination of parameters. ISP control parameters may include gain levels and color correction matrices for automatic white balance and color adjustment (eg, during RGB processing), and lens 912 shading correction parameters.

In this embodiment, the above-mentioned image processing method can be implemented by using the image processing technology shown in FIG. 9 .

Any reference to a memory, storage, database, or other medium as used herein may include non-volatile and/or volatile memory. Suitable nonvolatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in various forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous Link (Synchlink) DRAM (SLDRAM), Memory Bus (Rambus) Direct RAM (RDRAM), Direct Memory Bus Dynamic RAM (DRDRAM), and Memory Bus Dynamic RAM (RDRAM).

The above-mentioned embodiments only represent several embodiments of the present application, and the descriptions thereof are relatively specific and detailed, but should not be construed as a limitation on the scope of the patent of the present application. It should be noted that, for those skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the scope of protection of the patent of the present application shall be subject to the appended claims.

Claims (12)

1. an image processing method, is characterized in that, comprises: Obtain at least two brightening center points in the image to be processed; the brightening center points are the pixel points corresponding to the center of the light source; A light effect model is established according to the brightening center point, and the light effect model is a model in which the brightening center point is used as a light source to simulate the change of light intensity at the position of each pixel point; Perform processing of adding light effects to the to-be-processed image according to the light effect model; The method further includes: acquiring a target area of the image to be processed, where the target area is the area of the object to be photographed; the at least two highlight center points include a highlight center point in the target area and a highlight outside the target area center point; processing the first light effect on the brightening center point in the target area; processing the second light effect on the brightening center point outside the target area, the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect; The method also includes: The brightness enhancement coefficient in the light effect model is determined according to the brightness information of the to-be-processed image, and the brightness enhancement coefficient is used to adjust the intensity of the light intensity change in the light effect model. 2. The method according to claim 1, wherein the method further comprises: determining the face area of the image to be processed; processing the first light effect on the brightening center point in the face area; acquiring the portrait area corresponding to the face area in the to-be-processed image; The second light effect processing is performed on the brightened central point in the portrait area, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect. 3. The method according to claim 1, wherein the establishing a light effect model according to the highlighting center point comprises: Get the two-dimensional Gaussian distribution function; determining the distribution amplitude according to the luminance enhancement coefficient; The highlight center point is taken as the maximum value point of the two-dimensional Gaussian distribution function, and a light effect model is constructed according to the maximum value point and the distribution amplitude. 4. The method according to any one of claims 1 to 3, wherein the method further comprises: Obtain pixel enhancement coefficients corresponding to each pixel in the image to be processed according to the light effect model; The processing of adding light effects is performed on the pixel points according to the pixel enhancement coefficients corresponding to the pixel points. 5. The method according to claim 4, wherein the method further comprises: When the pixel point has multiple pixel enhancement coefficients, weighting the multiple pixel enhancement coefficients of the pixel point to obtain the pixel enhancement coefficient corresponding to the pixel point, according to the pixel enhancement coefficient corresponding to the pixel point. Pixels are processed. 6. An image processing device, comprising: an acquisition module, configured to acquire at least two brightening center points in the to-be-processed image; the brightening center points are the pixel points corresponding to the center of the light source; a model establishment module, used for establishing a light effect model according to the brightening center point, and the light effect model is a model in which the brightening center point is used as a light source to simulate the change of light intensity at the position of each pixel point; a processing module, configured to perform processing of adding light effects to the to-be-processed image according to the light effect model; The processing module is also used to obtain the target area of the image to be processed, and the target area is the area of the object to be photographed; the at least two highlight center points include the highlight center point in the target area and the area outside the target area. brighten the center point; The first light effect processing is performed on the brightening center point in the target area; the second light effect processing is performed on the brightening center point outside the target area, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect; The model building module is further configured to determine a brightness enhancement coefficient in the light effect model according to the brightness information of the image to be processed, where the brightness enhancement coefficient is used to adjust the intensity of light intensity changes in the light effect model. 7. The device of claim 6, wherein The processing module is further configured to determine the face area of the to-be-processed image; perform the first light effect processing on the brightening center point in the face area; The portrait area corresponding to the face area; the highlighting center point in the portrait area is processed with a second light effect, and the brightness enhancement coefficient of the second light effect is lower than the brightness enhancement coefficient of the first light effect. 8. The device of claim 6, wherein The model building module is also used to obtain a two-dimensional Gaussian distribution function; determine the distribution amplitude according to the brightness enhancement coefficient; take the highlight center point as the maximum value point of the two-dimensional Gaussian distribution function, The value points and distribution amplitudes are used to construct a light effect model. 9. The device according to any one of claims 6 to 8, characterized in that, The processing module is further configured to acquire pixel enhancement coefficients corresponding to each pixel in the image to be processed according to the light effect model; and perform processing of adding light effects to the pixel points according to the pixel enhancement coefficient corresponding to the pixel. 10. The device of claim 9, wherein: The processing module is further configured to, when there are multiple pixel enhancement coefficients at the pixel point, weight the multiple pixel enhancement coefficients of the pixel point to obtain the pixel enhancement coefficient corresponding to the pixel point, according to the pixel point The corresponding pixel enhancement coefficients process the pixel points. 11. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor is made to execute any one of claims 1 to 5 The steps of the image processing method. 12. A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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