Image processing method for underwater image and related device

Abstract

The invention discloses an image processing method and device for an underwater image and a storage medium, and is applied to underwater shooting equipment, the underwater shooting equipment comprises a water quality detection sensor, a light detection sensor, a pressure sensor and a temperature sensor, and the method comprises the following steps: when the underwater shooting equipment is located underwater, the water quality detection sensor detects the underwater image; acquiring a first water quality detection parameter through a water quality detection sensor; acquiring a first light detection parameter through a light detection sensor; acquiring a first pressure parameter through a pressure sensor; acquiring a first temperature parameter through a temperature sensor; determining a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter; determining a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter; and performing underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image. By adopting the embodiment of the invention, the intelligence of underwater shooting can be improved.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to an image processing method and related device for underwater images. Background Art

[0002] In life, underwater photography refers to taking photos or videos in water. For example, the photographer (videographer) carries a camera (video camera) with a protective cover and diving equipment, dives into the water and shoots directly.

[0003] At present, underwater shooting is relatively mechanized and not flexible enough. Therefore, the problem of how to improve the intelligence of underwater shooting needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present application provide an image processing method and related devices for underwater images, which can improve the intelligence of underwater photography.

[0005] In a first aspect, an embodiment of the present application provides an image processing method for underwater images, which is applied to an underwater shooting device, wherein the underwater shooting device includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. The method includes:

[0006] When the underwater shooting device is located underwater, obtaining a first water quality detection parameter through the water quality detection sensor;

[0007] Acquiring a first light detection parameter through the light detection sensor;

[0008] Acquiring a first pressure parameter through the pressure sensor;

[0009] Acquiring a first temperature parameter through the temperature sensor;

[0010] Determine a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter;

[0011] determining a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter;

[0012] Underwater shooting is performed according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image.

[0013] In a second aspect, an embodiment of the present application provides an image processing device for underwater images, which is applied to underwater shooting equipment, wherein the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor, and the device includes:

[0014] an acquisition unit, configured to acquire, when the underwater photographing device is underwater, a first water quality detection parameter through the water quality detection sensor; a first light detection parameter through the light detection sensor; a first pressure parameter through the pressure sensor; and a first temperature parameter through the temperature sensor;

[0015] a determining unit, configured to determine a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter; and determine a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter;

[0016] A shooting unit is used to perform underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image.

[0017] In a third aspect, an embodiment of the present application provides an underwater shooting device, which includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing some or all of the steps described in the method described in the first aspect of the embodiment of the present application.

[0018] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, wherein the computer program is executed by a processor to implement part or all of the steps described in the method described in the first aspect of the embodiment of the present application.

[0019] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the method described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0020] Implementing the embodiments of the present application has the following beneficial effects:

[0021] It can be seen that the image processing method, device and storage medium for underwater images described in the embodiments of the present application are applied to underwater shooting equipment, and the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. When the underwater shooting equipment is located underwater, a first water quality detection parameter is obtained through the water quality detection sensor, a first light detection parameter is obtained through the light detection sensor, a first pressure parameter is obtained through the pressure sensor, and a first temperature parameter is obtained through the temperature sensor. A first software shooting parameter is determined according to the first water quality detection parameter and the first light detection parameter, and a first hardware shooting parameter is determined according to the first pressure parameter and the first temperature parameter. Underwater shooting is performed according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image. On the one hand, at the algorithm level, software shooting parameters corresponding to water quality and light can be obtained, which helps to ensure the image shooting effect. On the other hand, at the hardware level, the performance of pressure and temperature compensation equipment (camera, underwater shooting equipment, etc.) can be used to improve the intelligence of underwater shooting. In this way, the intelligence of underwater shooting can be deeply improved.

[0022] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 is a flowchart of an image processing method for underwater images provided in an embodiment of the present application;

[0025] Figure 2 is a structural schematic diagram of an underwater shooting device provided in an embodiment of the present application;

[0026] Figure 3 It is a structural schematic diagram of an image processing device for underwater images provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0028] The following are detailed descriptions of each.

[0029] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0030] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] Below, some terms in this application are explained to facilitate understanding by those skilled in the art.

[0032] In the embodiments of the present application, the underwater shooting equipment may include at least one of the following: an underwater camera, a smart phone, a wearable device, a smart diving device (with a camera function), a smart camera, etc., which are not limited here.

[0033] The embodiments of the present application are described in detail below.

[0034] like Figure 1 As shown, Figure 1 1 is a flow chart of an image processing method for underwater images provided in an embodiment of the present application, which is applied to underwater shooting equipment, wherein the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. The image processing method for underwater images includes:

[0035] 101. When the underwater shooting device is located underwater, obtain a first water quality detection parameter through the water quality detection sensor.

[0036] In an embodiment of the present application, the underwater shooting equipment may include: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor.

[0037] In a specific implementation, when the underwater shooting device is located underwater, the first water quality detection parameter can be obtained through the water quality detection sensor. The first water quality detection parameter may include at least one of the following: pH value, density, salt content, total nitrogen, chromaticity, turbidity, COD, ammonia nitrogen, total phosphorus, total coliform bacteria, petroleum and animal and plant oil organic matter and organic compounds thereof, trace harmful chemical element content, etc., which are not limited here.

[0038] Among them, COD can be understood as the amount of oxygen required by chemical oxidants to oxidize organic pollutants in water.

[0039] 102. Acquire a first light detection parameter through the light detection sensor.

[0040] In a specific implementation, the first light detection parameter may include at least one of the following: ambient light brightness, light source type, etc., which are not limited here. Specifically, the first light detection parameter may be obtained through a light detection sensor.

[0041] 103. Acquire a first pressure parameter through the pressure sensor.

[0042] In the embodiment of the present application, different water depths correspond to different water pressures. Therefore, a first pressure parameter can be obtained through a pressure sensor, and the first pressure parameter reflects the water depth to a certain extent.

[0043] 104. Acquire a first temperature parameter through the temperature sensor.

[0044] In the embodiment of the present application, due to different water depths, the corresponding temperatures are also different, so the first temperature data can be obtained through a temperature sensor.

[0045] 105. Determine a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter.

[0046] The first software shooting parameter can be understood as the shooting parameter at the algorithm level during the shooting process to optimize the shooting effect. In a specific implementation, the first software shooting parameter may include at least one of the following: white balance (WB) parameter, shooting mode, resolution, focal length, auto focus parameter, sensitivity (ISO), exposure time, etc., which are not limited here.

[0047] In the embodiment of the present application, water quality and light will affect the image quality to a certain extent. Therefore, the first software shooting parameter can be determined according to the first water quality detection parameter and the first light detection parameter. Thus, the software shooting parameter corresponding to the water quality and light can be obtained, which helps to ensure the image shooting effect.

[0048] 106. Determine a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter.

[0049] The first hardware shooting parameter can be understood as changing the hardware configuration parameters during the shooting process to optimize the image effect. The first hardware shooting parameter can include at least one of the following: processor configuration parameters, aperture (F), shutter speed (S), metering mode (M), camera configuration parameters, etc., which are not limited here.

[0050] In a specific implementation, pressure and temperature will affect the performance of the camera to a certain extent. Therefore, the first hardware shooting parameter can be determined according to the first pressure parameter and the first temperature parameter. That is, the performance of the pressure and temperature compensation equipment (camera, underwater shooting equipment, etc.) can be based on the pressure and temperature to a certain extent, thereby improving the intelligence of underwater shooting.

[0051] 107. Perform underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image.

[0052] In the specific implementation, on the one hand, at the algorithm level, the software shooting parameters corresponding to the water quality and light can be obtained, which helps to ensure the image shooting effect. On the other hand, at the hardware level, the performance of pressure and temperature compensation equipment (cameras, underwater shooting equipment, etc.) can be used to improve the intelligence of underwater shooting. In this way, the intelligence of underwater shooting can be deeply improved.

[0053] Optionally, the above step 107, performing underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain the first image, may include the following steps:

[0054] Determining a first shooting angle of the underwater shooting device;

[0055] Determining a first feedback adjustment parameter corresponding to the first shooting angle;

[0056] adjusting the first software shooting parameter according to the first feedback parameter to obtain a second software shooting parameter;

[0057] Underwater shooting is performed according to the second software shooting parameter and the first hardware shooting parameter to obtain the first image.

[0058] In a specific implementation, a first shooting angle of the underwater shooting device can be determined, and a mapping relationship between a preset shooting angle and a feedback adjustment parameter can be pre-stored. Then, a first feedback adjustment parameter corresponding to the first shooting angle can be determined based on the mapping relationship, and then the first software shooting parameter is adjusted according to the first feedback adjustment parameter to obtain a second software shooting parameter. The first feedback adjustment parameter can perform feedback adjustment on part or all of the parameters in the first software shooting parameter. Finally, underwater shooting can be performed according to the second software shooting parameter and the first hardware shooting parameter to obtain a first image. Due to different shooting angles, the corresponding light refractive index and light reflectivity are different. Then, the corresponding first feedback adjustment parameter can be determined based on the shooting angle, thereby further compensating the first software shooting parameter so that the software shooting parameter is further adapted to the actual light environment. In this way, software shooting parameters corresponding to water quality and light are obtained, which helps to ensure the image shooting effect. In addition, at the hardware level, the performance of pressure and temperature compensation equipment (camera, underwater shooting equipment, etc.) can be used to improve the intelligence of underwater shooting. In this way, the intelligence of underwater shooting can be deeply improved.

[0059] Optionally, the above step of determining the first software shooting parameter according to the first water quality detection parameter and the first light detection parameter includes:

[0060] Determining a first software shooting parameter set corresponding to the first water quality detection parameter;

[0061] Determining a second software shooting parameter set corresponding to the first light detection parameter;

[0062] The first software shooting parameter is determined according to the first software shooting parameter set and the second software shooting parameter set.

[0063] The first software shooting parameter set may include at least one software shooting parameter, and the second software shooting parameter set may include at least one software shooting parameter.

[0064] In a specific implementation, the mapping relationship between the preset water quality detection parameters and the software shooting parameter set can be pre-stored, and then, the first software shooting parameter set corresponding to the first water quality detection parameter can be determined based on the mapping relationship. The mapping relationship between the preset light detection parameters and the software shooting parameter set can also be pre-stored, and then, the second software shooting parameter set corresponding to the first light detection parameter can be determined based on the mapping relationship.

[0065] Next, the first software shooting parameter can be determined based on the first software shooting parameter set and the second software shooting parameter set. For example, the union of the first software shooting parameter set and the second software shooting parameter set can be determined as the first software shooting parameter. For example, the water quality detection parameter determines part of the software shooting parameter, and the light detection parameter determines another part of the software shooting parameter. By merging the two parts of the software shooting parameter together, the software shooting parameter corresponding to the water quality and the light can be obtained, which helps to ensure the image shooting effect. For another example, the intersection of the first software shooting parameter set and the second software shooting parameter set can be determined as the first software shooting parameter. For example, the water quality detection parameter determines a software shooting parameter range, and the light detection parameter determines another software shooting parameter range. By taking the intersection of the two software shooting parameter ranges, the software shooting parameter corresponding to the water quality and the light can be obtained, which helps to ensure the image shooting effect.

[0066] Optionally, the above step 106, determining the first hardware shooting parameter according to the first pressure parameter and the first temperature parameter, may include the following steps:

[0067] determining a reference hardware shooting parameter corresponding to the first pressure parameter;

[0068] determining a first optimization parameter corresponding to the first temperature parameter;

[0069] The reference hardware shooting parameters are optimized according to the first optimization parameters to obtain the first hardware shooting parameters.

[0070] In a specific implementation, a mapping relationship between preset pressure parameters and hardware shooting parameters can be pre-stored, and then, a reference hardware shooting parameter corresponding to the first pressure parameter can be determined based on the mapping relationship. A mapping relationship between preset temperature parameters and optimization parameters can also be pre-stored, and then, a first optimization parameter corresponding to the first temperature parameter can be determined based on the mapping relationship. Finally, the reference hardware shooting parameter can be optimized according to the first optimization parameter to obtain the first hardware shooting parameter. That is, the performance of pressure and temperature compensation equipment (camera, underwater shooting equipment, etc.) can be used to improve the intelligence of underwater shooting to a certain extent.

[0071] Optionally, the following steps may also be included:

[0072] Performing image quality evaluation on the first image to obtain a first image quality evaluation value;

[0073] When the first image quality evaluation value is greater than a preset threshold, saving the first image;

[0074] When the first image quality evaluation value is less than or equal to the preset threshold, determining a first high-frequency component and a first low-frequency component of the first image;

[0075] Determining a feature point distribution density threshold corresponding to the first light detection parameter;

[0076] Determining an energy threshold corresponding to the first water quality detection parameter;

[0077] Determine a first feature point distribution density corresponding to the first high-frequency component, and determine a first energy value corresponding to the first low-frequency component;

[0078] Perform image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and save the second image.

[0079] In a specific implementation, at least one image quality evaluation index can be used to evaluate the image quality of the first image to obtain a first image quality evaluation value. Specifically, the image quality evaluation index may include at least one of the following: clarity, average gradient, information entropy, signal-to-noise ratio, etc., which are not limited here. When at least one image quality evaluation index is used to evaluate the image quality of the first image, at least one image quality evaluation value can be obtained. Each image quality evaluation index corresponds to an image quality evaluation value and a weight. The sum of the weights corresponding to at least one image quality evaluation index is. At least one image quality evaluation value can be weighted to obtain a first image quality evaluation value.

[0080] The preset threshold value may be preset or set by system default.

[0081] In a specific implementation, when the first image quality evaluation value is greater than a preset threshold, it indicates that the first image quality is good, and the first image can be saved. Conversely, when the first image quality evaluation value is less than or equal to the preset threshold, the first high-frequency component and the first low-frequency component of the first image can be determined, that is, the first image can be decomposed by a multi-scale decomposition method to obtain the first high-frequency component and the first low-frequency component, wherein the first high-frequency component reflects the image details, and the first low-frequency component reflects the image body. The multi-scale decomposition method may include at least one of the following: a Gaussian pyramid transform algorithm, a contourlet transform algorithm, a non-subsampled contourlet transform algorithm, a wavelet transform algorithm, etc., which are not limited here.

[0082] Next, the mapping relationship between the preset light detection parameters and the characteristic point distribution density threshold can be pre-stored, and then, the characteristic point distribution density threshold corresponding to the first light detection parameter can be determined based on the mapping relationship, and the mapping relationship between the preset water quality detection parameters and the energy threshold can be pre-stored, that is, the energy threshold corresponding to the first water quality detection parameter can be determined based on the mapping relationship.

[0083] In a specific implementation, feature extraction can be performed on the first high-frequency component to obtain multiple features, the number of features of the multiple features can be counted, and the area of ​​the first high-frequency component can be determined. The first feature point distribution density can then be determined based on the number of features and the area, that is, the first feature point distribution density = number of features / area. The first energy value corresponding to the first low-frequency component can also be determined.

[0084] Next, the first image is enhanced according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and the second image is saved. Since the influence of light on the high-frequency part is dominant, and the influence of water quality on the low-frequency part is dominant, the feature point distribution density threshold reflects the influence of light on the high-frequency part to a certain extent, and the energy threshold reflects the influence of water quality on the low-frequency part to a certain extent. Therefore, based on the actual image situation, the low-frequency part and / or the high-frequency part of the image can be targetedly enhanced so that the depth of the enhancement effect conforms to the actual situation, thereby improving the underwater image shooting quality and improving the user experience.

[0085] Optionally, the above step of performing image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image and saving the second image may include the following steps:

[0086] When the first feature point distribution density is greater than or equal to the feature point distribution density threshold and the first energy value is less than the energy threshold, performing a first image enhancement process on the first low-frequency component to obtain a second low-frequency component, and reconstructing the first high-frequency component and the second low-frequency component to obtain the second image;

[0087] or,

[0088] When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is greater than or equal to the energy threshold, performing a second image enhancement process on the first high-frequency component to obtain a second high-frequency component, and reconstructing the second high-frequency component and the first low-frequency component to obtain the second image;

[0089] or,

[0090] When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is less than the energy threshold, the first high-frequency component is subjected to a third image enhancement process to obtain a third high-frequency component, the first low-frequency component is subjected to a fourth image enhancement process to obtain a third low-frequency component, and the third high-frequency component and the third low-frequency component are reconstructed to obtain the second image.

[0091] In a specific implementation, when the first feature point distribution density is greater than or equal to the feature point distribution density threshold and the first energy value is less than the energy threshold, it means that the high-frequency part has good quality, but the main body of the image is poor. Therefore, the first low-frequency component can be subjected to a first image enhancement process to obtain a second low-frequency component, and the first high-frequency component and the second low-frequency component are reconstructed to obtain a second image. Since the influence of light on the high-frequency part is dominant, and the influence of water quality on the low-frequency part is dominant, the feature point distribution density threshold reflects the influence of light on the high-frequency part to a certain extent, and the energy threshold reflects the influence of water quality on the low-frequency part to a certain extent. Furthermore, the low-frequency part of the image can be targetedly enhanced based on the actual image situation, so that the depth of the enhancement effect conforms to the actual situation, thereby improving the underwater image shooting quality and improving the user experience.

[0092] In a specific implementation, when the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is greater than or equal to the energy threshold, it means that the quality of the high-frequency part is poor, but the main body of the image is good. Therefore, the first high-frequency component can be subjected to a second image enhancement process to obtain a second high-frequency component, and the second high-frequency component and the first low-frequency component are reconstructed to obtain a second image. Since the influence of light on the high-frequency part is dominant, and the influence of water quality on the low-frequency part is dominant, the feature point distribution density threshold reflects the influence of light on the high-frequency part to a certain extent, and the energy threshold reflects the influence of water quality on the low-frequency part to a certain extent. Furthermore, the high-frequency part of the image can be targetedly enhanced based on the actual image situation, so that the depth of the enhancement effect conforms to the actual situation, thereby improving the quality of underwater image shooting and improving user experience.

[0093] In a specific implementation, when the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is less than the energy threshold, it means that the quality of the high-frequency part is poor and the main body of the image is poor. Then, the first high-frequency component can be subjected to a third image enhancement process to obtain a third high-frequency component, and the first low-frequency component can be subjected to a fourth image enhancement process to obtain a third low-frequency component. The third high-frequency component and the third low-frequency component are reconstructed to obtain a second image. Since the influence of light on the high-frequency part is dominant and the influence of water quality on the low-frequency part is dominant, the feature point distribution density threshold reflects the influence of light on the high-frequency part to a certain extent, and the energy threshold reflects the influence of water quality on the low-frequency part to a certain extent. Furthermore, the low-frequency part and the high-frequency part of the image can be targetedly enhanced based on the actual image situation, so that the depth of the enhancement effect conforms to the actual situation, thereby improving the underwater image shooting quality and improving the user experience.

[0094] Optionally, performing a first image enhancement process on the first low-frequency component to obtain a second low-frequency component includes:

[0095] Determine a first image enhancement algorithm corresponding to the first water quality detection parameter, and obtain a first default algorithm control parameter corresponding to the first image enhancement algorithm;

[0096] determining a first deviation between the first energy value and the energy threshold;

[0097] determining a first adjustment parameter corresponding to the first deviation;

[0098] Adjust the first default algorithm control parameter according to the first adjustment parameter to obtain a first algorithm control parameter;

[0099] The first low-frequency component is enhanced according to the first image enhancement algorithm and the first algorithm control parameter to obtain the second low-frequency component.

[0100] In a specific implementation, a mapping relationship between preset water quality detection parameters and image enhancement algorithms can be pre-stored, and then, a first image enhancement algorithm corresponding to the first water quality detection parameter can be determined based on the mapping relationship. A first default algorithm control parameter corresponding to the first image enhancement algorithm can also be obtained. The first default algorithm control parameter can be used to control the image enhancement effect of the first image enhancement algorithm, and specifically may include at least one of the following: image enhancement speed, image enhancement area, image enhancement method, image enhancement degree, etc., which are not limited here.

[0101] Furthermore, a first deviation between the first energy value and the energy threshold can be determined, that is, the first deviation = (first energy value-energy threshold) / energy threshold, and a first mapping relationship between a preset deviation and an adjustment parameter can be pre-stored, that is, a first adjustment parameter corresponding to the first deviation can be determined based on the first mapping relationship, and then the first default algorithm control parameter is adjusted according to the first adjustment parameter to obtain the first algorithm control parameter. The first adjustment parameter can adjust part or all of the parameters of the first default algorithm control parameter, for example, the first algorithm control parameter = (1+first adjustment parameter)*first default algorithm control parameter. Finally, the first low-frequency component can be enhanced according to the first image enhancement algorithm and the first algorithm control parameter to obtain the second low-frequency component. On the one hand, the influence of water quality on the low-frequency part is dominant, and an image enhancement algorithm corresponding to the actual water quality can be determined. The algorithm control parameter can also be dynamically adjusted based on the difference between the actual energy of the low-frequency part and the energy threshold, so that the enhancement effect better meets the energy threshold. Then, the low-frequency part of the image is targetedly enhanced based on the actual image situation, so that the depth of the enhancement effect conforms to the actual situation, thereby improving the underwater image shooting quality and improving the user experience.

[0102] Optionally, the above step of performing a second image enhancement process on the first high-frequency component to obtain a second high-frequency component may include the following steps:

[0103] Determine a second image enhancement algorithm corresponding to the first light detection parameter, and obtain a second default algorithm control parameter corresponding to the second image enhancement algorithm;

[0104] Determining a second deviation between the first feature point distribution density and the feature point distribution density threshold;

[0105] determining a second adjustment parameter corresponding to the second deviation;

[0106] Adjust the second default algorithm control parameter according to the second adjustment parameter to obtain a second algorithm control parameter;

[0107] The first high-frequency component is enhanced according to the second image enhancement algorithm and the second algorithm control parameter to obtain the second high-frequency component.

[0108] In a specific implementation, the mapping relationship between the preset light detection parameters and the image enhancement algorithm can be pre-stored, and then, the second image enhancement algorithm corresponding to the first light detection parameters can be determined based on the mapping relationship. Accordingly, the second default algorithm control parameters corresponding to the second image enhancement algorithm can also be obtained. The second default algorithm control parameters can be used to control the image enhancement effect of the second image enhancement algorithm, and specifically may include at least one of the following: image enhancement speed, image enhancement area, image enhancement method, image enhancement degree, etc., which are not limited here.

[0109] Next, a second deviation between the first feature point distribution density and the feature point distribution density threshold can also be determined, that is, the second deviation = (first feature point distribution density - feature point distribution density threshold) / feature point distribution density threshold, and a second mapping relationship between a preset deviation and an adjustment parameter can be pre-stored, that is, a second adjustment parameter corresponding to the second deviation can be determined based on the second mapping relationship, and then the second default algorithm control parameter is adjusted according to the second adjustment parameter to obtain the second algorithm control parameter. The second adjustment parameter can adjust part or all of the parameters of the second default algorithm control parameter, for example, the second algorithm control parameter = (1 + second Adjustment parameters)*second default algorithm control parameters. Finally, the first high-frequency component can be enhanced according to the second image enhancement algorithm and the second algorithm control parameters to obtain the second high-frequency component. On the one hand, the influence of light on the high-frequency part is dominant, and the image enhancement algorithm corresponding to the actual light can be determined. The algorithm control parameters can also be dynamically adjusted based on the difference between the first feature point distribution density of the high-frequency part and the feature point distribution density threshold, so that the enhancement effect better meets the energy threshold. Furthermore, based on the actual image situation, the low-frequency part of the image is targetedly enhanced, so that the depth of the enhancement effect conforms to the actual situation, thereby improving the underwater image shooting quality and improving the user experience.

[0110] Optionally, the following steps may also be included:

[0111] Determining a first threshold value corresponding to the first water quality detection parameter;

[0112] determining a first influencing parameter corresponding to the first light detection parameter;

[0113] The preset threshold is determined according to the first influencing parameter and the first threshold.

[0114] In a specific implementation, a mapping relationship between preset water quality detection parameters and thresholds can be pre-stored, and then, a first threshold corresponding to a first water quality detection parameter can be determined based on the mapping relationship. A mapping relationship between preset light detection parameters and influencing parameters can also be pre-stored, and then, a first influencing parameter corresponding to the first light detection parameter can be determined based on the mapping relationship. Then, the preset threshold can be determined based on the first influencing parameter and the first threshold, that is, the preset threshold = (1 + first influencing parameter) * first threshold. That is, not only can the threshold corresponding to the water quality be determined, but the threshold can also be dynamically optimized considering the influence of light, so that the final preset threshold depth conforms to the actual situation, which helps to ensure the accuracy of underwater images, as well as improve the quality of underwater image shooting and enhance user experience.

[0115] It can be seen that the image processing method for underwater images described in the embodiment of the present application is applied to underwater shooting equipment, and the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. When the underwater shooting equipment is located underwater, a first water quality detection parameter is obtained through the water quality detection sensor, a first light detection parameter is obtained through the light detection sensor, a first pressure parameter is obtained through the pressure sensor, and a first temperature parameter is obtained through the temperature sensor. A first software shooting parameter is determined according to the first water quality detection parameter and the first light detection parameter, and a first hardware shooting parameter is determined according to the first pressure parameter and the first temperature parameter. Underwater shooting is performed according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image. On the one hand, at the algorithm level, software shooting parameters corresponding to water quality and light can be obtained, which helps to ensure the image shooting effect. On the other hand, at the hardware level, the performance of pressure and temperature compensation equipment (camera, underwater shooting equipment, etc.) can be used to improve the intelligence of underwater shooting. In this way, the intelligence of underwater shooting can be deeply improved.

[0116] In accordance with the above embodiment, please refer to Figure 2 , Figure 2 : is a structural schematic diagram of an underwater shooting device provided in an embodiment of the present application. As shown in the figure, the underwater shooting device includes a processor, a memory, a communication interface and one or more programs. The one or more programs are stored in the memory and are configured to be executed by the processor. In the embodiment of the present application, the underwater shooting device includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. The program includes instructions for executing the following steps:

[0117] When the underwater shooting device is located underwater, obtaining a first water quality detection parameter through the water quality detection sensor;

[0118] Acquiring a first light detection parameter through the light detection sensor;

[0119] Acquiring a first pressure parameter through the pressure sensor;

[0120] Acquiring a first temperature parameter through the temperature sensor;

[0121] Determine a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter;

[0122] determining a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter;

[0123] Underwater shooting is performed according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image.

[0124] Optionally, in the aspect of performing underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain the first image, the program includes instructions for executing the following steps:

[0125] Determining a first shooting angle of the underwater shooting device;

[0126] Determining a first feedback adjustment parameter corresponding to the first shooting angle;

[0127] adjusting the first software shooting parameter according to the first feedback parameter to obtain a second software shooting parameter;

[0128] Underwater shooting is performed according to the second software shooting parameter and the first hardware shooting parameter to obtain the first image.

[0129] Optionally, in determining the first software shooting parameter according to the first water quality detection parameter and the first light detection parameter, the program includes instructions for executing the following steps:

[0130] Determining a first software shooting parameter set corresponding to the first water quality detection parameter;

[0131] Determining a second software shooting parameter set corresponding to the first light detection parameter;

[0132] The first software shooting parameter is determined according to the first software shooting parameter set and the second software shooting parameter set.

[0133] Optionally, in determining the first hardware shooting parameter according to the first pressure parameter and the first temperature parameter, the program includes instructions for executing the following steps:

[0134] determining a reference hardware shooting parameter corresponding to the first pressure parameter;

[0135] determining a first optimization parameter corresponding to the first temperature parameter;

[0136] The reference hardware shooting parameters are optimized according to the first optimization parameters to obtain the first hardware shooting parameters.

[0137] Optionally, the program further includes instructions for executing the following steps:

[0138] Performing image quality evaluation on the first image to obtain a first image quality evaluation value;

[0139] When the first image quality evaluation value is greater than a preset threshold, saving the first image;

[0140] When the first image quality evaluation value is less than or equal to the preset threshold, determining a first high-frequency component and a first low-frequency component of the first image;

[0141] Determining a feature point distribution density threshold corresponding to the first light detection parameter;

[0142] Determining an energy threshold corresponding to the first water quality detection parameter;

[0143] Determine a first feature point distribution density corresponding to the first high-frequency component, and determine a first energy value corresponding to the first low-frequency component;

[0144] Perform image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and save the second image.

[0145] Optionally, in the aspect of performing image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and saving the second image, the program includes instructions for executing the following steps:

[0146] When the first feature point distribution density is greater than or equal to the feature point distribution density threshold and the first energy value is less than the energy threshold, performing a first image enhancement process on the first low-frequency component to obtain a second low-frequency component, and reconstructing the first high-frequency component and the second low-frequency component to obtain the second image;

[0147] or,

[0148] When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is greater than or equal to the energy threshold, performing a second image enhancement process on the first high-frequency component to obtain a second high-frequency component, and reconstructing the second high-frequency component and the first low-frequency component to obtain the second image;

[0149] or,

[0150] When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is less than the energy threshold, the first high-frequency component is subjected to a third image enhancement process to obtain a third high-frequency component, the first low-frequency component is subjected to a fourth image enhancement process to obtain a third low-frequency component, and the third high-frequency component and the third low-frequency component are reconstructed to obtain the second image.

[0151] Optionally, in the aspect of performing a first image enhancement process on the first low-frequency component to obtain a second low-frequency component, the program includes instructions for executing the following steps:

[0152] Determine a first image enhancement algorithm corresponding to the first water quality detection parameter, and obtain a first default algorithm control parameter corresponding to the first image enhancement algorithm;

[0153] determining a first deviation between the first energy value and the energy threshold;

[0154] determining a first adjustment parameter corresponding to the first deviation;

[0155] Adjust the first default algorithm control parameter according to the first adjustment parameter to obtain a first algorithm control parameter;

[0156] The first low-frequency component is enhanced according to the first image enhancement algorithm and the first algorithm control parameter to obtain the second low-frequency component.

[0157] Optionally, in the aspect of performing a second image enhancement process on the first high-frequency component to obtain a second high-frequency component, the program includes instructions for executing the following steps:

[0158] Determine a second image enhancement algorithm corresponding to the first light detection parameter, and obtain a second default algorithm control parameter corresponding to the second image enhancement algorithm;

[0159] Determining a second deviation between the first feature point distribution density and the feature point distribution density threshold;

[0160] determining a second adjustment parameter corresponding to the second deviation;

[0161] Adjust the second default algorithm control parameter according to the second adjustment parameter to obtain a second algorithm control parameter;

[0162] The first high-frequency component is enhanced according to the second image enhancement algorithm and the second algorithm control parameter to obtain the second high-frequency component.

[0163] Optionally, the program further includes instructions for executing the following steps:

[0164] Determining a first threshold value corresponding to the first water quality detection parameter;

[0165] determining a first influencing parameter corresponding to the first light detection parameter;

[0166] The preset threshold is determined according to the first influencing parameter and the first threshold.

[0167] It can be seen that the underwater shooting equipment described in the embodiment of the present application includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. When the underwater shooting equipment is located underwater, a first water quality detection parameter is obtained through the water quality detection sensor, a first light detection parameter is obtained through the light detection sensor, a first pressure parameter is obtained through the pressure sensor, and a first temperature parameter is obtained through the temperature sensor. A first software shooting parameter is determined according to the first water quality detection parameter and the first light detection parameter, and a first hardware shooting parameter is determined according to the first pressure parameter and the first temperature parameter. Underwater shooting is performed according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image. On the one hand, at the algorithm level, software shooting parameters corresponding to water quality and light can be obtained, which helps to ensure the image shooting effect. On the other hand, at the hardware level, the performance of pressure and temperature compensation equipment (camera, underwater shooting equipment, etc.) can be used to improve the intelligence of underwater shooting. In this way, the intelligence of underwater shooting can be deeply improved.

[0168] Figure 3 1 is a functional unit block diagram of an image processing device 300 for underwater images involved in an embodiment of the present application. The image processing device 300 for underwater images is applied to underwater shooting equipment, and the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. The image processing device 300 for underwater images includes:

[0169] The acquisition unit 301 is used to acquire a first water quality detection parameter through the water quality detection sensor; acquire a first light detection parameter through the light detection sensor; acquire a first pressure parameter through the pressure sensor; and acquire a first temperature parameter through the temperature sensor when the underwater shooting device is underwater.

[0170] A determination unit 302 is used to determine a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter; and to determine a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter;

[0171] The shooting unit 303 is used to perform underwater shooting according to the first software shooting parameters and the first hardware shooting parameters to obtain a first image.

[0172] Optionally, in the aspect of performing underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain the first image, the shooting unit 303 is specifically used for:

[0173] Determining a first shooting angle of the underwater shooting device;

[0174] Determining a first feedback adjustment parameter corresponding to the first shooting angle;

[0175] adjusting the first software shooting parameter according to the first feedback parameter to obtain a second software shooting parameter;

[0176] Underwater shooting is performed according to the second software shooting parameter and the first hardware shooting parameter to obtain the first image.

[0177] Optionally, in determining the first software shooting parameter according to the first water quality detection parameter and the first light detection parameter, the determining unit 302 is specifically used to:

[0178] Determining a first software shooting parameter set corresponding to the first water quality detection parameter;

[0179] Determining a second software shooting parameter set corresponding to the first light detection parameter;

[0180] The first software shooting parameter is determined according to the first software shooting parameter set and the second software shooting parameter set.

[0181] Optionally, in determining the first hardware shooting parameter according to the first pressure parameter and the first temperature parameter, the determining unit 302 is specifically configured to:

[0182] determining a reference hardware shooting parameter corresponding to the first pressure parameter;

[0183] determining a first optimization parameter corresponding to the first temperature parameter;

[0184] The reference hardware shooting parameters are optimized according to the first optimization parameters to obtain the first hardware shooting parameters.

[0185] Optionally, the image processing device 300 for underwater images is further specifically used for:

[0186] Performing image quality evaluation on the first image to obtain a first image quality evaluation value;

[0187] When the first image quality evaluation value is greater than a preset threshold, saving the first image;

[0188] When the first image quality evaluation value is less than or equal to the preset threshold, determining a first high-frequency component and a first low-frequency component of the first image;

[0189] Determining a feature point distribution density threshold corresponding to the first light detection parameter;

[0190] Determining an energy threshold corresponding to the first water quality detection parameter;

[0191] Determine a first feature point distribution density corresponding to the first high-frequency component, and determine a first energy value corresponding to the first low-frequency component;

[0192] Perform image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and save the second image.

[0193] Optionally, in the aspect of performing image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and saving the second image, the image processing device 300 for underwater images is specifically used for:

[0194] When the first feature point distribution density is greater than or equal to the feature point distribution density threshold and the first energy value is less than the energy threshold, performing a first image enhancement process on the first low-frequency component to obtain a second low-frequency component, and reconstructing the first high-frequency component and the second low-frequency component to obtain the second image;

[0195] or,

[0196] When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is greater than or equal to the energy threshold, performing a second image enhancement process on the first high-frequency component to obtain a second high-frequency component, and reconstructing the second high-frequency component and the first low-frequency component to obtain the second image;

[0197] or,

[0198] When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is less than the energy threshold, the first high-frequency component is subjected to a third image enhancement process to obtain a third high-frequency component, the first low-frequency component is subjected to a fourth image enhancement process to obtain a third low-frequency component, and the third high-frequency component and the third low-frequency component are reconstructed to obtain the second image.

[0199] Optionally, in the aspect of performing the first image enhancement processing on the first low-frequency component to obtain the second low-frequency component, the image processing device 300 for underwater images is specifically used for:

[0200] Determine a first image enhancement algorithm corresponding to the first water quality detection parameter, and obtain a first default algorithm control parameter corresponding to the first image enhancement algorithm;

[0201] determining a first deviation between the first energy value and the energy threshold;

[0202] determining a first adjustment parameter corresponding to the first deviation;

[0203] Adjust the first default algorithm control parameter according to the first adjustment parameter to obtain a first algorithm control parameter;

[0204] The first low-frequency component is enhanced according to the first image enhancement algorithm and the first algorithm control parameter to obtain the second low-frequency component.

[0205] Optionally, in the aspect of performing the second image enhancement processing on the first high-frequency component to obtain the second high-frequency component, the image processing device 300 for underwater images is specifically used for:

[0206] Determine a second image enhancement algorithm corresponding to the first light detection parameter, and obtain a second default algorithm control parameter corresponding to the second image enhancement algorithm;

[0207] Determining a second deviation between the first feature point distribution density and the feature point distribution density threshold;

[0208] determining a second adjustment parameter corresponding to the second deviation;

[0209] Adjust the second default algorithm control parameter according to the second adjustment parameter to obtain a second algorithm control parameter;

[0210] The first high-frequency component is enhanced according to the second image enhancement algorithm and the second algorithm control parameter to obtain the second high-frequency component.

[0211] Optionally, the image processing device 300 for underwater images is further specifically used for:

[0212] Determining a first threshold value corresponding to the first water quality detection parameter;

[0213] determining a first influencing parameter corresponding to the first light detection parameter;

[0214] The preset threshold is determined according to the first influencing parameter and the first threshold.

[0215] It can be seen that the image processing device, device and storage medium for underwater images described in the embodiments of the present application are applied to underwater shooting equipment, and the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor. When the underwater shooting equipment is located underwater, a first water quality detection parameter is obtained through the water quality detection sensor, a first light detection parameter is obtained through the light detection sensor, a first pressure parameter is obtained through the pressure sensor, and a first temperature parameter is obtained through the temperature sensor. A first software shooting parameter is determined according to the first water quality detection parameter and the first light detection parameter, and a first hardware shooting parameter is determined according to the first pressure parameter and the first temperature parameter. Underwater shooting is performed according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image. On the one hand, at the algorithm level, software shooting parameters corresponding to water quality and light can be obtained, which helps to ensure the image shooting effect. On the other hand, at the hardware level, the performance of pressure and temperature compensation equipment (camera, underwater shooting equipment, etc.) can be used to improve the intelligence of underwater shooting. In this way, the intelligence of underwater shooting can be deeply improved.

[0216] It can be understood that the functions of each program module of the image processing device for underwater images in this embodiment can be specifically implemented according to the method in the above method embodiment, and its specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0217] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments, and the above computer includes an underwater shooting device.

[0218] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an underwater shooting device.

[0219] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0220] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0221] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0222] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0223] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0224] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0225] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0226] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An image processing method for underwater images, characterized in that: Applied to underwater shooting equipment, the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor, and the method includes: When the underwater shooting device is located underwater, obtaining a first water quality detection parameter through the water quality detection sensor; Acquiring a first light detection parameter through the light detection sensor; Acquiring a first pressure parameter through the pressure sensor; Acquiring a first temperature parameter through the temperature sensor; Determine a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter; determining a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter; Underwater shooting is performed according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image.

2. The method according to claim 1, characterized in that: The step of performing underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image includes: Determining a first shooting angle of the underwater shooting device; Determining a first feedback adjustment parameter corresponding to the first shooting angle; adjusting the first software shooting parameter according to the first feedback parameter to obtain a second software shooting parameter; Underwater shooting is performed according to the second software shooting parameter and the first hardware shooting parameter to obtain the first image.

3. The method according to claim 1 or 2, characterized in that: The determining the first software shooting parameter according to the first water quality detection parameter and the first light detection parameter includes: Determining a first software shooting parameter set corresponding to the first water quality detection parameter; Determining a second software shooting parameter set corresponding to the first light detection parameter; The first software shooting parameter is determined according to the first software shooting parameter set and the second software shooting parameter set.

4. The method according to claim 1 or 2, characterized in that: The determining the first hardware shooting parameter according to the first pressure parameter and the first temperature parameter includes: determining a reference hardware shooting parameter corresponding to the first pressure parameter; determining a first optimization parameter corresponding to the first temperature parameter; The reference hardware shooting parameters are optimized according to the first optimization parameters to obtain the first hardware shooting parameters.

5. The method according to claim 1 or 2, characterized in that: The method further comprises: Performing image quality evaluation on the first image to obtain a first image quality evaluation value; When the first image quality evaluation value is greater than a preset threshold, saving the first image; When the first image quality evaluation value is less than or equal to the preset threshold, determining a first high-frequency component and a first low-frequency component of the first image; Determining a feature point distribution density threshold corresponding to the first light detection parameter; Determining an energy threshold corresponding to the first water quality detection parameter; Determine a first feature point distribution density corresponding to the first high-frequency component, and determine a first energy value corresponding to the first low-frequency component; Perform image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and save the second image.

6. The method according to claim 5, characterized in that The performing image enhancement processing on the first image according to the feature point distribution density threshold, the energy threshold, the first feature point distribution density and the first energy value to obtain a second image, and saving the second image comprises: When the first feature point distribution density is greater than or equal to the feature point distribution density threshold and the first energy value is less than the energy threshold, performing a first image enhancement process on the first low-frequency component to obtain a second low-frequency component, and reconstructing the first high-frequency component and the second low-frequency component to obtain the second image; or, When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is greater than or equal to the energy threshold, performing a second image enhancement process on the first high-frequency component to obtain a second high-frequency component, and reconstructing the second high-frequency component and the first low-frequency component to obtain the second image; or, When the first feature point distribution density is less than the feature point distribution density threshold and the first energy value is less than the energy threshold, the first high-frequency component is subjected to a third image enhancement process to obtain a third high-frequency component, the first low-frequency component is subjected to a fourth image enhancement process to obtain a third low-frequency component, and the third high-frequency component and the third low-frequency component are reconstructed to obtain the second image.

7. The method according to claim 6, characterized in that The performing a first image enhancement process on the first low-frequency component to obtain a second low-frequency component includes: Determine a first image enhancement algorithm corresponding to the first water quality detection parameter, and obtain a first default algorithm control parameter corresponding to the first image enhancement algorithm; determining a first deviation between the first energy value and the energy threshold; determining a first adjustment parameter corresponding to the first deviation; Adjust the first default algorithm control parameter according to the first adjustment parameter to obtain a first algorithm control parameter; The first low-frequency component is enhanced according to the first image enhancement algorithm and the first algorithm control parameter to obtain the second low-frequency component.

8. An image processing device for underwater images, characterized in that: Applied to underwater shooting equipment, the underwater shooting equipment includes: a water quality detection sensor, a light detection sensor, a pressure sensor, and a temperature sensor, and the device includes: an acquisition unit, configured to acquire, when the underwater photographing device is underwater, a first water quality detection parameter through the water quality detection sensor; a first light detection parameter through the light detection sensor; a first pressure parameter through the pressure sensor; and a first temperature parameter through the temperature sensor; a determining unit, configured to determine a first software shooting parameter according to the first water quality detection parameter and the first light detection parameter; and determine a first hardware shooting parameter according to the first pressure parameter and the first temperature parameter; A shooting unit is used to perform underwater shooting according to the first software shooting parameter and the first hardware shooting parameter to obtain a first image.

9. An underwater shooting device, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

Images