Underwater acoustic image optimization display method and system

Abstract

The invention provides an underwater acoustic image optimization display method and system, electronic equipment and a storage medium. The method comprises the following steps: converting the intensity of a received echo signal into gray values by using a cumulative distribution function, calculating distribution functions of different gray values, and mapping the gray values of the small part of the distribution functions to a new gray level through the cumulative distribution function. The cumulative distribution function redistributes the original concentrated gray values, so that the gray range of the whole image is more uniform. The contrast of the image is enhanced. And finally, according to the gray level around the pixel point, calculating a mean value, then when the variance is smaller than a certain index, replacing the gray level of the point with the mean value, and finally realizing denoising to obtain an optimized image. According to the scheme provided by the invention, the contrast of the image can be effectively improved, so that the details of the image are fuller; and aiming at the characteristics of the underwater image, the noise can be effectively removed, and other subsequent image processing is easier to carry out.

Description

Technical Field

[0001] The present invention belongs to the technical field of underwater acoustic image processing, and in particular relates to an underwater acoustic image optimization display method, system, electronic equipment and storage medium. Background Art

[0002] Underwater acoustic images are images generated by sonar equipment emitting sound waves and receiving echo signals. They are widely used in underwater detection, marine surveying, underwater archaeology and other fields. However, due to the complexity of the underwater environment, acoustic images are affected by many factors during the imaging process, resulting in poor quality. Various noises in the underwater environment (such as background noise and scattered noise) will cause noise spots to appear in the acoustic image, affecting the clarity and contrast of the image.

[0003] At the same time, when sound waves propagate in water, they are affected by reflection and refraction, which may produce multiple propagation paths, resulting in ghosting or blurring of the image. In addition, the energy loss of sound waves when propagating in water will cause the intensity of the echo signal to attenuate, especially the signal of distant targets becomes weak, which limits the dynamic range of the image. Due to the long wavelength of sound waves, the spatial resolution of acoustic images is lower than that of optical imaging, and the details are more difficult to distinguish. These factors cause underwater acoustic images to usually have problems such as low contrast, high noise, and blurred details. Therefore, how to optimize the display of underwater acoustic images to improve their visual effects and information quality has become an important research topic. Traditional optimization display methods mainly include image enhancement, noise removal, contrast adjustment and other technologies to improve the clarity and detail presentation of images. However, for underwater acoustic images, these methods have relatively single effects in processing images and cannot adapt well to the influence of factors such as underwater acoustic environment.

[0004] Therefore, how to provide an underwater acoustic image optimization display method, system, electronic device and storage medium has become a technical problem that urgently needs to be solved in this field. Summary of the invention

[0005] The purpose of the present invention is to provide an underwater acoustic image optimization display method, system, electronic equipment and storage medium.

[0006] According to a first aspect of the present invention, there is provided an underwater acoustic image optimization display, comprising:

[0007] Step S1, drawing a grayscale image according to the received echo signal; and obtaining the probability of each grayscale level according to the original grayscale value in the grayscale image;

[0008] Step S2, merging the pixel levels whose gray level probability is less than 0.1 with the gray level of the next higher level to obtain a new gray level and its probability;

[0009] Step S3, obtaining a cumulative distribution function according to the new gray level probability; mapping the original gray value to the new gray value according to the cumulative distribution function;

[0010] Step S4, replacing the original grayscale value of the grayscale image with the new grayscale value to obtain a new grayscale image; in the new grayscale image, calculating the variance of the grayscale points according to the mean of the grayscale levels in a predefined neighborhood;

[0011] Step S5: When the variance is less than a preset value, the grayscale level of the grayscale point in the new grayscale image is replaced by the mean value, and finally an optimized image is obtained.

[0012] According to the method of the first aspect of the present invention, in step S1, obtaining the probability of each gray level according to the original gray value in the gray image includes:

[0013] The distribution of the original grayscale values ​​in the grayscale image is calculated and normalized to obtain the probability of each grayscale level.

[0014] According to the method of the first aspect of the present invention, in step S2, obtaining the cumulative distribution function according to the new gray level probability includes:

[0015] Calculate the cumulative probability from the new gray level 0 to a certain gray level of the new gray level;

[0016] According to the cumulative probability, a cumulative distribution function is obtained.

[0017] According to the method of the first aspect of the present invention, in step S3, mapping the original grayscale value to the new grayscale value according to the cumulative distribution function comprises:

[0018] According to the cumulative distribution function and the total number of new gray levels, a gray value after equalization is calculated for each original gray value to obtain a new gray value.

[0019] The second aspect of the present invention discloses an underwater acoustic image optimization display system; the system comprises:

[0020] The first processing module is configured to draw a grayscale image according to the received echo signal; and obtain the probability of each grayscale level according to the original grayscale value in the grayscale image;

[0021] The second processing module is configured to merge the pixel levels with gray level probabilities less than 0.1 with the gray level of the next higher level to obtain a new gray level and its probability;

[0022] A third processing module is configured to obtain a cumulative distribution function according to the new gray level probability; and map the original gray value to the new gray value according to the cumulative distribution function;

[0023] The fourth processing module is configured to replace the original grayscale value of the grayscale image with the new grayscale value to obtain a new grayscale image; in the new grayscale image, calculate the variance of the grayscale point according to the mean of the grayscale level in the predefined neighborhood;

[0024] The fifth processing module is configured to replace the grayscale of the grayscale point in the new grayscale image with the mean value when the variance is less than a preset value, so as to finally obtain an optimized image.

[0025] According to the system of the second aspect of the present invention, the first processing module is specifically configured as follows: obtaining the probability of each gray level according to the original gray value in the gray map includes:

[0026] The distribution of the original grayscale values ​​in the grayscale image is calculated and normalized to obtain the probability of each grayscale level.

[0027] According to the system of the second aspect of the present invention, the second processing module is specifically configured as follows: obtaining the cumulative distribution function according to the new gray level probability comprises:

[0028] Calculate the cumulative probability from the new gray level 0 to a certain gray level of the new gray level;

[0029] According to the cumulative probability, a cumulative distribution function is obtained.

[0030] According to the system of the second aspect of the present invention, the third processing module is specifically configured as follows: mapping the original grayscale value to the new grayscale value according to the cumulative distribution function comprises:

[0031] According to the cumulative distribution function and the total number of new gray levels, a gray value after equalization is calculated for each original gray value to obtain a new gray value.

[0032] The third aspect of the present invention discloses an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods for optimizing the display of underwater acoustic images in the first aspect of the present disclosure are implemented.

[0033] The fourth aspect of the present invention discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any one of the underwater acoustic image optimization display methods in the first aspect of the present disclosure are implemented.

[0034] The beneficial effects brought by the present invention are as follows:

[0035] It can be seen from the above scheme that the embodiments of the present invention provide an underwater acoustic image optimization display method, system, electronic device and storage medium, which have the following beneficial effects: it can effectively improve the contrast of the image and make the image details appear fuller; according to the characteristics of underwater images, it can effectively remove noise and make it easier to perform subsequent other image processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flowchart of a method for optimizing display of underwater acoustic images provided according to an embodiment;

[0037] Figure 2 A structural diagram of an underwater acoustic image optimization display system according to an embodiment of the present invention;

[0038] Figure 3 The figure is a structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Embodiment 1:

[0041] According to a first aspect of the present invention, the present invention discloses a method for optimizing the display of underwater acoustic images. Figure 1 FIG. 4 is a flow chart of a method for optimizing display of underwater acoustic images according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0042] Step S1, drawing a grayscale image according to the received echo signal; and obtaining the probability of each grayscale level according to the original grayscale value in the grayscale image;

[0043] Step S2, merging the pixel levels whose gray level probability is less than 0.1 with the gray level of the next higher level to obtain a new gray level and its probability;

[0044] Step S3, obtaining a cumulative distribution function according to the new gray level probability; mapping the original gray value to the new gray value according to the cumulative distribution function;

[0045] Step S4, replacing the original grayscale value of the grayscale image with the new grayscale value to obtain a new grayscale image; in the new grayscale image, calculating the variance of the grayscale points according to the mean of the grayscale levels in a predefined neighborhood;

[0046] Step S5: When the variance is less than a preset value, the grayscale level of the grayscale point in the new grayscale image is replaced by the mean value, and finally an optimized image is obtained.

[0047] In step S1, a grayscale image is drawn according to the received echo signal; and the probability of each grayscale level is obtained according to the original grayscale value in the grayscale image.

[0048] In some embodiments, in step S1, obtaining the probability of each gray level according to the original gray value in the gray image includes:

[0049] The distribution of the original grayscale values ​​in the grayscale image is calculated and normalized to obtain the probability of each grayscale level.

[0050] In step S2, the pixel levels with gray level probabilities less than 0.1 are merged with the gray level of the next higher level to obtain a new gray level and its probability.

[0051] In some embodiments, in step S2, obtaining a cumulative distribution function according to the new gray level probability includes:

[0052] Calculate the cumulative probability from the new gray level 0 to a certain gray level of the new gray level;

[0053]

[0054] Among them, C k (r) represents the cumulative probability; H j (r) represents the j pole of the new gray level;

[0055] According to the cumulative probability, a cumulative distribution function is obtained.

[0056] In step S3, a cumulative distribution function is obtained according to the new gray level probability; and the original gray value is mapped to the new gray value according to the cumulative distribution function.

[0057] In some embodiments, in step S3, mapping the original grayscale value to the new grayscale value according to the cumulative distribution function includes:

[0058] According to the cumulative distribution function and the total number of new gray levels, a gray value after equalization is calculated for each original gray value to obtain a new gray value.

[0059] Specifically, s k =round((L-1)*C k (r)), L is the total number of gray levels, and s k Limited to the range of [0,255];

[0060] Among them, sk Represents the new grayscale value; round() means rounding to the nearest integer.

[0061] In step S4, the original grayscale values ​​of the grayscale image are replaced with the new grayscale values ​​to obtain a new grayscale image; in the new grayscale image, the variance of the grayscale points is calculated according to the mean of the grayscale levels in a predefined neighborhood.

[0062] Specifically,

[0063]

[0064] Where I'(x,y) represents the mean gray level in the predefined neighborhood; I(x+i,y+i) represents the gray level in the predefined neighborhood; s 2 represents the variance of grayscale points; ε represents the predefined neighborhood.

[0065] In summary, the solution proposed in the present invention can effectively improve the contrast of the image and make the image details appear fuller; according to the characteristics of underwater images, it can effectively remove noise and make it easier to perform other subsequent image processing.

[0066] Embodiment 2:

[0067] The invention discloses an underwater acoustic image optimization display system. Figure 2 FIG. 4 is a structural diagram of an underwater acoustic image optimization display system according to an embodiment of the present invention; Figure 2 As shown, the system 100 includes:

[0068] The first processing module 101 is configured to draw a grayscale image according to the received echo signal; and obtain the probability of each grayscale level according to the original grayscale value in the grayscale image;

[0069] The second processing module 102 is configured to merge the pixel levels with gray level probabilities less than 0.1 with the gray level of the next higher level to obtain a new gray level and its probability;

[0070] The third processing module 103 is configured to obtain a cumulative distribution function according to the new gray level probability; and map the original gray value to the new gray value according to the cumulative distribution function;

[0071] The fourth processing module 104 is configured to replace the original grayscale value of the grayscale image with the new grayscale value to obtain a new grayscale image; in the new grayscale image, calculate the variance of the grayscale point according to the mean of the grayscale level in the predefined neighborhood;

[0072] The fifth processing module 105 is configured to, when the variance is smaller than a preset value, replace the grayscale of the grayscale point in the new grayscale image with the mean value, and finally obtain an optimized image.

[0073] According to the system of the second aspect of the present invention, the first processing module 101 is specifically configured to obtain the probability of each gray level according to the original gray value in the gray map, including:

[0074] The distribution of the original grayscale values ​​in the grayscale image is calculated and normalized to obtain the probability of each grayscale level.

[0075] According to the system of the second aspect of the present invention, the second processing module 102 is specifically configured as follows: obtaining the cumulative distribution function according to the new gray level probability includes:

[0076] Calculate the cumulative probability from the new gray level 0 to a certain gray level of the new gray level;

[0077]

[0078] Among them, C k (r) represents the cumulative probability; H j (r) represents the j pole of the new gray level;

[0079] According to the cumulative probability, a cumulative distribution function is obtained.

[0080] According to the system of the second aspect of the present invention, the third processing module 103 is specifically configured as follows: mapping the original grayscale value to the new grayscale value according to the cumulative distribution function includes:

[0081] According to the cumulative distribution function and the total number of new gray levels, a gray value after equalization is calculated for each original gray value to obtain a new gray value.

[0082] Specifically, s k =round((L-1)*C k (r)), L is the total number of gray levels, and s k Limited to the range of [0,255];

[0083] Among them, s k Represents the new grayscale value; round() means rounding to the nearest integer.

[0084] According to the system of the second aspect of the present invention, the fourth processing module 104 is specifically configured as follows:

[0085]

[0086] Where I'(x,y) represents the mean gray level in the predefined neighborhood; I(x+i,y+i) represents the gray level in the predefined neighborhood; s 2 represents the variance of grayscale points; ε represents the predefined neighborhood.

[0087] Embodiment 3:

[0088] The present application discloses an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods for optimizing the display of underwater acoustic images in Embodiment 1 disclosed in the present invention are implemented.

[0089] Figure 3 is a structural diagram of an electronic device according to an embodiment of the present invention, such as Figure 3 As shown, the electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, near field communication (NFC) or other technologies. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a button, a trackball or a touch pad set on the housing of the electronic device, or an external keyboard, touch pad or mouse, etc.

[0090] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a structural diagram of the part related to the technical solution of the present disclosure, and does not constitute a limitation on the electronic device to which the technical solution of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0091] Embodiment 4:

[0092] The present invention discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any one of the underwater acoustic image optimization display methods in Embodiment 1 of the present invention are implemented.

[0093] Please note that the technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification. The above embodiments only express several implementation methods of the present application, and their descriptions are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, without departing from the concept of the present application, several variations and improvements can be made, which all belong to the scope of protection of the present application. Therefore, the scope of protection of the patent in this application shall be based on the attached claims.

[0094] The embodiments of the subject matter and functional operations described in this specification may be implemented in the following: digital electronic circuits, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or a combination of one or more of them. The embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules in computer program instructions encoded on a tangible non-temporary program carrier to be executed by a data processing device or to control the operation of the data processing device. Alternatively or additionally, the program instructions may be encoded on an artificially generated propagation signal, such as a machine-generated electrical, optical or electromagnetic signal, which is generated to encode information and transmit it to a suitable receiver device for execution by a data processing device. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of them.

[0095] The processes and logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform corresponding functions by operating on input data and generating output. The processes and logic flows can also be performed by special purpose logic circuits, such as FPGAs (field programmable gate arrays) or ASICs (application-specific integrated circuits), and the apparatus can also be implemented as special purpose logic circuits.

[0096] Computers suitable for executing computer programs include, for example, general and / or special microprocessors, or any other type of central processing unit. Typically, the central processing unit will receive instructions and data from a read-only memory and / or a random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, the computer will also include one or more large-capacity storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, or the computer will be operably coupled to this large-capacity storage device to receive data from it or to transmit data to it, or both. However, the computer does not necessarily have such a device. In addition, the computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0097] Computer readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including, for example, semiconductor memory devices (e.g., EPROM, EEPROM and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0098] Although this specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of protection claimed, but are mainly used to describe the features of the specific embodiments of specific inventions. Certain features described in multiple embodiments in this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although features may work in certain combinations as described above and even initially claim protection, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may point to a sub-combination or a variation of a sub-combination.

[0099] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or requiring that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0100] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0101] The above are preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for optimizing the display of underwater acoustic images, characterized in that: include: Step S1, drawing a grayscale image according to the received echo signal; According to the original grayscale value in the grayscale image, the probability of each grayscale level is obtained; Step S2, merging the pixel levels whose gray level probability is less than 0.1 with the gray level of the next higher level to obtain a new gray level and its probability; Step S3, obtaining a cumulative distribution function according to the new gray level probability; mapping the original gray value to the new gray value according to the cumulative distribution function; Step S4, replacing the original grayscale value of the grayscale image with the new grayscale value to obtain a new grayscale image; in the new grayscale image, calculating the variance of the grayscale points according to the mean of the grayscale levels in a predefined neighborhood; Step S5: When the variance is less than a preset value, the grayscale level of the grayscale point in the new grayscale image is replaced by the mean value, and finally an optimized image is obtained.

2. The method for optimizing and displaying underwater acoustic images according to claim 1, characterized in that: In the step S1, obtaining the probability of each gray level according to the original gray value in the gray image includes: The distribution of the original grayscale values ​​in the grayscale image is calculated and normalized to obtain the probability of each grayscale level.

3. The method for optimizing and displaying underwater acoustic images according to claim 1, characterized in that: In step S2, obtaining the cumulative distribution function according to the new gray level probability includes: Calculate the cumulative probability from the new gray level 0 to a certain gray level of the new gray level; According to the cumulative probability, a cumulative distribution function is obtained.

4. The method for optimizing and displaying underwater acoustic images according to claim 1, characterized in that: In the step S3, mapping the original grayscale value to a new grayscale value according to the cumulative distribution function includes: According to the cumulative distribution function and the total number of new gray levels, a gray value after equalization is calculated for each original gray value to obtain a new gray value.

5. An underwater acoustic image optimization display system, characterized in that: The system comprises: The first processing module is configured to draw a grayscale image according to the received echo signal; and obtain the probability of each grayscale level according to the original grayscale value in the grayscale image; The second processing module is configured to merge the pixel levels with gray level probabilities less than 0.1 with the gray level of the next higher level to obtain a new gray level and its probability; A third processing module is configured to obtain a cumulative distribution function according to the new gray level probability; and map the original gray value to the new gray value according to the cumulative distribution function; The fourth processing module is configured to replace the original grayscale value of the grayscale image with the new grayscale value to obtain a new grayscale image; in the new grayscale image, calculate the variance of the grayscale point according to the mean of the grayscale level in the predefined neighborhood; The fifth processing module is configured to replace the grayscale of the grayscale point in the new grayscale image with the mean value when the variance is less than a preset value, so as to finally obtain an optimized image.

6. The underwater acoustic image optimization display system according to claim 5, characterized in that: The first processing module is specifically configured to obtain the probability of each gray level according to the original gray value in the gray map, including: The distribution of the original grayscale values ​​in the grayscale image is calculated and normalized to obtain the probability of each grayscale level.

7. The underwater acoustic image optimization display system according to claim 5, characterized in that: The second processing module is specifically configured as follows: obtaining a cumulative distribution function according to the new gray level probability comprises: Calculate the cumulative probability from the new gray level 0 to a certain gray level of the new gray level; According to the cumulative probability, a cumulative distribution function is obtained.

8. The underwater acoustic image optimization display system according to claim 5, characterized in that: The third processing module is specifically configured such that mapping the original grayscale value to the new grayscale value according to the cumulative distribution function includes: According to the cumulative distribution function and the total number of new gray levels, a gray value after equalization is calculated for each original gray value to obtain a new gray value.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps in the underwater acoustic image optimization display method described in any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the underwater acoustic image optimization display method described in any one of claims 1 to 4 are implemented.

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