A real-time monitoring method and system for salt tides based on satellite remote sensing

Abstract

The present invention belongs to the field of image communication technology, and specifically relates to a real-time monitoring method and system for salt tides based on satellite remote sensing. The method includes: collecting remote sensing images of the monitoring area in real time; using a variable-length coding algorithm to assign codewords to the pixel values in each channel of the remote sensing images; dividing the codewords of each pixel value into several layers according to the loss thresholds of each layer to obtain sub-codewords of each layer of each pixel value; using the sub-codewords of each layer of each pixel value to perform hierarchical coding on each channel of the remote sensing images, and sequentially transmitting the coding results of different layers to the monitoring terminal for real-time monitoring of salt tides. The present invention performs hierarchical compression and transmission on remote sensing images, improving the real-time performance of salt tide monitoring.

Description

Technical Field

[0001] The present invention relates to the field of image communication technology, and more particularly to a method and system for real-time monitoring of salt tides based on satellite remote sensing. Background Art

[0002] Salt intrusion is a hydrological phenomenon in which seawater, driven by tides, flows back into river estuaries, increasing freshwater salinity. It is essentially a unique interfacial movement caused by the interaction of hydrodynamic forces and salinity gradients. This phenomenon is most common in winter at estuaries (such as the Yangtze and Pearl River estuaries). Salt intrusion can lead to abnormally high freshwater salinity, directly threatening drinking water safety. It can also exacerbate soil salinization and increase the costs of agricultural desalination and industrial equipment corrosion prevention. Therefore, real-time monitoring of salt intrusion is essential to ensure timely response measures.

[0003] Real-time monitoring of salt intrusion relies on high-resolution spatial and temporal data on water salinity dynamics. Traditional monitoring methods rely primarily on ground-based stations and buoy sensors, inferring salinity distribution from parameters such as conductivity and water level. However, this approach has limited spatial coverage and high maintenance costs, making it difficult to meet the continuous observation needs of large estuary areas. Satellite remote sensing technology, due to its wide-area coverage, has become an important tool for salt intrusion monitoring.

[0004] However, the massive amount of remote sensing images collected by satellite remote sensing technology creates significant transmission and storage pressures, necessitating image compression. While existing compression technologies (such as JPEG2000 and deep learning autoencoders) can achieve high compression ratios, they can also lose detailed information about salt intrusion.

[0005] Therefore, there is an urgent need for a compression technology for remote sensing images that can retain the detailed information of salt intrusion in remote sensing images and ensure the real-time monitoring of salt intrusion. Summary of the Invention

[0006] In order to solve the above-mentioned technical problem that detailed information of salt intrusion may be lost when compressing remote sensing images using existing compression methods, the present invention provides solutions in the following aspects.

[0007] In a first aspect, the present invention provides a method for real-time monitoring of salt tide based on satellite remote sensing, comprising:

[0008] Remote sensing images of the monitoring area are collected in real time; codewords are assigned to pixel values in each channel of the remote sensing image using a variable-length coding algorithm; the codewords of each pixel value are divided into several layers according to the loss threshold of each layer to obtain sub-codewords of each layer for each pixel value; each channel of the remote sensing image is layered encoded using the sub-codewords of each layer for each pixel value, and the encoding results of different layers are transmitted to the monitoring terminal in sequence for real-time salt tide monitoring.

[0009] The present invention intelligently layers the codewords of each pixel value according to a preset loss threshold, generates a multi-level sub-codeword structure, implements layered coding processing on each channel, and transmits the coded data sequentially to the monitoring terminal through the network according to the hierarchical priority. The layered coding mechanism ensures the priority transmission of key data and can still maintain the real-time performance of the monitoring system under limited bandwidth conditions. At the same time, the scalable hierarchical structure allows the transmission strategy to be dynamically adjusted according to the network status, ensuring the integrity and timeliness of salt tide monitoring data, and providing reliable data support for disaster prevention decision-making.

[0010] Preferably, the method for obtaining the sub-codewords of each layer of each pixel value is as follows: S101: bits and the first bit of the codeword of the target pixel value The pixel value with the same bits is used as the target pixel value. Homomorphic pixel values of the layer, The front of the target pixel value The total length of the sub-codewords of the layer, For the S102: Determine the target bit as the target pixel value and its first The homomorphic pixel value of the layer The sub-codeword of the layer Loss degree, target bit is the codeword of target pixel value to bits; S103: In response to the The loss is not greater than the preset The loss threshold of the layer, the target bit is taken as the target pixel value and its The homomorphic pixel value of the layer The sub-codeword of the layer, otherwise, The value of is increased by 1, and steps S101-S103 are repeated until the target pixel value and its first pixel value are obtained. The homomorphic pixel value of the layer The iteration stops when the sub-codeword of the layer is reached.

[0011] The present invention improves the traditional fixed coding mode into a dynamic adjustment process by introducing independent loss thresholds between layers, so that the sub-codewords of each layer of pixel values can meet the loss threshold requirements, thereby ensuring that the quality of the image restored according to the coding results of each layer during decoding can meet the requirements of salt tide monitoring.

[0012] Preferably, the The loss degree satisfies the expression: ;in, Indicates that the target bit is used as the target pixel value and its The homomorphic pixel value of the layer The sub-codeword of the layer Degree of loss represents the number of homomorphic pixel values of the layer corresponding to the target pixel value; represents the th homomorphic pixel value of the layer corresponding to the target pixel value; represents the target pixel value; represents the number of pixel points corresponding to the th homomorphic pixel value of the

[0013] By calculating the degree of loss, the system of the present invention quantifies the information loss under different coding granularities, providing a decision basis for the sub-codeword allocation of each layer. In the process of obtaining the degree of loss, the present invention considers the proportion of the number of pixel points corresponding to the homomorphic pixel values, effectively eliminating the statistical deviation caused by uneven pixel distribution and improving the robustness of the loss degree measurement.

[0014] Preferably, the hierarchical coding of each channel of the remote sensing image by using the sub-codewords of each layer of each pixel value includes: for each pixel point in each channel of the remote sensing image, taking the sub-codewords of each layer corresponding to the pixel value of the pixel point as the coding result of the pixel point in each layer; splicing the coding results of all pixel points in the same layer together in sequence as the coding result of each channel of the remote sensing image in this layer.

[0015] By hierarchically coding each channel of the remote sensing image, the present invention ensures the priority transmission of key data in the remote sensing image and can still maintain the real-time performance of the salt tide system under limited bandwidth conditions.

[0016] Preferably, the allocation of codewords to the pixel values in each channel of the remote sensing image by using the variable-length coding algorithm includes: obtaining the frequencies of the pixel values in the remote sensing image, and using Huffman coding to obtain the codewords of the pixel values according to the frequencies of the pixel values.

[0017] Preferably, the allocation of codewords to the pixel values in each channel of the remote sensing image by using the variable-length coding algorithm includes: obtaining the frequencies of the pixel values in the remote sensing image, sorting the pixel values according to the frequencies of the pixel values, and using Shannon-Fano coding to obtain the codewords of the pixel values according to the sorted order of the pixel values and the frequencies of the pixel values.

[0018] Preferably, the sorting of the pixel values according to the frequencies of the pixel values includes: sorting the pixel values in descending order according to the frequencies of the pixel values.

[0019] Preferably, sorting the pixel values according to the frequency of each pixel value includes: S201: constructing an empty sequence, denoted as the pixel sequence; S202: adding the pixel value with the maximum frequency to the pixel sequence; S203: for all pixel values not added to the pixel sequence, determining the priority of the pixel value according to the frequency of the pixel value and the difference between the pixel value and the last pixel value in the current pixel sequence: , represents the priority of the th pixel value not added to the pixel sequence currently; represents the th pixel value not added to the pixel sequence currently; represents the last pixel value in the current pixel sequence; represents the th pixel value not added to the pixel sequence currently; represents the absolute value symbol; adding the pixel value with the maximum priority to the end of the pixel sequence; S204: repeating S203 until all pixel values are added to the pixel sequence and then stopping the iteration.

[0020] The present invention determines the priority of adding pixel values to the pixel sequence based on the frequency of pixel values, so that the pixel sequence effectively retains the main statistical features of each channel of the remote sensing image, ensures that the codewords of high-frequency pixel values are as short as possible, thereby improving the coding efficiency. The present invention considers the difference between pixel values on the basis of frequency, so as to calculate the priority of adding pixel values to the pixel sequence, so that similar pixel values in the pixel sequence are arranged together as much as possible. Then, in the codewords of each pixel value obtained by Shannon-Fano coding, the codewords of similar pixel values are also similar. When layering the codewords, similar pixel values in the lower layer correspond to shorter identical sub-codewords, thereby reducing the amount of compressed data in the lower layer, and thus improving the real-time performance of salt tide monitoring.

[0021] Preferably, it further includes: in response to the monitoring terminal receiving the coding results of the first layer of each channel of the remote sensing image, decompressing the coding results of the first layer of each channel to obtain a decompressed image, and identifying whether there is a salt tide intrusion according to the decompressed image; in response to the monitoring terminal receiving the coding results of the remaining layers of each channel of the remote sensing image and there is a salt tide intrusion, decompressing the coding results of the remaining layers in sequence, updating the decompressed image according to the decompression results, and obtaining the detailed information of the salt tide intrusion according to the finally obtained decompressed image.

[0022] Through hierarchical processing, the present invention improves the response speed of salt tide monitoring. The monitoring system preferentially decompresses and analyzes the first-layer encoded data to quickly complete the preliminary judgment of salt tide intrusion. This fast screening mechanism based on the key layer significantly reduces the consumption of computing resources, enabling the salt tide monitoring system to quickly complete the preliminary warning. Only when it is confirmed that there is a salt tide intrusion, the system continues to decompress the data of the remaining levels. This conditional-triggered processing strategy avoids unnecessary data decompression operations and effectively saves computing resources.

[0023] In a second aspect, the present invention provides a satellite remote sensing-based real-time salt tide monitoring system, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement the above-mentioned satellite remote sensing-based real-time salt tide monitoring method.

[0024] By adopting the above technical solution, the above-mentioned satellite remote sensing-based real-time salt tide monitoring method is generated into a computer program and stored in the memory to be loaded and executed by the processor. Thus, a terminal device is manufactured based on the memory and the processor, which is convenient to use.

[0025] The beneficial effects of the present invention are as follows:

[0026] The hierarchical coding mechanism of the present invention ensures the priority transmission of key data, maintains the real-time performance of the monitoring system under limited bandwidth conditions, improves the response speed of salt tide monitoring, and at the same time, the scalable hierarchical structure allows dynamic adjustment of the transmission strategy according to the network conditions, ensuring the integrity and timeliness of salt tide monitoring data and providing reliable data support for disaster prevention decision-making; the present invention preferentially decompresses and analyzes the first-layer encoded data to quickly complete the preliminary judgment of salt tide intrusion. Only when it is confirmed that there is a salt tide intrusion, it continues to decompress the data of the remaining levels to obtain the details of salt tide intrusion, avoiding unnecessary data decompression operations and effectively saving computing resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flowchart schematically showing a satellite remote sensing-based real-time salt tide monitoring method in the present invention;

[0028] Figure 2 is a schematic diagram showing a Huffman tree;

[0029] Figure 3 is schematically showing Figure 2 the codewords of each pixel value corresponding to the Huffman tree in

[0030] Figure 4 is a schematic diagram showing a Shannon-Fano tree constructed in the order of decreasing pixel value frequency;

[0031] Figure 5is schematically shown Figure 4 A schematic diagram of codewords corresponding to each pixel value in the Shannon-Fano tree;

[0032] Figure 6 is a schematic diagram schematically showing the Shannon-Fano tree constructed according to the order of pixel values in the pixel sequence;

[0033] Figure 7 is schematically shown Figure 6 A schematic diagram of codewords corresponding to each pixel value in the Shannon-Fano tree;

[0034] Figure 8 is schematically shown for Figure 3 A schematic diagram of sub-codewords of each layer of each pixel value obtained by hierarchically dividing the codewords of each pixel value;

[0035] Figure 9 is schematically shown for Figure 5 A schematic diagram of sub-codewords of each layer of each pixel value obtained by hierarchically dividing the codewords of each pixel value;

[0036] Figure 10 is schematically shown for Figure 7 A schematic diagram of sub-codewords of each layer of each pixel value obtained by hierarchically dividing the codewords of each pixel value;

[0037] Figure 11 is schematically shown according to Figure 8 A schematic diagram of the decoding results of each layer obtained by decoding the encoding results of each layer according to the sub-codewords of each layer of each pixel value;

[0038] Figure 12 is schematically shown according to Figure 9 A schematic diagram of the decoding results of each layer obtained by decoding the encoding results of each layer according to the sub-codewords of each layer of each pixel value;

[0039] Figure 13 is schematically shown according to Figure 10 A schematic diagram of the decoding results of each layer obtained by decoding the encoding results of each layer according to the sub-codewords of each layer of each pixel value. Detailed implementation manners [[ID=

[52]

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0041] Next, the specific implementation manners of the present invention will be described in detail with reference to the accompanying drawings.

[0042] It should be noted that there seems to be a formatting issue with the "

[52] " in the original text. It might be a mislabel or an incorrect format. I've translated it as it is, but it might need to be corrected in the original source for a more accurate representation.An embodiment of the present invention discloses a real-time monitoring method for salt tides based on satellite remote sensing. Refer to Figure 1 , which includes steps S001 - S006:

[0043] S001. Real-time collect remote sensing images of the monitoring area.

[0044] Specifically, satellite remote sensing technology is used to real-time collect remote sensing images of the monitoring area. In this embodiment, the collected remote sensing images are visible light images, that is, RGB images. In other embodiments, the collected remote sensing images can be infrared images, hyperspectral images, etc.

[0045] S002. Use a variable-length coding algorithm to assign codewords to the pixel values in each channel of the remote sensing image.

[0046] The remote sensing image is an RGB image, including three channels of R, G, and B. The present invention encodes the images corresponding to each channel of the remote sensing image separately. Therefore, the present invention takes the image of any one of the R channel, G channel, and B channel as the target image, and takes the target image as an example to illustrate the specific method of encoding the images corresponding to each channel of the remote sensing image.

[0047] In the first embodiment, the variable-length coding algorithm uses Huffman coding. Then, Huffman coding is used to assign codewords to the pixel values in the target image, including:

[0048] Obtain the frequencies of each pixel value in the target image, and use Huffman coding to obtain the codewords of each pixel value according to the frequencies of each pixel value.

[0049] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 8, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, the pixel values included are 19, 20, 21, 22, 23, 24, 25, 77, 78, 79, 80, 189, 190, 192, 193 respectively, and the frequencies corresponding to each pixel value are , , , , , , , , , , , , , , , the Huffman tree constructed according to the frequencies of each pixel value can be seen in Figure 2 , then the codewords of each pixel value can be seen in Figure 3 .

[0050] In the second embodiment, the variable-length coding algorithm uses Shannon–Fano coding. Then, using Shannon–Fano coding to assign codewords to the pixel values in the target image includes:

[0051] Obtain the frequencies of each pixel value in the target image, sort the pixel values in descending order according to the frequencies of each pixel value, and use Shannon–Fano coding to obtain the codewords of each pixel value according to the sorted order of the pixel values and the frequencies of each pixel value.

[0052] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, the pixel values included are 19, 20, 21, 22, 23, 24, 25, 77, 78, 79, 80, 189, 190, 192, 193, and the corresponding frequencies of each pixel value are , , , , , , , , , , , , , , . The result of sorting the pixel values in descending order according to the frequencies of each pixel value is {80, 23, 190, 79, 22, 192, 78, 20, 189, 77, 19, 21, 24, 25, 193}. For the schematic diagram of the Shannon–Fano tree constructed in descending order according to the pixel value frequencies, see Figure 4 , and the codewords of each pixel value can be seen in Figure 5 .

[0053] In the third embodiment, the variable-length coding algorithm adopts Shannon-Fano coding. The frequencies of the pixel values in the target image are obtained, and the pixel values are sorted according to the frequencies of the pixel values and the differences between the pixel values. According to the sorted order of the pixel values and the frequencies of the pixel values, the codewords of the pixel values are obtained by using Shannon-Fano coding. Among them, sorting the pixel values according to the frequencies of the pixel values and the differences between the pixel values includes:

[0054] Construct an empty sequence, denoted as the pixel sequence. Add the pixel value with the highest frequency to the pixel sequence. For all pixel values that have not been added to the pixel sequence, determine the priority of the pixel value according to the frequency of the pixel value and the difference between the pixel value and the last pixel value in the current pixel sequence, and add the pixel value with the highest priority to the end of the pixel sequence to achieve one update of the pixel sequence; after each update of the pixel sequence, determine the priorities of all pixel values that have not been added to the pixel sequence again, and add the pixel value with the highest priority to the end of the pixel sequence to achieve another update of the pixel sequence; repeat the above process until all pixel values have been added to the pixel sequence and the iteration stops, then the finally obtained pixel sequence is the result of sorting the pixel values in the target image.

[0055] Among them, the priority of the pixel value that has not been added to the pixel sequence satisfies the expression:

[0056] ;

[0057] Among them, represents the priority of the th pixel value that has not been added to the pixel sequence currently; represents the th pixel value that has not been added to the pixel sequence currently; represents the last pixel value in the current pixel sequence; represents the frequency of the th pixel value that has not been added to the pixel sequence currently; represents the absolute value symbol.

[0058] It should be noted that the objective of the present invention is to perform hierarchical compression transmission on remote sensing images. The compressed data of the lower layer contains the global information in the remote sensing image, and the compressed data of the higher layer contains the detailed information in the remote sensing image. Therefore, in the third embodiment, the pixel values are sorted according to the frequency of the pixel values and the differences between the pixel values. Firstly, it can ensure that the codewords of the pixel values with a large frequency are as short as possible, thereby ensuring the compression efficiency. Secondly, the longer the same part of the codewords assigned to similar pixel values is, so that when performing hierarchical compression according to the codewords of the pixel values subsequently, in the lower layer, more similar pixel values can use the same part in the codewords for encoding, so as to achieve a small loss degree in the lower layer while the data volume corresponding to the compression result is small, thereby ensuring the real-time nature of salt tide monitoring.

[0059] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, it contains pixel values 19, 20, 21, 22, 23, 24, 25, 77, 78, 79, 80, 189, 190, 192, 193, and the frequencies corresponding to each pixel value are , , , , , , , , , , , , , , . Adding the pixel value 80 with the largest frequency to the pixel sequence, the pixel sequence becomes {80}, and the priority of the pixel value 19 is , the priority of the pixel value 20 is , similarly, calculate the priorities of the pixel values 21, 22, 23, 24, 25, 77, 78, 79, 189, 190, 192, 193 respectively. Among them, the priority of the pixel value 79 is the largest, which is , so the pixel value 79 is added to the end of the pixel sequence, and the pixel sequence becomes {80, 79}; similarly, according to the new pixel sequence, the priority of each pixel value that has not been added to the pixel sequence is calculated again, and the pixel value with the highest priority is added to the end of the pixel sequence. The above process is repeated continuously, and the finally obtained pixel sequence is {80, 79, 78, 77, 23, 22, 21, 20, 19, 24, 25, 190, 189, 192, 193}. For the schematic diagram of the Shannon-Fano tree constructed according to the order of pixel values in the pixel sequence, see Figure 6 , and the codewords of the pixel values are shown in Figure 7 .

[0060] S003. Divide the codewords of each pixel value into several layers according to the loss threshold of each layer to obtain the sub-codewords of each layer of each pixel value.

[0061] Specifically, starting from the pixel value with the highest frequency, obtain the first layer in the codewords of each pixel value as the sub-codeword of the first layer of each pixel value; in response to the sub-codeword of the first layer of the pixel value being the same as the codeword of the pixel value, this pixel value has no sub-codeword of the first layer, otherwise, obtain the second layer in the codewords of each pixel value based on the sub-codeword of the first layer as the sub-codeword of the second layer of each pixel value; in response to the bit string formed by splicing the sub-codeword of the first layer and the sub-codeword of the second layer of the pixel value being the same as the codeword of the pixel value, this pixel point has no sub-codeword of the third layer, otherwise, obtain the third layer in the codewords of each pixel value based on the sub-codeword of the first layer and the sub-codeword of the second layer as the sub-codeword of the third layer of each pixel value; and so on, until all pixel values have no sub-codeword of the next layer and the iteration stops.

[0062] Taking the th layer ( ) as an example to illustrate the method for obtaining the sub-codewords of the th layer of each pixel value:

[0063] 1. When , take the pixel value with the highest frequency among all pixel values that have not obtained the sub-codeword of the th layer as the target pixel value; when , in response to the bit string formed by splicing the sub-codewords of the previous th layer of the pixel value in the order of the number of layers being different from the codeword of the pixel value, take the pixel value as the candidate pixel value, and take the candidate pixel value with the highest frequency among all candidate pixel values that have not obtained the sub-codeword of the th layer as the target pixel value.

[0064] 2. Set the segmentation length of the th layer, and its initial value is 1.

[0065] 3. When When, the first several bits of the codeword of the target pixel value are used as the target bits, and the pixel values whose first several bits are the same as the target bits of the target pixel value are obtained as the homomorphic pixel values of the th layer of the target pixel value; when When, the th bit to the th bit of the codeword of the target pixel value are used as the target bits, and the pixel values whose first several bits are the same as the first several bits of the target pixel value are obtained as the homomorphic pixel values of the th layer of the target pixel value, where represents the length of the sub - codeword of the th layer of the target pixel value, represents the total length of the sub - codewords of the first layers of the target pixel value.

[0066] 4. Determine the th loss degree when using the target bits as the sub - codeword of the th layer of the target pixel value and its homomorphic pixel values according to the differences between the target pixel value and its homomorphic pixel values of each th layer and the number of pixel points corresponding to each homomorphic pixel value: ;

[0067] ;

[0068] Among them, represents the th loss degree when using the target bits as the sub - codeword of the th layer of the target pixel value and its homomorphic pixel values, represents the number of homomorphic pixel values of the th layer of the target pixel value; represents the th homomorphic pixel value of the th layer of the target pixel value; represents the target pixel value; represents the number of pixel points corresponding to the th homomorphic pixel value of the th layer of the target pixel value in the target image. If the target bits are used as the sub - codeword of the th layer of the target pixel value and its homomorphic pixel values, when encoding the th layer, the sub - codeword is used to encode the target pixel value and its homomorphic pixel values of the th layer, and in the subsequent decoding of the th layer, th layer, When encoding the result of a layer, the homomorphic pixel value of the layer is decoded into the target pixel value, then represents the th loss amount when the th homomorphic pixel value of the layer is decoded into the target pixel value, then reflects the average loss amount when all the pixel points corresponding to the homomorphic pixel values of the

[0069] 5. In response to the loss degree being greater than the preset layer loss threshold, increment the value of by one, and repeat steps 3 - 5 until the loss degree is not greater than the preset layer loss threshold, then stop the iteration.

[0070] 6. In response to the loss degree being not greater than the preset layer loss threshold, use the target bit as the target pixel value and the th layer sub - codeword of its homomorphic pixel value, and record the length of the th layer sub - codeword of the target pixel value and its homomorphic pixel value as .

[0071] 7. Repeat steps 1 - 6 until all the layer sub - codewords of all candidate pixel values have been obtained, then stop the iteration.

[0072] 8. Increment the value of by one, and repeat steps 1 - 8 until there are no candidate pixel values in the layer, then stop the iteration.

[0073] It should be noted that the loss threshold of each layer determines the loss degree of each layer. The purpose of the present invention is for the hierarchical compression and transmission of remote sensing images. When the monitoring terminal receives the compression result, it can decompress and display the remote sensing image layer by layer. The decompression result of the first layer contains the global information in the corresponding channel of the remote sensing image. As the decompression layer gets higher, the decompression result contains more details in the corresponding channel of the remote sensing image. Therefore, the lower the layer, the higher the allowable loss degree, and the higher the layer, the lower the allowable loss degree.

[0074] Therefore, in this embodiment, the loss threshold of the first layer is 15, the loss threshold of the second layer is 10, the loss threshold of the third layer is 5, the loss threshold of the fourth layer is 1, and the loss threshold of the fifth layer is 0. It should be noted that when the loss threshold of the fifth layer is set to 0, the first five layers already contain all the information in the corresponding channels of the remote sensing image. Therefore, there will be no sixth layer, and there is no need to set the loss threshold of the sixth layer. In other embodiments, the implementer can set the loss threshold of each layer according to the actual implementation situation.

[0075] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, when obtaining the codewords of each pixel value by using the method corresponding to the first embodiment in step S003, the process of obtaining the sub-codewords of each layer of each pixel value is as follows: Taking 80 as the target pixel value, the codeword of 80 is 110. Taking 1 as the target bit, the pixel values with the first 1 bit of the codeword being the same as 1 are 23, 24, 25, 79, 189, 192. Then 23, 24, 25, 79, 189, 192 are the homomorphic pixel values of 80 in the first layer. Then, when taking the target bit 1 as the first-layer sub-codeword of the target pixel value and its first-layer homomorphic pixel values, the first loss degree is (5×|23 - 80| + |24 - 80| + |25 - 80| + 3×|79 - 80| + 2×|189 - 80| + 3×|192 - 80|)÷(5 + 1 + 1 + 3 + 2 + 3)≈63.53. Since the first loss degree is greater than the loss threshold 15 of the first layer, taking 11 as the target bit, the pixel values with the first 2 bits of the codeword being the same as 11 are 79, 192. Then 79, 192 are the homomorphic pixel values of 80 in the first layer. Then, when taking the target bit 11 as the first-layer sub-codeword of the target pixel value and its first-layer homomorphic pixel values, the first loss degree is The first loss degree is greater than the loss threshold 15 of the first layer. Taking 110 as the target bit, there is no pixel value with the first 3 bits of the codeword being the same as 110. Then 80 has no homomorphic pixel values in the first layer. Then, when taking the target bit 110 as the first-layer sub-codeword of the target pixel value and its first-layer homomorphic pixel values, the first loss degree is 0. Since the first loss degree is not greater than the loss threshold 15 of the first layer, taking the target bit 110 as the first-layer sub-codeword of the pixel value 80. Similarly, for the sub-codewords of each layer of each pixel value, see Figure 8 .

[0076] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, when obtaining the codewords of each pixel value by using the method corresponding to the second embodiment in step S003, refer to the sub-codewords of each layer of each pixel value Figure 9 .

[0077] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, when obtaining the codewords of each pixel value by using the method corresponding to the third embodiment in step S003, refer to the sub-codewords of each layer of each pixel value Figure 10 .

[0078] S004. Perform hierarchical coding on each channel of the remote sensing image by using the sub-codewords of each layer of each pixel value.

[0079] Specifically, for each pixel point in the target image, encode the pixel point according to the codeword of the pixel value of the pixel point. During the encoding process, put the sub-codewords of each layer in the codeword into each layer respectively as the encoding result of the pixel point in each layer. Concatenate the encoding results of all pixel points in the same layer in sequence as the encoding result of the target image in this layer. Among them, if a certain pixel point does not have the sub-codeword of a certain layer, then skip this pixel point during the process of concatenating the encoding results of all pixel points in this layer.

[0080] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, if using Figure 8The sub-codewords of each layer corresponding to each pixel value in it are used to encode the sequence, and the encoding result of the first layer is 110110010011101101110110110111001000001011000000000010110110100101101100110011000100001101010111111110111111011011. The encoding result of the second layer is 110101011100001, and there is no encoding result for the third layer.

[0081] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, if Figure 9 the sub-codewords of each layer corresponding to each pixel value in it are used to encode the sequence, the encoding result of the first layer is 0000001010011000011000000011101011010110111011101111101000100000100100110000010011110111101100110001011111100110010101001010010, the encoding result of the second layer is 01, and there is no encoding result for the third layer.

[0082] Exemplarily, when the sequence formed by the pixel values of the pixel points in the target image is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, if Figure 10 the sub-codewords of each layer corresponding to each pixel value in it are used to encode the sequence, the encoding result of the first layer is 00000000000000000000011001001001000101010101010101100100111110111111110111101101, the encoding result of the second layer is 0011010011001000110101011010111001111, the encoding result of the third layer is 100010110011000, the encoding result of the fourth layer is 01, and there is no encoding result for the fifth layer.

[0083] It should be noted that Figure 8 、 Figure 9 、Figure 10 The sub-codewords of each pixel value respectively correspond to the first embodiment, the second embodiment, and the third embodiment in step S003. Using Figure 8 , Figure 9 , Figure 10 The sub-codeword pairs of each layer of each pixel value in encode the sequence {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 24, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, and the lengths of the encoding results of the first layer obtained are 114, 127, and 80 respectively. It can be seen that by obtaining the codewords of each pixel value according to the method in the third embodiment of step S003, then obtaining the sub-codewords of each layer of each pixel value, and encoding the sequence, the length of the encoding result of the first layer obtained is the shortest. When transmitting the encoding result of the first layer to the monitoring terminal later, the fewer bits required for transmission, the faster the transmission speed, making the real-time monitoring of salt tides stronger.

[0084] S005. Transmit the encoding results of different layers to the monitoring terminal in sequence, and the monitoring terminal decompresses the encoding results of each layer and performs real-time monitoring of salt tides according to the decompression results.

[0085] It should be noted that the encoding result of the first layer in the present invention can be decoded independently, and the decoding result contains the global information of the corresponding channel of the remote sensing image and can be used to monitor salt tides. To ensure the real-time nature of salt tide monitoring, the present invention transmits the encoding results of different layers in the hierarchical order of the encoding results.

[0086] In one embodiment, first transmit the encoding results of the first layer of each channel of the remote sensing image to the monitoring terminal, and then transmit the encoding results of the second layer of each channel of the remote sensing image, and so on until the sequential transmission of the encoding results of all levels is completed.

[0087] In response to the monitoring terminal receiving the encoding results of the first layer of each channel of the remote sensing image, decompress the encoding results of the first layer of each channel to obtain a decompressed image, and identify whether there is a salt tide intrusion according to the decompressed image. In response to the monitoring terminal receiving the encoding results of the remaining layers of each channel of the remote sensing image and there being a salt tide intrusion, decompress the encoding results of the remaining layers in sequence, update the decompressed image according to the decompression results, and obtain the detailed information of the salt tide intrusion according to the finally obtained decompressed image.

[0088] In another embodiment, the encoded result of the first layer of each channel of the remote sensing image is transmitted to the monitoring terminal. In response to the monitoring terminal receiving the encoded result of the first layer of each channel of the remote sensing image, the encoded result of the first layer of each channel is decompressed to obtain a decompressed image, and it is identified whether there is a salt tide intrusion according to the decompressed image. In response to the existence of a salt tide intrusion, the encoded results of the remaining layers of each channel of the remote sensing image are transmitted to the monitoring terminal, the encoded results of the remaining layers are decompressed in sequence, the decompressed image is updated according to the decompression results, and the detailed information of the salt tide intrusion is obtained according to the finally obtained decompressed image.

[0089] Specifically, the specific method for decompressing the encoded result of the first layer of each channel is as follows:

[0090] For the encoded result of the first layer of any channel, starting from the first undecoded bit in the encoded result, read the bits in the encoded result in the order from left to right. When there is a sub-codeword of the first layer of the pixel value that is the same as the read content, stop reading and use the pixel value as a decoding result. Repeat this process until all bits in the encoded result of the first layer of this channel have been decoded and the iteration stops. Fill all the decoding results into an empty matrix of the same size as this channel of the remote sensing image in sequence to obtain the decompression result of this channel. The decompression results of all channels constitute the decompressed image.

[0091] Exemplarily, when the encoded result of the first layer of a certain channel is 110110010011101101110110110111001000001011000000000010110110100101101100110011000100001101010111111110111111011011, the sub-codewords of each layer of each pixel value are shown in Figure 8When starting from the first undecoded bit in the encoding result (i.e., the first bit of the encoding result), read the bits in the encoding result in the order from left to right. When 110 is read, the sub-codeword of the first layer of the pixel value 80 is the same as 110, so 80 is the first decoding result; then start from the 4th bit in the encoding result, read the bits in the encoding result in the order from left to right. When 110 is read, the sub-codeword of the first layer of the pixel value 80 is the same as 110, so 80 is the second decoding result; then start from the 7th bit in the encoding result, read the bits in the encoding result in the order from left to right. When 0100 is read, the sub-codeword of the first layer of the pixel value 78 is the same as 0100, so 78 is the second decoding result; and so on. All decoding results can be obtained, and the sequence formed by all the final decoding results is: {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 22, 19, 22, 22, 22, 22, 22, 23, 2:3, 23, 22, 23, 23, 24, 24, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}.

[0092] Exemplarily, when the encoding result of the first layer of a certain channel is 0000001010011000011000000011101011010110111011101111101000100000100100110000010011110111101100110001011111100110010101^01010010, the sub-codewords of each layer of each pixel value are shown in Figure 9 When, the sequence formed by all the final decoding results is: {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 77, 19, 20, 20, 21, 22, 22, 23, 23, 23, 22, 23, 23, 21, 25, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}.

[0093] Exemplarily, when the encoding result of the first layer of a certain channel is 00000000000000000000011001001001000101010101010101100100111110111111110111101101, the sub-codewords of each layer of each pixel value are shown in Figure 10When it is, the sequence formed by all the final decoding results is: {80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 23, 20, 20, 20, 20, 23, 23, 23, 23, 23, 23, 23, 23, 20, 20, 192, 192, 190, 192, 192, 192, 190, 192, 190, 190}.

[0094] Furthermore, the specific method for decompressing the encoding results of the remaining layers in sequence is as follows:

[0095] Obtain all the decoding results of the sub-codewords of the layer in all the decoding results of the layer as the objects to be decoded, and decode all the objects to be decoded in sequence: for the current object to be decoded, use all the pixel values whose sub-codewords of the layer are the same as those of the current object to be decoded as the homomorphic pixel values of the current object to be decoded. Starting from the first undecoded bit in the encoding result of the layer, read the bits in the encoding result of the layer in the order from left to right. In response to the sub-codewords of the layer of the current object to be decoded being the same as the read content, stop reading, and take the current object to be decoded as the decoding result of the current object to be decoded in the layer; in response to any one of the homomorphic pixel values of the current object to be decoded having the sub-codewords of the layer being the same as the read content, stop reading, and take this homomorphic pixel value as the decoding result of the current object to be decoded in the layer. Replace each object to be decoded in the corresponding channel of the decompressed image with the decoding result of each object to be decoded in the

[0096] layer to achieve the th update of the decompressed image.

[0097] Exemplarily, when the encoding result of the second layer of a certain channel is 110101011100001, the sub-codewords of each pixel value in each layer are shown in Figure 8 ​, when the sequence formed by the decoding results of the first layer is {80, 80, 78, 79, 80, 79, 80, 80, 79, 78, 22, 19, 22, 22, 22, 22, 22, 23, 23, 23, 22, 23, 23, 24, 24, 189, 189, 190, 193, 192, 192, 190, 192, 190, 190}, if 22, 22, 22, 22, 22, 22, 22, 24, 24 in the decoding results of the first layer have sub-codewords of the second layer, then the sequence formed by the object to be decoded is {22, 22, 22, 22, 22, 22, 22, 24, 24}. For the first object to be decoded, which is 22, the pixel values 20, 77, 21 have the same sub-codewords of the first layer as 22. So, the pixel values 20, 77, 21 are the homomorphic pixel values of the object to be decoded, which is 22. Starting from the first undecoded bit in the encoding result (i.e., the first bit of the encoding result), read the bits in the encoding result in the order from left to right. When 110 is read, the sub-codewords of the first layer of the homomorphic pixel value 77 are the same as 110. Then 77 is the decoding result of the first object to be decoded, which is 22, in the second layer. For the second object to be decoded, which is 22, the homomorphic pixel values are 20, 77, 21. Starting from the 4th bit in the encoding result (i.e., the first bit of the encoding result), read the bits in the encoding result in the order from left to right. When 10 is read, the sub-codewords of the first layer of the homomorphic pixel value 20 are the same as 10. Then 20 is the decoding result of the second object to be decoded, which is 22, in the second layer. Similarly, the decoding results of all objects to be decoded in the second layer can be obtained. When the encoding result of the first layer is 110110010011101101110110110111001000001011000000000010110110100101101100110011000100001101010111111110111111011011, and the encoding result of the second layer is 110101011100001, the decoding results of each layer are shown in Figure 11 .

[0098] Exemplarily, when the sub-codewords of each pixel value of each layer are shown in Figure 9 , when the encoding result of the first layer is 0000001010011000011000000011101011010110111011101111101000100000100100110000010011110111101100110001011111100110010101001010010, and the encoding result of the second layer is 01, the decoding results of each layer are shown in Figure 12 .

[0099] Exemplarily, when the sub-codewords of each pixel value of each layer are shown in Figure 10, the encoding result of the first layer is 00000000000000000000011001001001000101010101010101100100111110111111110111101101, the encoding result of the second layer is 0011010011001000110101011010111001111, the encoding result of the third layer is 100010110011000, and when the encoding result of the fourth layer is 01, the decoding results of each layer can be seen in Figure 13 .

[0100] It should be noted that the decompressed image is a remote sensing image. Identifying whether there is salt tide intrusion based on the remote sensing image is a well-known technology. For example, salt tide intrusion will cause changes in the water body color. Fresh water usually appears blue-green or dark blue, while the area affected by salt tide intrusion may appear grayish-white or milky yellow due to suspended salts, and a clear color boundary, that is, the salt tide peak, may be formed at the confluence of fresh and salt water. Implementers can set recognition rules based on this feature to identify whether there is salt tide intrusion, which will not be elaborated here in detail.

[0101] It should be further noted that as the decompression layer gets higher, the more details in the corresponding channels of the remote sensing image are included in the decompression result, and the obtained decompressed image contains the complete information of the remote sensing image. Then, implementers can obtain the detailed information of salt tide intrusion based on the finally obtained decompressed image.

[0102] The embodiment of the present invention also discloses a salt tide real-time monitoring system based on satellite remote sensing, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, a salt tide real-time monitoring method based on the present invention is implemented.

[0103] The above system also includes other components well-known to those skilled in the art such as a communication bus and a communication interface. Their settings and functions are known in the art, so they will not be elaborated here.

Claims

1. A real-time monitoring method for salt tides based on satellite remote sensing, characterized in that, Including: Real-time collecting remote sensing images of the monitoring area; Using a variable-length coding algorithm to assign codewords to the pixel values in each channel of the remote sensing image; dividing the codewords of each pixel value into several layers according to the loss threshold of each layer to obtain the sub-codewords of each layer of each pixel value, specifically: S101: The front of the code word bits and the first bit of the codeword of the target pixel value The pixel value with the same bits is used as the target pixel value. Homomorphic pixel values of the layer, The front of the target pixel value The total length of the sub-codewords of the layer, For the S102: Determine the target bit as the target pixel value and its first The homomorphic pixel value of the layer The sub-codeword of the layer Loss degree, target bit is the codeword of target pixel value to bits; S103: In response to the The loss is not greater than the preset The loss threshold of the layer, the target bit is taken as the target pixel value and its The homomorphic pixel value of the layer The sub-codeword of the layer, otherwise, The value of is increased by 1, and steps S101-S103 are repeated until the target pixel value and its first pixel value are obtained. The homomorphic pixel value of the layer Stop iteration when the sub-codeword of the layer is reached; Using the sub-codewords of each layer of each pixel value to perform layered coding on each channel of the remote sensing image, and sequentially transmitting the coding results of different layers to the monitoring terminal for real-time salt tide monitoring; In response to the monitoring terminal receiving the coding result of the first layer of each channel of the remote sensing image, decompressing the coding result of the first layer of each channel to obtain a decompressed image, and identifying whether there is a salt tide intrusion according to the decompressed image; in response to the monitoring terminal receiving the coding results of the remaining layers of each channel of the remote sensing image and there is a salt tide intrusion, sequentially decompressing the coding results of the remaining layers, updating the decompressed image according to the decompression results, and obtaining the detailed information of the salt tide intrusion according to the finally obtained decompressed image.

2. The real-time monitoring method of salt tide based on satellite remote sensing according to claim 1, wherein The said The loss degree satisfies the expression: ； Among them, represents the loss degree when the target bit is used as the target pixel value and the sub-codeword of the layer of the homomorphic pixel value of the layer; loss degree, represents the number of homomorphic pixel values of the layer of the target pixel value; represents the th homomorphic pixel value of the layer of the target pixel value; represents the target pixel value; represents the number of pixel points corresponding to the th homomorphic pixel value of the layer of the target pixel value.

3. A real-time monitoring method for salt tides based on satellite remote sensing according to claim 1, characterized in that, The performing layered coding on each channel of the remote sensing image by using the sub-codewords of each layer of each pixel value includes: For each pixel point in each channel of the remote sensing image, taking the sub-codewords of each layer corresponding to the pixel value of the pixel point as the coding results of the pixel point in each layer; splicing the coding results of all pixel points in the same layer together in sequence as the coding result of each channel of the remote sensing image in this layer.

4. A real-time monitoring method for salt tides based on satellite remote sensing according to any one of claims 1-3, characterized in that, The using a variable-length coding algorithm to assign codewords to the pixel values in each channel of the remote sensing image includes: Obtaining the frequencies of the pixel values in the remote sensing image, and using Huffman coding to obtain the codewords of the pixel values according to the frequencies of the pixel values.

5. A real-time monitoring method for salt tides based on satellite remote sensing according to any one of claims 1-3, characterized in that, The using a variable-length coding algorithm to assign codewords to the pixel values in each channel of the remote sensing image includes: Obtaining the frequencies of the pixel values in the remote sensing image, sorting the pixel values according to the frequencies of the pixel values, and using Shannon-Fano coding to obtain the codewords of the pixel values according to the sorted order of the pixel values and the frequencies of the pixel values.

6. The real-time monitoring method of salt tide based on satellite remote sensing according to claim 5, characterized in that, The sorting the pixel values according to the frequencies of the pixel values includes: Sorting the pixel values in descending order according to the frequencies of the pixel values.

7. A real-time monitoring method for salt tides based on satellite remote sensing according to claim 5, characterized in that, The sorting the pixel values according to the frequencies of the pixel values includes: S201: Construct an empty sequence, denoted as the pixel sequence; S202: Add the pixel value with the highest frequency to the pixel sequence; S203: For all pixel values not yet added to the pixel sequence, determine the priority of the pixel value based on the frequency of the pixel value and the difference between the pixel value and the last pixel value in the current pixel sequence: , represents the priority of the -th pixel value not yet added to the pixel sequence; represents the -th pixel value not yet added to the pixel sequence; represents the last pixel value in the current pixel sequence; represents the -th pixel value not yet added to the pixel sequence; represents the absolute value symbol; Add the pixel value with the highest priority to the end of the pixel sequence; S204: Repeat S203 until all pixel values are added to the pixel sequence and stop the iteration.

8. A real-time monitoring system for salt tides based on satellite remote sensing, characterized in that, Including: A processor and a memory, the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the real-time salt tide monitoring method based on satellite remote sensing according to claim 1 is implemented.

Images