An image transmission method for low-power monitoring equipment

Abstract

The present invention belongs to the field of image transmission technology, and specifically relates to an image transmission method for low-power monitoring equipment, the method comprising: determining a standard order according to the definition requirement of the monitoring video collected by the monitoring equipment, adjusting the standard order according to the ratio of the actual power of the monitoring equipment to the estimated power, obtaining the adjusted order, evenly dividing all kinds of gray values ​​into kinds of gray levels, constructing an order gray co-occurrence matrix of the image according to the gray level pairs of all pixel pairs in any frame image of the monitoring video, selecting multiple elements from the main diagonal of the gray co-occurrence matrix and its vicinity as the first element, and recording the remaining elements as the second element, respectively, compressing and encoding all first pixel pairs and second pixel pairs according to the code words of the first element and the second element, obtaining the compressed encoding result of the image and transmitting it. The present invention reduces the energy consumption of the monitoring equipment when storing and transmitting images.

Description

Technical Field

[0001] The present invention relates to the field of image transmission technology, and more specifically, to an image transmission method for low-power monitoring equipment. Background Art

[0002] In order to optimize the energy consumption of monitoring equipment, the images captured by the monitoring equipment need to be compressed before transmission. This not only reduces the bandwidth requirements during data transmission, but also reduces the energy consumption of the device when processing and storing images, thereby extending the operating time of the monitoring equipment.

[0003] In the related technology, for example, the Chinese patent application document with application publication number CN119154993A discloses a method, system and equipment for transmission line visualization image compression detection, including: obtaining transmission line image data, environmental data and network data sent to the monitoring terminal, and dividing them into dynamic information and static information; obtaining a dynamic information evaluation value and a static information evaluation value; setting a dynamic information evaluation value threshold and a static information evaluation value threshold, and cutting the image and selecting a corresponding transmission strategy according to the relationship between the dynamic information evaluation value and the static information evaluation value and the dynamic information evaluation value threshold and the static information evaluation value threshold; compressing the cut image and sending it to the monitoring terminal for visualization; dynamically adjusting and optimizing according to the transmission effect; the invention dynamically adjusts the cutting block size and priority to make the image transmission fast and without distortion, thereby solving the problem of image distortion while ensuring the transmission speed in the prior art.

[0004] The power consumption of monitoring equipment is an ongoing process, especially in remote areas that are difficult to access or maintain frequently. Normally, the battery replacement time is predicted and scheduled based on the battery capacity of the monitoring equipment. However, in actual applications, external environmental factors such as temperature and humidity have a significant impact on the overall performance of the power supply and monitoring equipment. Especially in extreme climate conditions, such as severe cold weather, the internal resistance of the battery will increase, which may lead to additional and unnecessary power consumption. This increased energy consumption may shorten the time that the monitoring equipment can continue to operate before the power supply is replaced, resulting in a monitoring gap period during the scheduled maintenance cycle, affecting the continuity and reliability of monitoring. Summary of the invention

[0005] In order to solve the technical problem that the above-mentioned external environmental factors affect the overall performance of the power supply and monitoring equipment, resulting in a monitoring blank period before the monitoring equipment is replaced with a power supply, thereby affecting the continuity and reliability of monitoring, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides an image transmission method for a low-power monitoring device, comprising: determining a standard order according to a definition requirement for a monitoring video collected by the monitoring device, wherein the standard order is positively correlated with the definition requirement; during operation of the monitoring device, judging the power consumption of the monitoring device to obtain an estimated power of the monitoring device, adjusting the standard order according to a ratio of the actual power of the monitoring device to the estimated power, obtaining an adjusted order, and adjusting the standard order according to the adjusted order. Will All gray values ​​in the grayscales are used to construct the grayscale co-occurrence matrix; for any frame of the surveillance video: every two pixels with a fixed spatial position relationship in the image form a pixel pair; based on the grayscale pairs of all pixel pairs, the image is constructed. order gray-level co-occurrence matrix; select multiple elements from the main diagonal of the gray-level co-occurrence matrix and its vicinity as the first element, and record the remaining elements as the second element; compress and encode all first pixel pairs and second pixel pairs according to the code words of the first element and the second element, respectively, obtain the compressed encoding result of the image and transmit it; the first pixel pair refers to the pixel pair whose gray level belongs to the first element, and the second pixel pair refers to the pixel pair whose gray level belongs to the second element; the code words of the first element and the second element are respectively equal to the length of and The binary number, and the codeword of the first element and the codeword of the second element are different in the specific bit position, are the number of all first elements and all second elements respectively, Indicates rounding up.

[0007] The present invention, when transmitting monitoring videos, sets the parameters in the compression coding algorithm, i.e., the standard order, according to the definition requirements of the monitoring videos collected by the monitoring device in order to ensure that the definition of the received monitoring videos meets the requirements. Meanwhile, during the operation of the monitoring device, the power consumption of the monitoring device is judged regularly, and the parameters in the compression coding algorithm, i.e., the standard order, are adjusted regularly in combination with the change of the power consumption to adapt to the influence of the environment on the power consumption of the monitoring device, so as to better manage the energy use of the monitoring device and ensure the continuous operation of the monitoring device. The local similarity of the image is used to make the main diagonal and the gray level co-occurrence matrix of the monitoring device have the same local similarity. In view of the fact that the frequency of elements near the main diagonal is relatively large, the present invention selects multiple first elements from the main diagonal of the gray-level co-occurrence matrix and its vicinity, divides all elements in all gray-level co-occurrence matrices into first elements with relatively large frequencies and second elements with relatively small frequencies, compresses and encodes all first pixel pairs with relatively large numbers through codewords of first elements with relatively short lengths, and compresses and encodes all second pixel pairs with relatively small numbers through codewords of second elements with relatively long lengths, thereby reducing the amount of data in the compression encoding results of the image, thereby reducing the demand for storage space and transmission bandwidth, and thus reducing the energy consumption of the monitoring equipment when storing and transmitting images.

[0008] Preferably, the calculation formula of the standard order is: ; In the formula, is the standard order, To meet the requirements for the clarity of the surveillance video collected by the monitoring equipment, Indicates rounding up. The number of all grayscale values ​​in is equal to 256.

[0009] When the monitoring video is transmitted, the present invention determines the parameters in the compression coding algorithm in advance according to the definition requirement of the monitoring video collected by the monitoring device, so as to ensure that the definition of the received monitoring video meets the requirement.

[0010] Preferably, the calculation formula for the estimated power of the monitoring device is: ; In the formula, To monitor the estimated power consumption of the device, To monitor the initial power of the device when it starts working, To determine the power consumption of the monitoring device, The initial moment when the monitoring device starts working. This is the standard power consumption rate.

[0011] During the operation of the monitoring device, the present invention can better manage the energy use of the monitoring device by regularly judging the power consumption of the monitoring device, thereby ensuring the continuous operation of the monitoring device.

[0012] Preferably, the adjusted order The calculation formula is: ; In the formula, To monitor the actual power of the device, To monitor the estimated power consumption of the device, is the standard order, Indicates rounding up.

[0013] The present invention adjusts the standard order by the ratio of actual power to estimated power. When the power consumption rate of the monitoring device exceeds expectations, the clarity can be appropriately reduced to ensure the continuous operation of the monitoring device, and the energy consumption of the monitoring device can be effectively managed, so as to ensure that the monitoring device can continue to operate until the expected time node; at the same time, by limiting the adjusted order Always greater than or equal to , in order to ensure that the clarity of the received surveillance video can basically meet the actual requirements.

[0014] Preferably, the fixed spatial position relationship includes a fixed direction and a fixed step length, the fixed direction is one of the 0° direction, the 45° direction, the 90° direction and the 135° direction, and the fixed step length is An integer in the range of ; When the fixed direction is 0°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship; when the fixed direction is 45°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship; when the fixed direction is 90°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship; when the fixed direction is 135°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship.

[0015] Preferably, the grayscale pairs of all pixel pairs are used to construct an image. The invention provides a gray-level co-occurrence matrix, comprising: forming a gray-level pair of the pixel point pair by combining the gray-level values ​​of the two pixel points that form the pixel point pair; performing statistical analysis on the gray-level pairs of all pixel point pairs in the image to obtain the frequencies of all kinds of gray-level pairs; constructing the image according to the frequencies of all kinds of gray-level pairs. The gray-level co-occurrence matrix is The size of the gray-level co-occurrence matrix is , both the horizontal and vertical axes are gray levels, and each element in the gray level co-occurrence matrix corresponds to a gray level pair and its frequency.

[0016] Preferably, the step of selecting a plurality of elements from the main diagonal of the gray level co-occurrence matrix and its vicinity comprises: Any integer in the range as the value , Indicates rounding up; according to the value From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and as the first element, where are the horizontal and vertical coordinates of the element respectively.

[0017] Preferably, the step of selecting a plurality of elements from the main diagonal of the gray level co-occurrence matrix and its vicinity comprises: calculating Each integer in the range is taken as a value The amount of data transmission at Indicates rounding up; the integer with the smallest amount of data transmitted is used as the value , according to the value From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and as the first element, where are the horizontal and vertical coordinates of the element respectively.

[0018] The present invention uses different integers as numerical values ​​by calculation The amount of data transmitted at that time, from which the integer with the smallest amount of data transmission is selected as the value , which minimizes the data volume of the image compression encoding results, thereby minimizing the energy consumption of the monitoring equipment when storing and transmitting images.

[0019] Preferably, the calculation Each integer in the range is taken as a value The amount of data transmitted at that time includes: Integer in the range As a numerical value When, according to the integer From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and The element is taken as the first element, then the number of all first elements is obtained , To take the absolute value, Integer in the range As a numerical value Data transfer volume Satisfies the expression: ; ; ; Among them, the number of all elements in the gray-level co-occurrence matrix is ​​equal to , the number of elements except the first element is equal to , For the The frequency of the first element, For the The frequency of other elements.

[0020] Preferably, the codewords of the first and second elements are obtained by: obtaining a length corresponding to the sequence number of each first element in all first elements equal to The binary numbers of ; The length corresponding to the serial number of each second element in all second elements is equal to The binary numbers of ; In each binary number And each binary number The Add a bit after the bit as a specific bit to obtain each new binary number and each new binary number ,in, is a specific value, and , ; Requires each new binary number and each new binary number The digits at specific bits are different, then when each new binary number When the digit at a specific bit is 0, each new binary number The digital number at a specific bit is 1; and when each new binary number When the digit at a specific bit is 1, each new binary number The digital number at a specific bit is 0; each new binary number As the code word of each first element, each new binary number The codeword as the second element.

[0021] The present invention adds a specific bit position at a specific position in the codeword of the first element and the codeword of the second element, and requires that the codeword of the first element and the codeword of the second element have different digits at the specific bit position, so as to distinguish between two codewords of different lengths and ensure the decodability of the compression encoding result of the image.

[0022] The beneficial effects of the present invention are:

[0023] The present invention, when transmitting monitoring videos, sets the parameters in the compression coding algorithm, i.e., the standard order, according to the definition requirements of the monitoring videos collected by the monitoring device in order to ensure that the definition of the received monitoring videos meets the requirements. Meanwhile, during the operation of the monitoring device, the power consumption of the monitoring device is judged regularly, and the parameters in the compression coding algorithm, i.e., the standard order, are adjusted regularly in combination with the change of the power consumption to adapt to the influence of the environment on the power consumption of the monitoring device, so as to better manage the energy use of the monitoring device and ensure the continuous operation of the monitoring device. The local similarity of the image is used to make the main diagonal and the gray level co-occurrence matrix of the monitoring device have the same local similarity. In view of the fact that the frequency of elements near the main diagonal is relatively large, the present invention selects multiple first elements from the main diagonal of the gray-level co-occurrence matrix and its vicinity, divides all elements in all gray-level co-occurrence matrices into first elements with relatively large frequencies and second elements with relatively small frequencies, compresses and encodes all first pixel pairs with relatively large numbers through codewords of first elements with relatively short lengths, and compresses and encodes all second pixel pairs with relatively small numbers through codewords of second elements with relatively long lengths, thereby reducing the amount of data in the compression encoding results of the image, thereby reducing the demand for storage space and transmission bandwidth, and thus reducing the energy consumption of the monitoring equipment when storing and transmitting images. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0025] Figure 1 is a flow chart schematically illustrating an image transmission method for a low-power monitoring device in the present invention;

[0026] Figure 2 is a flow chart schematically illustrating step S2;

[0027] Figure 3 is a flow chart schematically illustrating step S3;

[0028] Figure 4 is a schematic diagram schematically showing a 0° direction, a 45° direction, a 90° direction, and a 135° direction;

[0029] Figure 5 is a schematic diagram schematically showing two pixels having a fixed spatial position relationship;

[0030] Figure 6 is a diagram schematically showing an 8-level grayscale co-occurrence matrix. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0032] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0033] The embodiment of the present invention discloses an image transmission method for a low-power monitoring device, referring to Figure 1 , comprising steps S1 to S3:

[0034] S1. Determine the standard order according to the definition requirements of the surveillance video collected by the surveillance equipment.

[0035] Specifically, the definition requirement for the surveillance video collected by the monitoring equipment mainly depends on the monitoring purpose and security requirements. For example, when the surveillance video collected by the monitoring equipment is mainly used in scenes requiring high-definition video such as face recognition and license plate recognition, the definition requirement for the surveillance video collected by the monitoring equipment is relatively high; areas with higher security levels, such as banks and airports, require higher definition of the surveillance video collected by the monitoring equipment in order to conduct accurate security analysis; therefore, for different monitoring equipment, the definition requirement for the surveillance video collected by different monitoring equipment can be set according to the actual monitoring purpose and security requirements. The value range of the definition requirement for the surveillance video collected by the monitoring equipment is In particular, when the surveillance video must be lossless, the clarity of the surveillance video collected by the surveillance equipment must be When the loss of surveillance video is acceptable, the clarity requirement for the surveillance video collected by the surveillance equipment is .

[0036] Furthermore, in order to ensure that the clarity of the received surveillance video meets the requirements, when the surveillance video is transmitted, the parameters in the compression coding algorithm are determined in advance according to the clarity requirements of the surveillance video collected by the monitoring device; the parameters in the compression coding algorithm of the present invention include the order of the grayscale co-occurrence matrix for constructing each frame of the surveillance video. Therefore, according to the clarity requirements of the surveillance video collected by the monitoring device, the standard order is determined, and the standard order is used to construct the grayscale co-occurrence matrix and is positively correlated with the clarity requirements; the calculation formula of the standard order is:

[0037] ;

[0038] In the formula, is the standard order, To meet the requirements for the clarity of the surveillance video collected by the monitoring equipment, Indicates rounding up. The number of all grayscale values ​​in is equal to 256.

[0039] S2. Determine the power consumption of the monitoring device to obtain the estimated power of the monitoring device, adjust the standard order according to the ratio of the actual power of the monitoring device to the estimated power, obtain the adjusted order, and evenly divide all grayscale values ​​into multiple grayscale levels according to the adjusted order.

[0040] See the flowchart of step S2. Figure 2 , including step S201 to step S202, specifically:

[0041] S201, determining the power consumption of a monitoring device to obtain an estimated power consumption of the monitoring device.

[0042] Specifically, the power consumption of the monitoring equipment is continuous, especially in remote locations or locations that are difficult to maintain frequently. By regularly judging the power consumption of the monitoring equipment, the energy use of the monitoring equipment can be better managed to ensure the continuous operation of the monitoring equipment. Therefore, during the operation of the monitoring equipment, the power consumption of the monitoring equipment is regularly judged to obtain the estimated power consumption of the monitoring equipment. The calculation formula for the estimated power consumption of the monitoring equipment is:

[0043] ;

[0044] In the formula, To monitor the estimated power consumption of the device, To monitor the initial power of the device when it starts working, To determine the power consumption of the monitoring device, The initial moment when the monitoring device starts working. This is the standard power consumption rate.

[0045] In this embodiment, the time interval between two adjacent power consumption judgments on the monitoring device is equal to 1 hour. In other embodiments, the time interval can be set according to actual application scenarios and requirements, and the time interval is taken as [0.5,2], in hours; the standard power loss rate is determined according to the ambient temperature at the time when the power consumption of the monitoring device is judged.

[0046] S202: adjusting the standard order according to the ratio of the actual power consumption of the monitoring device to the estimated power consumption to obtain an adjusted order.

[0047] Specifically, environmental changes may cause changes in the power consumption of the monitoring device. Regularly adjusting the parameters in the compression coding algorithm of the present invention in combination with the changes in power consumption can adapt to these changes. Therefore, the standard order is adjusted according to the ratio of the actual power consumption of the monitoring device to the estimated power consumption to obtain the adjusted order, which is used to construct the gray level co-occurrence matrix. The calculation formula is:

[0048] ;

[0049] In the formula, is the adjusted order, To monitor the actual power of the device, To monitor the estimated power consumption of the device, is the standard order, Indicates rounding up.

[0050] It should be noted that the smaller the actual power of the monitoring device is compared to the estimated power, the more it means that in the actual use scenario, the power consumption of the monitoring device has changed due to external factors. In order to ensure that the monitoring device can continue to operate until the expected time node, the standard order is adjusted by the ratio of the actual power to the estimated power. The smaller the ratio of the actual power to the estimated power, the smaller the adjusted order. At the same time, in order to ensure that the clarity of the received monitoring video can basically meet the actual requirements, when the ratio of the actual power to the estimated power is When the control is adjusted Always equal to .

[0051] It should be noted that before the next power consumption judgment of the monitoring device is performed, the gray-level co-occurrence matrix is ​​constructed based on the adjusted order obtained by the ratio of the actual power consumption of the monitoring device to the estimated power consumption using the current power consumption judgment of the monitoring device.

[0052] S203: According to the adjusted order, all gray values ​​are evenly divided into multiple gray levels.

[0053] Specifically, since the adjusted order is used to construct the gray level co-occurrence matrix, and the order of the gray level co-occurrence matrix determines the number of gray level types, therefore, according to the adjusted order ,Will All gray values ​​in the gray levels, among which Gray levels include All grayscale values ​​in the range, that is, All gray values ​​in the range belong to Gray levels.

[0054] It should be noted that the present invention obtains the estimated power consumption of the monitoring device by periodically judging the power consumption of the monitoring device, dynamically adjusts the standard order according to the ratio of the actual power consumption of the monitoring device to the estimated power consumption, and constructs the grayscale co-occurrence matrix of the image through the adjusted order to facilitate the subsequent compression encoding of the image according to the grayscale co-occurrence matrix. When the power consumption rate of the monitoring device exceeds expectations, the clarity can be appropriately reduced to ensure the continuous operation of the monitoring device, thereby effectively managing the energy consumption of the monitoring device and improving the efficiency and reliability of the monitoring system.

[0055] S3. For any frame image in the surveillance video, a grayscale co-occurrence matrix of the image is constructed according to the grayscale pairs of all pixel pairs in the image and the adjusted orders, a plurality of first elements are selected from the main diagonal of the grayscale co-occurrence matrix and its vicinity, and all first pixel pairs and second pixel pairs are compression-encoded according to the code words of the first elements and the second elements, respectively, to obtain the compression coding result of the image and transmit it.

[0056] See the flowchart of step S3. Figure 3 , including steps S301 to S303, specifically:

[0057] S301, constructing a gray level co-occurrence matrix of the image according to the gray level pairs of all pixel pairs in the image and the adjusted orders.

[0058] Specifically, for any frame image in the surveillance video, every two pixels with a fixed spatial position relationship in the image form a pixel pair; the fixed spatial position relationship includes a fixed direction and a fixed step size, the fixed direction is one of the 0° direction, the 45° direction, the 90° direction and the 135° direction, and the schematic diagrams of the 0° direction, the 45° direction, the 90° direction and the 135° direction are as shown in Figure 4 As shown; the fixed step size is An integer in the range.

[0059] For an image, the pixel point in the upper left corner of the image is taken as the origin, the horizontal direction to the left of the origin is taken as the horizontal axis, and the vertical direction downward from the origin is taken as the vertical axis; when the fixed direction is 0° and the fixed step size is When , the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship. Therefore, the coordinates in the image are The pixel points and coordinates are The pixels of the pixel point form a pixel point pair, as shown in the schematic diagram Figure 5 As shown in (1); when the fixed direction is 45° and the fixed step length is When , the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship. Therefore, the coordinates in the image are The pixel points and coordinates are The pixels of the pixel point form a pixel point pair, as shown in the schematic diagram Figure 5 As shown in (2); when the fixed direction is 90° and the fixed step length is When , the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship. Therefore, the coordinates in the image are The pixel points and coordinates are The pixels of the pixel point form a pixel point pair, as shown in the schematic diagram Figure 5 As shown in (3); when the fixed direction is 135° and the fixed step length is When , the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship. Therefore, the coordinates in the image are The pixel points and coordinates are The pixels of the pixel point form a pixel point pair, as shown in the schematic diagram Figure 5 As shown in (4).

[0060] Further, the grayscale values ​​of the two pixels constituting the pixel pair are combined into a grayscale pair of the pixel pair; the grayscale pairs of all pixel pairs in the image are statistically analyzed to obtain the frequencies of all kinds of grayscale pairs; and the image is constructed based on the frequencies of all kinds of grayscale pairs. The gray-level co-occurrence matrix is The size of the gray-level co-occurrence matrix is , is the adjusted order, the horizontal and vertical axes are gray levels, and each element in the gray level co-occurrence matrix corresponds to a gray level pair and its frequency; the schematic diagram of the 8-order gray level co-occurrence matrix is ​​as follows Figure 6 shown.

[0061] S302, selecting multiple first elements from the main diagonal of the gray-level co-occurrence matrix and its vicinity, and performing compression encoding on all first pixel pairs and second pixel pairs according to the code words of the first elements and the second elements, respectively, to obtain a compression encoding result of the image.

[0062] It should be noted that the grayscale co-occurrence matrix is ​​actually a joint distribution histogram of the grayscale values ​​of two pixels in the image. Since the image has local similarity, the frequency of elements on and near the main diagonal in the grayscale co-occurrence matrix of the image is relatively large, that is, the grayscale pairs of most pixel pairs in the image are distributed on and near the main diagonal of the grayscale co-occurrence matrix; therefore, multiple first elements are selected from the main diagonal of the grayscale co-occurrence matrix and its vicinity, and all first pixel pairs and second pixel pairs are compression encoded according to the codeword of the first element to obtain the compression encoding result of the image.

[0063] Specifically, from the image A plurality of elements are selected from the main diagonal and its vicinity of the gray-level co-occurrence matrix as first elements, and the remaining elements are recorded as second elements; and all first pixel pairs and second pixel pairs are compressed and encoded according to the code words of the first element and the second element, respectively, to obtain the compression encoding result of the image, wherein the first pixel pair refers to the pixel pair whose gray level pair belongs to the first element, and the second pixel pair refers to the pixel pair whose gray level pair belongs to the second element.

[0064] Among them, the codewords of the first element and the second element are respectively equal to and The binary number, , Indicates rounding up; and the codeword of the first element and the codeword of the second element are different in the specific bit position, then the method for obtaining the codewords of the first element and the second element is:

[0065] 1. Get the length of the sequence number of each first element in all first elements. The binary numbers of , is the number of all first elements in each binary number In the sequence from left to right, the first bit to the bits, and ; The length corresponding to the serial number of each second element in all second elements is equal to The binary numbers of , is the number of all second elements in each binary number In the sequence from left to right, the first bit to the bits, and ; The binary number is a number represented by two digits, 0 and 1.

[0066] 2. In each binary number And each binary number The Add a bit after the bit as a specific bit to obtain each new binary number and each new binary number ,in, is a specific value, and , ; then each new binary number The length is equal to , each new binary number The length is equal to ; Requires each new binary number and each new binary number The digits at specific bits are different, then when each new binary number When the digit at a specific bit is 0, each new binary number The digital number at a specific bit is 1; and when each new binary number When the digit at a specific bit is 1, each new binary number The digital number at a specific bit position is 0.

[0067] 3. Each new binary number As the code word of each first element, each new binary number The codeword as the second element.

[0068] It should be noted that the lengths of the codewords of the first element and the second element are different. There are codewords of two lengths in the compression coding result of the image. Mixing the codewords of the two lengths together will result in inaccurate decoding. Therefore, it is necessary to add a specific bit at a specific position in the codeword of the first element and the codeword of the second element, and require that the codeword of the first element and the codeword of the second element have different digits at the specific bit position, so as to distinguish the two codewords of different lengths and ensure the decodability of the compression coding result of the image.

[0069] In one embodiment, the step of selecting a plurality of elements from the main diagonal of the gray level co-occurrence matrix and its vicinity comprises: Any integer in the range as the value , is the adjusted order, Indicates rounding up; according to the value From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and as the first element, where are the horizontal and vertical coordinates of the element respectively.

[0070] It should be noted that the coordinates satisfy the expression and The elements of are the elements on the main diagonal of the gray-level co-occurrence matrix and the straight line parallel to the main diagonal, where , the coordinates satisfy the expression The elements of are the elements on the main diagonal of the gray-level co-occurrence matrix. and When the coordinates satisfy the expression The elements of are the elements on the straight line parallel to the main diagonal in the gray-level co-occurrence matrix. These elements are the elements on the main diagonal of the gray-level co-occurrence matrix and its vicinity.

[0071] It is further necessary to explain that Different integers in the range as values When the amount of data of the compressed encoding result of the obtained image is different, the amount of data transmission is different, and the degree of optimization of the energy consumption of the monitoring device is also different; therefore, the present invention calculates different integers as numerical values The amount of data transmitted at that time, from which the integer with the smallest amount of data transmission is selected as the value , which minimizes the data volume of the image compression encoding results, thereby minimizing the energy consumption of the monitoring equipment when storing and transmitting images.

[0072] In another embodiment, the step of selecting a plurality of elements from the main diagonal of the gray level co-occurrence matrix and its vicinity comprises: calculating Each integer in the range is taken as a value The amount of data transmission at is the adjusted order, Indicates rounding up; the integer with the smallest amount of data transmitted is used as the value , according to the value From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and as the first element, where are the horizontal and vertical coordinates of the element respectively.

[0073] Among them, Integer in the range As a numerical value When the number of first elements is obtained The calculation formula is:

[0074] ;

[0075] In the formula, is the adjusted order, To take the absolute value, the coordinates satisfy the expression The number of elements is equal to .

[0076] Among them, except for all the first elements, the remaining elements are the second elements, so the number of all second elements ; Among them, for all first elements, the length of the codeword when performing fixed-length compression encoding is equal to ; For all second elements, the length of the codeword when performing fixed-length compression encoding is equal to ; Subsequently, when all first pixel pairs and second pixel pairs are compressed and encoded according to the code words of the first element and the second element, two code words of different lengths are interspersed in the compressed encoding result of the obtained image. In order to accurately decode the compressed encoding result of the image, it is necessary to distinguish the two code words of different lengths. The present invention adds a specific bit at a specific position in the code word of the first element and the code word of the second element, and requires that the code word of the first element and the code word of the second element have different digits at the specific bit position, so as to distinguish the two code words of different lengths; In summary, the code words of the first element and the second element are respectively equal to and The binary number of .

[0077] Therefore, Integer in the range As a numerical value Data transfer volume The calculation formula is:

[0078] ;

[0079] ;

[0080] ;

[0081] In the formula, For the general Integer in the range As a numerical value The amount of data transferred when the first element is equal to , the number of all elements in the gray-level co-occurrence matrix is ​​equal to , then the number of all second elements obtained is equal to , the length of the first element of the codeword is equal to , the length of the codeword of the second element is equal to , the number of pixel pairs whose grayscale pairs belong to the first element is equal to , that is, the number of all first pixel pairs in the image is equal to , the number of pixel pairs whose grayscale values ​​belong to the second element is equal to , that is, the number of all first pixel pairs in the image is equal to , For the The frequency of the first element, For the The frequency of the second element, then the amount of data of the compressed encoding result of all the first pixel pairs in the image , the amount of data of the compressed encoding results of all second pixel pairs in the image , then the amount of data of the compressed encoding result of the image is equal to .

[0082] For example, for Figure 6 The 8-order gray-level co-occurrence matrix shown in FIG. 1 is composed of gray-level pairs of 100 pixel pairs; There are 8 elements on the main diagonal, including , , , , , , as well as The frequencies of these 8 elements are 0, 9, 15, 17, 25, 10, 4, and 0 respectively; taking these 8 elements as the first elements, the number of all first elements is , then the length of the codeword of the first element is equal to , the remaining elements as the second element, then the number of all second elements , then the length of the codeword of the second element is equal to ; The number of all first pixel pairs is , there are 100 pixel pairs in total, so the number of all second pixel pairs is ; then the amount of data of the compressed encoding result of the image is equal to ; Without dividing the elements in the gray-level co-occurrence matrix, the length of the codeword of all elements is equal to , the amount of data of the compressed encoding result of the image is equal to Therefore, the compression coding method of the present invention effectively reduces the data volume of the compression coding result of the image.

[0083] S303: Transmit the compression encoding result of the image.

[0084] Specifically, the adjusted order , Numeric and specific values As supplementary information, it is transmitted together with the compression encoding result of the image, so that the surveillance video receiving end can Determine all gray levels, based on the value Determine all first elements and all second elements combined with a specific value The code words of all the first elements and all the second elements are determined, and then the compression coding result of the image is accurately decoded.

[0085] It should be noted that, when the present invention transmits the surveillance video, in order to ensure that the clarity of the received surveillance video meets the requirements, the parameters in the compression coding algorithm, i.e., the standard order, are set according to the clarity requirements of the surveillance video collected by the monitoring device. At the same time, during the operation of the monitoring device, the power consumption of the monitoring device is judged regularly, and the parameters in the compression coding algorithm, i.e., the standard order, are adjusted regularly in combination with the changes in power consumption to adapt to the impact of the environment on the power consumption of the monitoring device. This can better manage the energy use of the monitoring device and ensure the continuous operation of the monitoring device. The local similarity of the image is utilized to make the main diagonal of its grayscale co-occurrence matrix According to the characteristic that the frequencies of elements on the gray level co-occurrence line and near the main diagonal are relatively large, the present invention selects multiple first elements from the main diagonal of the gray level co-occurrence matrix and its vicinity, divides all elements in all gray level co-occurrence matrices into first elements with relatively large frequencies and second elements with relatively small frequencies, compresses and encodes all first pixel pairs with relatively large numbers through code words of first elements with relatively short lengths, and compresses and encodes all second pixel pairs with relatively small numbers through code words of second elements with relatively long lengths, thereby reducing the data volume of the compression encoding results of the image, thereby reducing the demand for storage space and transmission bandwidth, and thus reducing the energy consumption of the monitoring equipment when storing and transmitting images.

[0086] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0087] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. An image transmission method for low-power monitoring equipment, characterized in that: include: Determine a standard order according to the definition requirement of the surveillance video collected by the surveillance device, wherein the standard order is positively correlated with the definition requirement; During the operation of the monitoring device, the power consumption of the monitoring device is judged to obtain the estimated power of the monitoring device, and the standard order is adjusted according to the ratio of the actual power of the monitoring device to the estimated power to obtain the adjusted order. Will All gray values ​​in the Gray levels are used to construct the gray-level co-occurrence matrix; For any frame of surveillance video: every two pixels with a fixed spatial position relationship in the image form a pixel pair; based on the gray level pairs of all pixel pairs, construct the image order gray-level co-occurrence matrix; select multiple elements from the main diagonal of the gray-level co-occurrence matrix and its vicinity as the first element, and record the remaining elements as the second element; compress and encode all first pixel pairs and second pixel pairs according to the code words of the first element and the second element, respectively, obtain the compressed encoding result of the image and transmit it; the first pixel pair refers to the pixel pair whose gray level belongs to the first element, and the second pixel pair refers to the pixel pair whose gray level belongs to the second element; the code words of the first element and the second element are respectively equal to the length of and The binary number, and the codeword of the first element and the codeword of the second element are different in the specific bit position, are the number of all first elements and all second elements respectively, Indicates rounding up.

2. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The calculation formula of the standard order is: ； In the formula, is the standard order, To meet the requirements for the clarity of the surveillance video collected by the monitoring equipment, Indicates rounding up. The number of all grayscale values ​​in is equal to 256.

3. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The calculation formula for the estimated power of the monitoring device is: ； In the formula, To monitor the estimated power consumption of the device, To monitor the initial power of the device when it starts working, To determine the power consumption of the monitoring device, The initial moment when the monitoring device starts working. This is the standard power consumption rate.

4. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The adjusted order The calculation formula is: ； In the formula, To monitor the actual power of the device, To monitor the estimated power consumption of the device, is the standard order, Indicates rounding up.

5. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The fixed spatial position relationship includes a fixed direction and a fixed step length, wherein the fixed direction is one of a 0° direction, a 45° direction, a 90° direction, and a 135° direction, and the fixed step length is An integer in the range of ; When the fixed direction is 0°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship; when the fixed direction is 45°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship; when the fixed direction is 90°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship; when the fixed direction is 135°, the coordinates in the image are The pixel points and coordinates are The pixel points are two pixel points with a fixed spatial position relationship.

6. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The gray level pairs of all pixel pairs are used to construct the image The gray-level co-occurrence matrix includes: The grayscale values ​​of the two pixels that make up the pixel pair form a grayscale pair of the pixel pair; statistical analysis is performed on the grayscale pairs of all pixel pairs in the image to obtain the frequency of all grayscale pairs; based on the frequency of all grayscale pairs, the image is constructed. The gray-level co-occurrence matrix is The size of the gray-level co-occurrence matrix is , both the horizontal and vertical axes are gray levels, and each element in the gray level co-occurrence matrix corresponds to a gray level pair and its frequency.

7. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The method of selecting a plurality of elements from the main diagonal of the gray level co-occurrence matrix and its vicinity includes: Will Any integer in the range as the value , Indicates rounding up; according to the value From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and as the first element, where are the horizontal and vertical coordinates of the element respectively.

8. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The method of selecting a plurality of elements from the main diagonal of the gray level co-occurrence matrix and its vicinity includes: calculate Each integer in the range is taken as a value The amount of data transmission at Indicates rounding up; the integer with the smallest amount of data transmitted is used as the value , according to the numerical value From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and as the first element, where are the horizontal and vertical coordinates of the element respectively.

9. The image transmission method for low-power monitoring equipment according to claim 8, characterized in that: The calculation Each integer in the range is taken as a value The amount of data transferred at the time includes: Will Integer in the range As a numerical value When, according to the integer From the main diagonal of the gray-level co-occurrence matrix and all the elements near it, select the coordinates that satisfy the expression and The element is taken as the first element, then the number of all first elements is obtained , To take the absolute value, Integer in the range As a numerical value Data transfer volume Satisfies the expression: ； ； ； Among them, the number of all elements in the gray-level co-occurrence matrix is ​​equal to , the number of elements except the first element is equal to , For the The frequency of the first element, For the The frequency of other elements.

10. The image transmission method for low-power monitoring equipment according to claim 1, characterized in that: The method for obtaining the codewords of the first element and the second element is: The length corresponding to the sequence number of each first element in all first elements is equal to The binary numbers of ; The length corresponding to the sequence number of each second element in all second elements is equal to The binary numbers of ; In each binary number And each binary number The Add a bit after the bit as a specific bit to obtain each new binary number and each new binary number ,in, is a specific value, and , ; Request each new binary number and each new binary number The digits at specific bits are different, then when each new binary number When the digit at a specific bit is 0, each new binary number The digital number at a specific bit is 1; and when each new binary number When the digit at a specific bit is 1, each new binary number The digital number at a specific bit position is 0; Each new binary number As the code word of each first element, each new binary number The codeword as the second element.

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