Remote data acquisition method based on tiantong-1 satellite communication

Abstract

The application discloses a remote data acquisition method based on Tianhong No.1 satellite communication and relates to the field of data transmission, and solves the problem of low efficiency of the existing remote data acquisition method, and comprises the following steps: S1, acquiring real-time data to be transmitted which needs satellite communication, dividing the acquired data to be transmitted into audio data to be transmitted and image data to be transmitted, screening the audio data to be transmitted in a cycle, obtaining audio transmission acquisition data according to the screening result, S2, screening the image data to be transmitted according to the audio transmission acquisition data, obtaining transmission image screening data according to the screening result, and S3, remotely transmitting the data to be transmitted according to the audio transmission acquisition data and the image transmission acquisition data, so that the application can improve the pertinence and transmission efficiency of the remote data acquisition method.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of data transmission, and relates to satellite communication technology, in particular to a remote data acquisition method based on Tianhong No. 1 satellite communication. BACKGROUND

[0002] The existing remote data acquisition method has the following defects when transmitting the collected data by satellite communication:

[0003] 1. When transmitting audio data by satellite, the existing remote data acquisition method usually needs to delete repeated sentences in the audio content to ensure the efficiency of remote audio data transmission. The existing technology usually only analyzes the repetition of audio semantic content, and does not further analyze the audio curve in the audio sentence to monitor the repetition of the audio sentence. It is difficult to accurately identify different emotional audio sentences, and it is difficult to fully retain the effective audio content, thereby easily leading to deviation of the remote audio transmission content.

[0004] 2. When transmitting image data by satellite, the existing remote data acquisition method does not distinguish between independent images and video stream images, and cannot monitor the repetition of independent images and video stream images respectively, so that the image repetition detection process lacks pertinence, and the image repetition monitoring process is prone to low efficiency, thereby affecting the efficiency of image remote transmission.

[0005] Therefore, we propose a remote data acquisition method based on Tianhong No. 1 satellite communication. SUMMARY

[0006] In view of the deficiencies of the prior art, the purpose of the present application is to provide a remote data acquisition method based on Tianhong No. 1 satellite communication, which aims to improve the pertinence of the remote data acquisition method and the efficiency of the remote transmission of communication data.

[0007] In order to achieve the above purpose, the application adopts the following technical scheme: a remote data acquisition method based on Tianhong No. 1 satellite communication, comprising the following steps:

[0008] Step S1: Real-time acquisition of the to-be-transmitted data that needs to be transmitted by satellite communication, segmentation of the acquired to-be-transmitted data into audio to-be-transmitted data and to-be-transmitted image data, and cyclic content screening of the audio to-be-transmitted data, to obtain audio transmission acquisition data according to the screening result;

[0009] Step S2: According to the audio transmission acquisition data, the to-be-transmitted image data is screened for repeated images, and transmission image screening data is obtained according to the screening result;

[0010] Step S3: Remote transmission of the to-be-transmitted data according to the audio transmission acquisition data and the image transmission acquisition data.

[0011] Further, the step S1 further comprises the following steps.

[0012] Step S11: Obtain a sample space region, and obtain the to-be-transmitted audio data and the to-be-transmitted image data generated by the sample space region;

[0013] Step S12: Perform key audio screening on the to-be-transmitted audio, and obtain transmission audio screening data according to a screening result;

[0014] Step S13: Set the to-be-transmitted image data and the transmission audio screening data as audio transmission collection data;

[0015] The step S12 further comprises the following steps.

[0016] Step S121: Use a voice recognition tool to intercept an audio segment in which a target type audio exists in the to-be-transmitted audio, to obtain a plurality of target audio segments;

[0017] Step S122: Arbitrarily select a sample target audio segment from the plurality of target audio segments, perform audio spectrum recognition on the sample target audio segment, screen the sample target audio segment according to a recognition result, and obtain segment screening audio corresponding to the sample target audio segment;

[0018] Step S123: Obtain the segment screening audio corresponding to each target audio segment, to obtain transmission audio screening data.

[0019] Further, the step S122 further comprises the following steps.

[0020] Step S1221: Mute the audio of the sample target audio segment except the target type audio, to obtain a mute target segment;

[0021] Step S1222: Obtain a frequency change curve generated by the mute target segment in a time sequence, to obtain a frequency time curve, and mark the obtained frequency time change curve in a plane rectangular coordinate system, to obtain a target audio curve coordinate graph;

[0022] Step S1223: Split the frequency time curve into a plurality of initial sub-segment curves, and arbitrarily select a sample sub-segment curve from the plurality of initial sub-segment curves;

[0023] Step S1224: Perform geometric coverage degree analysis on the sample sub-segment curve and a feature sub-segment curve, and obtain a curve coverage similarity corresponding to the feature sub-segment curve according to an analysis result;

[0024] Step S1225: According to the curve coverage similarity, the sample sub-segment curve is subjected to cyclic segment screening, and the cyclic audio segment corresponding to the sample sub-segment curve is obtained according to the screening result;

[0025] Step S1226: The cyclic audio segment is collected for each initial sub-segment curve, and the initial sub-segment curve in which the cyclic audio segment exists is divided into a cyclic sub-segment curve;

[0026] Step S1227: In the mute target segment, the original audio segment corresponding to the cyclic sub-segment curve is screened into an effective audio segment, the cyclic audio segment corresponding to the cyclic sub-segment curve is screened into an invalid audio segment, and the invalid audio segment is deleted to obtain a segment screening audio corresponding to the sample target audio segment.

[0027] Further, the step S1224 further includes the following steps:

[0028] The sample sub-segment curve is subjected to orthogonal movement, so that the midpoint of the sample curve coincides with the midpoint of the feature curve, the left end point of the sample sub-segment curve is set as a first sample end point, the right end point of the sample sub-segment curve is set as a second sample end point, the left end point of the feature sub-segment curve is set as a first feature end point, and the right end point of the feature sub-segment curve is set as a second feature end point;

[0029] The first sample end point, the second sample end point, the first feature end point, and the second feature end point are subjected to coordinate value comparison, and the geometric coverage left end point and the geometric coverage right end point are obtained according to the comparison result;

[0030] A straight line perpendicular to the coordinate x-axis is drawn through the geometric coverage left end point and the geometric coverage right end point, respectively, to obtain a left end point marker line and a right end point marker line, and a closed area surrounded by the sample sub-segment curve, the feature sub-segment curve, the left end point marker line, and the right end point marker line is set as a closed different area, and an area value of the closed different area is obtained to obtain a different area value.

[0031] Further, the step S1224 further includes the following steps:

[0032] The first sample end point and the second sample end point are subjected to geometric position analysis, the sample curve comparison area is divided according to the analysis result, and an area value of the sample comparison area is obtained;

[0033] The first feature end point and the second feature end point are subjected to geometric position analysis, the feature curve comparison area is divided according to the analysis result, and an area value of the feature comparison area is obtained;

[0034] The feature comparison area value, the different area value, and the sample comparison area value are used to calculate the curve coverage similarity corresponding to the feature sub-segment curve.

[0035] The step S1225 further includes the following steps:

[0036] A region coverage similarity reference interval is obtained. If the curve coverage similarity corresponding to the feature sub-segment curve is in the region coverage similarity reference interval, the feature sub-segment curve is divided into a pre-circulation sub-segment curve. If the curve coverage similarity corresponding to the feature sub-segment curve is not in the region coverage similarity reference interval, the feature sub-segment curve is divided into a non-circulation sub-segment curve.

[0037] Further, the step S1225 further includes the following steps:

[0038] If the feature sub-segment curve is a pre-circulation sub-segment curve, the initial sub-segment curve at the left end of the feature sub-segment curve is used to expand the feature sub-segment curve to obtain a first expanded feature curve. The initial sub-segment curve at the left end of the sample sub-segment curve is used to expand the sample sub-segment curve to obtain a first expanded sample curve. The curve coverage similarity between the first expanded feature curve and the first expanded sample curve is obtained. If the curve coverage similarity is in the region coverage similarity reference interval, the first expanded feature curve is divided into a pre-circulation sub-segment curve. If the curve coverage similarity is not in the region coverage similarity reference interval, the first expanded feature curve is divided into a non-circulation sub-segment curve.

[0039] By analogy, until the i+1th expanded feature curve obtained is a non-circulation field curve. If the time period audio covered by the ith expanded feature curve is a complete target audio segment, the ith expanded feature curve is divided into a valid circulation curve. If the circulation curve coverage time length is not a complete target audio segment, the ith expanded feature curve is divided into an invalid circulation curve.

[0040] Each initial sub-segment curve is traversed using the sample sub-segment curve to obtain multiple valid circulation curves. The audio segment corresponding to each valid circulation curve is obtained to obtain the circulation audio segment corresponding to the sample sub-segment curve.

[0041] Further, the step S2 further includes the following steps:

[0042] Step S21: Obtain audio transmission collection data. Obtain the to-be-transmitted image data according to the audio transmission collection data, and divide the to-be-transmitted image data into independent images and video stream images.

[0043] Step S22: randomly selecting a sample independent image from the obtained multiple independent images, using an image monitoring algorithm to monitor the sample independent image repeatedly, and obtaining a repeated independent image corresponding to the sample independent image according to the monitoring result;

[0044] Step S23: obtaining a repeated image corresponding to each independent image respectively, and obtaining independent image screening data;

[0045] Step S24: monitoring the video stream image repeatedly, and obtaining video stream image screening data according to the monitoring result;

[0046] Step S25: defining the video stream image screening data and the independent image screening data as image transmission collection data.

[0047] Further, the step S24 further includes the following steps:

[0048] Step S241: frame-intercepting the video stream image to obtain J1 video interception image to Ja video interception image;

[0049] Step S242: monitoring the repetition rate of the J1 video interception image and the J2 video interception image, and classifying the J2 video interception image according to the monitoring result;

[0050] Step S243: if the J2 video interception image is set as the same interception image, then analyzing the repetition degree of the J3 video interception image and the J1 video interception image, and classifying the J3 video interception image according to the analysis result; if the J2 video interception image is set as the different interception image, then analyzing the repetition degree of the J3 video interception image and the J2 video interception image, and classifying the J3 video interception image according to the analysis result; and so on, until the classification of the Ja video interception image is completed, the same interception image is deleted, and the video stream image screening data is obtained.

[0051] Further, the step S242 further includes the following steps:

[0052] marking the image object contour of the J1 video interception image, and obtaining multiple image object regions according to the image region surrounded by the closed contour, and naming the obtained multiple image object regions as T1 object region to Tb object region respectively;

[0053] naming the T1 object region in the J1 video interception image as a first image sample region, and using an edge detection algorithm to obtain a sample image object region in the J2 video interception image to obtain a second image sample region;

[0054] The J1 video cropped image is used to cover the J2 video cropped image. In the covered J2 video cropped image, the overlapping area of ​​the first image sample area and the second image sample area is marked to obtain the third image sample area.

[0055] The number of pixels in the first image sample region and the third image sample region are counted respectively to obtain the number of pixels in the first region and the number of pixels in the third region. The ratio of the number of pixels in the third region to the number of pixels in the first region is calculated to obtain the repeatability of region T1.

[0056] The region redundancy from object region T2 to object region Tb is obtained respectively, thus obtaining the region redundancy from T2 to Tb.

[0057] Obtain the ratio of the area of ​​object region T1 to object region Tb to the area of ​​the video cropped image J1, and get the area ratio of region T1 to region Tb.

[0058] The image repetition of the J2 video cropped image is obtained by calculating the area ratio of region T1 to region Tb and the repetition of region T1 to region Tb.

[0059] Obtain the preset range of image repetition. If the image repetition is within the preset range, set the J2 video cropped image to be the same cropped image. If the image repetition is not within the preset range, set the J2 video cropped image to be different cropped image.

[0060] Furthermore, step S3 also includes the following steps:

[0061] Acquire audio transmission data, and based on the audio transmission data, obtain audio data to be transmitted, image data to be transmitted, and audio screening data to be transmitted;

[0062] When using satellite communication technology to remotely transmit audio data, the audio data to be transmitted is replaced with the audio screening data and then transmitted.

[0063] Satellite communication technology is used to remotely transmit the image data to be transmitted, as follows:

[0064] Acquire image transmission acquisition data, and obtain video stream image screening data and independent image screening data based on the image transmission acquisition data;

[0065] When using satellite communication technology to remotely transmit independent images in audio data to be transmitted, the independent images are replaced with data by the independent image screening data and then transmitted.

[0066] When using satellite communication technology to remotely transmit video stream images in audio data to be transmitted, the independent images are replaced by video stream image screening data and transmitted.

[0067] In summary, due to the adoption of the above technical solutions, the present application has the following advantages:

[0068] 1. The present application can effectively identify different emotional audio statements and fully retain effective audio content, thereby ensuring the accuracy and transmission efficiency of remote audio transmission content, by analyzing the audio curve in the audio statement to further monitor the audio statement while repeatedly analyzing the semantic content of the audio.

[0069] 2. The present application can improve the relevance of image repetition detection and ensure the efficiency of image repetition monitoring and improve the efficiency of image remote transmission by distinguishing image data into independent images and video stream images and monitoring the independent images and video stream images for repetition. BRIEF DESCRIPTION OF DRAWINGS

[0070] For the convenience of those skilled in the art, the present application will be further described below with reference to the accompanying drawings.

[0071] Figure 1 is the implementation step diagram of the present application;

[0072] Figure 2 is the closed different area schematic diagram of the present application;

[0073] Figure 3 is the sample curve comparison area schematic diagram of the present application;

[0074] Figure 4 is the feature curve comparison area schematic diagram of the present application. DETAILED DESCRIPTION

[0075] The technical solutions of the present application will be described below in conjunction with the embodiments, obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0076] Embodiment one

[0077] Please refer to Figure 1 The present application provides a technical solution: a remote data acquisition method based on Tian Tong No. 1 satellite communication, including the following steps:

[0078] Step S1: Real-time acquisition of to-be-transmitted data requiring satellite communication, segmentation of the acquired to-be-transmitted data into audio to-be-transmitted data and to-be-transmitted image data, cyclic content screening of the audio to-be-transmitted data, and obtaining of audio transmission collection data according to the screening result;

[0079] The step S1 further includes the following steps:

[0080] Acquisition of a spatial region requiring remote data collection, obtaining of a plurality of data generation spatial regions, and arbitrary selection of a sample spatial region from the acquired plurality of data generation spatial regions, acquisition of to-be-transmitted data generated by the sample spatial region at a current time, acquisition of audio data in the to-be-transmitted data to obtain to-be-transmitted audio data, and acquisition of image data in the to-be-transmitted data to obtain to-be-transmitted image data;

[0081] It should be noted that:

[0082] In the present application, the collected and transmitted remote data only includes image data and audio data.

[0083] In the present application, the to-be-transmitted audio data includes pure audio data and an audio part in video data, and the to-be-transmitted image data includes an image cut from pure image data and video data.

[0084] Key audio screening of the to-be-transmitted audio, and obtaining of transmission audio screening data according to the screening result.

[0085] Specifically as follows:

[0086] Audio type comparison of the to-be-transmitted audio and target type audio using a voice recognition tool, cutting of an audio segment containing the target type audio to obtain a plurality of target audio segments.

[0087] It should be noted that:

[0088] The target type audio includes but is not limited to human voice, plant environment sound, and animal environment sound, and in the present application, the target type audio specifically refers to human voice.

[0089] Arbitrary selection of a sample target audio segment from the acquired plurality of target audio segments, audio spectrum recognition of the sample target audio segment, screening of the sample target audio segment according to the recognition result, and obtaining of a segment screening audio corresponding to the sample target audio segment.

[0090] Specifically as follows:

[0091] Silencing of audio other than the target type audio in the sample target audio segment using a silencing program to obtain a silencing target segment.

[0092] The frequency change curve generated by the time sequence of the sound elimination target segment is obtained to obtain a frequency-time curve, and the obtained frequency-time change curve is marked in a plane rectangular coordinate system to obtain a target audio curve coordinate graph;

[0093] It should be noted here that:

[0094] In this application, the abovementioned frequency change curve has a time sequence as the horizontal coordinate and a frequency value as the vertical coordinate in the target audio curve coordinate graph.

[0095] The frequency-time curve is divided into a plurality of initial sub-segment curves, and a sample sub-segment curve is selected from the plurality of initial sub-segment curves.

[0096] It should be noted here that:

[0097] In this application, the initial sub-segment curve corresponds to a time length that is the shortest time length required for reliable detection, identification, or analysis of a target type audio event corresponding to the target type audio.

[0098] In the target audio curve coordinate graph, a sample curve midpoint is obtained by acquiring a curve center point corresponding to the sample sub-segment curve, and a feature curve midpoint is obtained by acquiring a curve center point corresponding to a feature sub-segment curve selected from the initial sub-segment curves other than the sample sub-segment curve,

[0099] The sample sub-segment curve and the feature sub-segment curve are subjected to geometric coverage analysis, and the curve coverage similarity corresponding to the feature sub-segment curve is obtained according to the analysis result.

[0100] Specifically as follows:

[0101] The sample sub-segment curve is orthogonally moved to coincide the sample curve midpoint with the feature curve midpoint, the left end point of the sample sub-segment curve is set as a first sample end point, the right end point of the sample sub-segment curve is set as a second sample end point, the left end point of the feature sub-segment curve is set as a first feature end point, and the right end point of the feature sub-segment curve is set as a second feature end point.

[0102] The horizontal coordinate values of the first sample end point and the first feature end point are obtained to obtain a first sample horizontal coordinate value and a first feature horizontal coordinate value, if the first sample horizontal coordinate value is less than or equal to the first feature horizontal coordinate value, the first sample horizontal coordinate value is set as a geometric coverage left end point, and if the first sample horizontal coordinate value is greater than the first feature horizontal coordinate value, the first feature horizontal coordinate value is set as a geometric coverage left end point.

[0103] The abscissa value of the second sample end point and the second characteristic end point is obtained, and the second sample abscissa value and the second characteristic abscissa value are obtained. If the second sample abscissa value is less than or equal to the second characteristic abscissa value, the second characteristic abscissa value is set as the left end point of the geometric coverage. If the second sample abscissa value is greater than the second characteristic abscissa value, the second sample abscissa value is set as the right end point of the geometric coverage.

[0104] Please refer to Figure 2 , the left end point marking line and the right end point marking line are obtained by drawing straight lines perpendicular to the coordinate x-axis through the left end point of the geometric coverage and the right end point of the geometric coverage. The closed area surrounded by the sample sub-segment curve, the characteristic sub-segment curve, the left end point marking line and the right end point marking line is set as the closed distinct area, and the area value of the closed distinct area is obtained to obtain the distinct area area value.

[0105] Please refer to Figure 3 , the first sample end point perpendicular and the second sample end point perpendicular are obtained by drawing straight lines perpendicular to the coordinate x-axis through the first sample end point and the second sample end point. The ordinate value of the first sample end point is obtained to obtain the first sample ordinate value. The ordinate value of the second sample end point is obtained to obtain the second sample ordinate value. The first sample ordinate value and the second sample ordinate value are compared in value. If the first sample ordinate value is less than or equal to the second sample ordinate value, a straight line parallel to the coordinate x-axis is drawn through the first sample end point to obtain the sample horizontal reference line. If the first sample ordinate value is greater than the second sample ordinate value, a straight line parallel to the coordinate x-axis is drawn through the second sample end point to obtain the sample horizontal reference line. The closed area composed of the first sample end point perpendicular, the second sample end point perpendicular, the sample horizontal reference line and the sample sub-segment curve is set as the sample curve comparison area, and the area value of the sample curve comparison area is obtained to obtain the sample comparison area area value.

[0106] Please refer to Figure 4, the first feature end point and the second feature end point are respectively perpendicular to the straight line of the coordinate x axis, to obtain the first feature end point perpendicular line and the second feature end point perpendicular line, the first feature end point is subjected to the longitudinal coordinate value acquisition, to obtain the first feature longitudinal coordinate value, the second feature end point is subjected to the longitudinal coordinate value acquisition, to obtain the second feature longitudinal coordinate value, the first feature longitudinal coordinate value and the second feature longitudinal coordinate value are subjected to the numerical value comparison, if the first feature longitudinal coordinate value is less than or equal to the second feature longitudinal coordinate value, then the straight line parallel to the coordinate x axis is made through the first feature end point, to obtain the feature horizontal reference line, if the first feature longitudinal coordinate value is greater than the second feature longitudinal coordinate value, then the straight line parallel to the coordinate x axis is made through the second feature end point, to obtain the feature horizontal reference line, the closed area composed of the first feature end point perpendicular line, the second feature end point perpendicular line, the feature horizontal reference line and the feature subsegment curve is set as the feature curve comparison area, and the area value of the feature curve comparison area is obtained, to obtain the feature comparison area area value;

[0107] The feature comparison area area value, the dissimilar area area value and the sample comparison area area value are calculated to obtain the curve coverage similarity corresponding to the feature subsegment curve;

[0108] The curve coverage similarity corresponding to the feature subsegment curve is calculated, and the specific formula is as follows:

[0109] ;

[0110] Wherein, Fxd is the curve coverage similarity corresponding to the feature subsegment curve, Sxy is the dissimilar area area value, Stq is the feature comparison area area value, and Syq is the sample comparison area area value.

[0111] The region coverage similarity reference interval is obtained, if the curve coverage similarity corresponding to the feature subsegment curve is in the region coverage similarity reference interval, then the feature subsegment curve is divided into a pre-circulation subsegment curve, if the curve coverage similarity corresponding to the feature subsegment curve is not in the region coverage similarity reference interval, then the feature subsegment curve is divided into a non-circulation subsegment curve.

[0112] It should be noted here that:

[0113] In the present application, the historical feature subsegment curve divided into a pre-circulation subsegment curve is obtained, the curve coverage similarity corresponding to each historical feature subsegment curve is obtained respectively, and the obtained multiple curve coverage similarities are subjected to the numerical size comparison, the curve coverage similarity with the smallest value is marked as the lower limit of the region coverage similarity reference interval, and the curve coverage similarity with the largest value is marked as the upper limit of the region coverage similarity reference interval.

[0114] If the characteristic sub-segment curve is a pre-circulation sub-segment curve, the initial sub-segment curve at the left end of the characteristic sub-segment curve is used to expand the characteristic sub-segment curve to obtain a first expanded characteristic curve, the initial sub-segment curve at the left end of the sample sub-segment curve is used to expand the sample sub-segment curve to obtain a first expanded sample curve, the curve coverage similarity between the first expanded characteristic curve and the first expanded sample curve is obtained, if the curve coverage similarity is in the region coverage similarity reference interval, the first expanded characteristic curve is divided into a pre-circulation sub-segment curve, if the curve coverage similarity is not in the region coverage similarity reference interval, the first expanded characteristic curve is divided into a non-circulation sub-segment curve;

[0115] If the first expanded characteristic curve is a pre-circulation sub-segment curve, the initial sub-segment curve at the right end of the characteristic sub-segment curve is used to expand the first expanded characteristic curve to obtain a second expanded characteristic curve, the initial sub-segment curve at the right end of the first sample characteristic curve is used to expand the first sample characteristic curve to obtain a second expanded sample curve, the curve coverage similarity between the second expanded characteristic curve and the second expanded sample curve is obtained, if the curve coverage similarity is in the region coverage similarity reference interval, the second expanded characteristic curve is divided into a pre-circulation sub-segment curve, if the curve coverage similarity is not in the region coverage similarity reference interval, the second expanded characteristic curve is divided into a non-circulation sub-segment curve;

[0116] It should be noted here that:

[0117] Here, "when the first sample characteristic curve is a pre-circulation sub-segment curve, the initial sub-segment curve at the right end of the first sample characteristic curve is used to expand the first sample characteristic curve to obtain a first expanded sample curve" specifically refers to merging the initial sub-segment curve connected to the right end of the first sample characteristic curve with the first sample characteristic curve to expand the first sample characteristic curve and obtain a second expanded sample curve.

[0118] Here, "when the first expanded characteristic curve is a pre-circulation sub-segment curve, the initial sub-segment curve at the right end of the characteristic sub-segment curve is used to expand the first expanded characteristic curve to obtain a second expanded characteristic curve" specifically refers to merging the initial sub-segment curve connected to the right end of the first expanded characteristic curve with the first expanded characteristic curve to expand the first expanded characteristic curve and obtain a second expanded characteristic curve.

[0119] The above process is repeated until the i+1th expanded characteristic curve obtained is a non-circulation field curve, if the time period audio covered by the i th expanded characteristic curve is a complete target audio segment, the i th expanded characteristic curve is divided into an effective circulation curve, if the circulation curve coverage time length is not a complete target audio segment, the i th expanded characteristic curve is divided into an invalid circulation curve;

[0120] It should be noted here that:

[0121] In this application, the target type audio is specifically human voice, and the complete target audio segment referred to here is specifically a complete human voice language segment.

[0122] In this application, the second extended feature curve uses the initial sub-segment curve at the right end of the feature sub-segment curve to extend the first extended feature curve, and the third extended feature curve uses the initial sub-segment curve at the left end of the feature sub-segment curve to extend the second extended feature curve, and thus the extension sample curve and the extension feature curve extension curve selection position remain consistent.

[0123] Each initial sub-segment curve is traversed using a sample sub-segment curve to obtain multiple effective cycle curves, and each effective cycle curve corresponding to an audio segment is obtained to obtain a cycle audio segment corresponding to the sample sub-segment curve.

[0124] The acquisition process of the cycle audio segment corresponding to the sample sub-segment curve is repeated, and the cycle audio segment is collected for each initial sub-segment curve, and the initial sub-segment curve with the cycle audio segment is divided into a cycle sub-segment curve.

[0125] In the mute target segment, the original audio segment corresponding to the cycle sub-segment curve is screened into an effective audio segment, the cycle audio segment corresponding to the cycle sub-segment curve is screened into an invalid audio segment, and the invalid audio segment is deleted to obtain a segment screening audio corresponding to the sample target audio segment.

[0126] The segment screening audio corresponding to the sample target audio segment is repeated, and the segment screening audio corresponding to each target audio segment is obtained to obtain transmission audio screening data.

[0127] The to-be-transmitted image data and the transmission audio screening data are set as audio transmission collection data.

[0128] It should be noted here that:

[0129] The above step S1 can dynamically optimize the transmission link based on the depth analysis of the audio curve, reduce the loss of audio quality caused by electromagnetic interference and signal attenuation, and significantly improve the clarity and stability of the transmission, especially in the remote communication scene. At the same time, by compressing redundant data to reduce bandwidth occupation, efficiency and quality are improved. In addition, the emotional statement recognition technology gives the system the ability to perceive the emotional characteristics of the voice, accurately captures the user's emotional state by analyzing subtle changes in tone and speed, and provides key support for personalized interaction. This technology fusion not only promotes the upgrade of audio processing from single function to intelligence and scene.

[0130] Step S2: repeating image screening of the to-be-transmitted image data according to the audio transmission collection data, and obtaining transmission image screening data according to the screening result;

[0131] The step S2 further includes the following steps:

[0132] Obtaining audio transmission collection data, obtaining to-be-transmitted image data according to the audio transmission collection data, and dividing the to-be-transmitted image data into independent images and video stream images;

[0133] Randomly selecting a sample independent image from the obtained multiple independent images, using an image monitoring algorithm to monitor the sample independent image for repetition, and obtaining a repeated independent image corresponding to the sample independent image according to the monitoring result;

[0134] It should be noted that:

[0135] In the present application, the image monitoring algorithm referred to herein is an image feature point detection algorithm.

[0136] The repeated independent image corresponding to the sample independent image is repeatedly obtained, and the repeated image corresponding to each independent image is obtained to obtain independent image screening data;

[0137] Monitoring the video stream images for repetition, and obtaining video stream image screening data according to the monitoring result;

[0138] Specifically as follows:

[0139] Frame-wise intercepting the video stream images to obtain multiple video intercepted images, and marking the multiple video intercepted images as J1 video intercepted image to Ja video intercepted image according to the order of interception time;

[0140] It should be noted that:

[0141] In the present application, J1, J2, J3,..., and Ja in J1 video intercepted image to Ja video intercepted image are respectively video intercepted image numbers;

[0142] Monitoring the J1 video intercepted image and the J2 video intercepted image for repetition rate, and dividing the J2 video intercepted image into image types according to the monitoring result;

[0143] Specifically as follows:

[0144] Using an edge monitoring algorithm to mark the image object contour of the J1 video intercepted image, and obtaining multiple image object regions according to the image region surrounded by the closed contour, and naming the obtained multiple image object regions as T1 object region to Tb object region;

[0145] It should be noted that:

[0146] In the present application, T1, T2, T3……Tb in the T1 object region to the Tb object region are image object regions.

[0147] Name the T1 object region in the J1 video clipping image as a first image sample region, use an edge detection algorithm to obtain a sample image object region in the J2 video clipping image, and obtain a second image sample region;

[0148] Overlay the J2 video clipping image using the J1 video clipping image, mark the image overlap region of the first image sample region and the second image sample region in the overlaid J2 video clipping image, and obtain a third image sample region;

[0149] Respectively count the number of pixel points in the first image sample region and the third image sample region, obtain the first region pixel point number value and the third region pixel point number value, calculate the ratio of the third region pixel point number value to the first region pixel point number value, and obtain the T1 region repetition degree;

[0150] Repeat the process of obtaining the T1 region repetition degree, and obtain the T2 region repetition degree to the Tb region repetition degree corresponding to the T2 object region to the Tb object region;

[0151] Obtain the area values of the T1 object region to the Tb object region, obtain the T1 region area value to the Tb region area value, obtain the image area value of the J1 video clipping image, obtain the total area value, and obtain the ratio of the T1 region area value to the Tb region area value to the total area value, and obtain the T1 region area proportion to the Tb region area proportion;

[0152] Obtain the T1 region area proportion to the Tb region area proportion and the T1 region repetition degree to the Tb region repetition degree through calculation to obtain the image repetition degree corresponding to the J2 video clipping image;

[0153] Calculate the image repetition degree corresponding to the J2 video clipping image, and the specific formula is as follows:

[0154] ;

[0155] Wherein, Tcf is the image repetition degree corresponding to the J2 video clipping image, Qzi is the Ti region repetition degree, Mzi is the Ti region area proportion, b is the number value corresponding to the image object region, and b is an integer greater than 0;

[0156] It should be noted here that:

[0157] In the present application, the Ti area repetition degree referred to herein can be any one of T1 area repetition degree to Tb area repetition degree, and the Ti area area ratio referred to herein can be any one of T1 area repetition degree to Tb area repetition degree.

[0158] An image repetition degree preset interval is obtained, if the image repetition degree corresponding to the J2 video clipping image is in the image repetition degree preset interval, the J2 video clipping image is set as the same clipping image, if the image repetition degree corresponding to the J2 video clipping image is not in the image repetition degree preset interval, the J2 video clipping image is set as the different clipping image;

[0159] It should be noted here that:

[0160] The repeated independent images in the sample independent images are obtained, a plurality of repeated independent images are obtained, the minimum image repetition degree corresponding to each repeated independent image is obtained, a plurality of preset image repetition degrees are obtained, and the numerical value of the plurality of preset image repetition degrees is compared, the preset image repetition degree with the largest numerical value is set as the upper limit of the image repetition degree preset interval, and the preset image repetition degree with the smallest numerical value is set as the lower limit of the image repetition degree preset interval, to obtain the image repetition degree preset interval.

[0161] If the J2 video clipping image is set as the same clipping image, the repetition degree of the J3 video clipping image and the J1 video clipping image is analyzed, and the J3 video clipping image is classified according to the analysis result, if the J2 video clipping image is set as the different clipping image, the repetition degree of the J3 video clipping image and the J2 video clipping image is analyzed, and the J3 video clipping image is classified according to the analysis result, and so on, until the classification of the Ja video clipping image is completed, and the same clipping image is deleted, to obtain the video stream image screening data;

[0162] The video stream image screening data and the independent image screening data are defined as image transmission collection data;

[0163] Step S3: according to the audio transmission collection data and the image transmission collection data, the remote transmission of the to-be-transmitted data is performed;

[0164] The step S3 further includes the following steps:

[0165] The audio transmission collection data is obtained, the audio to-be-transmitted data, the to-be-transmitted image data and the transmission audio screening data are obtained according to the audio transmission collection data;

[0166] When the satellite communication technology is used to perform the remote transmission of the audio to-be-transmitted data, the transmission audio screening data is used to perform the data replacement and transmission of the audio to-be-transmitted data;

[0167] The satellite communication technology is used to remotely transmit the image data to be transmitted, and the specific process is as follows:

[0168] The image transmission collection data is acquired, the video stream image screening data and the independent image screening data are acquired according to the image transmission collection data;

[0169] When the satellite communication technology is used to remotely transmit the independent image in the audio data to be transmitted, the independent image screening data is used to replace the data of the independent image and transmit the independent image;

[0170] When the satellite communication technology is used to remotely transmit the video stream image in the audio data to be transmitted, the video stream image screening data is used to replace the data of the independent image and transmit the independent image;

[0171] It should be noted that:

[0172] The audio transmission collection data involved herein includes the image data to be transmitted and the transmission audio screening data.

[0173] In the present application, the satellite communication technology involved herein is based on Tianhong No. 1 satellite for communication transmission.

[0174] The preferred embodiments of the application disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details and limit the application to the specific embodiments. Obviously, according to the content of the present application, many modifications and changes can be made. The present application selects and specifically describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and use the application. The application is limited by the claims and their entire scope and equivalents.

Claims

1. A remote data acquisition method based on Tiantong-1 satellite communication, characterized in that, include: Step S1: Acquire the data to be transmitted for satellite communication in real time, divide the acquired data to be transmitted into audio data to be transmitted and image data to be transmitted, perform cyclic content screening on the audio data to be transmitted, obtain the audio screening data to be transmitted based on the screening results, and set the image data to be transmitted and the audio screening data to be transmitted as audio transmission acquisition data. Step S1 further includes the following steps: Step S11: Acquire the audio data and image data to be transmitted; Step S12: Perform key audio screening on the audio to be transmitted, and obtain the transmitted audio screening data based on the screening results; Step S13: Set the image data to be transmitted and the audio screening data to be transmitted as audio transmission acquisition data; Step S12 further includes the following steps: Step S121: Use a speech recognition tool to extract audio segments containing the target type of audio from the audio to be transmitted, and obtain multiple target audio segments; Step S122: Randomly select one sample target audio segment from the multiple acquired target audio segments, perform audio spectrum recognition on the sample target audio segment, and screen the sample target audio segment according to the recognition result to obtain the segment screening audio corresponding to the sample target audio segment; Step S123: Obtain the segment screening audio corresponding to each target audio segment to obtain the transmitted audio screening data; Step S122 further includes the following steps: Step S1221: Mute the audio of the sample target audio segment except for the target type audio to obtain the muted target segment; Step S1222: Obtain the frequency change curve generated by the noise reduction target segment in the time series to obtain the frequency-time curve, and mark the obtained frequency-time change curve in the Cartesian coordinate system to obtain the target audio curve coordinate graph; Step S1223: Divide the frequency-time curve into several initial sub-segment curves, and arbitrarily select one sample sub-segment curve from the multiple initial sub-segment curves obtained; Step S1224: Perform geometric coverage analysis on the sample sub-segment curve and the feature sub-segment curve, and obtain the curve coverage similarity corresponding to the feature sub-segment curve based on the analysis results; Step S1225: Perform loop segment screening on the sample sub-segment curves based on curve coverage similarity, and obtain the loop audio segments corresponding to the sample sub-segment curves based on the screening results; Step S1226: Collect loop audio segments for each initial sub-segment curve, and divide the initial sub-segment curve containing loop audio segments into loop sub-segment curves; Step S1227: In the target audio segment, the original audio segment corresponding to the loop segment curve is screened into a valid audio segment, the loop audio segment corresponding to the loop segment curve is screened into an invalid audio segment, and the invalid audio segment is deleted to obtain the segment screening audio corresponding to the target audio segment of the sample; Step S2: Repeated image screening is performed on the image data to be transmitted based on the audio transmission acquisition data, and the transmission image screening data is obtained based on the screening results; Step S2 further includes the following steps: Step S21: Acquire audio transmission acquisition data, acquire image data to be transmitted based on the audio transmission acquisition data, and divide the image data to be transmitted into independent images and video stream images; Step S22: Randomly select one sample independent image from the multiple independent images obtained, use the image detection algorithm to perform repeatability detection on the sample independent image, and obtain the repeating independent image corresponding to the sample independent image based on the detection result; Step S23: Obtain the repeating images corresponding to each independent image to obtain independent image screening data; Step S24: Perform repeatability monitoring on the video stream images and obtain video stream image screening data based on the monitoring results; Step S25: Define the video stream image screening data and the independent image screening data as image transmission acquisition data; Step S24 further includes the following steps: Step S241: Extract the video stream images frame by frame to obtain video cut images J1 to Ja; Step S242: Perform repetition rate monitoring on the images captured from video J1 and video J2, and classify the image type of the images captured from video J2 based on the monitoring results; Step S243: If the J2 video cropped image is set to the same cropped image, then perform a duplication analysis on the J3 video cropped image and the J1 video cropped image, and classify the J3 video cropped image according to the analysis results. If the J2 video cropped image is set to the different cropped image, then perform a duplication analysis on the J3 video cropped image and the J2 video cropped image, and classify the J3 video cropped image according to the analysis results. This process continues until the classification of the J1 video cropped images is completed. The same cropped images are deleted to obtain the video stream image screening data. Step S3: Remotely transmit the data to be transmitted based on the audio transmission acquisition data and the image transmission acquisition data.

2. The remote data acquisition method based on Tiantong-1 satellite communication according to claim 1, characterized in that, Step S1224 further includes the following steps: The sample sub-curve is orthogonally moved so that the midpoint of the sample curve coincides with the midpoint of the characteristic curve. The left endpoint of the sample sub-curve is set as the first sample endpoint, and the right endpoint of the sample sub-curve is set as the second sample endpoint. The left endpoint of the characteristic sub-curve is set as the first characteristic endpoint, and the right endpoint of the characteristic sub-curve is set as the second characteristic endpoint. The coordinate values ​​of the first sample endpoint, the second sample endpoint, the first feature endpoint, and the second feature endpoint are compared, and the left and right endpoints of geometric coverage are obtained based on the comparison results. Draw straight lines perpendicular to the x-axis through the left and right endpoints of the geometric coverage to obtain the left endpoint marker line and the right endpoint marker line. Set the closed region enclosed by the sample sub-segment curve, the feature sub-segment curve, the left endpoint marker line, and the right endpoint marker line as the closed dissimilar region, and obtain the area value of the dissimilar region.

3. The remote data acquisition method based on Tiantong-1 satellite communication according to claim 2, characterized in that, Step S1224 further includes the following steps: Geometric position analysis is performed on the first and second sample endpoints. Based on the analysis results, the sample curve comparison area is divided, and its area value is obtained to obtain the area value of the sample comparison area. Geometric position analysis is performed on the first and second feature endpoints. Based on the analysis results, the feature curve comparison region is divided, and its area value is obtained to obtain the area value of the feature comparison region. The curve coverage similarity corresponding to the feature segment curve is obtained by calculating the area values ​​of the feature comparison region, the area values ​​of the dissimilar region, and the area values ​​of the sample comparison region. Step S1225 further includes the following steps: Obtain the regional coverage similarity benchmark interval. If the curve coverage similarity corresponding to the feature segment curve is within the regional coverage similarity benchmark interval, then the feature segment curve is divided into a pre-cyclic segment curve. If the curve coverage similarity corresponding to the feature segment curve is not within the regional coverage similarity benchmark interval, then the feature segment curve is divided into a non-cyclic segment curve.

4. The remote data acquisition method based on Tiantong-1 satellite communication according to claim 3, characterized in that, Step S1225 further includes the following steps: If the feature segment curve is a pre-cyclic segment curve, the feature segment curve is expanded using the initial segment curve at the left end of the feature segment curve to obtain the first expanded feature curve. The sample segment curve is expanded using the initial segment curve at the left end of the sample segment curve to obtain the first expanded sample curve. The curve coverage similarity between the first expanded feature curve and the first expanded sample curve is obtained. If the curve coverage similarity is within the region coverage similarity benchmark interval, the first expanded feature curve is divided into a pre-cyclic segment curve. If the curve coverage similarity is not within the region coverage similarity benchmark interval, the first expanded feature curve is divided into a non-cyclic segment curve. Until the obtained (i+1)th extended feature curve is a non-cyclic field curve, the audio time period covered by the i-th extended feature curve is a complete target audio segment, and the i-th extended feature curve is divided into a valid cyclic curve. If the duration covered by the cyclic curve is not a complete target audio segment, the i-th extended feature curve is divided into an invalid cyclic curve. The sample sub-segment curve is used to traverse each initial sub-segment curve to obtain multiple valid loop curves. The audio segment corresponding to each valid loop curve is then obtained to obtain the loop audio segment corresponding to the sample sub-segment curve.

5. The remote data acquisition method based on Tiantong-1 satellite communication according to claim 1, characterized in that, Step S242 further includes the following steps: Image objects are marked on the captured images of J1 video, and multiple image object regions are obtained based on the image regions enclosed by the closed contours. The multiple image object regions are named T1 object region to Tb object region respectively. The object region T1 in the cropped image of video J1 is named the first image sample region. The object region in the sample image of video J2 is obtained by using an edge detection algorithm to obtain the second image sample region. The J1 video cropped image is used to cover the J2 video cropped image. In the covered J2 video cropped image, the overlapping area of ​​the first image sample area and the second image sample area is marked to obtain the third image sample area. The number of pixels in the first image sample region and the third image sample region are counted respectively to obtain the number of pixels in the first region and the number of pixels in the third region. The ratio of the number of pixels in the third region to the number of pixels in the first region is calculated to obtain the repeatability of region T1. The region redundancy from object region T2 to object region Tb is obtained respectively, thus obtaining the region redundancy from T2 to Tb. Obtain the ratio of the area of ​​object region T1 to object region Tb to the area of ​​the video cropped image J1, and get the area ratio of region T1 to region Tb. The image repetition of the J2 video cropped image is obtained by calculating the area ratio of region T1 to region Tb and the repetition of region T1 to region Tb. Get the preset range of image repetition. If the image repetition is within the preset range, set the J2 video cropped image to be the same cropped image. If the image repetition is not within the preset range, set the J2 video cropped image to be different cropped image.

6. The remote data acquisition method based on Tiantong-1 satellite communication according to claim 1, characterized in that, Step S3 further includes the following steps: Acquire audio transmission data, and based on the audio transmission data, obtain audio data to be transmitted, image data to be transmitted, and audio screening data to be transmitted; When using satellite communication technology to remotely transmit audio data, the audio data to be transmitted is replaced with the audio screening data and then transmitted. Satellite communication technology is used to remotely transmit the image data to be transmitted, as follows: Acquire image transmission acquisition data, and obtain video stream image screening data and independent image screening data based on the image transmission acquisition data; When using satellite communication technology to remotely transmit independent images in audio data to be transmitted, the independent images are replaced with data by the independent image screening data and then transmitted. When using satellite communication technology to remotely transmit video stream images within audio data to be transmitted, the video stream images are used to filter data and replace individual images with data before transmission.

Images