CN108053440B - Method for processing day-by-day snow coverage rate image - Google Patents
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Abstract
The invention provides a method for processing a day-by-day snow cover rate image, which is characterized in that an morning star snow cover rate image and an afternoon star snow cover rate image of the current day are synthesized and adjusted into snow cover rates corresponding to pixels of snow in the images, and then the snow cover rate image is continuously processed in multiple steps; in the processing process of each step, the snow coverage rate image obtained by the previous step in each step is used as a basis, the pixel with the cloud type is adjusted, the snow coverage rate corresponding to the pixel with the snow type adjusted from the cloud to the snow is adjusted, and finally the final snow coverage rate image of the current day is obtained; by taking the combination of multiple methods into consideration, the snow coverage rate image with low cloud coverage (or no cloud) and snow coverage details is obtained, and the requirement of high Asia areas on day-by-day snow coverage rate images can be met.
Description
Technical Field
The invention relates to the technical field of satellite remote sensing image processing, in particular to a method for processing a day-by-day snow coverage rate image.
Background
The high Asia area is an Asian high altitude area with Qinghai-Tibet plateau as the center, is an important distribution area of global accumulated snow, is one of three stable accumulated snow coverage areas in China, is an area with the largest accumulated snow coverage area and the main areas with concentrated snow at low latitude and middle latitude on the earth, is a source of a plurality of large rivers, and is one of main sources of surface runoff and underground water, and the ablation of the accumulated snow has important influence on surface water balance and regional climate. Some researches show that the snow in the high Asia region has obvious warming trend, the frozen layer of the snow has obvious change, the dynamic change of the snow in the high Asia region is an important index for diagnosing the response of the snow in the mountainous region to the global warming, researching the change of the middle Asia environment and the like, and the snow in the high Asia region is very important for accurately and dynamically monitoring the snow in the high Asia region. In addition, the snow cover is closely related to hydrology and biology in the surrounding areas of high Asia, so that the space-time pattern information of the snow cover of the high Asia is very important for scientific research and management application of the areas.
At present, satellite remote sensing plays an important role in dynamic monitoring of snow by virtue of the advantages of large scale, rapidness, periodicity, multi-scale, multi-temporal phase, low cost and the like, wherein MODIS is widely applied by the characteristics of medium spatial resolution and high temporal resolution, and particularly has higher monitoring precision in the aspects of snow remote sensing binary products and coverage rate products, but in MODIS products in high Asia regions, the influence of cloud coverage causes the problem of influence on the cloud of the MODIS products to be considered in daily monitoring; the existing method for eliminating the cloud influence has the following main effects: the multi-sensor fusion and passive microwave data are combined to remove clouds, when the pixel in the MODIS snow coverage rate image is a cloud and the corresponding pixel of a passive microwave sensor (such as AMSR-E) snow equivalent product is snow, the pixel in the MODIS snow coverage rate image, which is the cloud, is assigned as snow, and the same principle is adopted for land, lake and ice, the lost data of the passive microwave sensor is replaced by the value of the previous day, but the snow coverage rate cannot be estimated; the method comprises the steps of fitting an accumulated snow boundary by using a function, using an MODIS accumulated snow coverage rate image of continuous days as a computing unit, requiring the MODIS accumulated snow boundary to be a continuous space-time flow which can be represented by a three-dimensional implicit function in the days, and finding the accumulated snow boundary of a cloud coverage part through the implicit function, wherein accumulated snow is in the boundary, and land is out of the boundary.
Because seasonal accumulated snow has the characteristics of short occurrence time and thin snow layer in high Asia regions, particularly in Tibet plateau regions, dynamic information of the snow coverage rate of few clouds (cloud coverage is less than 10%) day by day is urgently needed in the research of the problems of water circulation and the like; however, in the current method for processing the day-by-day snow coverage rate image with high cloud amount, a method of multi-sensor fusion or function fitting of snow boundary is usually adopted to ensure the effect of eliminating cloud influence, but the method cannot estimate the snow coverage rate of the pixel, or only can determine the snow coverage boundary, cannot reflect the specific details of snow coverage at the boundary, and is difficult to meet the requirement of the day-by-day snow coverage rate image product in the high asian area.
Disclosure of Invention
To overcome the above problems or to at least partially solve the above problems, the present invention provides a method of processing a day-by-day snow coverage image.
According to an aspect of the invention, there is provided a method of processing a day-by-day snow coverage image, comprising:
acquiring a morning star snow coverage rate image and an afternoon star snow coverage rate image of the current day, synthesizing the morning star snow coverage rate image and the afternoon star snow coverage rate image of the current day into a synthetic image, and adjusting and integrating snow coverage rates corresponding to pixels of snow in the synthetic image to obtain a first snow coverage rate image of the current day;
based on the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day, adjusting the pixel of which the type is cloud in the first snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a second snow coverage rate image of the current day;
based on the type of a pixel adjacent to the pixel with the cloud type in the second snow coverage rate image of the current day, adjusting the pixel with the cloud type in the second snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to snow so as to obtain a third snow coverage rate image of the current day;
based on the elevation of the pixel in the third snow coverage image of the current day, adjusting the pixel of which the type is cloud in the third snow coverage image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a fourth snow coverage image of the current day;
based on a fourth snow coverage image containing preset days of the day, adjusting the pixel with the cloud type in the fourth snow coverage image of the day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to be snow so as to obtain a final snow coverage image of the day;
wherein, the types of the picture elements comprise land, lake ice, snow and cloud.
In yet another aspect of the invention, a computer program product is provided, the computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method described above.
In yet another aspect of the present invention, a non-transitory computer-readable storage medium is provided, which stores a computer program that causes a computer to perform the above-described method.
The invention provides a method for processing a day-by-day snow cover rate image, which is characterized in that an morning star snow cover rate image and an afternoon star snow cover rate image of the current day are synthesized and adjusted into snow cover rates corresponding to pixels of snow in the images, and then the snow cover rate image is continuously processed in multiple steps; in the processing process of each step, the snow coverage rate image obtained by the previous step in each step is used as a basis, the pixel with the cloud type is adjusted, the snow coverage rate corresponding to the pixel with the snow type adjusted from the cloud to the snow is adjusted, and finally the final snow coverage rate image of the current day is obtained; by taking the combination of multiple methods into consideration, the snow coverage rate image with low cloud coverage and snow coverage details is obtained, and the requirement of high Asia regions on day-by-day snow coverage rate images can be met.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for MODIS day-by-day snow coverage image processing according to an embodiment of the present invention;
FIG. 2 is a graph of the remaining cloud cover after the snow coverage image is cloud-removed according to various steps of the embodiment of the invention;
FIG. 3 is a comparison graph of spatial coverage of a snow remote sensing binary image and a final snow coverage image of an embodiment of the present invention;
fig. 4 is a schematic diagram of the snow number of the snow remote sensing binary image and the final snow coverage image according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In one embodiment of the present invention, referring to fig. 1, there is provided a method of processing a day-by-day snow coverage image, comprising:
s11, acquiring a current morning star snow coverage rate image and a current afternoon star snow coverage rate image, synthesizing the current morning star snow coverage rate image and the current afternoon star snow coverage rate image into a synthetic image, and adjusting and integrating snow coverage rates corresponding to pixels of snow in the synthetic image to obtain a current first snow coverage rate image;
s12, based on the first snow coverage image of the previous day and the first snow coverage image of the next day, adjusting the pixel with the cloud type in the first snow coverage image of the current day, and adjusting the snow coverage corresponding to the pixel with the cloud type adjusted to be snow so as to obtain a second snow coverage image of the current day;
s13, based on the type of the pixel adjacent to the pixel with the cloud type in the second snow coverage image of the current day, adjusting the pixel with the cloud type in the second snow coverage image of the current day, and adjusting the snow coverage corresponding to the pixel with the cloud type adjusted to be snow so as to obtain a third snow coverage image of the current day;
s14, based on the elevation of the pixel in the third snow coverage image of the current day, adjusting the pixel of which the type is cloud in the third snow coverage image of the current day, and adjusting the snow coverage corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a fourth snow coverage image of the current day;
s15, based on a fourth snow coverage image containing preset days of the day, adjusting the pixel of which the type is cloud in the fourth snow coverage image of the day, and adjusting the snow coverage corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a final snow coverage image of the day;
wherein, the types of the picture elements comprise land, lake ice, snow and cloud.
Specifically, according to the characteristics of the high asian region, the embodiment considers the combination of multiple methods, a method with good reliability is preferentially adopted in the combination process, a method with poor reliability is placed behind the combination process, the day-by-day snow coverage rate image is processed through multiple steps, and the accuracy of the day-by-day snow coverage rate image can be maintained to the greatest extent through the combination of the methods.
Based on the day-by-day snow coverage rate image, the day-by-day snow coverage rate image is processed by adopting the five steps S11-S15, and the five steps S11-S15 can be abbreviated as 'composition in the morning and afternoon', 'composition in three days', 'adjacent pixels', 'snow land stabilization' and 'maximum land' in sequence.
In the step of "synthesizing at noon and afternoon", in the process of synthesizing the morning star snow coverage image and the afternoon star snow coverage image of the current day into a synthesized image, the type of each pixel in the synthesized image is determined first, and then the color value of each pixel is adjusted according to the type of each pixel in the synthesized image. In the case of cloudy days (high cloud coverage), assuming that the snow coverage remains substantially unchanged for a short time, the following rule is applied in determining the type of each pixel in the composite image:
for any pixel in the synthesized image, taking any pixel as a target pixel, and acquiring a first type of the pixel with the same position as the target pixel in the morning star snow coverage rate image of the day and a second type of the pixel with the same position as the target pixel in the afternoon star snow coverage rate image of the day;
if the first type is the same as the second type, taking the first type or the second type as the type of the target pixel in the synthetic image;
if at least one of the first type and the second type is lake or lake ice, taking the corresponding lake or lake ice as the type of the target pixel in the synthetic image;
if the first type is different from the second type and is respectively land or snow, taking the first type as the type of a target pixel in the synthetic image;
if one of the first type and the second type is cloud and the other is land or snow, taking the corresponding land or snow as the type of the target pixel in the composite image;
and if the data of the first type and the data of the second type are both missing or invalid, setting the type of the target pixel in the synthetic image as cloud.
The type of picture element can be embodied by adjusting the color value of the picture element. For example, if the color of the preset land is brown, the color value of the pixel of the type land is adjusted to be a brown color value.
The regulation of the snow cover rate corresponding to the pixel with the snow type in the integrated image is as follows:
if the first type and the second type are both snow, adjusting the snow coverage rate corresponding to the target pixel in the synthetic image to be the average value of the snow coverage rates corresponding to the pixels with the same positions as the target pixel in the morning star snow coverage rate image and afternoon star snow coverage rate image of the current day;
if the first type is snow cover and the second type is cloud or land, adjusting the snow cover rate corresponding to the target pixel in the composite image to be the snow cover rate corresponding to the pixel with the same position as the target pixel in the morning star snow cover rate image of the day;
if the second type is snow cover and the first type is cloud, the snow cover rate corresponding to the target pixel in the synthetic image is adjusted to be the snow cover rate corresponding to the pixel with the same position as the target pixel in the afternoon star snow cover rate image of the day.
The coverage of the accumulated snow may also be embodied by adjusting the color value, or may also be embodied by other methods, which is not limited herein.
In the embodiment, an image of the coverage rate of the accumulated snow of the morning star and an image of the coverage rate of the accumulated snow of the afternoon star are synthesized, the images are adjusted and integrated into the coverage rate of the accumulated snow corresponding to the pixel of which the type is the accumulated snow, and then the images of the coverage rate of the accumulated snow are continuously processed in multiple steps; in the processing process of each step, the snow coverage rate image obtained by the previous step in each step is used as a basis, the pixel with the cloud type is adjusted, the snow coverage rate corresponding to the pixel with the snow type adjusted from the cloud to the snow is adjusted, and finally the final snow coverage rate image of the current day is obtained; by taking the combination of multiple methods into consideration, the snow coverage rate image with low cloud coverage and snow coverage details is obtained, and the requirement of high Asia regions on day-by-day snow coverage rate images can be met.
As shown in fig. 2, day-by-day snow coverage images of high asian areas in a certain period of time are selected for processing, and MOD10a1 and MYD10a1 respectively represent an morning star snow coverage image and an afternoon star snow coverage image in the period of time; during this time, the average cloud numbers of MOD10a1 (i.e., MOD in fig. 2) and MYD10a1 (i.e., MYD in fig. 2) were 39.3% and 43.6%, respectively, and after the "composition in the morning and afternoon" treatment, the removed cloud number was about 8.7%, and the average cloud number was reduced to 32.8%, and the treated images could not be directly used for real-time dynamic monitoring of snow accumulation, so further treatment was required. Because the snow melting probability on cloudy days (cloud is more) is low, when the time window is 3 days, the snow accumulation coverage rate is considered to be basically maintained unchanged in the time span, and the image can be further processed by adopting a three-day synthesis method.
Based on the above embodiment, based on the first snow coverage image of the previous day and the first snow coverage image of the subsequent day, adjusting the pixel of which the type is cloud in the first snow coverage image of the current day, and adjusting the snow coverage corresponding to the pixel of which the type is adjusted from cloud to snow, includes:
taking a pixel with the cloud type in the first snow coverage rate image of the current day as a first pixel, taking any first pixel as a target first pixel for any first pixel, and acquiring the types of the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day;
if at least one of the types of the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day is a lake or lake ice, adjusting the type of the target first pixel to be the corresponding lake or lake ice;
if the types of the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day are both the land, adjusting the type of the target first pixel to be the land;
if the types of the pixels at the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day are both snow, the type of the target first pixel is adjusted to be snow, and the snow coverage rate corresponding to the target first pixel is adjusted to be the average value of the snow coverage rates corresponding to the pixels at the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day.
As shown in fig. 2, after the "three-day synthesis" method, the average cloud content was reduced to 25.7%, and the removed cloud content was about 7.1%; due to the spatial continuity of snow, the image can be further processed by adopting a method of 'adjacent pixels'.
Based on the above embodiment, based on the type of the pixel adjacent to the pixel of which the type is cloud in the second snow coverage image of the current day, the pixel of which the type is cloud in the second snow coverage image of the current day is adjusted, and the snow coverage corresponding to the pixel of which the type is adjusted from cloud to snow is adjusted, including:
taking a pixel with the cloud type in the second snow coverage rate image of the current day as a second pixel, taking any second pixel as a target second pixel for any second pixel, and acquiring the types of four pixels directly adjacent to the target second pixel;
if at least three pixels in the four pixels directly adjacent to the target second pixel are snow, adjusting the type of the target second pixel to be snow, and adjusting the snow coverage rate corresponding to the target second pixel to be the average value of the snow coverage rates corresponding to the snow-accumulated pixels in the eight pixels adjacent to the target second pixel;
and if at least three pixel types in the four pixels directly adjacent to the target second pixel are land, adjusting the type of the target second pixel to be land.
As shown in fig. 2, cloud pollution is removed by using a method of 'adjacent pixels', the removed cloud amount is about 0.57%, the method has less cloud amount removal and higher precision, and can well remove a small range of fragmentary pixels with cloud types; in high Asia regions, there are perennial snow and ice and land (regions with little snow), and the method of 'stabilizing snow land' can fully utilize the characteristics.
Based on the above embodiment, based on the elevation of the pixel in the third snow coverage image of the current day, adjusting the pixel of which the type is cloud in the third snow coverage image of the current day, and adjusting the snow coverage corresponding to the pixel of which the type is adjusted from cloud to snow, includes:
taking a pixel with the cloud type in a third accumulated snow coverage rate image of the current day as a third pixel, taking any third pixel as a target third pixel for any third pixel, acquiring the elevation of the target third pixel, and determining the time period of the season of the current day;
if the elevation of the target third pixel is larger than the first preset value, the type of the target third pixel is adjusted to be snow cover, and the snow cover rate corresponding to the target third pixel is adjusted to be the average value of the snow cover rates corresponding to the pixels with the same positions as the target third pixel in all third snow cover rate images in the time period;
if the elevation of the target third pixel is smaller than the first preset value and larger than the second preset value, and the proportion of the type of the pixel, which is the same as the position of the target third pixel, of the accumulated snow or the number of cloud days in all the third accumulated snow coverage rate images in the time period to the total number of days in the time period exceeds the third preset value, adjusting the type of the target third pixel to be the accumulated snow, and adjusting the accumulated snow coverage rate corresponding to the target third pixel to be the average value of the accumulated snow coverage rate corresponding to the pixel, which is the same as the position of the target third pixel, in all the third accumulated snow coverage rate images in the time period;
and if the elevation of the target third pixel is smaller than a second preset value, in all third accumulated snow coverage rate images in the time period, the proportion of the number of days of which the pixel is the same as the position of the target third pixel and is cloud to the total number of days of the time period is smaller than a fourth preset value, and the sum of the number of days of which the pixel is the same as the position of the target third pixel and the number of days of which the pixel is land is the total number of days of the time period, adjusting the type of the target third pixel to land.
The first preset value may be set to 5800m, the second preset value may be 3000m, the third preset value may be set to 90%, and the fourth preset value may be set to 20%.
The time period of the season refers to that the total time period is divided into a plurality of time periods according to the characteristic of the region, for example, the accumulated snow year is taken as the total time period, and 7 months and 1 day to the next 6 months and 30 days of each year are taken as an accumulated snow year. One snow year is divided into 2 seasons: summer is from 7 months 1 to 9 months 30 days, winter is from 10 months 1 to next year 4 months 30 days, and summer is from 5 months 1 to 6 months 30 days.
As shown in fig. 2, the cloud amount of the image processed by the method of "stabilizing snow land" is about 5.2%, the cloud coverage of the image processed by the method is still 20%, and the method of "maximum land" has great uncertainty, but can effectively remove cloud pollution.
Based on the above embodiment, based on the fourth snow coverage image including the preset number of days of the current day, adjusting the pixel of which the type is cloud in the fourth snow coverage image of the current day, and adjusting the snow coverage corresponding to the pixel of which the type is adjusted from cloud to snow, includes:
taking a pixel with the cloud type in the fourth snow coverage rate image of the current day as a fourth pixel, taking any fourth pixel as a target fourth pixel for any fourth pixel, and acquiring the types of the pixels with the same positions as the target fourth pixel in all fourth snow coverage rate images in preset days;
if the type of the pixel at the same position as the target fourth pixel in the fourth snow coverage image of at least one day in the preset days is a lake or lake ice, adjusting the type of the target fourth pixel to be the corresponding lake or lake ice;
if the type of the pixel at the same position as the fourth pixel of the target in the fourth snow coverage rate image of at least one day in the preset days is the land, adjusting the type of the fourth pixel of the target to be the land;
if the type of the pixel with the same position as the target fourth pixel in all the fourth snow coverage rate images of the preset days is cloud or snow, the type of the target fourth pixel is adjusted to be snow, and the snow coverage rate corresponding to the target fourth pixel is adjusted to be the average value of the snow coverage rate corresponding to the pixel with the same position as the target fourth pixel and the same type as snow in all the fourth snow coverage rate images of the preset days.
The preset days can be eight days or sixteen days. Cloud coverage of images processed by the "maximum land" method may be reduced to below 10%.
For feasibility of the final snow coverage rate image obtained by the processing method, the day-by-day cloud-free coverage snow remote sensing binary image in the same time period is randomly selected as a reference, consistency between the images is analyzed, as shown in a comparison graph of space coverage shown in fig. 3 (5-day image in 2015), as can be seen from the graph, the day-by-day cloud-free coverage snow remote sensing binary image (i.e., binary product in fig. 3) is very consistent with the final snow coverage rate image (i.e., snow coverage rate product in fig. 3) in spatial distribution, but the snow area edge of the final snow coverage rate image obtained by the processing method represents more details.
On the time series, a daily non-cloud-coverage snow remote sensing binary image and a final snow coverage rate image obtained by the processing method are selected to compare the areas (the number of pixels) in the winter time period of a snow year, fig. 4 shows the number of snow pixels in the snow coverage rate range (FSC is more than 0%, FSC is more than 20%, FSC is more than 30% and FSC is more than 50%) with different degrees in the snow coverage rate range from 10/1/2013 to 4/30/2014, and the conditions of the areas of the snow corresponding to the snow are reflected by the number of the respective pixels.
Therefore, as can be seen from the spatial comparison and the time series comparison, the final snow coverage ratio image obtained by the processing method has high consistency with the monitoring of the snow and the contemporaneous day-by-day non-cloud-coverage snow remote sensing binary image, but the final snow coverage ratio image can effectively transmit snow coverage ratio information, and the cloud coverage is averagely controlled within 10%.
By the method, the snow coverage rate image of the high Asian region in 2002-2016 every day is calculated and constructed, the method is an important supplement for the remote sensing binary image of the snow without cloud coverage every day in the high Asian region, the snow coverage rate image can reflect the change characteristics of the snow in the high Asian region on a daily scale, can be used for analyzing the spatial and temporal change of the snow and researching the climate change, and has important values for ecological and climate change research, snow melting runoff model establishment, snow disaster prediction and water and energy circulation research in the high Asian region.
As yet another embodiment of the present invention, there is provided a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the methods provided by the above-described method embodiments, for example, including: acquiring a morning star snow coverage rate image and an afternoon star snow coverage rate image of the current day, synthesizing the morning star snow coverage rate image and the afternoon star snow coverage rate image of the current day into a synthetic image, and adjusting and integrating snow coverage rates corresponding to pixels of snow in the synthetic image to obtain a first snow coverage rate image of the current day; based on the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day, adjusting the pixel of which the type is cloud in the first snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a second snow coverage rate image of the current day; based on the type of a pixel adjacent to the pixel with the cloud type in the second snow coverage rate image of the current day, adjusting the pixel with the cloud type in the second snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to snow so as to obtain a third snow coverage rate image of the current day; based on the elevation of the pixel in the third snow coverage image of the current day, adjusting the pixel of which the type is cloud in the third snow coverage image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a fourth snow coverage image of the current day; based on a fourth snow coverage image containing preset days of the day, adjusting the pixel with the cloud type in the fourth snow coverage image of the day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to be snow so as to obtain a final snow coverage image of the day; wherein, the types of the picture elements comprise land, lake ice, snow and cloud.
As yet another embodiment of the present invention, there is provided a non-transitory computer-readable storage medium storing a computer program that causes a computer to perform the methods provided by the above-described method embodiments, including, for example: acquiring a morning star snow coverage rate image and an afternoon star snow coverage rate image of the current day, synthesizing the morning star snow coverage rate image and the afternoon star snow coverage rate image of the current day into a synthetic image, and adjusting and integrating snow coverage rates corresponding to pixels of snow in the synthetic image to obtain a first snow coverage rate image of the current day; based on the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day, adjusting the pixel of which the type is cloud in the first snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a second snow coverage rate image of the current day; based on the type of a pixel adjacent to the pixel with the cloud type in the second snow coverage rate image of the current day, adjusting the pixel with the cloud type in the second snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to snow so as to obtain a third snow coverage rate image of the current day; based on the elevation of the pixel in the third snow coverage image of the current day, adjusting the pixel of which the type is cloud in the third snow coverage image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a fourth snow coverage image of the current day; based on a fourth snow coverage image containing preset days of the day, adjusting the pixel with the cloud type in the fourth snow coverage image of the day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to be snow so as to obtain a final snow coverage image of the day; wherein, the types of the picture elements comprise land, lake ice, snow and cloud.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to computer program instructions, where the computer program may be stored in a computer readable storage medium, and when executed, the computer program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, the description is as follows: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (5)
1. A method of processing a day-by-day snow coverage image, comprising:
acquiring a morning star snow coverage rate image and an afternoon star snow coverage rate image of the current day, synthesizing the morning star snow coverage rate image and the afternoon star snow coverage rate image of the current day into a synthetic image, and adjusting snow coverage rate corresponding to a pixel of which the type is snow in the synthetic image to acquire a first snow coverage rate image of the current day;
based on the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day, adjusting the pixel of which the type is cloud in the first snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a second snow coverage rate image of the current day;
based on the type of a pixel adjacent to a pixel with the cloud type in the second snow coverage rate image of the current day, adjusting the pixel with the cloud type in the second snow coverage rate image of the current day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to be snow so as to obtain a third snow coverage rate image of the current day;
based on the elevation of the pixel in the third snow coverage image of the current day, adjusting the pixel of which the type is cloud in the third snow coverage image of the current day, and adjusting the snow coverage rate corresponding to the pixel of which the type is adjusted from cloud to snow so as to obtain a fourth snow coverage image of the current day;
based on a fourth snow coverage image containing preset days of the day, adjusting the pixel with the cloud type in the fourth snow coverage image of the day, and adjusting the snow coverage rate corresponding to the pixel with the cloud type adjusted to be snow so as to obtain a final snow coverage image of the day;
wherein the types of the pixels comprise land, lake ice, snow and cloud; the method for synthesizing the morning star snow coverage rate image and the afternoon star snow coverage rate image of the current day into a synthetic image comprises the following steps:
determining the type of each image element in the composite image;
adjusting the color value of each pixel according to the type of each pixel in the synthetic image;
wherein the determining the type of each pel in the composite image comprises:
for any pixel in the synthetic image, taking the any pixel as a target pixel, and acquiring a first type of the pixel with the same position as the target pixel in the morning star snow coverage rate image of the day and a second type of the pixel with the same position as the target pixel in the afternoon star snow coverage rate image of the day;
if the first type is the same as the second type, taking the first type or the second type as the type of the target pixel in the synthetic image;
if at least one of the first type and the second type is lake or lake ice, taking the corresponding lake or lake ice as the type of the target pixel in the composite image;
if the first type is different from the second type and is respectively land or snow, taking the first type as the type of the target pixel in the synthetic image;
if one of the first type and the second type is cloud and the other is land or snow, taking the corresponding land or snow as the type of the target pixel in the composite image;
if the data of the first type and the data of the second type are both missing or invalid, the type of the target pixel in the synthetic image is set to be cloud;
wherein, the adjusting the snow coverage rate corresponding to the pixel of which the type is snow in the synthetic image comprises:
if the first type and the second type are both snow, adjusting the snow coverage rate corresponding to the target pixel in the composite image to be the average value of the snow coverage rates corresponding to the pixels with the same positions as the target pixel in the morning star snow coverage rate image and the afternoon star snow coverage rate image of the current day;
if the first type is snow cover and the second type is cloud or land, adjusting the snow cover rate corresponding to the target pixel in the composite image to be the snow cover rate corresponding to the pixel with the same position as the target pixel in the morning star snow cover rate image of the day;
if the second type is snow accumulation and the first type is cloud, adjusting the snow coverage rate corresponding to the target pixel in the synthetic image to be the snow coverage rate corresponding to the pixel with the same position as the target pixel in the afternoon star snow coverage rate image of the current day;
wherein, based on the first snow cover rate image of the preceding day and the first snow cover rate image of the following day, adjust the pixel that the type is cloud in the first snow cover rate image of the current day to the snow cover rate that the adjustment is adjusted the type by the cloud to the pixel of snow corresponds, include:
taking a pixel with the cloud type in the first snow coverage rate image of the current day as a first pixel, taking any first pixel as a target first pixel, and acquiring the types of the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day;
if at least one of the types of the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day is a lake or lake ice, adjusting the type of the target first pixel to be the corresponding lake or lake ice;
if the types of the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day are both land, adjusting the type of the target first pixel to be land;
if the types of the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day are both snow, the type of the target first pixel is adjusted to be snow, and the snow coverage rate corresponding to the target first pixel is adjusted to be the average value of the snow coverage rates corresponding to the pixels with the same positions as the target first pixel in the first snow coverage rate image of the previous day and the first snow coverage rate image of the next day.
2. The method of claim 1, wherein the adjusting of the pixels of the cloud type in the second snow coverage image of the current day based on the type of the pixels adjacent to the pixels of the cloud type in the second snow coverage image of the current day and the adjusting of the snow coverage corresponding to the pixels of the cloud type to snow comprises:
taking a pixel with the type of cloud in a second accumulated snow coverage rate image of the current day as a second pixel, taking any second pixel as a target second pixel, and acquiring the types of four pixels directly adjacent to the target second pixel;
if at least three pixels in the four pixels directly adjacent to the target second pixel are snow, adjusting the type of the target second pixel to be snow, and adjusting the snow coverage rate corresponding to the target second pixel to be the average value of the snow coverage rates corresponding to the snow-accumulated pixels in the eight pixels adjacent to the target second pixel;
and if the types of at least three pixels in the four pixels directly adjacent to the target second pixel are land, adjusting the type of the target second pixel to be land.
3. The method of claim 1, wherein adjusting the pixels of the third snow coverage image of the current day that are of the cloud type based on the elevations of the pixels in the third snow coverage image of the current day, and adjusting the snow coverage corresponding to the pixels of the cloud-to-snow type comprises:
taking a pixel with the cloud type in a third accumulated snow coverage rate image of the current day as a third pixel, taking any third pixel as a target third pixel, acquiring the elevation of the target third pixel, and determining the time period of the season of the current day;
if the elevation of the target third pixel is larger than a first preset value, adjusting the type of the target third pixel to be snow cover, and adjusting the snow cover rate corresponding to the target third pixel to be the average value of the snow cover rates corresponding to the pixels with the same positions as the target third pixel in all third snow cover rate images in the time period;
if the elevation of the target third pixel is smaller than a first preset value and larger than a second preset value, and the proportion of the types of the pixels, which are the same as the position of the target third pixel, of the snow or the number of cloud days in all third snow coverage rate images in the time period to the total number of days in the time period exceeds a third preset value, adjusting the type of the target third pixel to be snow, and adjusting the snow coverage rate corresponding to the target third pixel to be the average value of the snow coverage rate corresponding to the pixels, which are the same as the position of the target third pixel, in all third snow coverage rate images in the time period;
if the elevation of the target third pixel is smaller than a second preset value, the proportion of the number of cloud days in the pixel type same as the position of the target third pixel in all the third accumulated snow coverage rate images in the time period to the total number of days in the time period is smaller than a fourth preset value, and the sum of the number of cloud days in the pixel type same as the position of the target third pixel and the number of land days in the pixel type is equal to the total number of days in the time period, the type of the target third pixel is adjusted to be land.
4. The method according to claim 1, wherein the adjusting of the pixel of the cloud type in the fourth snow coverage image of the current day based on the fourth snow coverage image including the preset number of days of the current day, and the adjusting of the snow coverage corresponding to the pixel of the cloud type to snow comprises:
taking a pixel with the cloud type in a fourth snow coverage image of the current day as a fourth pixel, taking any fourth pixel as a target fourth pixel, and acquiring the types of the pixels with the same positions as the target fourth pixel in all fourth snow coverage images in preset days;
if the type of the pixel at the same position as the target fourth pixel in the fourth accumulated snow coverage rate image of at least one day in preset days is a lake or lake ice, adjusting the type of the target fourth pixel to be the corresponding lake or lake ice;
if the type of the pixel at the same position as the target fourth pixel in the fourth snow coverage rate image of at least one day in the preset days is land, adjusting the type of the target fourth pixel to be land;
if the type of the pixel with the same position as the target fourth pixel in all fourth snow coverage rate images of the preset days is cloud or snow, the type of the target fourth pixel is adjusted to be snow, and the snow coverage rate corresponding to the target fourth pixel is adjusted to be the average value of the snow coverage rate corresponding to the pixel with the same position as the target fourth pixel and the same type of snow in all fourth snow coverage rate images of the preset days.
5. A non-transitory computer-readable storage medium storing a computer program that causes a computer to perform the method according to any one of claims 1 to 4.
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