CN115861309A - Method, device, terminal and medium for accelerating MPCM (Multi-point modulation) for detecting infrared small and weak targets - Google Patents
Method, device, terminal and medium for accelerating MPCM (Multi-point modulation) for detecting infrared small and weak targets Download PDFInfo
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Abstract
The invention relates to the field of target detection, and particularly discloses an MPCM (multi-point modulation) accelerating method, device, terminal and medium for infrared weak and small target detection, wherein a current frame image is obtained, the current frame image is converted into a gray image, and average filtering is performed to obtain an image M; calculating PCM for the image M; carrying out pyramid downsampling on the image M by n1 times, n2 times, 8230, 8230and nh times; respectively calculating PCM (pulse code modulation) for the images subjected to the pyramid downsampling; respectively carrying out up-sampling on n1 times, n2 times, \ 8230 \ 8230; \ 8230and nh times on a comparison graph corresponding to the computed PCM after down-sampling; calculating MPCM based on each comparison map PCM; and carrying out binarization on the MPCM according to a threshold value to obtain a target position. The invention processes the image by down-sampling, calculates PCM for the down-sampled image, and then up-samples, can improve the processing speed of the MPCM algorithm, and meets the requirement of real-time processing.
Description
Technical Field
The invention relates to the field of target detection, in particular to the field of infrared target detection, and specifically relates to an accelerating method, device, terminal and medium for infrared small and weak target detection MPCM.
Background
Infrared weak target detection is one of the most important technologies in passive defense systems. On one hand, due to noise interference, small targets are usually submerged in background clutter; on the other hand, the detection of small objects is very challenging because they do not have obvious shape features and useful texture information.
The current infrared weak and small target detection algorithm is mainly divided into multi-frame detection and single-frame detection, the multi-frame detection realizes the infrared small target detection by utilizing the continuity and the correlation of a moving target in a multi-frame image, the single-frame detection mainly utilizes a single-frame image to extract the characteristics of the small target such as gradient, gray scale, contrast and the like in the infrared image, and the weak and small target detection is realized by means of target enhancement, background inhibition and the like. However, many schemes for single frame detection focus on contrast enhancement mechanisms, namely highlighting enhancement targets and suppressing background regions, but algorithms based on human visual contrast mechanisms still have some defects, some schemes cannot well suppress the background, some schemes can only enhance highlight targets, and some schemes can smooth the targets.
The MPCM (Multiscale batch-based contrast) algorithm can well calculate the contrast between a target and a background, and can achieve a better detection effect no matter whether the target is high-brightness or darker than the background, but the multi-scale calculation of the original algorithm is slow, and the real-time processing cannot be achieved on an image with a slightly higher resolution.
Disclosure of Invention
In order to solve the problems, the invention provides an accelerating method, device, terminal and medium for detecting an MPCM (multi-point pulse width modulation) of an infrared weak and small target.
In a first aspect, the technical solution of the present invention provides an accelerating method for detecting an MPCM on an infrared weak and small target, comprising the following steps:
acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M;
calculating PCM for the image M, and recording the PCM as a first PCM;
carrying out pyramid downsampling on the image M by n1 times, n2 times, 8230, 8230and nh times;
respectively calculating PCM (pulse code modulation) of the pyramid down-sampled images to obtain an nth 1PCM, an nth 2PCM, a \8230, an 8230and an nth PCM;
respectively up-sampling a contrast image corresponding to the nth 1PCM, the nth 2PCM, the (8230); the (nphPCM) by n1 times, n2 times, the (8230); and the (nh) times;
calculating MPCM based on the first PCM and the comparison map PCM after each up-sampling;
and carrying out binarization on the MPCM according to a threshold value to obtain a target position.
Further, the method specifically comprises the following steps:
performing convolution operation on the image M by using mean convolution kernel to obtain a scale image C 3 ；
Performing convolution operation on the images subjected to pyramid down-sampling and the mean convolution kernel to respectively obtain a scale image C n1 、C n2 、……、C nh ；
A single scale image C k Is marked as C, is calculated corresponding to C: (i，j) Contrast value D of a point i j（，） Obtaining each PCM; whereink=3、n1、h2……nh。
Further, the method specifically comprises calculating MPCM by the following formula:
wherein,
h is the height of the image and W is the width of the image.
Further, when the MPCM is subjected to binarization, the threshold value is
(ii) a Wherein it is present>
,/>
Is->
Is based on the mean value of>
Is->
Standard deviation of (2).
Further, the method specifically comprises the following steps:
and (4) carrying out average filtering on the gray-scale image by adopting a 3-by-3 average filter.
In a second aspect, the present invention provides an infrared small and weak target detection MPCM acceleration apparatus, comprising,
an image preprocessing module: acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M;
a down-sampling module: carrying out pyramid downsampling on the image M by n1 times, n2 times, 8230, 8230and nh times;
the PCM calculation module: calculating PCM for the image M, and recording the PCM as a first PCM; respectively calculating PCM (pulse code modulation) of the pyramid down-sampled images to obtain an nth 1PCM, an nth 2PCM, a \8230, an 8230and an nth PCM;
an up-sampling module: respectively up-sampling a contrast image corresponding to the nth 1PCM, the nth 2PCM, the (8230); the (nphPCM) by n1 times, n2 times, the (8230); and the (nh) times;
MPCM calculation module: calculating MPCM based on the first PCM and the comparison map PCM after each up-sampling;
a target location determination module: and carrying out binarization on the MPCM according to a threshold value to obtain a target position.
Further, the PCM calculation module performs PCM calculation by:
carrying out convolution operation on the image M by using the mean convolution kernel to obtain a scale image C 3 ；
Performing convolution operation on the images subjected to pyramid down-sampling and the mean convolution kernel to obtain scale images C n1 、C n2 、……、C nh ；
A single scale image C k Is marked as C, and is calculated corresponding to Ci，j) Contrast value D of a point i j（，） Obtaining each PCM; whereink=3、n1、h2……nh。
Further, the MPCM computation module computes the MPCM by the following equation:
wherein,
h is the height of the image, W is the width of the image;
when the target position determining module carries out binaryzation on the MPCM, the threshold value is
(ii) a Wherein it is present>
,/>
Is composed of
Is based on the mean value of>
Is->
Standard deviation of (d).
In a third aspect, a technical solution of the present invention provides a terminal, including:
the memory is used for storing an infrared small and weak target detection MPCM acceleration program;
and the processor is used for realizing the steps of the infrared small and weak target detection MPCM acceleration method in any one of the above steps when the infrared small and weak target detection MPCM acceleration program is executed.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where an infrared small and weak target detection MPCM acceleration program is stored on the readable storage medium, and when being executed by a processor, the infrared small and weak target detection MPCM acceleration program implements the steps of the infrared small and weak target detection MPCM acceleration method described in any one of the above.
Compared with the prior art, the method, the device, the terminal and the medium for accelerating the MPCM for detecting the infrared small and weak targets have the following beneficial effects: after the acquired image is preprocessed, the preprocessed image is directly subjected to PCM calculation, the image is subjected to down-sampling processing, the PCM is calculated again on the down-sampled image, and finally the MPCM is calculated based on each PCM to determine the target. The invention processes the image by down-sampling, calculates PCM for the down-sampled image, performs up-sampling processing and finally calculates MPCM, thereby improving the processing speed of MPCM algorithm and meeting the requirement of real-time processing.
Drawings
For a clearer explanation of the embodiments or technical solutions of the prior art of the present application, the drawings needed for the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of an infrared small and weak target detection MPCM acceleration method provided in an embodiment of the present invention.
Fig. 2 is a flowchart illustrating an embodiment of an infrared small and weak target detection MPCM acceleration method according to an embodiment of the present invention.
Figure 3 is a 3 x 3 mean filter template schematic.
Fig. 4 is a schematic view of a sliding window structure.
Fig. 5 is a schematic diagram of a detection result of an infrared small and weak target detection MPCM acceleration method according to an embodiment of the present invention.
Fig. 6 is a schematic block diagram of an infrared small and weak target detection MPCM acceleration apparatus according to an embodiment of the present invention.
Fig. 7 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
Some terms related to the present invention are explained below.
PCM: and (3) path-based contrast measure, which is a measure of the contrast of the target at a certain scale.
MPCM: multiscale patch-based contrast measure, multiscale block contrast method.
In order that those skilled in the art will better understand the disclosure, the following detailed description will be given with reference to the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
Fig. 1 is a schematic flow chart of an infrared small and weak target detection MPCM acceleration method provided in an embodiment of the present invention, and as shown in fig. 1, the method includes the following steps.
S1, acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M.
And acquiring a current frame image from the video stream, and carrying out target detection based on the current frame image. Firstly, carrying out gray processing on an image, then filtering a gray image, and filtering noise interference. The user selects the mean filter as desired.
And S2, calculating PCM for the image M, and marking the PCM as the first PCM.
And preprocessing an image acquired by the pull flow and then directly performing PCM calculation.
S3, pyramid downsampling is conducted on the image M by n1 time, n2 time, 8230, 8230and nh times.
The image obtained by the pull stream is preprocessed and then subjected to pyramid downsampling, and certainly, several times of downsampling is adopted, so that a user can select according to needs, for example, the image M is subjected to pyramid downsampling by 2 times and 4 times, and subsequent processing is performed on the image M based on the pyramid downsampling by 2 times and 4 times.
And S4, respectively calculating the PCM of each pyramid down-sampled image to obtain an nth 1PCM, an nth 2PCM, a 8230, a 8230and an nth PCM.
The PCM is calculated for the down-sampled image to obtain a plurality of PCMs.
S5, up-sampling n1 times, n2 times, \8230 \ 8230: (8230) times, 82308230and nh times respectively on a comparison graph corresponding to the nth PCM, the (2) \\ 8230: (nhPCM).
Certainly, after the PCM is calculated for the down-sampled image, the up-sampling process is performed, and the MPCM is calculated after the up-sampling process.
And S6, calculating the MPCM based on the first PCM and the comparison picture PCM after up-sampling.
And S7, carrying out binarization on the MPCM according to a threshold value to obtain a target position.
In the method for accelerating the MPCM for detecting the infrared weak and small targets provided by this embodiment, the image is processed by down-sampling, the PCM is calculated for the down-sampled image, then the up-sampling process is performed, and finally the MPCM is calculated.
To further understand the present invention, a specific embodiment is provided below to further explain the present invention in detail, fig. 2 is a schematic flow chart of the specific embodiment, and as shown in fig. 2, the specific embodiment includes the following steps.
S1, carrying out pull flow to obtain a current frame image I.
And S2, converting the image I into a gray image G.
And S3, carrying out mean value filtering on the gray level image G to obtain an image M.
The averaging filtering is performed to filter out noise interference, for example, a 3 × 3 averaging filter may be selected, and fig. 3 is a 3 × 3 averaging filter template.
The algorithm principle of the 3 × 3 mean filter is as follows:
。
s4, performing convolution operation on the image M by using the 3 x 3 mean value convolution kernel to obtain
Respectively carrying out pyramid downsampling on the image M by 2 times and 4 times, and carrying out convolution operation on the image M and the mean value convolution kernel to respectively obtain->
。
S5, after convolution operation, single scale image
(where k can be set to 3,5,7, etc.) is recorded as C, and a contrast value ≧ is calculated for C at point (i, j)>
The calculation formula is as follows:
the sliding window structure is shown in fig. 4, where T is the target area and B is the background area.
T,
Can be derived from the coordinate value of C, where the mean value of T is ^ or ^>
,/>
Has a mean value of
,/>
Has a mean value of->
,/>
Has a mean value of->
,/>
Has a mean value of->
,/>
Has a mean value of->
,/>
Has a mean value of->
,/>
Has a mean value of->
,/>
Has a mean value of->
Ksize =3 is the scale of the convolution, < >>
H and W are the height and width of the image, and the contrast ratio of other pyramid downsampled images is calculated in the same way.
And S6, after the contrast map of the pyramid downsampling image is calculated, upsampling the corresponding contrast map.
S7, calculating the MPCM of the resolution size of the original image according to the following formula:
s8, according to the threshold TH pair
And carrying out binarization to obtain the position of the target.
Wherein the content of the first and second substances,
is an empirical value; />
Is->
In the mean value of (a)>
Is->
Standard deviation of (d).
Through tests, a plurality of pyramid downsampling scales are integrated, 3 scales are used, namely the original image is downsampled by 2 times, the original image is downsampled by 4 times, the processing speed of 640 x 640 images on the Haisi chip can reach 29.5 frames/second, the speed of calculating the MPCM is improved by 2.4 times compared with the speed of an original algorithm, and the requirement of real-time detection can be completely met. As shown in fig. 5, (a) is an original image, (b) is an original PCM, (c) is a PCM obtained by down-sampling the original image by 2 times, (d) is a PCM obtained by down-sampling the original image by 4 times, and (e) is a target calibration result.
The above detailed description is given to an embodiment of an infrared small and weak target detection MPCM acceleration method, and based on the infrared small and weak target detection MPCM acceleration method described in the above embodiment, an embodiment of the present invention further provides an infrared small and weak target detection MPCM acceleration apparatus corresponding to the method.
Fig. 6 is a schematic block diagram of an infrared small and weak target detection MPCM acceleration apparatus provided in an embodiment of the present invention, and as shown in fig. 6, the apparatus includes: an image pre-processing module 101, a down-sampling module 102, a PCM calculation module 103, an up-sampling module 104, an MPCM calculation module 105, and a target position determination module 106.
The image preprocessing module 101: and acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M.
The down-sampling module 102: pyramid downsampling is carried out on the image M by n1 times, n2 times, 8230, 8230and nh times.
The PCM calculation module 103: calculating PCM for the image M, and recording the PCM as a first PCM; and respectively calculating the PCM of each pyramid down-sampled image to obtain an nth 1PCM, an nth 2PCM, a \8230 \ 8230and an nth PCM.
Specifically, the module performs PCM calculation by: performing convolution operation on the image M by using mean convolution kernel to obtain a scale image C 3 (ii) a Performing convolution operation on the images subjected to pyramid down-sampling and the mean convolution kernel to respectively obtain a scale image C n1 、C n2 、……、C nh (ii) a A single scale image C k Is marked as C, and is calculated corresponding to Ci，j) Contrast value D of a point i j（，） Obtaining each PCM; whereink=3、n1、h2……nh。
The upsampling module 104: and (3) respectively carrying out up-sampling on n1 times, n2 times, 8230, 82308230, and nh times on comparison graphs corresponding to the n1PCM, the n2PCM, the 8230, the 8230and the nh times.
The MPCM calculation module 105: the MPCM is calculated based on the first PCM, the respective up-sampled contrast PCM.
MPCM is calculated by the following formula:
(ii) a Wherein +>
H is the height of the image and W is the width of the image.
The target location determination module 106: and carrying out binarization on the MPCM according to a threshold value to obtain a target position.
Wherein the threshold value
，/>
,/>
Is->
Is based on the mean value of>
Is->
Standard deviation of (2). />
The infrared small and weak target detection MPCM acceleration apparatus of this embodiment is used for implementing the aforementioned infrared small and weak target detection MPCM acceleration method, and therefore, the specific implementation of this apparatus can be seen in the foregoing description of the embodiment of the infrared small and weak target detection MPCM acceleration method, and therefore, the specific implementation thereof can refer to the description of the corresponding partial embodiments, and will not be further described herein.
In addition, since the infrared small and weak target detection MPCM acceleration apparatus of this embodiment is used to implement the aforementioned infrared small and weak target detection MPCM acceleration method, its function corresponds to that of the aforementioned method, and is not described herein again.
Fig. 7 is a schematic structural diagram of a terminal 700 according to an embodiment of the present invention, including: processor 710, memory 720, and communication unit 730. The processor 710 is configured to implement the following steps when implementing the infrared small and weak target detection MPCM acceleration program stored in the memory 720:
acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M;
calculating PCM for the image M, and recording the PCM as a first PCM;
carrying out pyramid downsampling on the image M by n1 times, n2 times, 8230, 8230and nh times;
respectively calculating PCM (pulse code modulation) of the pyramid down-sampled images to obtain an nth 1PCM, an nth 2PCM, a \8230, an 8230and an nth PCM;
respectively up-sampling a contrast image corresponding to the nth 1PCM, the nth 2PCM, the (8230); the (nphPCM) by n1 times, n2 times, the (8230); and the (nh) times;
calculating MPCM based on the first PCM and the comparison map PCM after each up-sampling;
and carrying out binarization on the MPCM according to a threshold value to obtain a target position.
The invention processes the image by down-sampling, calculates PCM for the down-sampled image, performs up-sampling processing and finally calculates MPCM, thereby improving the processing speed of MPCM algorithm and meeting the requirement of real-time processing.
The terminal 700 includes a processor 710, a memory 720, and a communication unit 730. The components communicate via one or more buses, and those skilled in the art will appreciate that the architecture of the servers shown in the figures is not intended to be limiting, and may be a bus architecture, a star architecture, a combination of more or less components than those shown, or a different arrangement of components.
The memory 720 may be used for storing instructions executed by the processor 710, and the memory 720 may be implemented by any type of volatile or non-volatile storage terminal or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The executable instructions in memory 720, when executed by processor 710, enable terminal 700 to perform some or all of the steps in the method embodiments described below.
The processor 710 is a control center of the storage terminal, connects various parts of the entire electronic terminal using various interfaces and lines, and performs various functions of the electronic terminal and/or processes data by operating or executing software programs and/or modules stored in the memory 720 and calling data stored in the memory. The processor may be formed by an Integrated Circuit (IC), for example, a single packaged IC, or a plurality of packaged ICs with the same or different functions. For example, the processor 710 may include only a Central Processing Unit (CPU). In the embodiment of the present invention, the CPU may be a single operation core, or may include multiple operation cores.
A communication unit 730, configured to establish a communication channel so that the storage terminal can communicate with other terminals. And receiving user data sent by other terminals or sending the user data to other terminals.
The present invention also provides a computer storage medium, wherein the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a Random Access Memory (RAM).
The computer storage medium stores an infrared small and weak target detection MPCM acceleration program that when executed by a processor implements the steps of:
acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M;
calculating PCM for the image M, and recording the PCM as a first PCM;
pyramid downsampling is carried out on the image M by n1 times, n2 times, \8230, 8230and nh times;
respectively calculating PCM (pulse code modulation) of the pyramid down-sampled images to obtain an nth 1PCM, an nth 2PCM, a \8230, an 8230and an nth PCM;
respectively up-sampling a contrast image corresponding to the nth 1PCM, the nth 2PCM, the (8230); the (nphPCM) by n1 times, n2 times, the (8230); and the (nh) times;
calculating MPCM based on the first PCM and the comparison map PCM after each up-sampling;
and carrying out binarization on the MPCM according to a threshold value to obtain a target position.
The invention processes the image by down-sampling, calculates PCM for the down-sampled image, performs up-sampling processing and finally calculates MPCM, thereby improving the processing speed of MPCM algorithm and meeting the requirement of real-time processing.
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied in the form of a software product, where the computer software product is stored in a storage medium, such as a usb disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like, and the storage medium can store program codes, and includes several instructions to enable a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, and the like) to perform all or part of the steps of the methods in the embodiments of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The above disclosure is only for the preferred embodiments of the present invention, but the present invention is not limited thereto, and any non-inventive changes that can be made by those skilled in the art and several modifications and amendments made without departing from the principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. An infrared small and weak target detection MPCM acceleration method is characterized by comprising the following steps:
acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M;
calculating PCM for the image M, and recording the PCM as a first PCM;
carrying out pyramid downsampling on the image M by n1 times, n2 times, 8230, 8230and nh times;
respectively calculating PCM (pulse code modulation) of the pyramid down-sampled images to obtain an nth 1PCM, an nth 2PCM, a method 8230, a method 8230and an nth PCM;
respectively up-sampling a contrast image corresponding to the nth 1PCM, the nth 2PCM, the (8230); the (nphPCM) by n1 times, n2 times, the (8230); and the (nh) times;
calculating MPCM based on the first PCM and the comparison map PCM after each up-sampling;
and carrying out binarization on the MPCM according to a threshold value to obtain a target position.
2. The method for accelerating the MPCM for detecting the infrared weak small target as claimed in claim 1, wherein the method specifically comprises:
performing convolution operation on the image M by using mean convolution kernel to obtain a scale image C 3 ；
Performing convolution operation on the images subjected to pyramid down-sampling and the mean convolution kernel to respectively obtain a scale image C n1 、C n2 、……、C nh ；
A single scale image C k Is marked as C, is calculated corresponding to C: (i，j) Contrast value D of a point i j（，） Obtaining each PCM; whereink=3、n1、h2……nh。
3. The method for accelerating the MPCM for detecting weak and small infrared targets as claimed in claim 2, wherein the method specifically comprises calculating the MPCM by the following formula:
wherein,
h is the height of the image and W is the width of the image.
4. The method for accelerating MPCM for detecting infrared weak small objects as recited in claim 3, wherein the threshold value is set as follows when performing binarization on MPCM
(ii) a Wherein it is present>
,/>
Is->
Is based on the mean value of>
Is->
Standard deviation of (2).
5. The method for accelerating the MPCM for detecting the infrared weak small target as set forth in claim 4, wherein the method specifically comprises:
and (4) carrying out average filtering on the gray-scale image by adopting a 3-by-3 average filter.
6. An infrared small and weak target detection MPCM accelerating device is characterized by comprising,
an image preprocessing module: acquiring a current frame image, converting the current frame image into a gray image, and performing mean value filtering to obtain an image M;
a down-sampling module: carrying out pyramid downsampling on the image M by n1 times, n2 times, 8230, 8230and nh times;
the PCM calculation module: calculating PCM for the image M, and recording the PCM as a first PCM; respectively calculating PCM (pulse code modulation) of the pyramid down-sampled images to obtain an nth 1PCM, an nth 2PCM, a \8230, an 8230and an nth PCM;
an up-sampling module: respectively up-sampling a contrast image corresponding to the nth 1PCM, the nth 2PCM, the (8230); the (nphPCM) by n1 times, n2 times, the (8230); and the (nh) times;
MPCM calculation module: calculating MPCM based on the first PCM and the comparison map PCM after each up-sampling;
a target location determination module: and carrying out binarization on the MPCM according to a threshold value to obtain a target position.
7. The infrared small and weak target detection MPCM acceleration device of claim 6, wherein the PCM calculation module performs PCM calculation by:
performing convolution operation on the image M by using mean convolution kernel to obtain a scale image C 3 ；
Performing convolution operation on the images subjected to pyramid down-sampling and the mean convolution kernel to respectively obtain a scale image C n1 、C n2 、……、C nh ；
A single scale image C k Is marked as C, is calculated corresponding to C: (i，j) Contrast value D of a point i j（，） Obtaining each PCM; whereink=3、n1、h2……nh。
8. The infrared small and weak target detection MPCM acceleration device of claim 7, wherein the MPCM calculation module calculates MPCM by the following formula:
wherein,
h is the height of the image, W is the width of the image;
when the target position determining module carries out binaryzation on the MPCM, the threshold value is
(ii) a Wherein it is present>
,/>
Is->
Is based on the mean value of>
Is->
Standard deviation of (2).
9. A terminal, comprising:
the memory is used for storing an infrared small and weak target detection MPCM acceleration program;
a processor for implementing the steps of the infrared small target detection MPCM acceleration method as claimed in any one of claims 1-5 when executing the infrared small target detection MPCM acceleration program.
10. A computer readable storage medium, having stored thereon an infrared small object detection MPCM acceleration program, which when executed by a processor, performs the steps of the infrared small object detection MPCM acceleration method of any one of claims 1-5.
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