WO2019196009A1

WO2019196009A1 - Method for detecting defective pixel of image sensor, and photography apparatus, unmanned aerial vehicle and storage medium

Info

Publication number: WO2019196009A1
Application number: PCT/CN2018/082502
Authority: WO
Inventors: 孙旭斌; 白高平; 杨豪
Original assignee: 深圳市大疆创新科技有限公司
Priority date: 2018-04-10
Filing date: 2018-04-10
Publication date: 2019-10-17
Also published as: CN110463199A

Abstract

A method for detecting a defective pixel of an image sensor. The method comprises: detecting positions of image defective pixels of taken pictures or video frames; recording and storing positions of image defective pixels of a plurality of pictures or video frames that meet certain conditions among from the pictures or video frames; compiling statistics on the recorded positions of the image defective pixels; and determining the position of an image defective pixel, which appears in each of more than a certain number of pictures or video frames from among the plurality of pictures or video frames that meet the certain conditions, as the position of a defective pixel of an image sensor. Further disclosed are a photography apparatus, an unmanned aerial vehicle and a storage medium. Thus, a bright spot defective pixel and a dark spot defective pixel which are newly added can be simultaneously corrected without a user operation.

Description

Image sensor dead pixel detection method, photographing device, drone, and storage medium

Technical field

Embodiments of the present application relate to a method for detecting a dead pixel of an image sensor in an imaging device, an imaging device, a drone, and a storage medium.

Background technique

Image sensors (such as CCD and CMOS) of cameras and other cameras have a certain number of bad pixels. The brightness values of these pixels do not reflect the captured image, which is usually called a dead pixel.

There are two kinds of bad points according to the probability of occurrence, namely static dead points and dynamic dead points: (1) Static dead points are bad points that must occur under certain conditions (such as long enough exposure time and image sensor reaches a certain temperature); 2) The dynamic dead point is a bad point that appears probabilistic even if certain conditions are reached (ie, the bad point appears in this photo, the next shot may be normal; in the frame of the video, the next frame may be normal; or the image sensor This power-on has been appearing all the time, and the next power-up may have been normal.)

The bad point brightness can also be divided into two types, that is, bright point and dark point: (1) The bright point is when the overall brightness of the photo or video is dark, the brightness value is higher than the original brightness of the image, and the image is the position. The original brightness does not have a corresponding relationship; (2) the dark point is that when the overall brightness of the photo or video is bright, the brightness value is lower than the original brightness of the image, and there is no corresponding relationship with the original brightness of the image. .

For the correction of the dead pixels, the following two correction methods are generally used.

(1) One is static dead pixel correction, in which static dead pixel correction is further divided into two types, namely static bright spot correction and static dark point correction.

Static bright spot correction: Before leaving the factory, the camera lens is blacked out, and the RAW format photo of all the effective pixels of the image sensor is taken for specific exposure parameters, and then all the pixels are analyzed by software to find that the brightness is higher than the average value of the surrounding pixels. The coordinates of a certain threshold pixel, mark these pixels as bright spots, and save their coordinates. In normal photographing and recording, the value of the pixel marked as a bright spot is not used, but the value of the pixel marked as a bright point is replaced by a value obtained by calculating the value of the same kind of pixel around it;

Static dark spot correction: Before leaving the factory, the camera shoots a RAW format photo of a specific exposure parameter against a uniform light source, and then analyzes all the pixels through software to find a pixel whose brightness is lower than the average value of the surrounding pixels. The coordinates of the pixels are marked as dark points and their coordinates are saved. In normal photographing and recording, the value of the pixel marked as a dark spot is not taken, but the value of the pixel marked as a dark dot is replaced by a value obtained by a certain calculation of the value of the same kind of pixel around it.

Static dead-point correction is to analyze the dead-point position under ideal test conditions (blackout the lens at the camera factory or use a high-quality uniform light plane source with fixed exposure parameters), and the coordinate position of the dead point is reliable. Therefore, it can be considered that the static dead point is "image sensor dead point".

In the following, a brief description will be given of the "certain calculation" mentioned in the above static bright spot correction and static dark spot correction process. Fig. 5 is a schematic diagram showing a conventional calculation method employed in static dead point correction. As shown in FIG. 5, it is assumed that c is a green pixel dead pixel, and there are nine pixels around c, wherein a, b, d, and e are normal green pixels, and c is a similar pixel; c is directly above and below Red pixels, the left and right are blue pixels, and c is a different type of pixel. Then the value of c is calculated by a, b, d, e: c = ((a + d) / 2 + (b + e) / 2) / 2. Thus, instead of the pixel value of the dead point c, the value obtained by the above calculation for the value of the same type of pixel around the dead point c can be utilized.

(2) The other is dynamic dead pixel correction.

Dynamic bad point correction is to analyze and compare the difference between each pixel and the surrounding pixels in the normal picture or video. If the surrounding pixel values are consistent and the pixel value is different, then The pixel is marked as a dead pixel. For this photo or video frame, the value of the pixel is not used, but the value of the pixel marked as a dead pixel is replaced by a value calculated by the value of the similar pixel around it. . Since the dynamic bad point correction is to calculate the normal taken photo or video frame, the condition for finding the bad point position is not ideal (the exposure parameters of the normally taken photo or video are uncertain, and the picture content is complicated, the dynamic bad point correction is very It may leak or catch some noise points, so the dynamic dead pixels are not necessarily reliable, and the position of the pixel will not be saved. Dynamic dead-point correction detects both bright and dark spots. In the present application, the dynamic bad point is sometimes referred to as "image dead point".

After the camera is shipped, as the usage time increases, the number of dead pixels also increases, and some pixels on the image sensor that are not originally dead pixels may also become dead pixels. These added dead pixels will be a problem for cameras. For the added dead pixels, the camera now generally adopts two strategies: (1) no processing, this method is usually used for lower-end cameras that do not require high image quality; (2) adding users to the camera software Cover the camera with a lens cover, etc., and do a static highlight correction procedure to eliminate the new bright spots. However, in order to detect dark spots, it is necessary to prepare a high-quality uniform light plane light source, so that it is difficult for ordinary consumers to realize, so the correction of new dark point dead pixels is generally abandoned.

For the above two strategies, the first (1) will not reduce the image quality; the second (2) requires the user to trigger the operation and participate in it. When the user is not professional or the operation is not correct, the correction function may not be triggered or The calibration failed, and the dark spots were not corrected, and the function was one-sided.

Summary of the invention

Embodiments of the present application provide a method, a photographing device, a drone, and a storage medium for detecting (calibrating) a dead pixel of an image sensor. The main technical idea is to capture static dead pixels by analyzing dynamic dead pixels, and to determine the bad points by detecting multiple photos or points captured in the same position in multiple video frames.

In a first aspect, a method for detecting a dead pixel of an image sensor is provided, including:

Detecting the position of the image dead point on the captured photo or video frame;

Recording and storing the location of image dead pixels of a plurality of photos or video frames in a photo or video frame that meet certain conditions;

Counting the position of the recorded image dead pixels;

The position of the image dead point appearing in each of a certain number of photos or video frames in a plurality of photos or video frames that meet certain conditions is determined as the position of the image sensor dead point.

In a second aspect, a photographing apparatus is provided, comprising:

Lens group

An image sensor that converts optical information acquired by the lens group into image data;

a processor that controls the entire imaging device;

Storage media, storing various data and programs,

The processor executes:

Recording and storing the location of image dead pixels of a plurality of photos or video frames in a photo or video frame that meet certain conditions in a storage medium;

Counting the position of the recorded image dead pixels;

In a third aspect, a drone is provided, which wirelessly communicates with a smart terminal, and the smart terminal remotely controls the drone, the drone includes:

The photographing device of the above second aspect;

PTZ, used to fix the camera.

A fourth aspect provides a computer readable storage medium storing an executable program that, when executed by a processor, causes the processor to perform the image sensor dead point detection method of the first aspect described above.

According to the image sensor dead center detecting method, the photographing device, the drone, and the storage medium according to the embodiment of the present application, it is possible to realize the user operation as much as possible (reducing the problem caused by the user operation error), and simultaneously calibrate the newly added bright spot dead pixels. And dark spots are bad points to correct these dead pixels.

DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings to be used in the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present application. For ordinary technicians, other drawings can be obtained based on these drawings without paying for creative labor.

1 is a schematic block diagram of a photographing apparatus of an embodiment of the present application;

2 is a schematic structural view of a drone according to an embodiment of the present application;

3 is a schematic flowchart of a method for detecting a dead pixel of an image sensor according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a specific example of an image sensor dead center detecting method according to an embodiment of the present application.

Fig. 5 is a schematic diagram showing a conventional calculation method employed in static dead point correction.

detailed description

The technical solutions in the embodiments of the present application are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present application. It is obvious that the described embodiments are a part of the 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 of the present application without departing from the inventive scope shall fall within the scope of the application.

First, the configuration of the imaging apparatus 100 of the embodiment of the present application will be described with reference to FIG.

FIG. 1 is a schematic block diagram of a photographing apparatus 100 of an embodiment of the present application. As shown in FIG. 1, the photographing apparatus 100 includes at least a lens group 101, an image sensor 102 that converts optical information acquired by the lens group 101 into image data, a processor 103 that controls the entire photographing apparatus 100, and a storage medium 104 that stores There are various data and programs, and when the program is executed, the processor 103 can execute the detection method of the image sensor dead pixels of the embodiment of the present application.

By way of example and not limitation, in the embodiment of the present application, the processor 103 may be a central processing unit (Central Processing Unit (CPU), or other general-purpose processor, digital signal processor (DSP), dedicated. Integrated Circuits (ASICs), Field Programmable Gate Arrays ("FPGAs") or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, and the like. Also, the above general purpose processor may be a microprocessor or may be any conventional processor or the like. In addition, the image sensor 102 in the embodiment of the present application may include a charge-coupled device (CCD) and a complementary metal oxide semiconductor (CMOS). In addition, the storage medium 104 in the embodiment of the present application includes, but is not limited to, cloud storage, U disk, hard disk, SD card, NandFlash, NorFlash, Read-Only Memory (ROM), and random. A variety of media that can store data and program code, such as a random access memory (RAM), a disk, or an optical disk.

In addition, in the embodiment of the present application, the above-described photographing apparatus 100 may be, for example, a camera, a video camera, or a terminal device (for example, a mobile phone, a tablet computer, or a notebook computer) having an image capturing function.

Alternatively, the above-described imaging device 100 may be used in a drone or the like. Unmanned Aerial Vehicle (UAV) has been developed from military to more and more civilian applications, such as UAV plant protection, UAV aerial photography, UAV forest fire alarm monitoring, etc., and civilization is also the future of UAV. The trend of development. In some scenarios, the UAV can carry payloads for performing specific tasks through the carrier. For example, when using UAV for aerial photography, the UAV can carry the shooting device through the pan/tilt.

Next, the drone 1000 of the embodiment of the present application will be described with reference to FIG. FIG. 2 is a schematic structural diagram of a drone 1000 according to an embodiment of the present application. The drone 1000 performs wireless communication with the smart terminal 2000, and the smart terminal 2000 remotely controls the drone 1000. The drone includes at least the photographing device 100 of the embodiment of the present application; and the pan/tilt head 200 for fixing the photographing device 100.

The smart terminal 2000 can be a terminal such as a smart phone or a tablet computer. The smart terminal 2000 is configured to: when receiving the triggering operation on the control interface displayed on the screen, the command signal is wirelessly forwarded to the drone 1000, thereby performing flight operations and shooting on the drone 1000. The shooting operation of the device 100 is controlled.

Hereinafter, a method for detecting a dead pixel of an image sensor according to an embodiment of the present application will be described with reference to FIG. FIG. 3 is a schematic flowchart of a method for detecting a dead pixel of an image sensor according to an embodiment of the present application.

In the embodiment of the present application, an algorithm based on the dynamic dead point correction idea described in the background art section may be built in the photographing apparatus 100 as needed. An example of this algorithm can be given, as shown in Fig. 5, if c>((a+d)/2+(b+e)/2)/2+x, or c<((a+d)/2 +(b+e)/2)/2-y, the pixel pointed to by c is considered to be a dead pixel, where x and y are threshold values and are positive integers. When a user takes a photo or video using the photographing device 100, the dynamic dead pixel correction algorithm performs a dead pixel position (pixel position) detection (including bright spots and dark spots) for each frame of each photo or video, for a photo or video. The frame is analyzed to compare the difference between each pixel and the surrounding pixels. If the surrounding pixel values are relatively consistent and the pixel value is different, the pixel is marked as a dynamic dead pixel (ie, an image dead point).

As shown in FIG. 3, first, in step S1, the position of the image dead point is detected for the photographed photo or video frame. In step S2, the position of the image dead point of a plurality of photos or video frames in a photo or video frame that meet certain conditions is recorded and stored. In step S3, the position of the recorded image dead point is counted, and then, in step S4, a certain number or more (for example, 80% or more) of the plurality of photos or video frames satisfying the certain condition are used. The position of the image dead point appearing in each of the photo or video frames is determined as the position of the image sensor dead point.

Through the above method, it is possible to automatically and automatically calibrate new dead pixels on a regular basis without requiring user operations.

By way of example and not limitation, in the embodiment of the present application, the image sensor dead pixels include a bright point dead point and a dark point dead point, and the certain condition means that the RAW format picture brightness and the exposure parameter of the photo or video frame are specified. The range is different, and the certain conditions are different for the bright point and the dark point. Specifically, in the case of detecting the bright spot dead point, the certain condition is that the RAW format picture brightness of the photo or video frame is lower than the first brightness value, the exposure time is greater than the first duration, and the sensitivity value is higher than the first a sensitivity value, in the case of detecting the dark spot dead point, the certain condition is that the RAW format picture brightness of the photo or video frame is higher than the second brightness value greater than the first brightness value and less than the highest value, The exposure time is less than a second time length shorter than the first time length, and the sensitivity value is lower than the second sensitivity value smaller than the first sensitivity value. In addition, the image sensor dead point is a dead point that must occur under a predetermined condition, and the image dead point is a bad point that occurs probabilistically even if the predetermined condition is reached, and the predetermined condition is, for example, that the exposure time is greater than The specified value and the image sensor reach the specified temperature.

In some embodiments, the location of the recorded image dead pixels is triggered to be counted when the recorded photo or video frame reaches a predetermined number (eg, 100).

In some embodiments, the location of the previously stored image dead point is deleted after the location of the image sensor dead point is determined.

In some embodiments, for a pixel that is marked as a dead pixel of an image sensor, the value obtained by calculating the value of the surrounding pixels of its kind is substituted for its value.

A specific example of the method for detecting an image sensor dead pixel in the embodiment of the present application will be described below with reference to FIG. FIG. 4 is a schematic diagram of a specific example of an image sensor dead center detecting method according to an embodiment of the present application.

In the process of shooting by the user using the photographing device 100, the position of the dynamic dead point of the photo or video frame that meets certain conditions is recorded (here, "certain condition" refers to, for example, the RAW format brightness of the photo or video frame, and the exposure parameter is Within a certain range, and the conditions for the bright spots and the dark spots are different, and these locations are saved to the storage medium 104 in the same photo or the same frame. As shown in FIG. 4, when a recorded number of photos or frames reaches a certain number (100 sheets: P1 to P100), the recorded dynamic dead point positions are analyzed and counted. In FIG. 4, points A to I indicate dynamic bad. Point, if point A appears in most photos or frames (ie, the number of photos or frames containing the point A exceeds a certain percentage, for example, can be set to 80%), the position of the point A is marked as a static dead point ( That is, the image sensor is a dead pixel). In addition, considering the problem of the storage space, after the above-mentioned series of detection operations are completed, the position data of each of the previously stored dynamic dead pixels is deleted, thereby leaving more storage space for the subsequent detection. Since the dynamic dead-point correction algorithm may capture noise or a point that is different from the surrounding in the actual image, the noise may randomly appear on one or a few adjacent pixels of the image sensor. It will not always be fixed on one or a few pixels, and the points in the actual image that differ greatly from the surroundings will also appear at different positions on different photos or frames as the camera or subject moves. In this way, at the point captured by the same pixel position of most photos or frames, it can be determined that it is a static dead pixel (the reason why it does not appear on all photos is because the photos taken by the user, not the brightness of all areas of the entire photo. Meet the conditions for exposing dead pixels).

In addition, with regard to the "certain conditions" mentioned above, for bright spots, the conditions of photos or frames generally require a lower brightness of the RAW format (for example, less than 40 (in the range of 0-255 brightness)), and the exposure time is relatively long (for example) More than 2 seconds, generally close to the maximum exposure time that the camera can support), high ISO (generally high ISO (sensitivity) starts at 800, ≥ 800). For dark spots, the condition of the photo or frame generally requires a higher brightness in the RAW format (usually higher than a certain value, but lower than the highest value, such as higher than 120 and lower than 255 (with a brightness range of 0-255) Calculate)), the exposure time can not be too long (for example, less than 1/100 seconds), low ISO (generally take ISO100). The above numerical values are merely examples, and the present application is not limited thereto, and may be any condition that can detect bright spots or dark spots.

According to the above method of the embodiment of the present application, a new dead point (static dead pixel, that is, an image sensor dead point) can be caught in the background without a user operation, and includes a bright point dead point and a dark point dead point, compared with the conventional method. Not only is the function more comprehensive, but it also reduces the risk of bad mark error due to user unprofessionality, and also reduces the trouble of user operation. Since the software in the photographing device operates automatically and in real time as long as the photographing device takes a photo or video, it is possible to increase the appearance of a dead pixel.

Based on the same concept as the above method, the embodiment of the present application further provides a computer readable storage medium 104, which stores an executable program, and when executed by the processor 103, the processor 103 executes the image of the embodiment of the present application. Method for detecting sensor dead pixels.

In addition, for the drone having the shooting function, the embodiment of the present application further provides another method for marking the new dead point (bright spot): triggering through the menu or virtual button of the App on the mobile phone or the Pad, the command signal The remote control (smart terminal) wirelessly forwards to the camera on the drone, the camera closes the mechanical shutter to create a black environment for the image sensor, and the camera sets a long exposure time, high ISO shooting one or more RAW Format photo, the software reads all the photos and detects all the bad points on the photo; then the software reads the dead spots that the camera has been calibrated before leaving the factory, by comparing the original dead spots and detecting this time. The bad point position, pick out the bad points of this detection and store it as a new bad point to store in the storage medium. In the actual shooting, the factory has a bad point position and a new dead point corrected at the same time. When the user performs the operation calibration more than once, the RAW format photo is also taken. The software compares the position of this dead pixel and all previous calibrations (including the factory and the user's own calibration), and calibrates the newly added dead pixels and the previous users themselves. The bad points are stored together as a new dead point.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of cells is only a logical function division. In actual implementation, there may be another division manner. For example, multiple units or components may be combined or integrated. Go to another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be electrical, mechanical or otherwise. The units described as separate components may or may not be physically separated, and the components represented as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

It should be understood that, in the various embodiments of the present application, the size of the sequence numbers of the foregoing processes does not mean the order of execution sequence, and the order of execution of each process should be determined by its function and internal logic, and should not be applied to the embodiment of the present application. The implementation process constitutes any limitation. Some block diagrams and/or flowcharts are shown in the drawings. It will be understood that some blocks or combinations of the block diagrams and/or flowcharts can be implemented by computer program instructions. These computer program instructions may be provided to a general purpose computer, a special purpose computer or a processor of other programmable data processing apparatus such that when executed by the processor, the instructions may be used to implement the functions illustrated in the block diagrams and/or flowcharts. / operating device. Thus, the techniques of this disclosure may be implemented in the form of hardware and/or software (including firmware, microcode, etc.). Additionally, the techniques of this disclosure may take the form of a computer program product on a computer readable medium storing instructions for use by or in connection with an instruction execution system (eg, one or more processors) . In the context of the present disclosure, a computer readable medium can be any medium that can contain, store, communicate, propagate or transport the instructions.

Finally, it should be noted that the above embodiments are only for explaining the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that The technical solutions described in the foregoing embodiments may be modified, or some or all of the technical features may be equivalently replaced; and the modifications or substitutions do not deviate from the technical solutions of the embodiments of the present application. The scope should be covered by the scope of protection of this application.

Claims

A method for detecting a dead pixel of an image sensor, comprising:

Detecting the position of the image dead point on the captured photo or video frame;

Recording and storing the location of image dead pixels of a plurality of photos or video frames in the photo or video frame that meet certain conditions;

Counting the position of the recorded image dead pixels;

The position of the image dead point appearing in each of a certain number of photos or video frames in the plurality of photos or video frames that meet the certain conditions is determined as the position of the image sensor dead point.
The method of detecting a dead pixel of an image sensor according to claim 1, wherein

The image sensor dead pixels include bright spot dead pixels and dark spot dead pixels.
The method of detecting a dead pixel of an image sensor according to claim 2, wherein

The certain condition means that the RAW format picture brightness and the exposure parameter of the photo or video frame are within a prescribed range, and the certain conditions are different for the bright point dead point and the dark point dead point.
The method of detecting a dead pixel of an image sensor according to claim 3, wherein

In the case of detecting the bright spot dead point, the certain condition means that the RAW format picture brightness of the photo or video frame is lower than the first brightness value, the exposure time is greater than the first time length, and the sensitivity value is higher than the first sensitivity value. ,

In the case of detecting the dark spot dead point, the certain condition means that the RAW format picture brightness of the photo or video frame is higher than the second brightness value greater than the first brightness value and less than the highest value, and the exposure time is less than the first For a second duration of time, the sensitivity value is lower than the second sensitivity value that is less than the first sensitivity value.
The method of detecting a dead pixel of an image sensor according to claim 1, wherein

When the recorded photo or video frame reaches a predetermined number, the position of the recorded image dead point is triggered to be counted.
The method of detecting a dead pixel of an image sensor according to claim 1, wherein

The percentage of the certain number relative to the total number of the plurality of photos or video frames that meet certain conditions is 80%.
The method of detecting a dead pixel of an image sensor according to claim 1, wherein

After the position of the image sensor dead point is determined, the position of the previously stored image dead point is deleted.
The method of detecting a dead pixel of an image sensor according to claim 1, wherein

The image sensor dead point is a dead point that must occur under specified conditions.

The image dead point is a bad point that occurs probabilistically even if the prescribed condition is reached.
The method of detecting a dead pixel of an image sensor according to claim 8, wherein

The predetermined condition means that the exposure time is greater than a predetermined value and the image sensor reaches a predetermined temperature.
The method of detecting an image sensor dead pixel according to any one of claims 1 to 9, wherein

For a pixel that is marked as a dead pixel of an image sensor, the value obtained by calculating the value of the same type of pixel around it is substituted for its value.
A photographing device comprising:

Lens group

An image sensor that converts optical information acquired by the lens group into image data;

a processor that controls the entire imaging device;

a storage medium that stores various data and programs.

The processor executes:

Detecting the position of the image dead point on the captured photo or video frame;

Recording and storing, in the storage medium, a position of an image dead point of a plurality of photos or video frames in the photo or video frame that meet certain conditions;

Counting the position of the recorded image dead pixels;

The position of the image dead point appearing in each of a certain number of photos or video frames in the plurality of photos or video frames that meet the certain conditions is determined as the position of the image sensor dead point.
The photographing apparatus according to claim 11, wherein

The image sensor dead pixels include bright spot dead pixels and dark spot dead pixels.
The photographing apparatus according to claim 12, wherein

The certain condition means that the RAW format picture brightness and the exposure parameter of the photo or video frame are within a prescribed range, and the certain conditions are different for the bright point dead point and the dark point dead point.
The photographing apparatus according to claim 13, wherein

In the case of detecting the bright spot dead point, the certain condition means that the RAW format picture brightness of the photo or video frame is lower than the first brightness value, the exposure time is greater than the first time length, and the sensitivity value is higher than the first sensitivity value. ,

In the case of detecting the dark spot dead point, the certain condition means that the RAW format picture brightness of the photo or video frame is higher than the second brightness value greater than the first brightness value and less than the highest value, and the exposure time is less than the first For a second duration of time, the sensitivity value is lower than the second sensitivity value that is less than the first sensitivity value.
The photographing apparatus according to claim 11, wherein

The processor controls such that when the recorded photo or video frame reaches a predetermined number, the location of the recorded image dead point is triggered to be counted.
The photographing apparatus according to claim 11, wherein

The percentage of the certain number relative to the total number of the plurality of photos or video frames that meet certain conditions is 80%.
The photographing apparatus according to claim 11, wherein

The processor controls such that after determining the position of the image sensor dead point, the position of the image dead point previously stored in the storage medium is deleted.
The photographing apparatus according to claim 11, wherein

The image sensor dead point is a dead point that must occur under specified conditions.

The image dead point is a bad point that occurs probabilistically even if the prescribed condition is reached.
The photographing apparatus according to claim 18, wherein

The predetermined condition means that the exposure time is greater than a predetermined value and the image sensor reaches a predetermined temperature.
The photographing apparatus according to any one of claims 11 to 19, wherein

The processor also executes:

For a pixel that is marked as a dead pixel of an image sensor, the value obtained by calculating the value of the same type of pixel around it is substituted for its value.
A drone that wirelessly communicates with a smart terminal that remotely controls a drone, the drone including:

The photographing apparatus according to any one of claims 11 to 20;

A cloud platform for fixing the camera.
A computer readable storage medium storing an executable program that, when executed by a processor, causes the processor to perform the image sensor dead pixel detection method according to any one of claims 1 to 10.