WO2020181522A1

WO2020181522A1 - Defective pixel detection method, image processing chip, and electronic device

Info

Publication number: WO2020181522A1
Application number: PCT/CN2019/077989
Authority: WO
Inventors: 汪超
Original assignee: 深圳市汇顶科技股份有限公司
Priority date: 2019-03-13
Filing date: 2019-03-13
Publication date: 2020-09-17
Also published as: CN112020729A

Abstract

A defective pixel detection method, an image processing chip and an electronic device. The defective pixel detection method comprises: determining at least two pixel points within a neighboring area of a target pixel point, as a first pixel point and a second pixel point, at least one of the first pixel point and the second pixel point being adjacent to the target pixel point (S101); calculating a pixel difference between every two pixel points having an adjacent position relationship among the target pixel point, the first pixel point and the second pixel point, to obtain a first pixel difference and a second pixel difference (S102); and according to the first pixel difference and the second pixel difference, determining whether the target pixel point is a defective pixel (S103). The defective pixel detection method effectively realizes the detection of a defective pixel, provides effective basic data for the correction of a defective pixel, and can be implemented on the basis of simple hardware logic, having the advantages of quick detection and high efficiency.

Description

Image dead pixel detection method, image processing chip and electronic equipment

Technical field

The embodiments of the present application relate to the field of image processing technology, and in particular, to a method for detecting image dead pixels, an image processing chip, and an electronic device.

Background technique

The array formed by the light collection points (pixels) on the image sensor has process defects, or errors occur in the process of converting light signals into electrical signals, which will cause pixel information on the image to be incorrect, resulting in incorrect pixel values in the image. Accurately, these defective pixels are image dead pixels.

Due to different process technologies and sensor manufacturers, especially for some low-cost, consumer products, the number of dead pixels will be many. In addition, the sensor will have more and more dead pixels in a long-term, high-temperature environment, thereby destroying the clarity and integrity of the image.

Summary of the invention

In view of this, one of the technical problems solved by the embodiments of the present invention is to provide a method for detecting dead pixels, an image processing chip, and an electronic device to overcome the above-mentioned defects in the prior art.

The embodiment of the application provides a method for detecting dead pixels in an image, which includes:

Determining at least two pixel points in the neighborhood of the target pixel point as a first pixel point and a second pixel point, respectively, at least one of the first pixel point and the second pixel point and the target pixel point;

Calculating the pixel difference value of every two pixels having an adjacent position relationship among the target pixel point, the first pixel point, and the second pixel point to obtain the first pixel difference value and the second pixel difference value respectively;

According to the first pixel difference value and the second pixel difference value, it is determined whether the target pixel is a bad image.

Optionally, in any embodiment of the present application, the method further includes: determining whether the target pixel is located at the edge of the pixel array, so as to determine at least two pixels in the neighborhood of the target pixel according to the result of the determination.

Optionally, in any embodiment of the present application, if the target pixel is located at the left edge of the pixel array, the neighborhood is at least one of a right neighborhood, an upper neighborhood, and a lower neighborhood; If the target pixel is located at the right edge of the pixel array, the neighborhood is at least one of a left neighborhood, an upper neighborhood, and a lower neighborhood; if the target pixel is located at the upper edge of the pixel array, then The neighborhood is at least one of a lower neighborhood, a left neighborhood, and a right neighborhood; if the target pixel is located at the lower edge of the pixel array, the neighborhood is an upper area, a left neighborhood, and a right neighborhood. At least one of the domains.

Optionally, in any embodiment of the present application, the pixel difference value of every two pixels having an adjacent position relationship among the target pixel, the first pixel, and the second pixel is calculated , Respectively obtaining the first pixel difference value and the second pixel difference value, including: calculating the pixel difference value between the target pixel point and the first pixel point to obtain the first pixel difference value; calculating the first pixel point and the first pixel point The pixel difference value of the two pixels obtains the second pixel difference value.

Optionally, in any embodiment of the present application, the pixel difference value of every two pixels having an adjacent position relationship among the target pixel, the first pixel, and the second pixel is calculated , Respectively obtaining the first pixel difference value and the second pixel difference value, including: calculating the pixel difference value between the target pixel and the first pixel to obtain the first pixel difference; calculating the second pixel and the target The pixel difference value of the pixel point obtains the second pixel difference value.

Optionally, in any embodiment of the present application, determining the first pixel and the second pixel in the neighborhood of the target pixel includes: determining the first pixel and the second pixel in several neighborhoods of the target pixel Two pixels, for each neighborhood, calculate the pixel difference of every two pixels that have an adjacent position relationship among the target pixel, the first pixel, and the second pixel to obtain respectively The first pixel difference and the second pixel difference;

Correspondingly, judging whether the target pixel is a bad image according to the first pixel difference value and the second pixel difference value includes: according to the first pixel difference value and the second pixel difference value corresponding to at least one of the neighborhoods. The pixel difference value is used to preliminarily determine whether the target pixel is a suspicious bad image; according to the first pixel difference value and the second pixel difference value corresponding to at least one of the remaining neighborhoods, the suspicious image is judged again as bad Whether the dots are actually dead pixels of the image.

Correspondingly, judging whether the target pixel is a bad image according to the first pixel difference value and the second pixel difference value includes: according to the first pixel difference value and the second pixel difference value corresponding to at least one of the neighborhoods. Pixel difference value, to determine whether the target pixel is a suspicious bad image; according to the first pixel difference value and the second pixel difference value corresponding to at least one of the remaining neighborhoods, determine whether the target pixel point is Suspicious dead pixels in the image; if the number of times the target pixel is determined to be a suspicious dead pixel in the image is greater than or equal to two times, it is determined that the target pixel is a substantial dead pixel in the image.

Optionally, in any embodiment of the present application, judging whether the target pixel is a bad image based on the first pixel difference value and the second pixel difference value includes: determining the first pixel difference The pixel difference value and the pixel change rate between the second pixel difference value; according to the pixel change rate and the pixel change rate threshold, it is determined whether the target pixel is an image dead pixel.

An embodiment of the present application also provides an image processing chip, which includes a controller, and the controller is used to determine at least two pixels in the neighborhood of the target pixel as the first pixel and the second pixel, respectively. At least one of the first pixel point and the second pixel point is related to the target pixel point, and every two pixels of the target pixel point, the first pixel point, and the second pixel point that have an adjacent position relationship The pixel difference values of the dots are obtained respectively to obtain a first pixel difference value and a second pixel difference value; and according to the first pixel difference value and the second pixel difference value, it is determined whether the target pixel is an image bad pixel.

The application also provides an electronic device, which includes the image processing chip in the embodiment of the application.

In the technical solution provided by the embodiments of the present application, at least two pixels in the neighborhood of the target pixel are determined as the first pixel and the second pixel; the target pixel, the first pixel, and the The pixel difference values of every two pixels in the second pixel point that have an adjacent position relationship are obtained as a first pixel difference value and a second pixel difference value, at least one of the first pixel point and the second pixel point Adjacent to the target pixel; determining whether the target pixel is a bad image based on the first pixel difference value and the second pixel difference value. The detection method of image dead pixels effectively realizes the detection of image dead pixels, provides effective basic data for the correction of dead pixels, and can be realized based on simple hardware logic, and has the characteristics of rapid detection and high efficiency.

Description of the drawings

Hereinafter, some specific embodiments of the embodiments of the present application will be described in detail in an exemplary but not restrictive manner with reference to the accompanying drawings. The same reference numerals in the drawings indicate the same or similar components or parts. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the attached picture:

FIG. 1 is a schematic flowchart of a method for detecting dead pixels in an image in Embodiment 1 of this application;

2 is a schematic flowchart of a method for detecting dead pixels in an image in Embodiment 2 of this application;

3 is a schematic flowchart of a method for detecting dead pixels in an image in Embodiment 3 of the application;

4 is a schematic diagram of the structure of the image processing chip in the fourth embodiment of the application.

detailed description

The implementation of any technical solution of the embodiments of the present invention does not necessarily need to achieve all the above advantages at the same time.

The specific implementation of the embodiments of the present invention will be further described below in conjunction with the accompanying drawings of the embodiments of the present invention.

In the technical solution provided by the embodiment of the present application, at least two pixels in the neighborhood of the target pixel are determined as the first pixel and the second pixel, and at least one of the first pixel and the second pixel is 1. Adjacent to the target pixel; calculating the pixel difference of every two pixels having an adjacent position relationship among the target pixel, the first pixel, and the second pixel to obtain the first pixel respectively A difference value and a second pixel difference value; according to the first pixel difference value and the second pixel difference value, it is determined whether the target pixel is a bad image. The detection method of image dead pixels effectively realizes the detection of image dead pixels, provides effective basic data for the correction of dead pixels, and can be realized based on simple hardware logic, and has the characteristics of rapid detection and high efficiency.

Figure 1 is a schematic flow chart of the method for detecting dead pixels in an image in the first embodiment of this application; as shown in Figure 1, in this embodiment, it is described as an example to separately detect whether a certain pixel on the pixel array of the image is a dead pixel. Specifically, the corresponding method for detecting dead pixels on the image includes:

S101. Determine at least two pixel points in the neighborhood of the target pixel point as a first pixel point and a second pixel point respectively, and at least one of the first pixel point and the second pixel point is similar to the target pixel point adjacent;

In this embodiment, the bad pixel detection of the image is performed based on the pixel difference between the target pixel and the pixel in its neighborhood. If the location of the target pixel is different, the selection of its neighborhood may be different, especially for the pixel array. For pixels located at the edge, which can also be called edge pixels here, the direction of the neighborhood is relatively small compared to non-edge pixels in other locations. It is necessary to ensure that the target pixel has an optional neighborhood, and that there are optional pixels in the neighborhood.

Therefore, in consideration of the above situation, in this embodiment, step S101 may include determining whether the target pixel is located at the edge of the pixel array, so as to determine at least two pixels in the neighborhood of the target pixel according to the result of the determination. For example, by scanning the pixels to determine at least two pixels in the neighborhood of the target pixel.

Further, in this embodiment, the edges of the pixel array may specifically include a left edge, a right edge, an upper edge, and a lower edge. The pixels located on these edges may be called edge pixels, such as left edge pixels and right edges. Pixels, upper edge pixels, and lower edge pixels; therefore, if the target pixel is located at the left edge of the pixel array, the neighborhood is at least one of the right neighborhood, the upper neighborhood, and the lower neighborhood ; If the target pixel is located at the right edge of the pixel array, the neighborhood is at least one of the left neighborhood, upper neighborhood, and lower neighborhood; if the target pixel is located at the upper edge of the pixel array, The neighborhood is at least one of the lower neighborhood, the left neighborhood, and the right neighborhood; if the target pixel is located at the lower edge of the pixel array, the neighborhood is the upper area, the left neighborhood, and the right neighborhood. At least one of the neighborhoods.

Especially if the target pixel is an edge pixel, as mentioned above, its neighborhood may only exist in a certain direction. For example, if it is a left edge pixel, its neighborhood is the right neighborhood, including the horizontal direction and the horizontal direction. The right neighborhood defined by the diagonal direction with an acute angle. For other right edge pixels, upper edge pixels, and lower edge pixels, the corresponding neighborhoods are the left neighborhood, the lower neighborhood, and the upper neighborhood, respectively.

Therefore, for the above-mentioned edge pixels, in order to determine the change in the pixel difference, two pixels are successively selected as the first pixel and the second pixel respectively in the neighborhood direction, and the target pixel is The pixel difference with the first pixel is the first pixel difference; the pixel difference between the second pixel and the target pixel is calculated as the second pixel difference. For example, if the target pixel is the left edge pixel, since its neighborhood is the right neighborhood, two consecutive pixels are selected from the same row of pixels on the right as the first pixel and the second pixel. The first pixel point is adjacent to the target pixel point.

Of course, in other application scenarios, if the target pixel is the left edge pixel, since its neighbor is the right neighbor, a pixel from the same row of pixels on the right is selected as the first pixel, and the pixel is One pixel is selected from the pixels in the same column as the second pixel.

In practical applications, because the pixels at the edge of the pixel array are less effective, in this embodiment, the so-called edge pixels are preferably other edge pixels except for the pixels at the edge of the pixel array, such as sub-edge pixels or also called Sub-edge pixels, however, if the edge pixels are more effective, of course, the edge pixels can also include these edge pixels.

Further, in other embodiments, if the target pixel is not located at the left edge of the pixel array, there are at least four choices for the neighborhood of non-edge pixels: right area, left neighborhood, lower neighborhood, and upper neighborhood , It can be flexibly selected according to the application scenario; the comparison shows that the neighborhood of non-edge pixels has a larger choice than the neighborhood of edge pixels. In an application scenario, one of the pixels in the right neighborhood and the left neighborhood can be selected as the first pixel and the second pixel, for example, a non-edge target pixel in the left neighborhood and the same as the target pixel. The adjacent pixel point is regarded as the first pixel point, the pixel point located in the right neighborhood of the non-edge target pixel point and adjacent to the target pixel point is regarded as the second pixel point, the first pixel point, the target pixel point, the second pixel point The pixels are in the same row. Or, in another application scenario, a pixel located in the upper neighborhood of the non-edge target pixel and adjacent to the target pixel is used as the first pixel, and located in the lower neighborhood of the non-edge target pixel and connected to the The pixel point adjacent to the target pixel point is used as the second pixel point, and the first pixel point, the target pixel point, and the second pixel point are located in the same column. Or, in another application scenario, a pixel located in the right neighborhood of a non-edge target pixel and in the same row as the target pixel and adjacent to each other is used as the first pixel, located in the right area of the target pixel and A pixel adjacent to the first pixel and in the same column is used as the second pixel, the first pixel and the target pixel are located in the same row, and the first pixel and the second pixel are located in the same column.

S102. Calculate the pixel difference value of every two pixels having an adjacent position relationship among the target pixel point, the first pixel point, and the second pixel point to obtain a first pixel difference value and a second pixel point respectively Difference.

In this embodiment, when the first pixel difference value and the second pixel difference value are obtained by calculating the pixel difference value in step S102, it may specifically include calculating the pixel difference value between the target pixel and the first pixel to obtain the first pixel difference. A pixel difference value; the pixel difference value between the second pixel point and the target pixel point is calculated to obtain the second pixel difference value. Specifically, for example, if the target pixel is a left edge pixel, and the pixel in its right neighborhood is two consecutive pixels in the same row as the left edge pixel, one of the pixels is adjacent to the left edge pixel, that is, The pixel with the left edge pixel is regarded as the first pixel, and the pixel adjacent to the first pixel is regarded as the second pixel. In step S102, the pixels between the target pixel and the first pixel are calculated The difference is the first pixel difference, and the pixel difference between the first pixel and the second pixel is the second pixel difference. For other edge pixels, the calculation method of the corresponding first pixel difference and second pixel difference is similar to the case where the target pixel is the left edge pixel, and details are not repeated here.

In this embodiment, when calculating the pixel difference value of every two pixels having an adjacent position relationship among the target pixel point and the pixel points in its neighborhood, to obtain the first pixel difference value and the second pixel difference value, the specific Calculate the pixel difference of every two pixels that have an adjacent position relationship among the target pixel, the first pixel, and the second pixel to obtain the first pixel difference and the second pixel difference respectively .

Here, it should be noted that when calculating the pixel difference of the two adjacent pixels, the direction of calculating the difference must be the same, that is, the previous pixel value is used to subtract the next pixel value; or, after uniform use Just subtract the previous pixel value from one pixel value.

Further, in order to further improve the accuracy of dead pixel detection, when determining the first pixel and the second pixel in the target pixel and its neighborhood in step S102, specifically determine the first pixel in several neighborhoods of the target pixel Point and second pixel point, to calculate the pixel difference value of every two pixels in the adjacent position relationship among the target pixel point, the first pixel point, and the second pixel point for each neighborhood , Respectively obtain the first pixel difference value and the second pixel difference value.

For example, if the above target pixel is an edge pixel, select its two neighborhoods to select the first pixel and the second pixel. For each neighborhood, calculate the above pixel difference once to obtain the corresponding first pixel. Pixel difference value and second pixel difference value; two neighborhoods total two first pixel difference values and two second pixel difference values. For the case where the target pixel is a non-edge pixel, it is similar to the case of the edge pixel here.

S103: Determine whether the target pixel is a bad image according to the first pixel difference value and the second pixel difference value.

Specifically, in this embodiment, the pixel change rate between the first pixel difference value and the second pixel difference value is determined in step S103; the pixel change rate and the pixel change rate threshold are used to determine the Whether the target pixel is a bad image.

In this embodiment, the size of the pixel change rate threshold is flexibly configured according to the requirements of the application scenario. In fact, from the point of view of bad pixel detection, the pixel change rate threshold can also be called the detection intensity.

As mentioned above, if in order to improve the detection accuracy of dead pixels, if the pixel is selected from at least two neighborhood directions, that is, a first pixel and a second pixel are selected from a neighborhood direction Therefore, a first pixel difference value and a second pixel difference value will be obtained in each neighborhood direction, and then a preliminary judgment is made based on the corresponding first pixel difference value and second pixel difference value in one of the neighborhood directions Whether the target pixel is a suspicious bad pixel of the image, when it is preliminarily judged to be a suspicious bad pixel of the image, such as the difference between the first pixel difference and the second pixel difference, that is, the pixel change rate is greater than the set first pixel change The target pixel is judged to be a suspected bad pixel in the image when the rate threshold is used. Then use the corresponding first pixel difference value and the second pixel difference value in another neighborhood direction to judge again, to finally determine whether the suspicious image defect is a substantial image defect; for example, the corresponding one in another neighborhood direction When the pixel change rate between the first pixel difference value and the second pixel difference value is greater than the set second pixel change rate threshold value, it is determined that the suspected bad pixel of the image is the substantial bad pixel of the image. Here, it should be noted that the first pixel change rate threshold may be the same as or different from the second pixel difference threshold.

That is to say, for any single target pixel, if multiple neighborhoods are determined for it, a preliminary judgment is made based on the first pixel difference and the second pixel difference corresponding to at least one of the neighborhoods Whether the target pixel is a suspicious bad image; according to the first pixel difference and the second pixel difference corresponding to at least one of the remaining neighborhoods, it is judged again whether the suspicious image bad pixel is a substantial image bad point. For example, in the initial judgment, for the first pixel and the second pixel in at least one neighborhood, the pixel change rate between the first pixel difference and the second pixel difference is greater than the set first pixel. In the case of the pixel change rate threshold, it is preliminarily determined that the target pixel is a suspicious bad pixel of the image. If it is determined again, for the first pixel and the second pixel in at least one neighborhood in the remaining area, there will be If the pixel change rate between the first pixel difference value and the second pixel difference value is greater than the set threshold value of the first pixel change rate, it is possible to finally determine the actual bad pixels of the image.

In the above FIG. 1, it is described as an example to detect whether a single target pixel is a dead pixel. In the following embodiments, the detection of dead pixels on an image sensed by the image sensor is taken as an example to describe, that is, to determine the actual dead pixels on a complete image. For this reason, in the following embodiments, the detection is performed sequentially according to the row direction of the pixel array as a whole, and each row of pixels is detected, the next row of pixels is entered to continue the detection of dead pixels. That is, when there are multiple target pixels, how to detect dead pixels.

Figure 2 is a schematic flow chart of the method for detecting dead pixels in an image in the second embodiment of the application; as shown in Figure 2, it includes:

S201: Determine the first pixel point and the second pixel point in the respective neighborhood of the current target pixel point;

In this embodiment, the detailed execution of step S201 can refer to the record of the embodiment in FIG. 1, that is, it is determined whether the target pixel is an edge pixel or a non-edge pixel. If it is an edge pixel, determine the first pixel and the second pixel in the corresponding neighborhood. If it is a non-edge pixel, the first pixel and the second pixel in the corresponding neighborhood are also determined. In order to improve the detection accuracy, the first pixel and the second pixel can also be determined in multiple neighborhoods.

S202. Obtain a pixel difference value group according to the pixel difference value of every two pixels having an adjacent position relationship among the current target pixel point, the first pixel point, and the second pixel point. The value group includes a first pixel difference value and a second pixel difference value;

In this embodiment, the difference between the pixel values of adjacent pixels is calculated based on the pixel values of a total of three pixels including the target pixel, the first pixel, and the second pixel to obtain two pixel differences. , The two pixel differences can form a pixel difference group.

As mentioned above, when the first pixel and the second pixel are respectively determined from multiple neighborhoods of the target pixel, multiple pixel difference groups will be obtained.

S203. According to the first pixel difference value and the second pixel difference value in the pixel difference value group corresponding to the current target pixel point, preliminary judgment is made whether the current target pixel point is a suspicious or bad image pixel, and then the current target pixel point is determined Whether the target pixel is a real dead pixel of the image.

In this embodiment, if the number of neighborhoods in step S201 is one, and for a scene with higher accuracy, the first pixel difference and the second pixel difference in a pixel difference group are used to determine The dead pixels of is actually considered to be suspicious dead pixels of the image, and may not be real dead pixels. Therefore, here, the processing of re-determination of dead pixels is added.

In this embodiment, as mentioned above, if the first pixel and the second pixel in at least two neighborhoods are determined for the current target pixel, then at least one of the neighborhoods can correspond to The first pixel difference value and the second pixel difference value are used to preliminarily determine whether the target pixel is a suspicious bad image; according to the first pixel difference value and the second pixel difference value corresponding to at least one of the remaining neighborhoods , Judge again whether the suspicious image defect is a substantial image defect. For example, whether the pixel change rates corresponding to at least two areas are both greater than the first pixel change rate threshold and the second pixel change rate threshold respectively set. If both are greater than, the target pixel is the substantial dead pixel of the image; otherwise, the target Pixels are only suspected dead pixels in the image. Here, the values of the first pixel change rate threshold and the second pixel change rate threshold may be the same, or it is also called that only one pixel change rate threshold is set, which is used for preliminary judgment and second judgment at the same time.

Or, in another case, for the situation where the target pixel has at least two neighborhoods, if there are at least two neighborhoods where the pixel change rate is greater than the corresponding pixel change rate threshold, that is, the pixel change rate is greater than the corresponding pixel If the number of times of the change rate threshold is greater than or equal to twice, it is directly determined that the target pixel is a substantial dead pixel of the image. That is, if the target pixel is judged according to the first pixel difference value and the second pixel difference value corresponding to at least one of the neighborhoods, whether the target pixel is a suspicious bad image; according to the first pixel corresponding to at least one of the remaining neighborhoods The pixel difference value and the second pixel difference value are used to determine whether the target pixel is a suspicious bad image; if the target pixel is determined to be a suspicious bad image more than twice, then the target pixel is determined It is the real dead pixels of the image.

S204: End the detection of the current target pixel, and start the dead pixel detection of the next target pixel.

Here, it should be noted that if the current target pixel is the last pixel in the row, the next target pixel is the first pixel in the next row. If the current target pixel is the non-last pixel in the row, the next target pixel is located in the same row as the current target pixel, which means that the image failure of each row of pixels in the row direction is achieved. Point detection, that is, switch to the next line to continue the detection of dead pixels in the image.

Fig. 3 is a schematic flow chart of the method for detecting dead pixels in an image in the third embodiment of the application; as shown in Fig. 3, it includes:

S301: Determine first pixel points and second pixel points in respective neighborhoods of a plurality of target pixels;

The difference from the above-mentioned embodiment is that in this embodiment, after determining the first pixel and the second pixel in the respective neighborhoods of all target pixels, jump to step S302 for execution, not for one of the aforementioned After the target pixel completes step S301, it immediately jumps to step S302, and continues to process the same image to be detected. Here, step S301 can also be understood as batch processing of multiple target pixels to determine the first pixel and the second pixel in the respective neighborhoods of all the target pixels.

S302. Calculate the pixel difference value of every two pixels having an adjacent position relationship among each of the target pixel point, the first pixel point, and the second pixel point to obtain a pixel difference value group, respectively, The pixel difference group includes a first pixel difference value and a second pixel difference value, so as to obtain multiple target pixel points corresponding to multiple pixel difference value groups;

In this embodiment, step S302 is similar to the batch design of step S301 above, that is, the execution result of step S302 is that all target pixels correspond to multiple pixel difference groups. At this time, it jumps to step S303 for execution. After completing step S302 for one target pixel, immediately jump to step S303.

S303. For each target pixel point, according to the first pixel difference value and the second pixel difference value in the corresponding pixel difference value group, it is preliminarily determined whether the corresponding target pixel point is a suspicious bad pixel in the image, so as to determine how much If there are suspicious dead pixels in one image, the actual dead pixels of the image are filtered out from the suspicious dead pixels in multiple images.

In this embodiment, step S03 is similar to the batch design of steps S301 and S302, that is, the execution result of step S303 is to obtain whether all target pixels are suspected bad pixels, which can also be called obtaining all suspected bad images. Point, and then further filter out the real bad pixels of the image from all the suspicious bad pixels of the image.

In order to implement the method embodiments in the above embodiments, the embodiments of the present application provide an image processing chip, which may include: a controller, and the controller is used to determine at least two pixel points in the neighborhood of the target pixel point as The first pixel point and the second pixel point, at least one of the first pixel point and the second pixel point and the target pixel point, and the calculation target pixel point, the first pixel point, and the second pixel The pixel difference values of every two pixels in the point that have an adjacent position relationship are respectively obtained as a first pixel difference value and a second pixel difference value; and according to the first pixel difference value and the second pixel difference value, It is determined whether the target pixel is a bad image.

Further, as shown in FIG. 4, it is a schematic diagram of the structure of the image processing chip in the fourth embodiment of the application; as shown in FIG. 4, in addition to the controller, it also includes a memory, a scanning unit, and an output unit. In order to store the pixel values of the pixel array, the scanning unit is used to determine the target pixel and the first pixel and the second pixel in its neighborhood, and the output unit is used to output the detection result, such as image defect Quantity, location, and the number and location of non-image dead pixels, etc.

This embodiment also provides an electronic device, which includes the image processing chip in the foregoing embodiment.

The electronic devices in the embodiments of this application exist in various forms, including but not limited to:

(1) Mobile communication equipment: This type of equipment is characterized by mobile communication functions, and its main goal is to provide voice and data communications. Such terminals include: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones.

(2) Ultra-mobile personal computer equipment: This type of equipment belongs to the category of personal computers, has calculation and processing functions, and generally also has mobile Internet features. Such terminals include: PDA, MID and UMPC devices, such as iPad.

(3) Portable entertainment equipment: This type of equipment can display and play multimedia content. Such devices include: audio, video players (such as iPod), handheld game consoles, e-books, as well as smart toys and portable car navigation devices.

(4) Server: A device that provides computing services. The composition of a server includes a processor 810, hard disk, memory, system bus, etc. The server is similar to a general computer architecture, but because it needs to provide highly reliable services, it is High requirements in terms of performance, reliability, security, scalability, and manageability.

(5) Other electronic devices with data interaction functions.

So far, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown in order to achieve the desired result. In certain embodiments, multitasking and parallel processing may be advantageous.

In the 1990s, the improvement of a technology can be clearly distinguished between hardware improvements (for example, improvements in circuit structures such as diodes, transistors, switches, etc.) and software improvements (improvements in method flow). However, with the development of technology, the improvement of many methods and processes of today can be regarded as a direct improvement of the hardware circuit structure. Designers almost always get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be realized by hardware entity modules. For example, a programmable logic device (Programmable Logic Device, PLD) (for example, a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user's programming of the device. It is programmed by the designer to "integrate" a digital system on a PLD without requiring the chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly realized by "logic compiler" software, which is similar to the software compiler used in program development and writing. The original code must also be written in a specific programming language, which is called Hardware Description Language (HDL), and there is not only one type of HDL, but many types, such as ABEL (Advanced Boolean Expression Language) , AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description), etc., currently most commonly used It is VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. It should also be clear to those skilled in the art that only a little logic programming of the method flow in the above-mentioned hardware description languages and programming into an integrated circuit can easily obtain the hardware circuit that implements the logic method flow.

The controller can be implemented in any suitable manner. For example, the controller can take the form of, for example, a microprocessor or a processor and a computer-readable medium storing computer-readable program codes (such as software or firmware) executable by the (micro)processor. , Logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers and embedded microcontrollers. Examples of controllers include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicon Labs C8051F320, the memory controller can also be implemented as a part of the memory control logic. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, it is entirely possible to program the method steps to make the controller use logic gates, switches, application specific integrated circuits, programmable logic controllers and embedded The same function can be realized in the form of a microcontroller, etc. Therefore, such a controller can be regarded as a hardware component, and the devices included in it for implementing various functions can also be regarded as a structure within the hardware component. Or even, the device for realizing various functions can be regarded as both a software module for realizing the method and a structure within a hardware component.

The systems, devices, modules, or units illustrated in the above embodiments may be specifically implemented by computer chips or entities, or implemented by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cell phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or Any combination of these devices.

For the convenience of description, when describing the above device, the functions are divided into various units and described separately. Of course, when implementing this application, the functions of each unit can be implemented in the same one or more software and/or hardware.

Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

The present invention is described with reference to flowcharts and/or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and/or block in the flowchart and/or block diagram, and the combination of processes and/or blocks in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing equipment to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are generated It is a device that realizes the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device. The device implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operation steps are executed on the computer or other programmable equipment to produce computer-implemented processing, so as to execute on the computer or other programmable equipment. The instructions provide steps for implementing functions specified in a flow or multiple flows in the flowchart and/or a block or multiple blocks in the block diagram.

It should also be noted that the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, product or equipment including a series of elements not only includes those elements, but also includes Other elements that are not explicitly listed, or include elements inherent to this process, method, commodity, or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, commodity, or equipment that includes the element.

Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, this application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

This application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific transactions or implement specific abstract data types. The present application can also be practiced in distributed computing environments. In these distributed computing environments, remote processing devices connected through a communication network execute transactions. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

The above descriptions are only examples of this application and are not used to limit this application. For those skilled in the art, this application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the scope of the claims of this application.

Claims

A method for detecting dead pixels in an image, which is characterized in that it includes:

Determining at least two pixels in the neighborhood of the target pixel as a first pixel and a second pixel respectively, and at least one of the first pixel and the second pixel is adjacent to the target pixel;

Calculating the pixel difference value of every two pixels having an adjacent position relationship among the target pixel point, the first pixel point, and the second pixel point to obtain the first pixel difference value and the second pixel difference value respectively;

According to the first pixel difference value and the second pixel difference value, it is determined whether the target pixel is a bad image.
The method according to claim 1, further comprising: determining whether the target pixel is located at the edge of the pixel array, so as to determine at least two pixels in the neighborhood of the target pixel according to the result of the determination.
The method according to claim 1, wherein if the target pixel is located at the left edge of the pixel array, the neighborhood is at least one of a right neighborhood, an upper neighborhood, and a lower neighborhood; if If the target pixel is located at the right edge of the pixel array, the neighborhood is at least one of a left neighborhood, an upper neighborhood, and a lower neighborhood; if the target pixel is located at the upper edge of the pixel array, then The neighborhood is at least one of a lower neighborhood, a left neighborhood, and a right neighborhood; if the target pixel is located at the lower edge of the pixel array, the neighborhood is an upper area, a left neighborhood, and a right neighborhood At least one of them.
The method according to claim 1, wherein the pixel difference value of every two pixels having an adjacent position relationship among the target pixel, the first pixel, and the second pixel is calculated, Obtaining the first pixel difference value and the second pixel difference value respectively includes: calculating the pixel difference value between the target pixel point and the first pixel point to obtain the first pixel difference value; calculating the first pixel point and the second pixel point The pixel difference value of the pixel point obtains the second pixel difference value.
The method according to claim 1, wherein the pixel difference value of every two pixels having an adjacent position relationship among the target pixel, the first pixel, and the second pixel is calculated, Obtaining the first pixel difference and the second pixel difference respectively includes: calculating the pixel difference between the target pixel and the first pixel to obtain the first pixel difference; calculating the second pixel and the target pixel The pixel difference value of the point obtains the second pixel difference value.
The method according to claim 1, wherein the determining the first pixel and the second pixel in the neighborhood of the target pixel comprises: determining the first pixel and the second pixel in several neighborhoods of the target pixel Pixels, for each neighborhood, calculate the pixel difference of every two pixels that have an adjacent position relationship among the target pixel, the first pixel, and the second pixel to obtain the first A pixel difference value and a second pixel difference value;

Correspondingly, judging whether the target pixel is a bad image according to the first pixel difference value and the second pixel difference value includes: according to the first pixel difference value and the second pixel difference value corresponding to at least one of the neighborhoods. The pixel difference value is used to preliminarily determine whether the target pixel is a suspicious bad image; according to the first pixel difference value and the second pixel difference value corresponding to at least one of the remaining neighborhoods, the suspicious image is judged again as bad Whether the dots are actually dead pixels of the image.
The method according to claim 1, determining the first pixel and the second pixel in the neighborhood of the target pixel includes: determining the first pixel and the second pixel in several neighborhoods of the target pixel to For each neighborhood, calculate the pixel difference of every two pixels that have an adjacent position relationship among the target pixel, the first pixel, and the second pixel to obtain the first pixel difference respectively And the second pixel difference;

Correspondingly, judging whether the target pixel is a bad image according to the first pixel difference value and the second pixel difference value includes: according to the first pixel difference value and the second pixel difference value corresponding to at least one of the neighborhoods. Pixel difference value, to determine whether the target pixel is a suspicious bad image; according to the first pixel difference value and the second pixel difference value corresponding to at least one of the remaining neighborhoods, determine whether the target pixel point is Suspicious dead pixels in the image; if the number of times the target pixel is determined to be a suspicious dead pixel in the image is greater than or equal to twice, it is determined that the target pixel is a substantial dead pixel in the image.
The method according to claim 1, wherein determining whether the target pixel is a bad image based on the first pixel difference value and the second pixel difference value comprises: determining the first pixel The pixel change rate between the difference value and the second pixel difference value; according to the pixel change rate and the pixel change rate threshold, it is determined whether the target pixel is an image dead pixel.
An image processing chip, characterized by comprising: a controller, the controller is used to determine at least two pixels in the neighborhood of a target pixel as a first pixel and a second pixel, the first pixel At least one of the dot and the second pixel is adjacent to the target pixel, and every two pixels of the target pixel, the first pixel, and the second pixel that have an adjacent position relationship are calculated The first pixel difference value and the second pixel difference value are obtained respectively; and according to the first pixel difference value and the second pixel difference value, it is determined whether the target pixel is a bad image.
An electronic device, characterized by comprising the image processing chip of claim 11.