Noise determination method, apparatus and storage medium for image sensor

Abstract

The present disclosure provides a noise determination method of an image sensor, which can be applied to noise determination of an image sensor of a camera module. Based on a preset shooting scene, an initial image under n times gain of the image sensor is obtained, and a light sensing area and a non-light sensing area in the initial image are identified; the non-light sensing area includes a first non-light sensing area and a second non-light sensing area; wherein, along a first direction, the light sensing area and the second non-light sensing area are included in sequence; along a second direction, the first non-light sensing area and the second non-light sensing area are included in sequence; the first direction and the second direction form a preset included angle; based on pixel values of the first non-light sensing area and the second non-light sensing area, a noise state of the image sensor under n times gain is determined, and the accuracy of noise determination of the image sensor is improved.

Description

Technical Field

[0001] This disclosure relates to the field of image processing, and more specifically to a method, apparatus, and storage medium for determining noise in an image sensor. Background Technology

[0002] In related technologies, noise caused by image sensors is one of the main sources of image noise. For example, with the increasing use of CMOS (Complementary Metal Oxide Semiconductor) image sensors in camera modules, photos taken by camera modules using CMOS image sensors exhibit SHBN (Smear-like Horizontal Band Noise) noise in testing environments. SHBN noise also originates from the image sensor.

[0003] In existing methods, SHBN noise is determined by capturing images of actual high dynamic range (HVR) scenes (such as nighttime light bulbs) and observing for horizontal, abnormal bright bands. The presence of significant horizontal bands indicates severe SHBN noise in the camera. However, observing SHBN noise through HVR scenes has several drawbacks: First, the shooting scenes are complex, and real-life HVR environments are diverse. The limitations of visual perception lead to varying degrees of SHBN noise perception, making accurate determination impossible. Therefore, providing a method for accurately determining the noise generated by an image sensor is a pressing technical problem. Summary of the Invention

[0004] To overcome the problems existing in related technologies, this disclosure provides a method, apparatus and storage medium for determining noise in an image sensor.

[0005] According to a first aspect of the present disclosure, a method for determining noise in an image sensor is provided, the method comprising: An initial image is acquired based on a preset shooting scene at an n-fold gain of the image sensor; where n is a positive integer greater than or equal to 1. Identify light-sensitive and non-light-sensitive regions in the initial image; the non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region; wherein, along a first direction, the light-sensitive region and the second non-light-sensitive region are sequentially included; along a second direction, the first non-light-sensitive region and the second non-light-sensitive region are sequentially included; the first direction and the second direction form a preset angle; Based on the pixel values ​​of the first non-photosensitive region and the pixel values ​​of the second non-photosensitive region, the noise state of the image sensor under n times gain is determined.

[0006] In one embodiment, the non-photosensitive area further includes a third non-photosensitive area, and the first non-photosensitive area, the second non-photosensitive area, and the third non-photosensitive area are arranged sequentially along the second direction; Based on the pixel values ​​of the first non-photosensitive region, the second non-photosensitive region, and the third non-photosensitive region, the noise state of the image sensor under n times gain is determined.

[0007] In one embodiment, identifying light-sensitive and non-light-sensitive regions in the initial image includes: The initial image is binarized according to the color channels, and the area where the number of pixels with a value of 1 is greater than the first preset threshold is the light-sensitive area; Based on the light-sensitive area, the second non-light-sensitive area is determined along the first direction; Based on the second non-photosensitive region, the first non-photosensitive region and the third non-photosensitive region are determined along the second direction.

[0008] In one embodiment, the region where the number of pixels with a value of 1 is greater than a first preset threshold is defined as a light-sensitive region, including: Determine the position of each pixel with a value of 1, row by row, using pixels as the unit; The area formed by the position where the number of pixels with a value of 1 in each row is greater than the second preset threshold is determined as the light-sensing area.

[0009] In one embodiment, determining the noise state of the image sensor at n times gain based on the pixel values ​​of the first non-photosensitive region, the second non-photosensitive region, and the third non-photosensitive region includes: Calculate the average pixel value of the preset color channel in the first non-light-sensitive area to obtain a first average value; calculate the average pixel value of the preset color channel in the second non-light-sensitive area to obtain a second average value; calculate the average pixel value of the preset color channel in the third non-light-sensitive area to obtain a third average value. Based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, the noise state of the preset color channel under n times gain of the image sensor is determined.

[0010] In one embodiment, determining the noise state of the preset color channel at n times gain of the image sensor, based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, includes: The absolute value of the difference between the second average value and the first average value, and the maximum value of the absolute value of the difference between the second average value and the third average value, are taken as the noise difference of the preset color channel under the n-fold gain of the image sensor. Based on the noise difference, the noise state of the preset color channel under n times gain of the image sensor is determined.

[0011] In one embodiment, the preset color channels include an R channel, a Gr channel, a Gb channel, and a B channel.

[0012] In one embodiment, determining the noise state of the preset color channel at n times gain of the image sensor based on the noise difference includes: Based on the noise difference values ​​of the R channel, the Gr channel, the Gb channel, and the B channel, the noise state of the image sensor at an n-fold gain is determined.

[0013] In one embodiment, the preset shooting scene includes a light-transmitting area and a non-light-transmitting area, and the light-transmitting area and the non-light-transmitting area are isolated by a light-isolation area.

[0014] In one embodiment, the noise determination method further includes: Determine the noise state of the image sensor at all gains; The noise state of the image sensor is determined based on the noise state at all gains.

[0015] According to a second aspect of the present disclosure, a noise determination apparatus for an image sensor is provided, the noise determination apparatus for the image sensor comprising: Acquisition module: configured to acquire an initial image based on the image sensor at an n-fold gain, according to a preset shooting scene; where n is a positive integer greater than or equal to 1; Recognition module: configured to recognize light-sensitive regions and non-light-sensitive regions in the initial image; the non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region; wherein, along a first direction, the light-sensitive region and the second non-light-sensitive region are included in sequence; along a second direction, the first non-light-sensitive region and the second non-light-sensitive region are included in sequence; the first direction and the second direction form a preset angle; The first determining module is configured to determine the noise state of the image sensor at n times gain based on the pixel values ​​of the first non-photosensitive region and the pixel values ​​of the second non-photosensitive region.

[0016] In one embodiment, the identification module is configured as follows: Based on the pixel values ​​of the first non-photosensitive region, the second non-photosensitive region, and the third non-photosensitive region, the noise state of the image sensor under n times gain is determined.

[0017] In one embodiment, the identification module is configured as follows: The initial image is binarized according to the color channels, and the area where the number of pixels with a value of 1 is greater than the first preset threshold is the light-sensitive area; Based on the light-sensitive area, the second non-light-sensitive area is determined along the first direction; Based on the second non-photosensitive region, the first non-photosensitive region and the third non-photosensitive region are determined along the second direction.

[0018] In one embodiment, the identification module is configured as follows: Determine the position of each pixel with a value of 1, row by row, using pixels as the unit; The area formed by the position where the number of pixels with a value of 1 in each row is greater than the second preset threshold is determined as the light-sensing area.

[0019] In one embodiment, the first determining module is configured to: Calculate the average pixel value of the preset color channel in the first non-light-sensitive area to obtain a first average value; calculate the average pixel value of the preset color channel in the second non-light-sensitive area to obtain a second average value; calculate the average pixel value of the preset color channel in the third non-light-sensitive area to obtain a third average value. Based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, the noise state of the preset color channel under n times gain of the image sensor is determined.

[0020] In one embodiment, the first determining module is configured to: The absolute value of the difference between the second average value and the first average value, and the maximum value of the absolute value of the difference between the second average value and the third average value, are taken as the noise difference of the preset color channel under the n-fold gain of the image sensor. Based on the noise difference, the noise state of the preset color channel under n times gain of the image sensor is determined.

[0021] In one embodiment, the first determining module is configured such that the preset color channels include an R channel, a Gr channel, a Gb channel, and a B channel.

[0022] In one embodiment, the first determining module is configured to: Based on the noise difference values ​​of the R channel, the Gr channel, the Gb channel, and the B channel, the noise state of the image sensor at an n-fold gain is determined.

[0023] In one embodiment, the acquisition module is configured such that the preset shooting scene includes a light-transmitting area and a non-light-transmitting area, and the light-transmitting area and the non-light-transmitting area are isolated by a light-isolation area.

[0024] In one embodiment, the noise determination device further includes: The second determining module is configured to determine the noise state of the image sensor at all gains. The third determining module is configured to determine the noise state of the image sensor based on the noise state under all gains.

[0025] According to a third aspect of the present disclosure, a noise determination apparatus for an image sensor is provided, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to execute the noise determination method for the image sensor provided in this disclosure.

[0026] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, wherein when instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to perform a noise determination method for an image sensor, the method including the noise determination method for an image sensor provided in this disclosure.

[0027] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects: The noise determination method and apparatus for image sensors provided in this disclosure distinguishes between light-sensitive and non-light-sensitive areas based on a preset shooting scene, further distinguishes different non-light-sensitive areas based on the light-sensitive areas, and determines the noise state of the image sensor under n times gain based on the pixel values ​​of different non-light-sensitive areas. This can realize the noise state of the image sensor based on a preset shooting scene, thereby improving the accuracy of noise determination for the image sensor.

[0028] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0029] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0030] Figure 1This is a flowchart illustrating a noise determination method for an image sensor according to an exemplary embodiment; Figure 2 This is a schematic diagram of a shooting fixture 1 according to an exemplary embodiment; Figure 3 This is illustrated according to an exemplary embodiment. Figure 2 An initial image taken in the shooting fixture 1 shown; Figure 4 This is a schematic diagram of a shooting fixture 2 according to an exemplary embodiment; Figure 5 This is illustrated according to an exemplary embodiment. Figure 4 An initial image taken in the shooting fixture 1 shown; Figure 6 This is illustrated according to an exemplary embodiment. Figure 1 The flowchart of step S120 in the illustrated embodiment is shown. Figure 7 This is illustrated according to an exemplary embodiment. Figure 6 The method flowchart of step S1201 in the embodiment shown is shown. Figure 8 This is illustrated according to an exemplary embodiment. Figure 1 The flowchart of step S130 in the illustrated embodiment is shown. Figure 9 This is illustrated according to an exemplary embodiment. Figure 8 The method flowchart of step S1302 in the embodiment shown; Figure 10 This is a schematic diagram illustrating the structure of a noise determination device for an image sensor according to an exemplary embodiment. Figure 11 This is a block diagram illustrating a noise determination apparatus for an image sensor according to an exemplary embodiment. Detailed Implementation

[0031] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0032] This disclosure provides a noise determination method for an image sensor, which can be applied to the noise determination of image sensors in camera modules. An initial image is acquired based on a preset shooting scene and at an n-fold gain of the image sensor. The initial image is then identified as having light-sensitive and non-light-sensitive regions. The non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region. Along a first direction, the image sensor includes both a light-sensitive region and a second non-light-sensitive region; along a second direction, the image sensor includes both a first non-light-sensitive region and a second non-light-sensitive region. The first and second directions form a preset angle. Based on the pixel values ​​of the first and second non-light-sensitive regions, the noise state of the image sensor at an n-fold gain is determined. In the exemplary embodiments of this disclosure, the noise determination method for an image sensor distinguishes between light-sensitive and non-light-sensitive regions based on a preset shooting scene, differentiates different non-light-sensitive regions based on the light-sensitive regions, and determines the noise state of the image sensor at an n-fold gain based on the pixel values ​​of the different non-light-sensitive regions. This method can accurately determine the noise state of the image sensor.

[0033] Exemplary embodiments of this disclosure provide a noise determination method for an image sensor, exemplarily used to determine the noise state of an image sensor in a camera module. Figure 1 This is a flowchart of a noise determination method according to an exemplary embodiment of this disclosure, with reference to... Figure 1 As shown, the noise determination method includes: Step S110: Acquire an initial image based on an image sensor with an n-fold gain, according to a preset shooting scene; where n is a positive integer greater than or equal to 1. Step S120: Identify light-sensitive regions and non-light-sensitive regions in the initial image; the non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region; wherein, along the first direction, the light-sensitive region and the second non-light-sensitive region are included in sequence; along the second direction, the first non-light-sensitive region and the second non-light-sensitive region are included in sequence; the first direction and the second direction form a preset angle. Step S130: Based on the pixel values ​​of the first non-light-sensitive area and the second non-light-sensitive area, determine the noise state of the image sensor under n times gain.

[0034] The noise determination method for an image sensor provided by the exemplary embodiments of this disclosure can, for example, be used to determine the SHBN noise state of a CMOS image sensor. An initial image is acquired based on a preset shooting scene and at an n-fold gain of the image sensor; where n is a positive integer greater than or equal to 1. Light-sensitive regions and non-light-sensitive regions in the initial image are identified; the non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region; wherein, along a first direction, the light-sensitive region and the second non-light-sensitive region are sequentially included, and along a second direction, the first non-light-sensitive region and the second non-light-sensitive region are sequentially included; the first direction and the second direction form a preset angle. The preset angle can be any angle, for example, 90 degrees. Based on the pixel values ​​of the first non-light-sensitive region and the second non-light-sensitive region, the noise state of the image sensor at an n-fold gain is determined.

[0035] Based on the preset shooting scene, the system distinguishes between light-sensitive areas and non-light-sensitive areas. It further distinguishes between different non-light-sensitive areas based on the light-sensitive areas, and determines the noise state of the image sensor under n times gain based on the pixel values ​​of different non-light-sensitive areas. This allows for the accurate determination of the noise phenomenon of the image sensor.

[0036] In the exemplary embodiments provided in this disclosure, in order to accurately determine the noise state of the image sensor, an initial image at n times the gain of the image sensor can be acquired under a preset shooting scenario. The preset shooting scenario may include a light-transmitting area and a non-light-transmitting area. For example, the preset shooting scenario may include a shooting fixture, such as... Figure 2 As shown, Figure 2 A schematic diagram of an imaging fixture shown in an exemplary embodiment of this disclosure is illustrated. The imaging fixture 1 includes a panel 10. The panel 10 includes a light-transmitting area 101 and a light-blocking area 200. The light-transmitting area 101 can be set at any position as needed, for example, it can be as follows: Figure 2 The lower left corner, as shown, can also be set as follows: Figure 4 The left-side center position is shown. The non-transparent area can be an area corresponding to the transparent area along the first axis. For example, the transparent area is located on the left side of the panel, and the non-transparent area can be correspondingly located on the right side along the first vertical axis 11 of the panel. This arrangement of the transparent and non-transparent areas can effectively reproduce the scene caused by horizontal noise.

[0037] In order to further ensure the opacity of the opaque areas, a light isolation area 301 is set between the light-transmitting and opaque areas to further isolate the light-transmitting and opaque areas.

[0038] When capturing images, the camera can be placed in a dark environment, such as a darkroom. The shooting fixture is positioned within the darkroom, and a light source of the same proportion is placed on one side of panel 10. A camera module is used on the other side of panel 10 to capture images of panel 10, ensuring that panel 10 fills the entire frame. Since the initial image's aspect ratio is typically 4:3, the panel can be set in a 4:3 ratio, for example, with the horizontal direction as the length and the vertical direction as the width. The light source can also be set in a 4:3 ratio.

[0039] Shooting modules, such as the camera on a terminal, all have a corresponding gain of n times. For example, n can be 16, meaning there can be a gain of 1 to 16 times. When capturing images, different gains can be selected to obtain initial images with different gains.

[0040] by Figure 2 The illustrated imaging fixture serves as an example to illustrate a method for determining the SHBN noise of a CMOS image sensor, using methods such as... Figure 2 The shooting fixture shown includes a panel 10 with an aspect ratio of 4:3. In a darkroom, a light source proportional to the panel is placed on one side of the panel 10. For example, a light source proportional to the panel can be placed on one side of the panel 10. The light source can be a high-brightness light source, for example, with a surface illuminance greater than 30,000 lux. The fixture has a light-transmitting area 101 located at the lower left corner of the panel 10. A non-light-transmitting area 200 is isolated from the light-transmitting area 101 by a light-isolating area 301. The light source is turned on, and a camera module, such as a terminal camera, is positioned on the other side of the panel 10. At n times gain, the panel 10 is photographed so that the panel 10 fills the entire shooting frame, and an image is acquired to obtain an initial image at n times gain of the image sensor of the camera module.

[0041] Since it is difficult to determine whether the panel 10 fills the entire shooting screen in a dark environment, auxiliary markers 41 can be set at the four corners of the panel 10 to help determine whether the entire panel 10 fills the entire shooting screen. That is, the four corners of the image captured by the shooting module correspond to the auxiliary markers 41 at the four corners of the panel 10. The auxiliary markers 41 can be triangular or other graphic symbols.

[0042] In step S110, an initial image is acquired based on a preset shooting scene and an image sensor gain of n times; where n is a positive integer greater than or equal to 1.

[0043] As described above, the terminal's camera has a corresponding gain of n times, and can obtain an initial image at n times gain in any way. It can obtain an initial image at a certain gain, or it can obtain initial images at all gains. The following explanation uses obtaining initial images at all gains as an example. Using the aforementioned darkroom environment as the preset shooting scene, a light isolation area 301 is set on panel 10 to isolate the light-transmitting area 101 and the non-light-transmitting area 200. The exposure parameters of the camera module are set, including exposure time and gain coefficient. The exposure time is set to a fixed value, for example, 1 second. The analog gain increases in fixed steps, for example, when the step size is 1, it is set to 1x gain, 2x gain, ..., nx gain, where n is a positive integer. Initial images at different gains are captured. Based on the above shooting scene and the camera module's shooting exposure parameters, the initial images corresponding to the camera module at different gains can be obtained, thus determining the SHBN noise state of the camera module at different gains.

[0044] In step S120, light-sensitive regions and non-light-sensitive regions in the initial image are identified; the non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region; wherein, along the first direction, the second non-light-sensitive region and the light-sensitive region are sequentially included; along the second direction, the first non-light-sensitive region and the second non-light-sensitive region are sequentially included; the first direction and the second direction form a preset angle.

[0045] Acquire initial images based on the image sensor gain n times in a preset shooting scene; for example, obtain one initial image for each gain. Determine the noise level for each initial image. Figure 3 Is Figure 2 The image shown is an initial image taken in the preset shooting scene with an image sensor gain of n times, as referenced. Figure 3 As shown, a light-sensitive region 1001 and a non-light-sensitive region 2000 are identified in the initial image. The non-light-sensitive region 2000 includes a first non-light-sensitive region 2001 and a second non-light-sensitive region 2002. Along a first direction, the light-sensitive region 1001 and the second non-light-sensitive region 2002 are sequentially included; along a second direction, the first non-light-sensitive region 2001 and the second non-light-sensitive region 2002 are sequentially included. The first and second directions are perpendicular. Figure 3As shown, the light-sensitive area 1001 is located on the left side of the image and is quadrilateral in shape. A second non-light-sensitive area 2002 is identified, positioned horizontally opposite to it. The width of the second non-light-sensitive area 2002 is the same as the width of the light-sensitive area 1001. The sum of the lengths of the light-sensitive area 1001 and the second non-light-sensitive area 2002 is equal to the length of the image. The first non-light-sensitive area 2001 is located above the second non-light-sensitive area 2002. Its horizontal length is equal to the length of the second non-light-sensitive area 2002, and the sum of its vertical width and the width of the second non-light-sensitive area 2002 is equal to the width of the image. The light-sensitive area 1001 corresponds to the light-transmitting area 101 of the panel.

[0046] In an exemplary embodiment of this disclosure, an initial image is identified with a light-sensitive region 1001 and a non-light-sensitive region 2000, and the non-light-sensitive region 2000 is further identified as a first non-light-sensitive region 2001 and a second non-light-sensitive region 2002. If SHBN noise exists at n times the gain of the image sensor, the light from the light-sensitive region will diffuse in a horizontal direction along the light-sensitive region, forming a strip-shaped light beam. Therefore, the pixel value of the second non-light-sensitive region 2002 will differ from the pixel value of the first non-light-sensitive region 2001 due to the SHBN noise. By distinguishing between the first and second non-light-sensitive regions, and using the pixel values ​​of the first and second non-light-sensitive regions, the noise at n times the gain of the image sensor, such as SHBN noise, can be effectively determined. When determining SHBN noise, since it generates a horizontal strip-shaped light beam diffusion, the width of the second non-light-sensitive region can be equal to that of the light-sensitive region 1001, thus allowing for a more accurate determination of the SHBN noise at n times the gain of the image sensor.

[0047] In exemplary embodiments of this disclosure, the non-photosensitive region may further include a third non-photosensitive region. For example... Figure 4 As shown, Figure 4 A schematic diagram of a shooting fixture according to an exemplary embodiment of this disclosure is shown. The shooting fixture includes a panel 20. The panel 20 includes a light-transmitting area 111 and a light-blocking area 210. The light-transmitting area 111 is located at the center left side of the panel 20, and the light-blocking area 210 is correspondingly arranged to the light-transmitting area 111. For example, the light-transmitting area is located on the left side, and the light-blocking area can be correspondingly arranged on the right side along the first vertical axis 11 of the panel. This arrangement of the light-transmitting and light-blocking areas can effectively reproduce the scene caused by horizontal noise. The light-transmitting area 111 and the light-blocking area 210 are isolated by a light-isolating area 311.

[0048] according to Figure 4 The images captured by the shooting fixture shown are as follows: Figure 5 As shown, Figure 5 yes Figure 4The image shown is an initial image captured in a preset shooting scene at an n-fold gain of the image sensor. A light-sensitive region 1101 and a non-light-sensitive region 2100 corresponding to it are defined. The non-light-sensitive region 2100 includes a first non-light-sensitive region 2101, a second non-light-sensitive region 2102, and a third non-light-sensitive region 2103. Along a first direction, the light-sensitive region 1101 and the second non-light-sensitive region 2102 are sequentially included. Along a second direction, the first non-light-sensitive region 2101, the second non-light-sensitive region 2102, and the third non-light-sensitive region 2103 are sequentially included. The light-sensitive region 1101 corresponds to the position of the light-transmitting region 110. In this embodiment, the noise state of the image sensor at an n-fold gain can be determined based on the pixel values ​​of the first non-light-sensitive region, the second non-light-sensitive region, and the third non-light-sensitive region.

[0049] In an exemplary embodiment of this disclosure, the non-light-sensitive region 2100 identifies a first non-light-sensitive region 2101, a second non-light-sensitive region 2102, and a third non-light-sensitive region 2103. The first non-light-sensitive region 2101 and the third non-light-sensitive region 2103 are vertically positioned on either side of the second non-light-sensitive region 2102. The pixel values ​​of the second non-light-sensitive region 2102, the first non-light-sensitive region 2101, and the third non-light-sensitive region 2103 are compared and analyzed to determine the SHBN noise under n times gain of the image sensor, resulting in higher accuracy.

[0050] In the exemplary embodiments of this disclosure, light-sensitive and non-light-sensitive regions can be identified in the captured initial image, such as... Figure 6 This is an exemplary embodiment of the present disclosure. Figure 1 The flowchart of step S120 in the illustrated embodiment is shown below. Figure 6 As shown, identifying the light-sensitive and non-light-sensitive regions in the initial image includes: Step S1201: The initial image is binarized according to the color channels, and the area where the number of pixels with a value of 1 is greater than the first preset threshold is the light-sensitive area. Step S1202: Based on the light-sensitive area, determine the second non-light-sensitive area along the first direction; Step S1203: Based on the second non-light-sensing region, determine the first non-light-sensing region and the third non-light-sensing region along the second direction.

[0051] by Figure 5Taking the initial image as an example, the initial image is binarized according to preset color channels. The number of pixels with a value of 1 in the binarized image is counted. The region where the number of pixels with a value of 1 is greater than a first preset threshold is the light-sensitive region. The light-sensitive region is used to determine the second non-light-sensitive region along a first direction. The second non-light-sensitive region is used to determine the first non-light-sensitive region and the third light-sensitive region along a second direction. By binarizing the initial image according to color channels, the light-sensitive region and the non-light-sensitive region of the initial image can be effectively identified.

[0052] In step S1201, the initial image is binarized according to the color channels, and the area where the number of pixels with a value of 1 is greater than the first preset threshold is the light-sensitive area.

[0053] The initial image is processed based on its color channels. For example, the initial image's color channels can be divided into R, Gr, Gb, and B channels, or they can be divided into R, G, and B channels. Each channel is then binarized. The number of pixels with a value of 1 in each row of the binarized image is counted. The region where the number of pixels with a value of 1 is greater than a first preset threshold is considered the light-sensitive region. Figure 7 As shown, Figure 7 The flowchart of the method for defining the region where the number of pixels with a value of 1 is greater than the first preset threshold in step S1201 as the light-sensitive region is shown below: Step S12011: Determine the position of the pixel with a value of 1 row by row, using pixels as the unit; In step S12012, the area formed by the position where the number of pixels with a value of 1 in each row is greater than the second preset threshold is determined as the light-sensing area.

[0054] When identifying light-sensitive regions, the positions of pixels with a value of 1 can be determined row by row. The region formed by the positions where the number of pixels with a value of 1 in each row is greater than a second preset threshold is defined as the light-sensitive region. Figure 5 Taking the initial image shown as an example, the positions of pixels with a value of 1 can be determined row by row from top to bottom or bottom to top to determine the number of pixels with a value of 1. For example, if each row has 1024 pixels, the positions of pixels with a value of 1 in each row can be determined from left to right. When the number of pixels with a value of 1 in a row is greater than 500, the row containing the position of the pixel with a value of 1 is recorded. Similarly, the rows containing the positions where the number of pixels with a value of 1 in each row is greater than 500 are recorded. The area formed by these rows is defined as the light-sensitive area. Figure 5 The light-sensing area 1101 used in the process.

[0055] In step S1202, based on the light-sensitive area, a second non-light-sensitive area is determined along the first direction. After determining the light-sensitive area, the second non-light-sensitive area is determined along the first direction. (Refer to...) Figure 5 As shown, after identifying the light-sensitive area 1101, the second non-light-sensitive area 2102 can be determined along the horizontal direction.

[0056] In step S1203, based on the second non-photosensitive region, a first non-photosensitive region and a third non-photosensitive region are determined along the second direction. (Refer to...) Figure 5 As shown, after determining the second non-light-sensing region 2102, the first non-light-sensing region 2101 and the third non-light-sensing region 2103 are determined in the vertical direction. The first non-light-sensing region 2101 is located above the second non-light-sensing region 2102, and the third non-light-sensing region 2103 is located below the second non-light-sensing region 2102.

[0057] In this embodiment, in step S130, the noise state of the image sensor under n times gain is determined based on the pixel values ​​of the first non-photosensitive region, the second non-photosensitive region, and the third non-photosensitive region. Figure 8 As shown, Figure 8 An exemplary flowchart illustrates a method for determining the noise state of an image sensor at n times gain based on pixel values ​​from a first non-photosensitive region, a second non-photosensitive region, and a third non-photosensitive region: Step S1301: Calculate the average pixel value of the preset color channel in the first non-light-sensitive area to obtain the first average value; calculate the average pixel value of the preset color channel in the second non-light-sensitive area to obtain the second average value; calculate the average pixel value of the preset color channel in the third non-light-sensitive area to obtain the third average value. Step S1302: Based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, determine the noise state of the preset color channel under n times gain of the image sensor.

[0058] In the exemplary embodiments of this disclosure, with Figure 5Using the initial image shown as an example, the average pixel value of the second non-light-sensitive region 2102 is used as a basis. This average value is then compared with the average pixel values ​​of the first non-light-sensitive region 2101 and the third non-light-sensitive region 2103, and the difference is taken to determine the noise state of the preset color channel under n times gain of the image sensor. The second non-light-sensitive region 2102 is horizontally adjacent to the light-sensitive region 1101. If SHBN noise exists under n times gain of the image sensor, it will form a stripe-like diffusion of light along the light-sensitive region 1101 in the horizontal direction. Therefore, the pixel value of the second non-light-sensitive region 2102 will differ from the pixel values ​​of the first and third non-light-sensitive regions 2101 and 2103 due to the SHBN noise. Since the first, second, and third non-light-sensitive regions 2101, 2102, and 2103 each include multiple pixel positions, taking the average pixel value of the corresponding region allows for a more accurate determination of the state of that region. Based on the average pixel value of the second non-photosensitive region 2102, it is compared with the average pixel value of the first non-photosensitive region 2101 and the average pixel value of the third non-photosensitive region 2103 respectively. The difference is taken, which can accurately determine whether there is a phenomenon of horizontal strip light diffusion in the second non-photosensitive region 2102. In this way, it can determine whether there is noise under the n times gain of the image sensor and the noise state in which noise exists.

[0059] Since an image can be described by the pixel values ​​corresponding to its color channels, the noise at n times gain of the image sensor can be determined based on the preset color channels of the initial image. The color channels of the initial image can be divided into R channels, Gr channels, Gb channels, and B channels, or they can be divided into R channels, G channels, and B channels. Each color channel of the initial image can be determined. Taking the B channel of the initial image as an example, the average pixel value of the B channel in the first non-light-sensitive region is calculated to obtain the first average value; the average pixel value of the B channel in the second non-light-sensitive region is calculated to obtain the second average value; the average pixel value of the B channel in the third non-light-sensitive region is calculated to obtain the third average value. Based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, the noise state of the B channel at n times gain of the image sensor is determined.

[0060] When Figure 3Taking the initial image shown as an example, i.e., when the non-light-sensitive area 2000 includes the first non-light-sensitive area 2001 and the second non-light-sensitive area 2002, taking the color channel B as an example, the average value of the pixel values ​​in the second non-light-sensitive area 2002, the second average value, and the average value of the pixel values ​​in the first non-light-sensitive area 2001, the first average value, are calculated. The average value of the pixel values ​​in the second non-light-sensitive area 2002 and the average value of the pixel values ​​in the first non-light-sensitive area 2001 can be compared, and the difference is taken to determine the noise state of the B channel under n times gain of the image sensor.

[0061] In the exemplary embodiments of this disclosure, based on a second non-photosensitive region adjacent to the photosensitive region in the horizontal direction, the pixel values ​​of the second non-photosensitive region are determined to be different from those of the first and third non-photosensitive regions, respectively, to determine the noise state of the image sensor at n times gain. This method can accurately determine the noise state of the image sensor at n times gain. Furthermore, determining the noise state based on a preset color channel better matches the descriptive state of the image, resulting in a more accurate determination of the noise state of the image sensor at n times gain.

[0062] In exemplary embodiments of this disclosure, such as Figure 9 As shown, Figure 9 It shows Figure 8 In step S1302, the flowchart of the method for determining the noise state of the B channel of the image sensor under n times gain is as follows: (The flowchart is not provided in the original text.) Step S13021: Take the absolute value of the difference between the second average value and the first average value, and the maximum value of the absolute value of the difference between the second average value and the third average value, as the noise difference of the preset color channel under the n times gain of the image sensor. Step S13022: Based on the noise difference, determine the noise state of the preset color channel under n times gain of the image sensor.

[0063] In an exemplary embodiment of this disclosure, the average pixel value of the second non-light-sensitive region is used as a basis, and is compared with the average pixel value of the first non-light-sensitive region, the first average pixel value, and the average pixel value of the third non-light-sensitive region, the third average pixel value. The absolute value of the difference is taken, and the maximum absolute value is taken as the noise difference of the preset color channel under the n times gain of the image sensor.

[0064] Taking the B channel in the initial image as an example, we take the maximum value among the absolute values ​​of the differences between the second and first average values, and the differences between the second and third average values ​​in the B channel. For example, using... Avg n,B,1 This represents the average pixel value in the first non-photosensitive region of the B channel under an n-fold gain. Avgn,B,2 This represents the average pixel value in the second non-photosensitive region of the B channel under an n-fold gain. Avg n,B,3 Let represent the average pixel value in the third non-light-sensitive region of the B channel under n times gain. Then, the noise difference of the B channel of this image sensor under n times gain can be expressed by the following formula: diff n,B = max(abs(Avg n,B,2 - Avg n,B,1 ), abs(Avg n,B,2 - Avg n,B,3 )) The maximum value among the differences between the second average value and the first average value, and the absolute values ​​of the differences between the second average value and the third average value, is used as the noise difference value to determine the noise state of the B channel under n times gain of the image sensor.

[0065] In the exemplary embodiments of this disclosure, the maximum value among the difference between the second average value and the first average value in the preset color channel, and the absolute value of the difference between the second average value and the third average value, is taken. That is, the difference between the average pixel value of the second non-light-sensitive area and the average pixel value of the two adjacent non-light-sensitive areas above and below is taken as the noise difference value for determining the noise state of the B channel under n times gain of the image sensor. This can more accurately determine the noise state of the preset color channel under n times gain of the image sensor.

[0066] In exemplary embodiments of this disclosure, the noise state of each color channel under an n-fold gain of the image sensor can be determined. For example, if the preset color channels include R, Gr, Gb, and B channels, the noise state under an n-fold gain of the image sensor can be determined based on the noise difference values ​​of the R, Gr, Gb, and B channels, respectively. For example, the noise difference value of each color channel can be compared with a preset threshold. When the noise difference value of each color channel exceeds the preset threshold, it indicates that the noise under an n-fold gain of the image sensor is large. If the noise difference value of a certain color channel is much larger than the noise difference values ​​of other color channels, it indicates that the noise under an n-fold gain of the image sensor tends to favor the color represented by that color channel. For example, if the noise difference value of the B channel is much larger than the noise difference values ​​of other color channels, it indicates that the noise under an n-fold gain of the image sensor tends to favor blue.

[0067] The noise determination method for an image sensor provided in the exemplary embodiments of this disclosure can determine the noise state of the image sensor under all gains, and determine the noise state of the image sensor based on the noise state under all gains.

[0068] For camera modules, such as the camera in a terminal, the corresponding gain ranges from 1 to 16. The noise state of the image sensor can be determined at each gain, and then the noise state of the image sensor can be determined based on the noise state at all gains.

[0069] The noise determination method for an image sensor disclosed herein acquires an initial image of the image sensor at n times gain, identifies a light-sensitive region, a first non-light-sensitive region, and a second non-light-sensitive region in the original image, and determines the noise state of the image sensor at n times gain by using the pixel values ​​of the first non-light-sensitive region and the second non-light-sensitive region, thereby accurately determining the noise state of the image sensor.

[0070] This disclosure also provides a noise determination apparatus for an image sensor, exemplarily used to determine the SHBN noise state of a CMOS image sensor. Figure 10 This is a schematic diagram illustrating the structure of a noise determination device for an image sensor according to an exemplary embodiment, with reference to... Figure 10 As shown, the noise determination device for an image sensor provided in this embodiment includes: an acquisition module 21, an identification module 22, a first determination module 23, a second determination module 24, and a third determination module 25, wherein... The acquisition module 21 is configured to acquire an initial image based on the image sensor at a gain of n times based on a preset shooting scene; where n is a positive integer greater than or equal to 1. The recognition module 22 is configured to recognize light-sensitive regions and non-light-sensitive regions in the initial image; the non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region; wherein, along a first direction, the light-sensitive region and the second non-light-sensitive region are included in sequence; along a second direction, the first non-light-sensitive region and the second non-light-sensitive region are included in sequence; the first direction and the second direction form a preset angle. The first determining module 23 is configured to determine the noise state of the image sensor at n times gain based on the pixel values ​​of the first non-photosensitive region and the pixel values ​​of the second non-photosensitive region.

[0071] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10 As shown, the identification module 22 is configured as follows: Based on the pixel values ​​of the first non-photosensitive region, the second non-photosensitive region, and the third non-photosensitive region, the noise state of the image sensor under n times gain is determined.

[0072] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10As shown, the identification module 22 is configured as follows: The initial image is binarized according to the color channels, and the area where the number of pixels with a value of 1 is greater than the first preset threshold is the light-sensitive area; Based on the light-sensitive area, the second non-light-sensitive area is determined along the first direction; Based on the second non-photosensitive region, the first non-photosensitive region and the third non-photosensitive region are determined along the second direction.

[0073] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10 As shown, the identification module 22 is configured as follows: Determine the position of each pixel with a value of 1, row by row, using pixels as the unit; The area formed by the position where the number of pixels with a value of 1 in each row is greater than the second preset threshold is determined as the light-sensing area.

[0074] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10 As shown, the first determining module 23 is configured as follows: Calculate the average pixel value of the preset color channel in the first non-light-sensitive area to obtain a first average value; calculate the average pixel value of the preset color channel in the second non-light-sensitive area to obtain a second average value; calculate the average pixel value of the preset color channel in the third non-light-sensitive area to obtain a third average value. Based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, the noise state of the preset color channel under n times gain of the image sensor is determined.

[0075] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10 As shown, the first determining module 23 is configured as follows: The absolute value of the difference between the second average value and the first average value, and the maximum value of the absolute value of the difference between the second average value and the third average value, are taken as the noise difference of the preset color channel under the n-fold gain of the image sensor. Based on the noise difference, the noise state of the preset color channel under n times gain of the image sensor is determined.

[0076] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10 As shown, the first determining module 23 is configured such that the preset color channels include R channel, Gr channel, Gb channel, and B channel.

[0077] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10 The first determining module 23 shown is configured as follows: Based on the noise difference values ​​of the R channel, the Gr channel, the Gb channel, and the B channel, the noise state of the image sensor at an n-fold gain is determined.

[0078] The present disclosure provides a noise determination device for an image sensor, such as... Figure 10 As shown, the acquisition module 21 is configured such that the preset shooting scene includes a light-transmitting area and a non-light-transmitting area, and the light-transmitting area and the non-light-transmitting area are isolated by a light-isolation area.

[0079] In the noise determination device for an image sensor provided in the embodiments of this disclosure: The second determining module 24 is configured to determine the noise state of the image sensor under all gains; The third determining module 25 is configured to determine the noise state of the image sensor based on the noise state under all gains.

[0080] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0081] Figure 11 A block diagram of a noise determination apparatus 300 for an image sensor is shown according to an exemplary embodiment. For example, apparatus 300 may be a device with an image sensor, such as a camera, mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0082] Reference Figure 11 The device 300 may include one or more of the following components: processing component 302, memory 304, power component 306, multimedia component 308, audio component 310, input / output (I / O) interface 312, sensor component 314, and communication component 316.

[0083] Processing component 302 typically controls the overall operation of device 300, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 302 may include one or more processors 320 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 302 may include one or more modules to facilitate interaction between processing component 302 and other components. For example, processing component 302 may include a multimedia module to facilitate interaction between multimedia component 308 and processing component 302.

[0084] Memory 304 is configured to store various types of data to support the operation of device 300. Examples of such data include instructions for any application or method operating on device 300, contact data, phonebook data, messages, pictures, videos, etc. Memory 304 can be implemented by any type of volatile or non-volatile storage device or a 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 storage, flash memory, magnetic disk, or optical disk.

[0085] The power supply component 306 provides power to the various components of the device 300. The power supply component 306 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to the device 300.

[0086] Multimedia component 308 includes a screen that provides an output interface between the device 300 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 308 includes a front-facing camera and / or a rear-facing camera. When the device 300 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0087] Audio component 310 is configured to output and / or input audio signals. For example, audio component 310 includes a microphone (MIC) configured to receive external audio signals when device 300 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 304 or transmitted via communication component 316. In some embodiments, audio component 310 also includes a speaker for outputting audio signals.

[0088] I / O interface 312 provides an interface between processing component 302 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, start buttons, and lock buttons.

[0089] Sensor assembly 314 includes one or more sensors for providing state determination of various aspects of device 300. For example, sensor assembly 314 may detect the on / off state of device 300, the relative positioning of components such as the display and keypad of device 300, changes in the position of device 300 or a component of device 300, the presence or absence of user contact with device 300, the orientation or acceleration / deceleration of device 300, and temperature changes of device 300. Sensor assembly 314 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 314 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 314 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0090] Communication component 316 is configured to facilitate wired or wireless communication between device 300 and other devices. Device 300 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 316 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 316 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0091] In an exemplary embodiment, the apparatus 300 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0092] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 304 including instructions, which can be executed by a processor 320 of the device 300 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0093] A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a terminal's processor, enables the terminal to perform the noise determination method for an image sensor provided in this disclosure.

[0094] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0095] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for determining noise in an image sensor, characterized in that, The noise determination method includes: An initial image is acquired based on a preset shooting scene at an n-fold gain of the image sensor; where n is a positive integer greater than or equal to 1. Identify light-sensitive and non-light-sensitive regions in the initial image; the non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region; wherein, along a first direction, the light-sensitive region and the second non-light-sensitive region are sequentially included; along a second direction, the first non-light-sensitive region and the second non-light-sensitive region are sequentially included; the first direction and the second direction form a preset angle, the first direction being a horizontal direction, and the second non-light-sensitive region and the light-sensitive region are correspondingly arranged in the first direction to sense the light diffused by the light-sensitive region; Based on the pixel values ​​of the first non-photosensitive region and the pixel values ​​of the second non-photosensitive region, the noise state of the image sensor under n times gain is determined.

2. The noise determination method for an image sensor according to claim 1, characterized in that, The non-photosensitive area also includes a third non-photosensitive area, and the first non-photosensitive area, the second non-photosensitive area and the third non-photosensitive area are arranged sequentially along the second direction; Based on the pixel values ​​of the first non-photosensitive region, the second non-photosensitive region, and the third non-photosensitive region, the noise state of the image sensor under n times gain is determined.

3. The noise determination method for an image sensor according to claim 2, characterized in that, The identification of light-sensitive regions and non-light-sensitive regions in the initial image includes: The initial image is binarized according to the color channels, and the area where the number of pixels with a value of 1 is greater than the first preset threshold is the light-sensitive area; Based on the light-sensitive area, the second non-light-sensitive area is determined along the first direction; Based on the second non-photosensitive region, the first non-photosensitive region and the third non-photosensitive region are determined along the second direction.

4. The noise determination method for an image sensor according to claim 3, characterized in that, The region where the number of pixels with a value of 1 is greater than the first preset threshold is a light-sensitive region, including: Determine the position of each pixel with a value of 1, row by row, using pixels as the unit; The area formed by the position where the number of pixels with a value of 1 in each row is greater than the second preset threshold is determined as the light-sensing area.

5. The noise determination method for an image sensor according to claim 3, characterized in that, Based on the pixel values ​​of the first non-photosensitive region, the second non-photosensitive region, and the third non-photosensitive region, the noise state of the image sensor at n times gain is determined, including: Calculate the average pixel value of the preset color channel in the first non-light-sensitive area to obtain a first average value; calculate the average pixel value of the preset color channel in the second non-light-sensitive area to obtain a second average value; calculate the average pixel value of the preset color channel in the third non-light-sensitive area to obtain a third average value. Based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, the noise state of the preset color channel under n times gain of the image sensor is determined.

6. The noise determination method for an image sensor according to claim 5, characterized in that, Determining the noise state of the preset color channel at n times gain of the image sensor based on the difference between the second average value and the first average value, and the difference between the second average value and the third average value, includes: The absolute value of the difference between the second average value and the first average value, and the maximum value of the absolute value of the difference between the second average value and the third average value, are taken as the noise difference of the preset color channel under the n-fold gain of the image sensor. Based on the noise difference, the noise state of the preset color channel under n times gain of the image sensor is determined.

7. The noise determination method for an image sensor according to claim 6, characterized in that, The preset color channels include the R channel, Gr channel, Gb channel, and B channel.

8. The noise determination method for an image sensor according to claim 7, characterized in that, Based on the noise difference, determining the noise state of the preset color channel at n times gain of the image sensor includes: Based on the noise difference values ​​of the R channel, the Gr channel, the Gb channel, and the B channel, the noise state of the image sensor at an n-fold gain is determined.

9. The noise determination method for an image sensor according to claim 1, characterized in that, The preset shooting scene includes a light-transmitting area and a non-light-transmitting area, which are separated by a light-isolation area.

10. The noise determination method for an image sensor according to claim 1, characterized in that, The noise determination method further includes: Determine the noise state of the image sensor at all gains; The noise state of the image sensor is determined based on the noise state at all gains.

11. A noise determination device for an image sensor, characterized in that, The noise determination device includes: Acquisition module: configured to acquire an initial image based on the image sensor at an n-fold gain, according to a preset shooting scene; where n is a positive integer greater than or equal to 1; The recognition module is configured to recognize light-sensitive and non-light-sensitive regions in the initial image. The non-light-sensitive regions include a first non-light-sensitive region and a second non-light-sensitive region. Along a first direction, the light-sensitive region and the second non-light-sensitive region are sequentially included. Along a second direction, the first non-light-sensitive region and the second non-light-sensitive region are sequentially included. The first direction and the second direction form a preset angle, with the first direction being horizontal. The second non-light-sensitive region and the light-sensitive region are correspondingly positioned along the first direction to sense the light diffused from the light-sensitive region. The first determining module is configured to determine the noise state of the image sensor at n times gain based on the pixel values ​​of the first non-photosensitive region and the pixel values ​​of the second non-photosensitive region.

12. A noise determination device for an image sensor, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to perform the noise determination method for the image sensor according to any one of claims 1-10.

13. A non-transitory computer-readable storage medium, wherein instructions in the storage medium, when executed by a processor of a terminal, enable the terminal to perform the noise determination method of an image sensor according to any one of claims 1-10.

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