Patent Description:
With the development of Internet technologies, requirements for image quality are increasingly high in all walks of life. For example, as a most important part among the functions of an office collaboration product, the remote video conference has a high requirement for the image quality of a video. If a user is in a poor lighting environment, the image quality of a scenario in the video conference will be relatively poor. If the scenario image in such environment is not processed, experience of the video conference will be quite poor.

To display a high-quality image, a brightness of an image generally needs to be enhanced. However, in the current image processing method, enhancement of a pixel brightness generally depends on an enhancement result of another pixel before the pixel is enhanced, which undoubtedly causes the enhancement process of the image brightness occupies a large amount of image processing resources, such as valuable Central Processing Unit (CPU) resources, for a long time. For example, in the field of video conferences, most processing resources of the video conference system are used for such image processing tasks, which greatly hinder the performance improvement of the video conference system.

A document (<CIT>) discloses a method for adjusting image luminance performed at an electronic device. The method includes: determining a target pixel with original luminance lower than a luminance threshold in an original image, the luminance threshold being determined according to luminance of pixels in the original image; obtaining a luminance distribution intensity of pixels adjacent to the target pixel; determining a difference between the luminance threshold and the luminance distribution intensity of the adjacent pixels; and adjusting the target pixel to corresponding target luminance according to the difference and the original luminance of the target pixel.

Document <CIT> relates to a real-time video enhancing method, which involves determining first local enhancement curve of present frame corresponding to image average brightness and determining second local enhancement curve according to enhancing line of current frame.

Embodiments of this disclosure will be described in more detail with reference to the accompanying drawings.

The following descriptions provide specific details for thoroughly understanding and implementing various embodiments of this disclosure. Persons skilled in the art can understand that the technical solutions of this disclosure may be implemented without these details in some cases. In some cases, some well-known structures and functions are not shown or described in detail to make the descriptions of the embodiments of this disclosure clearer. Terms used in the embodiments of this disclosure is to be understood in its broadest reasonable manner, even if they are used in combination with specific embodiments of this disclosure.

First, some terms involved in the embodiments of this disclosure are described to help persons skilled in the art to understand this disclosure.

LUT: Look-Up-Table, which essentially is a RAM. After data is pre-written in the RAM, each time a signal is inputted, it is equivalent to inputting an address to look up the table and find out content corresponding to the address, and then outputting the content. The LUT has a wide range of applications, for example, the LUT may be used as a mapping table of pixel brightness, which converts an actual sampled pixel brightness value (for example, through inversion, binarization, linear or non-linear conversion) to another corresponding brightness value, thereby highlighting useful information of the image and enhancing light contrast of the image.

RGB color space: the RGB color space is based on three primary colors of Red (R), Green (G), and Blue (B), which are superimposed to varying degrees to produce rich and extensive colors, so it is commonly known as the three primary color mode. The greatest advantage of the RGB color space is intuitive and easy to understand, and the disadvantage thereof is that the three components of R, G, and B are highly related, that is, if a component of one color changes to a certain extent, the color will be likely to change.

YUV color space: RGB signals may undergo a series of conversions to determine one brightness signal Y and two color difference signals R-Y (that is, U) and B-Y (that is, V). This representation method of color is referred to as YUV color space representation. The importance of using the YUV color space is that the brightness signal Y and the chrominance signals U and V are separated. "Y" represents a brightness, that is, a grayscale value, and "U" and "V" represent chrominance, which is to describe the color and saturation of an image, and is used for specifying a pixel color. Generally, color spaces such as Y'UV, YUV, YCbCr, and YPbPr all may be collectively referred to as the YUV color space.

<FIG> is an exemplary application scenario <NUM> in which the technical solutions according to the embodiments of this disclosure can be implemented. As shown in <FIG>, the application scenario <NUM> typically may be a scenario of a video conference, where a participant at a near end (that is, local) has a video conference with a participant at a remote end in the scenario. As shown in <FIG>, a camera <NUM> at the near end of the video conference may capture a video of the video conference. The video is formed by a series of video frames, and the video frames are, for example, near-end images of a local participant or a speaker in the video conference. If there is poor light in the environment of the local video conference, quality (in particular, brightness) of the near-end image captured by the camera will be relatively poor. In this case, an image processing apparatus <NUM> in a computing device <NUM> may be configured to enhance a brightness of the image to determine an enhanced image having relatively good quality. On the one hand, the enhanced image may be displayed on a local display <NUM>. On the other hand, the enhanced image may also be transmitted to the remote end of the video conference for display to the far-end participant. As an example, an encoder <NUM> in the computing device <NUM> may be used to encode the enhanced image, and then the encoded image is transmitted to the remote end via a network <NUM>. At the remote end, a decoder <NUM> may be used to decode the received encoded image, and then the decoded image may be displayed on a remote-end display <NUM>, so that the remote-end participant can watch the high-quality near-end image.

The network <NUM>, for example, may be a Wide Area Network (WAN), a Local Area Network (LAN), a wireless network, a public telephone network, an intranet, and any other type of network well-known to persons skilled in the art. The scenario described above is just an example in which the embodiments of this disclosure can be implemented. Actually, the embodiments of this disclosure may be implemented in any scenario in which image processing, and in particular, brightness enhancement of the image is needed.

<FIG> is a schematic flowchart of an image processing method <NUM> according to an embodiment of this disclosure. The method <NUM> is performed by a computing device, for example, the computing device <NUM> shown in <FIG> or the computing device <NUM> shown in <FIG>. As shown in <FIG>, the method <NUM> includes the following steps.

In step <NUM>, determine a brightness value of an image.

The brightness value of the image may be determined in various manners. In some embodiments, the image is represented in the format of YUV color space data. In the YUV space, each color has a brightness component Y and two chrominance components U and V. In this case, the YUV color space data of the image may be determined first, and then the brightness value of the image may be determined based on the brightness component in the YUV color space data.

In some embodiments, the image is represented in the format of RGB color space data. The RGB color space is a space defined according to the colors of Red (R), Green (G), and Blue (B) recognized by human eyes. In the RGB color space, the hue, brightness and saturation are represented together and are hard to separate. In this case, the RGB color space data of the image may be determined first, and then the RGB color space data of the image may be converted to the YUV color space data of the image.

As an example, the RGB color space data of the image may be converted to the YUV color space data of the image according to the following formulas: <MAT> <MAT> <MAT>.

In some embodiments, any appropriate method may be used for determining the brightness value of the image based on a brightness component Y in the YUV color space data. For example, brightness components of all pixels of the image may be determined, and then an average value of the brightness components may be used as the brightness value of the image. Definitely, this is not limited in this disclosure. Any other appropriate method will be considered.

In step <NUM>, enhance a brightness of the image in response to the brightness value of the image being less than an image brightness threshold.

In other words, the brightness of the image may not be enhanced in response to the brightness value of the image not being less than the image brightness threshold, because in this case the image meets the requirement for the image brightness and generally has a high quality.

Step <NUM> may further include the following step <NUM> to step <NUM>.

In step <NUM>, determine each pixel of the image as a to-be-enhanced pixel.

In the embodiments of this disclosure, there is a need to enhance the brightness of the image based on each independent pixel.

In step <NUM>, determine a brightness enhancement value of the to-be-enhanced pixel based on the brightness value of the image, an initial brightness value of the to-be-enhanced pixel, and initial brightness values of neighboring pixels of the to-be-enhanced pixel.

The initial brightness value of the pixel represents the brightness value in response to the pixel not being enhanced, that is, the brightness value before the pixel is enhanced.

In some embodiments, the neighboring pixels of the to-be-enhanced pixel may be pixels other than the to-be-enhanced pixel in a region with the to-be-enhanced pixel as a central point. The shape and size of the region may be preset according to requirements. As an example, the region may be a square region having a size of <NUM>×<NUM> pixels, which definitely is not limited.

In step <NUM>, use the brightness enhancement value as an enhanced brightness value of the to-be-enhanced pixel.

After the brightness enhancement value of the to-be-enhanced pixel is determined, the brightness value of the to-be-enhanced pixel may be adjusted to the brightness enhancement value to enhance the brightness of the to-be-enhanced pixel. The enhancement of the brightness of the image is implemented by enhancing the brightness of each to-be-enhanced pixel.

In the embodiments of this disclosure, by comprehensively considering the brightness value of the image, the initial brightness value of the to-be-enhanced pixel, and the initial brightness values of the neighboring pixels of the to-be-enhanced pixel, the quality of the to-be-enhanced pixel can be more thoroughly determined, thereby achieving a relatively accurate enhancement result. In addition, the whole enhancement process is performed just based on the initial brightness values of the pixels. Therefore, different from the conventional image processing technologies that rely on dependency or coupling relationships among of pixels, in this disclosure, the enhancement of the brightness of the pixels in the image does not rely on such dependency or coupling relationships and can be performed in parallel, thereby greatly reducing a resource occupancy rate in the image processing process.

Although the embodiments of this disclosure are described with the enhancement of the image as the theme, the embodiments of this disclosure may also be applicable to a scenario where a video is enhanced, because enhancing the video essentially is to enhance each frame of image in the video.

In the foregoing description, after the YUV color space data of the image is determined, the brightness value of the image may be determined based on the brightness component in the YUV color space data. <FIG> is a schematic flowchart of an image processing method <NUM> for determining, based on a brightness component in YUV color space data of an image, a brightness value of the image according to an embodiment of this disclosure. The method <NUM> is performed by a computing device, for example, the computing device <NUM> shown in <FIG> or the computing device <NUM> shown in <FIG>. The method <NUM> includes the following steps.

In step <NUM>, sample pixels of the image at a sampling interval to determine brightness components in YUV color space data of the sampled pixels.

The sampling interval depends on a sampling rate Y of the pixels of the image. In some embodiments, the sampling interval has a first interval component in a row direction of the pixels of the image, and has a second interval component in a column direction of the pixels of the image. The first interval component is a value determined by dividing a quantity of pixels in the row direction by the sampling rate, and the second interval component is a value determined by dividing a quantity of pixels in the column direction by the sampling rate. During sampling, the sampling may start from a start point of the row direction and the column direction of the image (for example, an upper left corner of the image), and the pixels of the image are sampled at each sampling interval, which definitely is not limited herein.

As an example, assuming that a quantity of pixels in the row direction of the pixels of the image is Iw (which is also referred to as an image width), and a quantity of pixels in the column direction of the pixels of the image is IH (which is also referred to as an image height), the first interval component (that is, the sampling interval in the row direction) is IW/Υ, and the second interval component (that is, the sampling interval in the column direction) is IH/Υ.

In step <NUM>, add the brightness components of the sampled pixels to determine a sum of brightness of the sampled pixels, that is, add the brightness values of all sampled pixels to determine the sum of the brightness of the sampled pixels LT.

In step <NUM>, perform sampling rate smoothing on the sum of the brightness of the sampled pixels to determine a smoothed brightness value. As an example, the sum of the brightness of the sampled pixels may be divided by a square of the sampling rate to determine the smoothed brightness value, that is, the smoothed brightness value LS = LT/(Υ<NUM>). Other manners that can smooth the sum of the brightness of the sampled pixels can also be considered.

In step <NUM>, determine the smoothed brightness value as the brightness value of the image.

By means of the foregoing steps, the brightness value of the image is determined with the method <NUM> that is quick, accurate, and occupies fewer resources.

<FIG> is an exemplary flowchart of a method <NUM> for determining, based on a brightness value of an image, an initial brightness value of a to-be-enhanced pixel, and initial brightness values of neighboring pixels of the to-be-enhanced pixel, a brightness enhancement value of the to-be-enhanced pixel according to an embodiment of this disclosure. The method <NUM> is performed by a computing device, for example, the computing device <NUM> shown in <FIG> or the computing device <NUM> shown in <FIG>. The method <NUM> may be used for implementing step <NUM> described with reference to <FIG>.

In step <NUM>, filter the initial brightness value of the to-be-enhanced pixel, based on the initial brightness value of the to-be-enhanced pixel and the initial brightness values of the neighboring pixels of the to-be-enhanced pixel, to determine a filtered brightness value of the to-be-enhanced pixel.

In some embodiments, a filtering template may be configured to filer the initial brightness value of the to-be-enhanced pixel. The filtering template includes weights which are in one-to-one correspondence to the brightness of the to-be-enhanced pixel and the brightness of the neighboring pixels of the to-be-enhanced pixel. In this case, the filtering template may be used to determine a weighted sum of the initial brightness value of the to-be-enhanced pixel and the initial brightness values of the neighboring pixels. The weights of the brightness of the involved pixels are the weights in the filtering template. Then, the weighted sum is determined as the filtered brightness value of the to-be-enhanced pixel. It may be seen that the whole filtering process is performed based on the initial brightness value of the to-be-enhanced pixel and the initial brightness values of the neighboring pixels. In other words, in the filtering process, the filtering of a subsequent pixel does not depend on a filtering result of a previous pixel. Therefore, different from the conventional image processing technologies that rely on the dependency of pixels, in this disclosure, the enhancement of the brightness of the pixels in the image can be performed in parallel, thereby greatly reducing a resource occupancy rate in the image processing process.

As an example, <FIG> is a schematic diagram of an exemplary filtering template <NUM> according to an embodiment of this disclosure. As shown in <FIG>, the filtering template corresponds to a square region having a size of <NUM>×<NUM> pixels (including a to-be-enhanced pixel and neighboring pixels of the to-be-enhanced pixel). The filtering template also includes weights a0, a1, a2, a3, a4, a5, a6, a7, and a8, which are in one-to-one correspondence to the brightness of the to-be-enhanced pixel and the brightness of the neighboring pixels of the to-be-enhanced pixel, where a0 is a weight corresponding to the brightness of the to-be-enhanced pixel, and a1, a2, a3, a4, a5, a6, a7, and a8 are weights corresponding to the weights of the neighboring pixels, and the sum of the weights typically equals <NUM>. Optionally, the value of a0 is <NUM>/<NUM>, the values of a2, a4, a6, and a8 are <NUM>/<NUM>, and the values of a1, a3, a5, and a7 are <NUM>, which is beneficial in image processing, especially in image processing of a video conference scenario.

As an example, <FIG> is a schematic diagram showing that the filtering template <NUM> in <FIG> is used to filter brightness values of pixels of an image. As shown in <FIG>, the brightness values may be filtered in a row direction from left to right and in a column direction from top to bottom of the pixels of the image. Actually, the brightness values of the pixels of the image can be filtered in any order, for example, brightness values of a plurality of pixels at any different positions may be filtered at the same time. This is because the filtering process does not rely on the pixel dependency in conventional technologies. Assuming that an initial brightness value of a central point pixel (that is, a to-be-enhanced pixel) shown in <FIG> is I<NUM>, and initial brightness values of eight neighboring pixels starting from the upper left corner of the central point pixel in a clockwise direction are respectively I<NUM>, I<NUM>, I<NUM>, I<NUM>, I<NUM>, I<NUM>, I<NUM>, and I<NUM>, and a filtered brightness value of the to-be-enhanced pixel (that is, the central point pixel) determined by using the filtering template shown in <FIG> to filter the initial brightness value of the to-be-enhanced pixel is <MAT>.

In step <NUM>, determine the brightness enhancement value of the to-be-enhanced pixel based on the brightness value of the image, the initial brightness value of the to-be-enhanced pixel, and the filtered brightness value of the to-be-enhanced pixel. In some embodiments, the brightness enhancement value of the to-be-enhanced pixel may be determined according to the following formula, <MAT> where E(x) is the brightness enhancement value of the to-be-enhanced pixel, I(x) is the initial brightness value of the to-be-enhanced pixel, and t(x) is atmospheric optical transmittance, and an expression of the atmospheric optical transmittance is: <MAT> where IB is the brightness value of the image, EV is the filtered brightness value of the to-be-enhanced pixel, A is an atmospheric optical intensity value, and w is a non-zero constant, and w optionally is <NUM>.

In some embodiments, each time before a brightness of an image is enhanced, a two-dimensional Look-Up-Table (LUT) among an initial brightness value of a to-be-enhanced pixel and a filtered brightness value of the to-be-enhanced pixel and a brightness enhancement value of to-be-enhanced pixel may be established in advance based on the foregoing formula, where the first dimension represents the initial brightness value of the to-be-enhanced pixel, the second dimension represents the filtered brightness value of the to-be-enhanced pixel, and the value determined by looking up in the table is the brightness enhancement value of the to-be-enhanced pixel.

As an example, the following algorithm may be used for establishing the two-dimensional LUT in advance:
<IMG>.

where the brightness value of the image is <NUM>, an atmospheric optical intensity value is <NUM>, i is the initial brightness value [(x) of the to-be-enhanced pixel, j is the filtered brightness value EV of the to-be-enhanced pixel, t is an atmospheric optical transmittance, m is the brightness enhancement value E(x) calculated according to the foregoing formula, and Tlut[i][j] is the brightness enhancement value of the to-be-enhanced pixel determined by looking up in the table; clip(·) is a numerical truncation function, if the value is between <NUM> and <NUM>, the value will be reserved; if the value is less than <NUM>, the value will be set to zero; if the value is greater than <NUM>, the value will be set to <NUM>. The foregoing step is to ensure that the calculated brightness enhancement value m is in the range of <NUM> to <NUM>, which, therefore, is not necessary, and m may be directly determined as Tlut[i][j].

In some embodiments, to make the brightness of the image smoother, the brightness enhancement value E(x) determined above may be smoothed as follows, that is, clip(<NUM> * E(x) + <NUM> * EV). The calculated result is used as the brightness enhancement value of the to-be-enhanced pixel to enhance the initial brightness of the to-be-enhanced pixel, which definitely is not necessary.

<FIG> is a schematic diagram of the effect of using the image processing method according to the embodiments of this disclosure to enhance an original image. It may be seen that, compared with an original image <NUM> on the left, on an enhanced image <NUM> on the right of <FIG>, both brightness <NUM> and brightness <NUM> of the overall image and brightness <NUM> and brightness <NUM> of a local part (for example, hand area) of the image are enhanced, and quality of the enhanced image is improved obviously. In addition, resource occupancy rates of the image processing method with parallel processing and pixel decoupling according to the embodiments of this disclosure and a conventional image processing method that relies on pixel dependency or pixel coupling on different hardware platform were compared, and comparison result is shown in table <NUM>.

It may be seen that, compared to the image processing method of the conventional technologies, the image processing method according to the embodiments of this disclosure greatly reduces the resource occupancy rate in the image processing process.

<FIG> is an exemplary structural diagram of an image processing apparatus <NUM> according to an embodiment of this disclosure. The image processing apparatus <NUM> is located in a computing device, for example, the computing device <NUM> shown in <FIG>. As shown in <FIG>, the apparatus <NUM> includes a determining module <NUM> and an enhancement module <NUM>, where the enhancement module <NUM> further includes a first determining submodule <NUM>, a second determining submodule <NUM>, and an enhancement submodule <NUM>.

The determining module <NUM> is configured to determine a brightness value of an image.

The determining module <NUM> may be configured to determine the brightness value of the image in various manners. In some embodiments, the image is represented in the format of YUV color space data. In the YUV space, each color has a brightness component Y and two chrominance components U and V. In this case, the determining module <NUM> may be configured to determine YUV color space data of the image, and to determine the brightness value of the image based on the brightness component in the YUV color space data.

In some embodiments, the determining module <NUM> may be configured to determine RGB color space data of the image, and to convert the RGB color space data of the image to the YUV color space data of the image.

In some embodiments, the determining module <NUM> may be configured to: sample pixels of the image at a sampling interval to determine brightness components in YUV color space data of the sampled pixels; add the brightness components of the sampled pixels to determine a sum of brightness of the sampled pixels; perform sampling rate smoothing on the sum of the brightness of the sampled pixels to determine a smoothed brightness value; and determine the smoothed brightness value as the brightness value of the image.

The enhancement module <NUM> is configured to enhance a brightness of the image in response to the brightness value being less than an image brightness threshold. In other words, the brightness of the image may not be enhanced by using the enhancement module <NUM> in response to the brightness value not being less than an image brightness threshold, because the image meets the requirement for the brightness of the image and generally has a high quality.

The first determining submodule <NUM> is configured to determine each pixel of the image as a to-be-enhanced pixel.

The second determining submodule <NUM> is configured to determine a brightness enhancement value of the to-be-enhanced pixel based on the brightness value of the image, an initial brightness value of the to-be-enhanced pixel, and initial brightness values of neighboring pixels of the to-be-enhanced pixel. The initial brightness value represents the brightness value in response to the to-be-enhanced pixel not being enhanced, that is, the brightness value before the pixel is enhanced.

In some embodiments, the neighboring pixels of the to-be-enhanced pixel may be pixels other than the to-be-enhanced pixel in a region with the to-be-enhanced pixel as a central point. The shape and size of the region may be preset according to requirements. As an example, the region may be a region having a size of <NUM>×<NUM> pixels, which definitely is not limited.

In some embodiments, the second determining submodule <NUM> may be configured to filter the initial brightness value of the to-be-enhanced pixel, based on the initial brightness value of the to-be-enhanced pixel and the initial brightness values of the neighboring pixels of the to-be-enhanced pixel, to determine a filtered brightness value of the to-be-enhanced pixel; and to determine the brightness enhancement value of the to-be-enhanced pixel based on the brightness value of the image, the initial brightness value of the to-be-enhanced pixel, and the filtered brightness value of the to-be-enhanced pixel. As an example, the second determining submodule <NUM> may be configured to determine a weighted sum of the initial brightness value of the to-be-enhanced pixel and the initial brightness values of the neighboring pixels, and to determine the weighted sum as the filtered brightness value of the to-be-enhanced pixel.

In some embodiments, the second determining submodule <NUM> may be configured to determine the brightness enhancement value of the to-be-enhanced pixel according to the following formula, <MAT> where E(x) is the brightness enhancement value of the to-be-enhanced pixel, I(x) is the initial brightness value of the to-be-enhanced pixel, and t(x) is atmospheric optical transmittance, and an expression of the atmospheric optical transmittance is: <MAT> where IB is the brightness value of the image, EV is the filtered brightness value of the to-be-enhanced pixel, A is an atmospheric optical intensity value, and w is a non-zero constant.

The enhancement submodule <NUM> is configured to use the brightness enhancement value as an enhanced brightness value of the to-be-enhanced pixel. After the brightness enhancement value of the to-be-enhanced pixel is determined, the enhancement submodule <NUM> may adjust the brightness value of the to-be-enhanced pixel to the brightness enhancement value to enhance the brightness of the to-be-enhanced pixel.

<FIG> shows an exemplary system <NUM>, which includes an exemplary computing device <NUM> representing one or more systems and/or devices to implement various technologies described in this disclosure. The computing device <NUM> may be, for example, a server of a service provider, a device associated with a server, a system-on-a-chip, and/or any other suitable computing device or computing system. The image processing apparatus <NUM> described above with reference to <FIG> may use a form of the computing device <NUM>. Alternatively, the image processing apparatus <NUM> may be implemented as a computer program in a form of an image processing application <NUM>.

The exemplary computing device <NUM> shown in the figure includes a processing system <NUM>, one or more computer readable media <NUM>, and one or more I/O interfaces <NUM> that are communicatively coupled to each other. Although not shown, the computing device <NUM> may further include a system bus or another data and command transfer system, which couples various components to each other. The system bus may include any one or a combination of different bus structures. The bus structure is, for example, a memory bus or a memory controller, a peripheral bus, a universal serial bus, and/or a processor or a local bus that uses any one of various bus architectures. Various other examples are also conceived, such as control and data lines.

The processing system <NUM> represents a function to perform one or more operations by using hardware. Therefore, the processing system <NUM> is shown to include a hardware element <NUM> that can be configured as a processor, a functional block, and the like. This may include implementation, in the hardware, as an application-specific integrated circuit or another logic device formed by using one or more semiconductors. The hardware element <NUM> is not limited by a material from which the hardware element is formed or a processing mechanism used herein. For example, the processor may be formed by (a plurality of) semiconductors and/or transistors (such as an electronic integrated circuit (IC)). In such a context, a processor executable instruction may be an electronic executable instruction.

The computer readable medium <NUM> is shown to include a memory/storage apparatus <NUM>. The memory/storage apparatus <NUM> represents a memory/storage capacity associated with one or more computer readable media. The memory/storage apparatus <NUM> may include a volatile medium (such as a random-access memory (RAM)) and/or a non-volatile medium (such as a read-only memory (ROM), a flash memory, an optical disc, and a magnetic disk). The memory/storage apparatus <NUM> may include a fixed medium (such as a RAM, a ROM, and a fixed hard disk drive) and a removable medium (such as a flash memory, a removable hard disk drive, and an optical disc). The computer readable medium <NUM> may be configured in various other manners further described below.

The one or more I/O interfaces <NUM> represent functions to allow a user to input a command and information to the computing device <NUM>, and, optionally, also allow information to be presented to the user and/or another component or device by using various input/output devices. An exemplary input device includes a keyboard, a cursor control device (such as a mouse), a microphone (for example, for speech input), a scanner, a touch function (such as a capacitive sensor or another sensor configured to detect a physical touch), a camera (for example, which may detect a motion that does not involve a touch as a gesture by using a visible or an invisible wavelength (such as an infrared frequency), and the like. An exemplary output device includes a display device (such as a monitor or a projector), a speaker, a printer, a network interface card, a tactile response device, and the like. Therefore, the computing device <NUM> may be configured in various manners further described below to support user interaction.

The computing device <NUM> further includes the image processing application <NUM>. The image processing application <NUM> may be, for example, a software instance of the image processing apparatus <NUM>, and implement the technologies described herein in combination with other elements in the computing device <NUM>.

Various technologies may be described herein in a general context of software, hardware elements or program modules. Generally, such modules include a routine, a program, an object, an element, a component, a data structure, and the like for executing a particular task or implementing a particular abstract data type. The terms "module", "function" and "component" used herein generally represent software, firmware, hardware or a combination thereof. The features of the technologies described herein are platform-independent, which means that such technologies may be implemented on various computing platforms having various processors.

Implementations of the described modules and the technologies may be stored on a certain form of computer readable media or transmitted across a particular form of a computer readable medium. The computer readable medium may include various media that can be accessed by the computing device <NUM>. By way of example, and not limitation, the computer-readable medium may include a "computer readable storage medium" and a "computer readable signal medium".

Contrary to pure signal transmission, a carrier or a signal, the "computer readable storage medium" is a medium and/or a device that can persistently store information, and/or a tangible storage apparatus. Therefore, the computer readable storage medium is a non-signal bearing medium. The computer readable storage medium includes hardware such as volatile and non-volatile, removable and non-removable media and/or storage devices implemented by using a method or a technology suitable for storing information (such as a computer readable instruction, a data structure, a program module, a logic element/circuit or other data). Examples of the computer readable storage medium include, but are not limited to, a RAM, a ROM, an EEPROM, a flash memory, or another memory technology, a CD-ROM, a digital versatile disk (DVD), or another optical storage apparatus, a hard disk, a cassette magnetic tape, a magnetic tape, a magnetic disk storage apparatus, or another magnetic storage device, or another storage device, a tangible medium, or an article of manufacture that is suitable for storing expected information and may be accessed by a computer.

The "computer-readable signal medium" is a signal bearing medium configured to send an instruction to hardware of the computing device <NUM>, for example, by using a network. A signal medium can typically embody a computer-readable instruction, a data structure, a program module, or other data in a modulated data signal such as a carrier, a data signal, or another transmission mechanism. The signal medium further includes any information transmission medium. The term "modulated data signal" is a signal that has one or more of features thereof set or changed in such a manner as to encode information. By way of example, and not limitation, a communication medium includes a wired medium such as a wired network or direct-wired connection, and a wireless medium such as a sound medium, an RF medium, an infrared medium, and another wireless medium.

As described above, the hardware element <NUM> and the computer readable medium <NUM> represent an instruction, a module, a programmable device logic and/or a fixed device logic that are implemented in the form of hardware, which may be used, in some embodiments, for implementing at least some aspects of the technologies described herein. The hardware element may include a component of an integrated circuit or a system-on-a-chip, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), and another implementation in silicon or another hardware device. In such a context, the hardware element may be used as a processing device for executing a program task defined by an instruction, a module, and/or a logic embodied by the hardware element, as well as a hardware device for storing an instruction for execution, such as the computer readable storage medium described above.

The above combination may also be configured to implement various technologies and modules described herein. Therefore, software, hardware or a program module and another program module may be implemented as one or more instructions and/or logic that are embodied on a certain form of a computer readable storage medium, and/or embodied by one or more hardware elements <NUM>. The computing device <NUM> may be configured to implement a specific instruction and/or function corresponding to a software and/or hardware module. Therefore, for example, by using the computer readable storage medium and/or the hardware element <NUM> of the processing system, the module may be implemented, at least partially in hardware, as a module that can be executed as software by the computing device <NUM>. The instruction and/or function may be executable/operable by one or more articles of manufacture (such as one or more computing devices <NUM> and/or processing systems <NUM>) to implement the technologies, modules, and examples described herein.

In various implementations, the computing device <NUM> may use various different configurations. For example, the computing device <NUM> may be implemented as a computer type device including a personal computer, a desktop computer, or a multi-screen computer, a laptop computer, a netbook, and the like. The computing device <NUM> may also be implemented as a mobile apparatus type device including a mobile device such as a mobile phone, a portable music player, a portable game device, a tablet computer, and a multi-screen computer. The computing device <NUM> may also be implemented as a television type device including a device having or connected to a generally larger screen in a casual viewing environment. The devices include a television, a set-top box, a game console, and the like.

The technologies described herein may be supported by the various configurations of the computing device <NUM>, which are not limited to specific examples of the technologies described herein. The function may also be completely or partially implemented on a "cloud" <NUM> by using a distributed system such as a platform <NUM> as described below.

The cloud <NUM> includes and/or represents the platform <NUM> for a resource <NUM>. The platform <NUM> abstracts an underlying function of hardware (such as a server) and software resources of the cloud <NUM>. The resource <NUM> may include an application and/or data that can be used when computer processing is performed on a server away from the computing device <NUM>. The resource <NUM> may also include a service provided by means of the Internet and/or a subscriber network such as a cellular or Wi-Fi network.

The platform <NUM> can abstract the resource and the function to connect the computing device <NUM> to another computing device. The platform <NUM> may also be used for abstracting scaling of resources to provide a corresponding level of scale to encountered demand for the encountered resource <NUM> implemented through the platform <NUM>. Therefore, in an interconnection device embodiment, the implementation of the functions described herein may be distributed throughout the system <NUM>. For example, the functions may be partially implemented on the computing device <NUM> and by the means of the platform <NUM> that abstracts the function of the cloud <NUM>.

For clarity, the embodiments of this disclosure are described with reference to different functional units. However, obviously, without departing from this disclosure, functionality of each functional unit may be implemented in a single unit, implemented in a plurality of units, or implemented as a part of another functional unit. For example, the functionality described as being performed by a single unit may be performed by a plurality of different units. A reference to a specific functional unit is only considered as the reference to an appropriate unit that is configured to provide the described functionality instead of indicating a strict logical or physical structure or organization. Therefore, this disclosure may be implemented in the single unit, or may be distributed among different units and circuits physically and functionally.

It is to be understood that, although the terms such as, first, second, and third may be used for describing various devices, elements, components or parts, these devices, elements, components or parts are not to be limited by these terms. These terms are only used for distinguishing a device, an element, a component or a part from another device, another element, another component or another part.

Claim 1:
An image processing method, executable by a computing device (<NUM>), the method comprising:
determining (<NUM>) a brightness value of an image, the image comprising a plurality of pixels; and
enhancing (<NUM>) a brightness of the image in response to the brightness value of the image being less than an image brightness threshold, by:
determining (<NUM>) each pixel of the image as a to-be-enhanced pixel;
determining (<NUM>) a brightness enhancement value of the to-be-enhanced pixel based on the brightness value of the image, an initial brightness value of the to-be-enhanced pixel, and initial brightness values of neighboring pixels of the to-be-enhanced pixel; and
using (<NUM>) the brightness enhancement value as an enhanced brightness value of the to-be-enhanced pixel;
wherein the determining (<NUM>) a brightness enhancement value of the to-be-enhanced pixel based on the brightness value of the image, an initial brightness value of the to-be-enhanced pixel, and initial brightness values of neighboring pixels of the to-be-enhanced pixel comprise:
filtering (<NUM>) the initial brightness value of the to-be-enhanced pixel, based on the initial brightness value of the to-be-enhanced pixel and the initial brightness values of the neighboring pixels of the to-be-enhanced pixel, to determine a filtered brightness value of the to-be-enhanced pixel; and
determining (<NUM>) the brightness enhancement value of the to-be-enhanced pixel based on the brightness value of the image, the initial brightness value of the to-be-enhanced pixel, and the filtered brightness value of the to-be-enhanced pixel, comprising:
determining the brightness enhancement value of the to-be-enhanced pixel according to the following formula, <MAT>
wherein E(x) is the brightness enhancement value of the to-be-enhanced pixel, I(x) is the initial brightness value of the to-be-enhanced pixel, and t(x) is atmospheric optical transmittance, and an expression of the atmospheric optical transmittance is: <MAT>
wherein IB is the brightness value of the image, EV is the filtered brightness value of the to-be-enhanced pixel, A is an atmospheric optical intensity value, and w is a non-zero constant.