WO2021223094A1

WO2021223094A1 - Method and apparatus for reducing noise, and computer usable medium storing software for implementing the method

Info

Publication number: WO2021223094A1
Application number: PCT/CN2020/088732
Authority: WO
Inventors: Jun Luo; Yuanjiao MA; Wei Quan
Original assignee: Guangdong Oppo Mobile Telecommunications Corp., Ltd.
Priority date: 2020-05-06
Filing date: 2020-05-06
Publication date: 2021-11-11
Also published as: CN115552457A

Abstract

A method for reducing noise in an image frame in moving image shooting mode or still image shooting mode according to the present disclosure includes: sequentially acquiring a current image frame and at least one previous image frame, setting one of the current image frame and the at least one previous image frame as a benchmark image frame, aligning the image frame (s) other than the benchmark image frame to the benchmark image frame, calculating a texture score in each patch of the benchmark image frame, blending the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score, and outputting the benchmark image frame with noise reduced.

Description

METHOD AND APPARATUS FOR REDUCING NOISE, AND COMPUTER USABLE MEDIUM STORING SOFTWARE FOR IMPLEMENTING THE METHOD

TECHNICAL FIELD

The present disclosure relates to the image processing technology field in general, and more specifically, to a method and an apparatus for reducing noise in an image frame, and a computer usable medium storing software for implementing the method.

BACKGROUND

In recent years, color imaging apparatuses have been developed and widely used in devices such as mobile phones, digital cameras, etc. Along with progresses in high-speed/large-capacity data communication, high-speed processors, or high color quality is required.

As one of the techniques for reduction of noise in an image frame, a multi-frame noise reduction (MFNR) method has been used, and one example of the MFNR method is disclosed in WO2015/172366A1. However, this method always requires a plurality of cameras for reducing noise. Thus, the burden on hardware is considerable and not cost-effective.

Though there are other methods for reducing noise, it is actually difficult to achieve not only to improve noise reduction, but also to prevent texture from being lost caused by blurring, ghost, etc.

SUMMARY

The present disclosure aims to solve at least one of the technical problems mentioned above. Accordingly, the present disclosure needs to provide a method and an apparatus for reducing noise in moving image shooting mode or still image shooting mode, and a computer usable medium storing software for causing a computer to implement the method for reducing noise.

According to one aspect of the disclosure, a method for reducing noise in an image frame may comprise:

acquiring a current image frame and at least one previous image frame, sequentially;

setting one of the current image frame and the at least one previous image frame as a benchmark image frame;

aligning the image frame (s) other than the benchmark image frame to the benchmark image frame;

calculating a texture score in each patch of the benchmark image frame;

blending the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score; and

outputting the benchmark image frame with noise reduced.

In some embodiments, the texture score in each patch of the benchmark image frame may be calculated by a following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs (x) is an absolute value of x.

In some embodiments, in response to blending the current image frame (s) other than the benchmark image frame to the benchmark image frame, the blending coefficient may be adjusted in accordance with the calculated texture score by taking a status of imaging scene into account.

According to one aspect of the disclosure, a method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the method may include:

acquiring at least two current image frames, simultaneously;

setting one of the current image frames as a benchmark image frame;

calculating a texture score in each patch of the benchmark image frame;

blending the image frame (s) other than the benchmark image frame to the benchmark current image frame by adjusting a blending coefficient in accordance with the calculated texture score; and

outputting the benchmark image frame with noise reduced.

According to one aspect of the disclosure, an apparatus for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the apparatus may comprise:

at least one camera unit configured to sequentially acquire a current image frame and at least one previous image frame;

a processor configured to input the current image frame and the at least one previous image frame, to set one of the current image frame and the at least one previous image frame as a benchmark image frame, to align the image frame (s) other than the benchmark image frame to the benchmark image frame, to calculate a texture score in each patch of the benchmark image frame, to blend the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score, and to output the benchmark image frame with noise reduced; and

a display unit configured to display the benchmark image frame with noise reduced.

According to one aspect of the disclosure, an apparatus for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the apparatus may include:

each of at least two camera units configured to simultaneously acquire a current image frame, respectively, at least two current image frames in total;

a processor configured to input the at least two current image frames, to set one of the current image frames as a benchmark image frame, to align the image frame (s) other than the benchmark image frame to the benchmark image frame, to calculate a texture score in each patch of the benchmark image frame, to blend the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score, and to output the benchmark image frame with noise reduced; and

According to one aspect of the disclosure, a computer usable medium storing software for causing a computer to implement a method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the method may comprise:

calculating a texture score in each patch of the benchmark image frame;

outputting the benchmark image frame with noise reduced.

According to one aspect of the disclosure, a computer usable medium storing software for causing a computer to implement a method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the method comprising:

acquiring at least two current image frames, simultaneously;

setting one of the current image frames as a benchmark image frame;

calculating a texture score in each patch of the benchmark image frame;

outputting the benchmark image frame with noise reduced.

BRIEF DESCRIPTION OF THE DRAWINGS

These and/or other aspects and advantages of embodiments of the present disclosure will become apparent and more readily appreciated from the following descriptions made with reference to the drawings, in which:

FIG. 1 is a block diagram schematically showing a circuit configuration of an apparatus for reducing noise in moving image shooting mode or still image shooting mode according to a first embodiment of the present disclosure;

FIG. 2A is a photo of an example of a previous image frame in a night scene in moving image shooting mode or still image shooting mode;

FIG. 2B is a photo of an example of a current image frame in the night scene in moving image shooting mode or still image shooting mode;

FIG. 3 is an explanatory graph showing an example of a texture score map of the current image frame (t) ;

FIG. 4 is a flowchart illustrating a method for reducing noise in moving image shooting mode or still image shooting mode according to a second embodiment of the present disclosure;

FIG. 5 is a block diagram schematically showing a circuit configuration of an apparatus for reducing noise in moving image shooting mode or still image shooting mode according to a third embodiment of the present disclosure; and

FIG. 6 is a flowchart illustrating a method for reducing noise in moving image shooting mode or still image shooting mode according to a fourth embodiment of the present disclosure.

DETAILED DESCRIPTION

Embodiments of the present disclosure will be described in detail and examples of the embodiments will be illustrated in the accompanying drawings. The same or similar elements and the elements having same or similar functions are denoted by like reference numerals throughout the descriptions. The embodiments described herein with reference to the drawings are explanatory and aim to illustrate the present disclosure, but shall not be construed to limit the present disclosure.

Referring to Fig. 1, an apparatus 10 for reducing noise in an image frame in moving image shooting mode or still image shooting mode according to a first embodiment of the present disclosure includes at least one camera unit 11, a processor 12, a display unit 13 and a memory 14.

The camera unit 11 sequentially acquires at least two image frames, namely a current image frame (t) , and at least one previous image frame (t-1; t is a natural number) in moving image shooting mode or still image shooting mode. The number of the previous image frames is not limited. In shooting mode, it is preferable to acquire two or more previous image frames (t-1, t-2, …t-m where m≧2 is an integer) to effectively reduce noise.

A night scene or an indoor dark scene is a typical example of a case in which it is difficult to achieve not only noise reduction but also to prevent texture from being lost caused by blurring, ghost, etc. If excessive noise reduction is applied, a texture, especially that of a bright image registration surrounded by a dark background is lost and image artifacts occur due to blurring, ghost, etc. If too little noise reduction is applied, noise, especially that in the dark background, will stand out.

Fig. 2A illustrates a previous image frame (t-1) , and Fig. 2B illustrates a current image frame (t) in a night scene, acquired sequentially by the camera unit 11.

Returning to Fig. 1, the processor 12 inputs the current image frame (n) and at least one previous image frame (n-1) acquired by the camera unit 11 in moving image shooting mode or still image shooting mode.

The Processor 12 sets one of the current image frame (n) and at least one previous image frame (n-1) as a benchmark image frame.

The processor 12 aligns the image frame other than the benchmark image frame to the benchmark image frame, specifically, it aligns image registrations included in the image frame other than the benchmark image frame to those (corresponding to the registrations in the image frame other than the benchmark image frame) included in the benchmark image frame.

The processor 12 further calculates a texture score in each patch of the benchmark image frame using the following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs (x) is an absolute value of x.

Using the above calculation, it is possible to obtain a texture score in each patch of the benchmark image frame with a relatively low amount of calculation.

Fig. 3 is a graph illustrating an example of a texture score map of the benchmark image frame, although it is not necessary to map the calculated texture scores in an actual process of noise reduction. In other words, this graph shows an example of a map of calculated texture scores (from zero to 60) , and the longitudinal and horizontal axes correspond to an image frame size.

By comparing Fig. 3 with Figs. 2A or 2B, it is clear that texture scores correspond to brightness (light intensity value) of image registrations in the image frame of Fig. 2A or 2B. A high texture score corresponds to a bright image registration (such as a tree or the moon) , and low texture score corresponds to a dark flat background.

Returning to Fig. 1, the processor 12 further blends the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient.

Adjustment of the blending coefficient is performed in accordance with the calculated texture score. Specifically, in a case that the calculated texture score is high, a noise component does not relatively stand out. Texture loss should be avoided and quality of an output image should not be degraded. Thus the blending coefficient is set to a low value. Noise reduction is not excessively applied, thus an effect of the image frame (s) other than the benchmark image frame on the benchmark image frame is relatively small.

In contrast, in a case that the calculated texture score is low, since a noise component stands out, it is possible to perform noise reduction strongly and the blending coefficient is set to a great value. The image frame (s) other than the benchmark image frame effect on the benchmark image frame is relatively strong.

The processor 12 outputs the benchmark image frame with noise reduced, and the display unit 13 receives the benchmark image frame with noise reduced and displays it on its screen.

As a result, it is possible to achieve not only to improve noise reduction, but also to prevent loss of texture due to blurring, ghost, etc., depending on the texture score, with a relatively low amount of calculation.

Further, when the blending coefficient is adjusted, it is preferably to take into account a status of an imaging scene, such as a night scene, an indoor scene, an outdoor scene, close up shooting mode, portrait shooting mode, landscape shooting mode, bokeh shooting mode, etc..

A method for reducing noise in an image frame in moving image shooting mode or still image shooting mode according to a second embodiment of the present disclosure includes the following steps shown in Fig. 4.

At the step S11, a current image frame (t) and at least one previous image frame (t-1) are sequentially acquired.

At the step S12, one of the current image frame (t) and the at least one previous image frame (t-1) is set as a benchmark image frame.

At the step S13, the image frame (s) other than the benchmark image frame is aligned to the benchmark image frame.

At the step S14, a texture score in each patch of the benchmark image frame is calculated.

At the step S15, the image frame (s) other than the benchmark image frame is blended to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score.

At the step S16, the benchmark image frame with noise reduced is output.

In the circuit configuration of the apparatus for reducing noise according to the above first embodiment, one camera unit 11 is included, as shown in Fig. 1. However, the number of camera unit (s) is not limited, and it is possible to include two or more camera units.

The apparatus for reducing noise in moving image shooting mode or still image shooting mode according to a third embodiment of the present disclosure includes two or more camera units 21-1, 21-2, …, 21-M (where M≧2 is an integer) , a processor 22, a display unit 23, and a memory 24, as shown in Fig. 5. These plural camera units 21-1, 21-2, …, 21-M are different from each other, for example, in aspects such as their focal length, angle of view or sensor type. More specifically, the camera unit 21-1 may include a color sensor, and the camera unit 21-2 may include a monochrome sensor. The color sensor acquires color information and brightness information. The monochrome sensor acquires brightness information of higher sensitivity than that of the color sensor.

At least two of the camera units simultaneously acquire at least two current image frames. For example, the camera unit 21-1 acquires a current image frame at the same time as the camera unit 21-2 acquires a current image frame.

The processor 22 inputs the at least two current image frames. For example, the processor 22 inputs the current image frame acquired by the camera unit 21-1 and the current image frame acquired by the camera unit 21-2. The processor 22 sets one of the at least two current image frames as a benchmark image frame. The processor 22 aligns the image frame (s) other than the benchmark image frame to the benchmark image frame.

The processor 22 calculates a texture score in each patch of the benchmark image frame using the above equation.

The processor 22 blends the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient.

The processor 22 outputs the benchmark image frame with noise reduced. The display unit 23 receives the benchmark image frame with noise reduced and displays it on its screen.

A method for reducing noise in an image frame in moving image shooting mode or still image shooting mode according to a fourth embodiment of the present disclosure includes the following steps shown in Fig. 6.

At the step S21, at least two current image frames are simultaneously acquired.

At the step S22, one of the at least two current image frames is set as a benchmark image frame.

At the step S23, the image frame (s) other than the benchmark image frame is aligned to the benchmark image frame.

At the step S24, a texture score in each patch of the benchmark image frame is calculated using the above equation.

At the step S25, the image frame (s) other than the benchmark image frame is blended to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score.

At the step S26, the benchmark image frame with noise reduced is output.

A computer usable medium according to a fourth embodiment of the present disclosure is a medium storing a software for causing a computer to implement the method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, and the method includes the above-mentioned steps shown in Fig. 4. Further, a computer usable medium according to a fourth embodiment of the present disclosure is a medium storing a software for causing a computer to implement the method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, and the method includes the above-mentioned steps shown in Fig. 6.

In the description of embodiments of the present disclosure, it is to be understood that terms such as "central" , "longitudinal" , "transverse" , "length" , "width" , "thickness" , "upper" , "lower" , "front" , "rear" , "back" , "left" , "right" , "vertical" , "horizontal" , "top" , "bottom" , "inner" , "outer" , "clockwise" and "counterclockwise" should be construed to refer to the orientation or the position as described or as shown in the drawings in discussion. These relative terms are only used to simplify the description of the present disclosure, and do not indicate or imply that the device or element referred to must have a particular orientation, or must be constructed or operated in a particular orientation. Thus, these terms cannot be constructed to limit the present disclosure.

In addition, terms such as "first" and "second" are used herein for purposes of description and are not intended to indicate or imply relative importance or significance or to imply the number of indicated technical features. Thus, a feature defined as "first" and "second" may comprise one or more of this feature. In the description of the present disclosure, "aplurality of" means “two or more than two” , unless otherwise specified.

In the description of embodiments of the present disclosure, unless specified or limited otherwise, the terms "mounted" , "connected" , "coupled" and the like are used broadly, and may be, for example, fixed connections, detachable connections, or integral connections; may also be mechanical or electrical connections; may also be direct connections or indirect connections via intervening structures; may also be inner communications of two elements which can be understood by those skilled in the art according to specific situations.

In the embodiments of the present disclosure, unless specified or limited otherwise, a structure in which a first feature is "on" or "below" a second feature may include an embodiment in which the first feature is in direct contact with the second feature, and may also include an embodiment in which the first feature and the second feature are not in direct contact with each other, but are in contact via an additional feature formed therebetween. Furthermore, a first feature "on" , "above" or "on top of" a second feature may include an embodiment in which the first feature is orthogonally or obliquely "on" , "above" or "on top of" the second feature, or just means that the first feature is at a height higher than that of the second feature; while a first feature "below" , "under" or "on bottom of" a second feature may include an embodiment in which the first feature is orthogonally or obliquely "below" , "under" or "on bottom of" the second feature, or just means that the first feature is at a height lower than that of the second feature.

Various embodiments and examples are provided in the above description to implement different structures of the present disclosure. In order to simplify the present disclosure, certain elements and settings are described in the above. However, these elements and settings are only by way of example and are not intended to limit the present disclosure. In addition, reference numbers and/or reference letters may be repeated in different examples in the present disclosure. This repetition is for the purpose of simplification and clarity and does not refer to relations between different embodiments and/or settings. Furthermore, examples of different processes and materials are provided in the present disclosure. However, it would be appreciated by those skilled in the art that other processes and/or materials may also be applied.

Reference throughout this specification to "an embodiment" , "some embodiments" , "an exemplary embodiment" , "an example" , "a specific example" or "some examples" means that a particular feature, structure, material, or characteristics described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. Thus, the appearances of the above phrases throughout this specification are not necessarily referring to the same embodiment or example of the present disclosure. Furthermore, the particular features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

Any process or method described in a flow chart or described herein in other ways may be understood to include one or more modules, segments or portions of codes of executable instructions for achieving specific logical functions or steps in the process, and the scope of a preferred embodiment of the present disclosure includes other implementations, in which it should be understood by those skilled in the art that functions may be implemented in a sequence other than the sequences shown or discussed, including in a substantially identical sequence or in an opposite sequence.

The logic and/or step described in other manners herein or shown in the flow chart, for example, a particular sequence table of executable instructions for realizing the logical function, may be specifically achieved in any computer readable medium to be used by the instructions execution system, device or equipment (such as a system based on computers, a system comprising processors or other systems capable of obtaining instructions from the instructions execution system, device and equipment executing the instructions) , or to be used in combination with the instructions execution system, device and equipment. As to the specification, "the computer readable medium" may be any device adaptive for including, storing, communicating, propagating or transferring programs to be used by or in combination with the instruction execution system, device or equipment. More specific examples of the computer readable medium comprise but are not limited to: an electronic connection (an electronic device) with one or more wires, a portable computer enclosure (amagnetic device) , a random access memory (RAM) , a read only memory (ROM) , an erasable programmable read-only memory (EPROM or a flash memory) , an optical fiber device and a portable compact disk read-only memory (CDROM) . In addition, the computer readable medium may even be a paper or other appropriate medium capable of printing programs thereon, this is because, for example, the paper or other appropriate medium may be optically scanned and then edited, decrypted or processed with other appropriate methods when necessary to obtain the programs in an electric manner, and then the programs may be stored in the computer memories.

It should be understood that each part of the present disclosure may be realized by the hardware, software, firmware or their combination. In the above embodiments, a plurality of steps or methods may be realized by the software or firmware stored in the memory and executed by the appropriate instructions execution system. For example, if it is realized by the hardware, likewise in another embodiment, the steps or methods may be realized by one or a combination of the following techniques known in the art: a discrete logic circuit having a logic gate circuit for realizing a logic function of a data signal, an application-specific integrated circuit having an appropriate combination logic gate circuit, a programmable gate array (PGA) , a field programmable gate array (FPGA) , etc.

Those skilled in the art shall understand that all or parts of the steps in the above exemplifying method of the present disclosure may be achieved by commanding the related hardware with programs. The programs may be stored in a computer readable storage medium, and the programs comprise one or a combination of the steps in the method embodiments of the present disclosure when run on a computer.

In addition, each function cell of the embodiments of the present disclosure may be integrated in a processing module, or these cells may be separate physical existence, or two or more cells are integrated in a processing module. The integrated module may be realized in a form of hardware or in a form of software function modules. When the integrated module is realized in a form of software function module and is sold or used as a standalone product, the integrated module may be stored in a computer readable storage medium.

The storage medium mentioned above may be read-only memories, magnetic disks, CD, etc.

Although embodiments of the present disclosure have been shown and described, it would be appreciated by those skilled in the art that the embodiments are explanatory and cannot be construed to limit the present disclosure, and changes, modifications, alternatives and variations can be made in the embodiments without departing from the scope of the present disclosure.

Claims

A method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the method comprising:

acquiring a current image frame and at least one previous image frame sequentially;

setting one of the current image frame and the at least one previous image frame as a benchmark image frame;

aligning the image frame (s) other than the benchmark image frame to the benchmark image frame;

calculating a texture score in each patch of the benchmark image frame;

blending the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score; and

outputting the benchmark image frame with noise reduced.
The method according to claim 1, wherein the texture score in each patch of the benchmark image frame is calculated by a following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs(x) is an absolute value of x.
The method according to claim 1 or 2, wherein in response to blending the current image frame (s) other than the benchmark image frame to the benchmark image frame, the blending coefficient is adjusted in accordance with the calculated texture score by taking a status of imaging scene into account.
A method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the method comprising:

acquiring at least two current image frames, simultaneously;

setting one of the current image frames as a benchmark image frame;

aligning the image frame (s) other than the benchmark image frame to the benchmark image frame;

calculating a texture score in each patch of the benchmark image frame;

blending the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score; and

outputting the benchmark image frame with noise reduced.
The method according to claim 4, wherein the texture score in each patch of the benchmark image frame is calculated by a following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs(x) is an absolute value of x.
The method according to claim 4 or 5, wherein in response to blending the current image frame (s) other than the benchmark image frame to the benchmark image frame, the blending coefficient is adjusted in accordance with the calculated texture score by taking a status of imaging scene into account.
An apparatus for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the apparatus comprising:

at least one camera unit configured to sequentially acquire a current image frame and at least one previous image frame;

a processor configured to input the current image frame and the at least one previous image frame, to set one of the current image frame and the at least one previous image frame as a benchmark image frame, to align the image frame (s) other than the benchmark image frame to the benchmark image frame, to calculate a texture score in each patch of the benchmark image frame, to blend the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score, and to output the benchmark image frame with noise reduced; and

a display unit configured to display the benchmark image frame with noise reduced.
The apparatus according to claim 7, wherein the texture score in each patch of the benchmark image frame is calculated by a following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs(x) is an absolute value of x.
The apparatus according to claim 7 or 8, wherein in response to blending the current image frame (s) other than the benchmark image frame to the benchmark image frame, the blending coefficient is adjusted in accordance with the calculated texture score by taking a status of imaging scene into account.
An apparatus for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the apparatus comprising:

each of at least two camera units configured to simultaneously acquiring a current image frame, respectively, at least two current image frames in total;

a processor configured to input the at least two current image frames, to set one of the current image frames as a benchmark image frame, to align the image frame (s) other than the benchmark image frame to the benchmark image frame, to calculate a texture score in each patch of the benchmark image frame, to blend the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score, and to output the benchmark image frame with noise reduced; and

a display unit configured to display the benchmark image frame with noise reduced.
The apparatus according to claim 10, wherein the texture score in each patch of the benchmark image frame is calculated by a following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs(x) is an absolute value of x.
The apparatus according to claim 10 or 11, wherein in response to blending the current image frame (s) other than the benchmark image frame to the benchmark current image frame, the blending coefficient is adjusted in accordance with the calculated texture score by taking a status of imaging scene into account.
A computer usable medium storing software for causing a computer to implement a method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the method comprising:

acquiring a current image frame and at least one previous image frame, sequentially;

setting one of the current image frame and the at least one previous image frame as a benchmark image frame;

aligning the image frame (s) other than the benchmark image frame to the benchmark image frame;

calculating a texture score in each patch of the benchmark image frame;

blending the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score; and

outputting the benchmark image frame with noise reduced.
The computer usable medium according to claim 13, wherein the texture score in each patch of the benchmark image frame is calculated by a following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs(x) is an absolute value of x.
The computer usable medium according to claim 13 or 14, wherein in response to blending the current image frame (s) other than the benchmark image frame to the benchmark frame, the blending coefficient is adjusted in accordance with the calculated texture score by taking a status of imaging scene into account.
A computer usable medium storing software for causing a computer to implement a method for reducing noise in an image frame in moving image shooting mode or still image shooting mode, the method comprising:

Acquiring at least two current image frames, simultaneously;

setting one of the current image frames as a benchmark image frame;

aligning the image frame (s) other than the benchmark image frame to the benchmark image frame;

calculating a texture score in each patch of the benchmark image frame;

blending the image frame (s) other than the benchmark image frame to the benchmark image frame by adjusting a blending coefficient in accordance with the calculated texture score; and

outputting the benchmark image frame with noise reduced.
The computer usable medium according to claim 16, wherein the texture score in each patch of the benchmark image frame is calculated by a following equation:

n is a number of pixels in each patch;

xi is a light intensity value of each pixel in each patch;

is an averaged value of the light intensity values in each patch; and

Abs(x) is an absolute value of x.
The computer usable medium according to claim 16 or 17, wherein in response to blending the current image frame (s) other than the benchmark image frame to the benchmark image frame, the blending coefficient is adjusted in accordance with the calculated texture score by taking a status of imaging scene into account.