A kind of evaluation method of awb algorithm, mobile terminal and computer storage medium

Abstract

The invention discloses an assessment method for an AWB (Automatic White Balance) algorithm, a mobile terminal and a computer storage medium. The method comprises the steps of acquiring a preset assessment image and a display parameter of the assessment image; respectively calculating AWB values of the assessment image through at least two preset AWB algorithms based on the display parameter of the assessment image to obtain at least two first AWB values; acquiring a second AWB value set for the assessment image; respectively calculating absolute values of difference values between the at least two first AWB values and the second AWB value; and determining one AWB algorithm in the at least two AWB algorithms according to the calculated absolute values of the difference values as a specified algorithm provided for the AWB values of all to-be-tested images.

Description

technical field

[0001] The invention relates to an automatic white balance evaluation technology, in particular to an evaluation method of an automatic white balance AWB algorithm, a mobile terminal and a computer-storable medium. Background technique

[0002] With the rapid development of mobile communications, handheld mobile terminals are becoming more and more intelligent. For example, the current touch-screen smart phones or tablet computers have more and more functions, and the operation is more and more convenient. With the increasing demand of users, the mobile communication terminal has more and more application programs. The mobile communication terminal has long been not only used to meet people's mutual connection, but has become a very important mobile personal entertainment terminal in people's daily life. .

[0003] Typically, since images shot in a room with fluorescent lighting will appear greenish, images shot indoors under tungsten lighting will appear ye...

Examples

Embodiment 1

[0089] image 3 It is a schematic flowchart of the first implementation method of the evaluation method of the AWB algorithm in the embodiment of the present invention. like image 3 As shown, the evaluation method of the AWB algorithm may include the following steps:

[0090] Step 301, acquiring a preset evaluation image and display parameters of the evaluation image.

[0091] Typically, the color reflected by an object has a lot to do with the color temperature of the light source. The reason why the human eye sees some objects as white, whether on a sunny day or cloudy day, indoors or under fluorescent lighting, is that the human brain can detect and correct color changes like this. The human eye can adapt itself, but digital video cameras do not have such intelligent functions. In order to be close to the human visual standard, a digital camera must imitate the human brain and adjust the image color according to the color temperature of the light source, that is, it ne...

Embodiment 2

[0126] Figure 9 It is a schematic flowchart of the second implementation method of the evaluation method of the AWB algorithm in the embodiment of the present invention. like Figure 9 As shown, the evaluation method of the AWB algorithm may include the following steps:

[0127] Step 901. Acquire a preset evaluation image and display parameters of the evaluation image.

[0128] In a specific embodiment of the present invention, the mobile terminal can acquire preset evaluation images and display parameters of the evaluation images. Specifically, when a touch operation on the touch screen of the mobile terminal is detected, the mobile terminal can determine whether the touch operation is a first function enabling operation, and generate a first judgment result; when the first judgment result indicates that the touch operation is When the first function is enabled and operated, start the photographing unit of the mobile terminal, and collect evaluation images through the pho...

Embodiment 3

[0139] Figure 10 It is a schematic diagram of the first component structure of the mobile terminal in the embodiment of the present invention. like Figure 10 As shown, the mobile terminal includes: an acquisition unit 1001, a calculation unit 1002, and a determination unit 1003; wherein,

[0140] The obtaining unit 1001 is configured to obtain a preset evaluation image and display parameters of the evaluation image;

[0141] The calculation unit 1002 is configured to calculate the AWB value of the evaluation image by using at least two preset AWB algorithms based on the display parameters of the evaluation image to obtain at least two first AWB values;

[0142] The acquiring unit 1001 is further configured to acquire a second AWB value set for the evaluation image;

[0143] The calculation unit 1002 is further configured to respectively calculate the absolute value of the difference between the at least two first AWB values ​​and the second AWB value;

[0144] The determ...

technical field

[0001] The invention relates to an automatic white balance evaluation technology, in particular to an evaluation method of an automatic white balance AWB algorithm, a mobile terminal and a computer-storable medium. Background technique

[0002] With the rapid development of mobile communications, handheld mobile terminals are becoming more and more intelligent. For example, the current touch-screen smart phones or tablet computers have more and more functions, and the operation is more and more convenient. With the increasing demand of users, the mobile communication terminal has more and more application programs. The mobile communication terminal has long been not only used to meet people's mutual connection, but has become a very important mobile personal entertainment terminal in people's daily life. .

[0003] Typically, since images shot in a room with fluorescent lighting will appear greenish, images shot indoors under tungsten lighting will appear ye...

Examples

Embodiment 1

[0089] image 3 It is a schematic flowchart of the first implementation method of the evaluation method of the AWB algorithm in the embodiment of the present invention. like image 3 As shown, the evaluation method of the AWB algorithm may include the following steps:

[0090] Step 301, acquiring a preset evaluation image and display parameters of the evaluation image.

[0091] Typically, the color reflected by an object has a lot to do with the color temperature of the light source. The reason why the human eye sees some objects as white, whether on a sunny day or cloudy day, indoors or under fluorescent lighting, is that the human brain can detect and correct color changes like this. The human eye can adapt itself, but digital video cameras do not have such intelligent functions. In order to be close to the human visual standard, a digital camera must imitate the human brain and adjust the image color according to the color temperature of the light source, that is, it ne...

Embodiment 2

[0126] Figure 9 It is a schematic flowchart of the second implementation method of the evaluation method of the AWB algorithm in the embodiment of the present invention. like Figure 9 As shown, the evaluation method of the AWB algorithm may include the following steps:

[0127] Step 901. Acquire a preset evaluation image and display parameters of the evaluation image.

[0128] In a specific embodiment of the present invention, the mobile terminal can acquire preset evaluation images and display parameters of the evaluation images. Specifically, when a touch operation on the touch screen of the mobile terminal is detected, the mobile terminal can determine whether the touch operation is a first function enabling operation, and generate a first judgment result; when the first judgment result indicates that the touch operation is When the first function is enabled and operated, start the photographing unit of the mobile terminal, and collect evaluation images through the pho...

Embodiment 3

[0139] Figure 10 It is a schematic diagram of the first component structure of the mobile terminal in the embodiment of the present invention. like Figure 10 As shown, the mobile terminal includes: an acquisition unit 1001, a calculation unit 1002, and a determination unit 1003; wherein,

[0140] The obtaining unit 1001 is configured to obtain a preset evaluation image and display parameters of the evaluation image;

[0141] The calculation unit 1002 is configured to calculate the AWB value of the evaluation image by using at least two preset AWB algorithms based on the display parameters of the evaluation image to obtain at least two first AWB values;

[0142] The acquiring unit 1001 is further configured to acquire a second AWB value set for the evaluation image;

[0143] The calculation unit 1002 is further configured to respectively calculate the absolute value of the difference between the at least two first AWB values ​​and the second AWB value;

[0144] The determ...

Images