CN101398929B - Method and device for restraining night image noise - Google Patents

Abstract

The invention discloses a method for suppressing noise of a night scene image. The method comprises the following steps: an original night scene image is copied twice to obtain a first temporary image and a second temporary image; a gray level image comprising noise of the original night scene image is obtained by threshold processing of the first temporary image, and a third temporary image is obtained by dimming the second temporary image; the original night scene image and the third temporary image are combined in Subtract mode by taking the gray level image comprising the noise of the original night scene image as a layer mask to obtain the finally desired image. The invention simultaneously discloses a device for suppressing noise of a night scene image. The method and the device can not affect the quality of the images while conveniently and effectively suppressing the noise of the night scene images, minimize the time and cost of users, and achieves more ideal treatment effect.

Description

A method and device for suppressing night scene image noise

technical field

The invention relates to the technical field of image denoising in image processing, in particular to a method and device for suppressing night scene image noise.

Background technique

With the increasing popularity of digital cameras, users have higher requirements for the effects of digital photos taken. Due to the lack of night light itself when shooting night scenes, in order to ensure the clarity of the image, a high-sensitivity (ISO) shooting method is generally used. Although it meets the desired clarity requirements, it also brings noise. This is because the digital camera itself The limitations of the equipment used lead to obvious noise in the night scene, which seriously affects the image quality.

To solve this problem, users usually need to use some software to post-process the night scene digital photos. At this time, the overall image is blurred, which obviously removes the noise, but at the same time causes the blurring of the entire image. Moreover, in the post-processing process, users need to adjust a series of complex parameters to achieve the purpose of removing the noise introduced in the shooting process, which is not only inconvenient to implement, but also difficult to achieve the desired effect.

Contents of the invention

In view of this, the main purpose of the present invention is to provide a method for suppressing night scene image noise, which can suppress night scene image noise conveniently and effectively.

Another object of the present invention is to provide a device for suppressing night scene image noise, which can conveniently and effectively suppress night scene image noise.

In order to achieve the above object, the technical solution of the present invention is specifically realized in the following way:

A method for suppressing night scene image noise, the method comprising:

Copying the original night scene image twice to obtain a first temporary image and a second temporary image;

Carrying out threshold processing on the first temporary image to obtain a grayscale image containing the noise of the original night scene image, and performing darkening processing on the second temporary image to obtain a third temporary image;

The red R, green G, and blue B components on each pixel in the original night scene image and the third temporary image are calculated in the following manner to obtain the final required image,

$\mathrm{<span\; class="notranslate">\; result</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; =</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; transparency</span>}<span\; class="notranslate">\; *</span>\frac{\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; MaskBmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span>}{\mathrm{<span\; class="notranslate">\; 255</span>}}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ,</span>$

Wherein, i represents any pixel; the bmp[i] represents the R, G or B component value on the i-th pixel in the original night scene image; the bmp2[i] represents the third temporary R, G or B component value on the ith pixel in the image; Said MaskBmp[i] represents the grayscale value of the i'th pixel in the grayscale image that contains the noise of the original night scene image; result[i] represents the R, G or B component value on the i-th pixel in the calculated final required image; the transparency represents transparency, and its value is a real number greater than or equal to 0 and less than or equal to 1; The * represents a multiplication sign, and the - represents a minus sign.

A device for suppressing night scene image noise, the device comprising:

a copying unit, for copying the original night scene image twice to obtain a first temporary image and a second temporary image;

A processing unit, configured to perform threshold processing on the first temporary image to obtain a grayscale image containing noise in the original night scene image, and perform darkening processing on the second temporary image to obtain a third temporary image;

The third calculation subunit is used to calculate the R, G, and B components of each pixel in the original night scene image and the third temporary image obtained by the processing unit in the following manner to obtain the final desired image,

$\mathrm{<span\; class="notranslate">\; result</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; =</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; transparency</span>}<span\; class="notranslate">\; *</span>\frac{\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; MaskBmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span>}{\mathrm{<span\; class="notranslate">\; 255</span>}}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ,</span>$

Wherein, i represents any pixel; the bmp[i] represents the R, G or B component value on the i-th pixel in the original night scene image; the bmp2[i] represents the third temporary R, G or B component value on the ith pixel in the image; Said MaskBmp[i] represents the grayscale value of the i'th pixel in the grayscale image that contains the noise of the original night scene image; result[i] represents the red R, green G or blue B component value on the i-th pixel in the calculated final required image; the transparency represents transparency, and its value is greater than or equal to 0 and less than or equal to 1 The real number; said * represents a multiplication sign, and said - represents a minus sign.

It can be seen that the adoption of the technical solution of the present invention fully utilizes the feature that the overall lighting of the night scene image is less, and generally presents black as a whole, and special processing is performed on the pixels within a certain threshold to determine the noise of the night scene image, and then the original night scene image is used to reduce the noise. The noise of the night scene image is removed, and the purpose of reasonably suppressing the noise of the night scene image is achieved while ensuring that the overall effect of the image remains unchanged; the scheme of the present invention can be applied to software, and the user only needs to click the corresponding button, and the software itself will The processing can be completed in the background according to the scheme of the present invention, which saves the user the process of adjusting a series of complex parameters, thereby saving time and cost for the user, and the processing effect is more ideal.

Description of drawings

FIG. 1 is a flow chart of an embodiment of the method for suppressing night scene image noise in the present invention.

FIG. 2 is a schematic diagram of the composition and structure of an embodiment of the device for suppressing night scene image noise of the present invention.

Detailed ways

In order to solve the problems existing in the prior art, the present invention has some common characteristics for night scene images, such as less overall lighting, generally black, and some details in the image, but the details are mostly high-light color areas, and there are few details in dark parts or Not obvious, etc., proposed a new scheme to suppress the noise of the night scene image: first, set a threshold for the original night scene image, and determine the noise of the original night scene image through the threshold; then, subtract the noise from the original night scene image The noise-reduced night scene image is obtained; under the premise of not changing the sharpness of the photo itself, this scheme can conveniently and effectively suppress the noise in the night scene photo, so that the photo can achieve a more perfect effect.

Before introducing the specific implementation scheme, first introduce the concept of the red-green-blue (RGB) color model. The RGB color model is a color standard in the industry. Various colors are obtained by changing the three color channels of R, G, and B and superimposing them on each other. Therefore, for each image in the image Pixels can be represented by three components (channels) of R, G, and B. Usually, the value range of each component is 0 to 255; thus, when the R, G, and B components take different values, the corresponding colors will also be different. For example, the R component value of pure red is 255, the G component value and B component value are both 0; the R component value of bright red is 246, the G component value is 20, and the B component value is 50.

Based on the above introduction, the specific implementation of the solution of the present invention includes: copying the original night scene image twice to obtain the first temporary image and the second temporary image; thresholding the first temporary image to obtain the noise containing the original night scene image The grayscale image of the second temporary image is darkened to obtain the third temporary image; the original night scene image and the third temporary image are merged by Subtract mode with the grayscale image containing the noise of the original night scene image as a mask , to get the final desired image.

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

FIG. 1 is a flow chart of an embodiment of the method for suppressing night scene image noise in the present invention. As shown in Figure 1, the following steps are included:

Step 101: Duplicate the original night scene image twice to obtain a first temporary image and a second temporary image.

How to copy it as a prior art will not be described in detail.

It should be noted that the copying of the original night scene image in this step is only for illustration and is not intended to limit the technical solution of the present invention. In this embodiment, the following processing operations may also be directly performed on the original night scene image.

Step 102: Perform threshold processing on the first temporary image to obtain a grayscale image containing noise in the original night scene image, and perform darkening processing on the second temporary image to obtain a third temporary image.

This step has two purposes: 1) After the image is thresholded, the grayscale image of the image noise can be obtained, which is fully prepared for the subsequent operation of removing noise; 2) Since the subsequent operation will adjust the entire image Brightness, and after dimming the image, the brightness of the image can be made darker. Therefore, after related operations later, the brightness of the image can be kept consistent with the original.

In this step, threshold processing is performed on the first temporary image to obtain a grayscale image containing noise in the original night scene image. The specific implementation is as follows:

By comparing the red (R) component value, green (G) component value and blue (B) component value on each pixel in the first temporary image respectively, find out the maximum component value, and use the maximum The component value of is set to r′;

For each r' in the first temporary image, the r component value is calculated in the following manner:

$\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}\\ \mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; Feather</span>}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Feather</span>}<span\; class="notranslate">\; ,</span>\\ \mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Feather</span>}\end{array}\right.$

Among them, Threshold is defined as the threshold point, and Feather is the feathering parameter. The point with a pixel value smaller than Threshold is blackened, and the point with a pixel value greater than Feather is whitened. Within the range of [Threshold, Threshold+Feather], whitening is a natural transition; threshold Threshold and The feathering parameter Feather is an empirical value, obtained according to user feedback and multiple mediations. The default value here is: Threshold=70, Feather=80; the r means to calculate the r on each pixel in the original night scene image ' and the value on each pixel obtained; the * represents a multiplication sign, the / represents a division sign, the + represents a plus sign, and the - represents a minus sign;

The calculated r component values are respectively assigned to the R component, G component and B component on the corresponding pixel points to obtain a grayscale image containing the noise of the original night scene image.

The implementation of dimming the second temporary image to obtain the third temporary image includes:

The R component value, the G component value and the B component value on each pixel in the second temporary image are calculated in the following manner:

t=t'-t'*Amount/255, to obtain the third temporary image,

Wherein, t' represents the R, G, and B component values on each pixel of the second temporary image, and t represents the calculated R, G, and B component values on each pixel of the third temporary image; Threshold Amount=180; the * indicates a multiplication sign, the / indicates a division sign, and the - indicates a minus sign.

Step 103: Merge the original night scene image and the third temporary image by using the grayscale image containing the noise of the original night scene image as a mask in Subtract mode to obtain the final desired image.

The Subtract mode in this step will adjust the brightness of the entire image.

Its specific implementation includes:

The R, G, and B components on each pixel in the original night scene image and the third temporary image are calculated in the following manner:

$\mathrm{<span\; class="notranslate">\; result</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; =</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; transparency</span>}<span\; class="notranslate">\; *</span>\frac{\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; MaskBmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span>}{\mathrm{<span\; class="notranslate">\; 255</span>}}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ,</span>$

Wherein, i represents any pixel; the bmp[i] represents the R, G or B component value on the i-th pixel in the original night scene image; the bmp2[i] represents the third temporary R, G or B component value on the ith pixel in the image; Said MaskBmp[i] represents the grayscale value of the i'th pixel in the grayscale image that contains the noise of the original night scene image; result[i] represents the R, G or B component value on the i-th pixel in the calculated final required image; the transparency represents transparency, and its value is a real number greater than or equal to 0 and less than or equal to 1; The * represents a multiplication sign, and the - represents a minus sign.

In this embodiment, when the transparency is 1, the values of the R, G, and B components on each pixel of the merged image in the Subtract mode are:

$\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; result</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; bmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Feather</span>}\\ \mathrm{<span\; class="notranslate">\; result</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; bmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; bmp</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}\\ \mathrm{<span\; class="notranslate">\; result</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; bmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; bmp</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Feather</span>}\end{array}\right.<span\; class="notranslate">\; ,</span>$

The result is the night scene image after noise removal.

The night scene noise suppression method adopted by the present invention can only be applied in night scenes, because most of the pixels in the night scene images are relatively dark, that is to say, R, G, and B are relatively small. If one or more pixel values in R, G, and B are higher, the pixel will be brighter.

So far, the process of suppressing night scene image noise in the method embodiment of the present invention is completed.

Based on the above method, FIG. 2 is a schematic diagram of the composition and structure of an embodiment of the device for suppressing night scene image noise according to the present invention. As shown in Figure 2, the device includes:

A copying unit 21, configured to copy two copies of the original night scene image to obtain a first temporary image and a second temporary image;

It should be noted that in this embodiment, there may be no copying unit 21, and the subsequent processing operations are directly performed on the original night scene image.

The processing unit 22 is configured to perform threshold processing on the first temporary image to obtain a grayscale image containing the noise of the original night scene image, and perform darkening processing on the second temporary image to obtain a third temporary image;

The computing unit 23 is configured to combine the original night scene image and the third temporary image by using the grayscale image containing the noise of the original night scene image as a mask layer through a Subtract mode to obtain a final desired image.

Wherein, the replication unit 21 includes:

The pending subunit 211 is used to save the original night scene image;

The copying subunit 212 is configured to perform the copying of the original night scene image in the subunit 211 to be processed.

It should be noted that, since the replication unit 21 may not be present in this embodiment, the subunit to be processed 211 and the replication subunit 212 included in the replication unit 21 may also be absent.

The processing unit 22 may specifically include:

The first processing subunit 221 is configured to perform threshold processing on the first temporary image to obtain a grayscale image containing the noise of the original night scene image, and the subprocessing unit 221 further includes:

The search subunit 2211 is used to find the largest component value among the red (R) component value, green (G) component value and blue (B) component value of each pixel in the first temporary image, and obtain the maximum component value The maximum component value is set to r';

The first calculation subunit 2212 is configured to calculate the value of the r component in the following manner for each r' in the first temporary image:

$\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}\\ \mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; Feather</span>}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Feather</span>}<span\; class="notranslate">\; ,</span>\\ \mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; ;</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; \&prime;</span><span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; Threshold</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Feather</span>}\end{array}\right.$

Among them, Threshold is defined as the threshold point, and Feather is the feathering parameter. The point with a pixel value smaller than Threshold is blackened, and the point with a pixel value greater than Feather is whitened. Within the range of [Threshold, Threshold+Feather], whitening is a natural transition; threshold Threshold and The feathering parameter Feather is an empirical value, obtained according to user feedback and multiple mediations, and the default value here is: Threshold=70, Feather=80; the r means to calculate the value of each pixel in the first temporary image The value on each pixel obtained by r'; the * represents a multiplication sign, the / represents a division sign, the + represents a plus sign, and the - represents a minus sign;

The assignment subunit 2213 is used to assign the r component value calculated by the first calculation subunit 2212 to the R component, G component and B component on the corresponding pixel, to obtain the grayscale image containing the noise of the original night scene image.

The second processing subunit 222 is configured to perform dimming processing on the second temporary image to obtain a third temporary image, and the processing subunit 222 may include:

The second calculation subunit 2221 is used to calculate the R component value, G component value and B component value of each pixel in the second temporary image in the following manner:

t=t'-t'*Amount/255, to obtain the third temporary image,

Wherein, t' represents the R, G, and B component values on each pixel of the second temporary image, and t represents the calculated R, G, and B component values on each pixel of the third temporary image; Threshold Amount=180; the * indicates a multiplication sign, the / indicates a division sign, and the - indicates a minus sign.

Wherein, the computing unit 23 may specifically be:

The third calculation subunit 231 is used to calculate the R, G, and B components of each pixel in the original night scene image and the third temporary image in the following manner:

$\mathrm{<span\; class="notranslate">\; result</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; =</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; bmp</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; transparency</span>}<span\; class="notranslate">\; *</span>\frac{\mathrm{<span\; class="notranslate">\; 255</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; MaskBmp</span>}<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span>}{\mathrm{<span\; class="notranslate">\; 255</span>}}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ]</span><span\; class="notranslate">\; ,</span>$

Wherein, i represents any pixel; the bmp[i] represents the R, G or B component value on the i-th pixel in the original night scene image; the bmp2[i] represents the third temporary R, G or B component value on the ith pixel in the image; Said MaskBmp[i] represents the grayscale value of the i'th pixel in the grayscale image that contains the noise of the original night scene image; result[i] represents the calculated R, G or B component value on the i-th pixel in the final required image; the transparency represents transparency, and its value is a real number greater than or equal to 0 and less than or equal to 1; The * represents a multiplication sign, and the - represents a minus sign.

For the specific working process of the device shown in FIG. 2 , please refer to the corresponding description in the method embodiment shown in FIG. 1 , which will not be repeated here.

As can be seen from the above-mentioned embodiments, the method for suppressing night scene image noise adopted in the present invention fully utilizes the characteristics that the overall lighting of the night scene image is less, and generally presents black as a whole, and performs special processing on the pixels within a certain threshold to determine the night scene. The noise of the image, and then subtract the noise of the night scene image from the original night scene image, so as to ensure that the overall effect of the image remains unchanged and achieve the purpose of reasonably suppressing the noise of the night scene image; the scheme of the present invention can be applied to software, and the user only needs to click Corresponding keys, the software itself can complete the processing in the background according to the scheme of the present invention, eliminating the need for the user to adjust a series of complex parameters, thereby saving time and cost for the user, and the processing effect is more ideal.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of the present invention. within the scope of protection.

Claims (8)

1. a method that suppresses night image noise is characterized in that, this method comprises:

With two parts of original night copying images, obtain first intermediate images and second intermediate images;

Described first intermediate images is carried out threshold process, obtain comprising the gray level image of described original night picture noise, described second intermediate images is dimmed processing, obtain the 3rd intermediate images;

To red R, green G on each pixel in described original night image and described the 3rd intermediate images, blue B component, calculate in such a way respectively, obtain final needing image,

$\mathrm{result}\left[i\right]=\left[\mathrm{bmp}\right[i]-[\mathrm{bmp}2\left[i\right]*\mathrm{transparency}*\frac{255-\mathrm{MaskBmp}\left[i\right]}{255}\left]\right],$

Wherein, i represents arbitrary pixel; Described bmp[i] R, G or B component value on i the pixel of expression in the described original night image; Described bmp2[i] R, G or B component value on i the pixel of expression in described the 3rd intermediate images; Described MaskBmp[i] i gray values of pixel points in the described gray level image that comprises described original night picture noise of expression; Result[i] R, G or B component value on i the pixel in the final needing image that calculates of expression; Described transparency represents transparency, and its value is one more than or equal to 0 and smaller or equal to 1 real number; Described * represents multiplication sign, and is described-the expression minus sign.

2. the method for claim 1 is characterized in that, described described first intermediate images is carried out threshold process, and the gray level image that obtains comprising described original night picture noise comprises:

Find out in the described original night image on each pixel component value maximum in R component value, G component value and the B component value, and the component value of described maximum is made as r ';

To the r ' on each pixel in the described original night image, carry out the r component value in such a way and calculate:

$\left\{\begin{array}{c}r=0;r^{\&prime;}<\mathrm{Threshold}\\ r=(r^{\&prime;}-\mathrm{Threshold})*255/\mathrm{Feather};\mathrm{Threshold}\&le;r^{\&prime;}\&le;\mathrm{Threshold}+\mathrm{Feather},\\ r=255;r^{\&prime;}>\mathrm{Threshold}+\mathrm{Feather}\end{array}\right.$

Wherein, described r represents to calculate the r ' on each pixel in the described original night image and value on each pixel of obtaining; Described Threshold=70, described Feather=80; Described * represents multiplication sign, and is described/the expression division sign, described+the expression plus sige, described-the expression minus sign;

R component value on each pixel that calculates difference assignment to the R component on the corresponding pixel points, G component and B component, is obtained comprising the gray level image of described original night picture noise.

3. the method for claim 1 is characterized in that, described described second intermediate images is dimmed processing, obtains the 3rd intermediate images and comprises:

With the R component value on each pixel in the described original night image, G component value and B component value, calculate in such a way respectively:

T=t '-t ' * Amount/255 obtains described the 3rd intermediate images,

Wherein, R, G, B component value on described each pixel of the 3rd intermediate images that R, G, B component value on described each pixel of original night image of t ' expression, t are represented to calculate; Threshold value A mount=180; Described * represents multiplication sign, and is described/the expression division sign, described-the expression minus sign.

4. a device that suppresses night image noise is characterized in that, this device comprises:

Copied cells is used for two parts of original night copying images are obtained first intermediate images and second intermediate images;

Processing unit is used for described first intermediate images is carried out threshold process, obtains comprising the gray level image of described original night picture noise, and described second intermediate images is dimmed processing, obtains the 3rd intermediate images;

The 3rd computation subunit is used for R, G, B component on each pixel of the 3rd intermediate images that obtains to described original night image and by described processing unit, calculates in such a way respectively, obtains final needing image,

$\mathrm{result}\left[i\right]=\left[\mathrm{bmp}\right[i]-[\mathrm{bmp}2\left[i\right]*\mathrm{transparency}*\frac{255-\mathrm{MaskBmp}\left[i\right]}{255}\left]\right],$

Wherein, i represents arbitrary pixel; Described bmp[i] R, G or B component value on i the pixel of expression in the described original night image; Described bmp2[i] R, G or B component value on i the pixel of expression in described the 3rd intermediate images; Described MaskBmp[i] i gray values of pixel points in the described gray level image that comprises described original night picture noise of expression; Result[i] red R, green G or blue B component value on i the pixel in the final needing image that calculates of expression; Described transparency represents transparency, and its value is one more than or equal to 0 and smaller or equal to 1 real number; Described * represents multiplication sign, and is described-the expression minus sign.

5. method as claimed in claim 4 is characterized in that, described copied cells comprises:

Pending subelement is used to preserve the original night image;

The replicon unit is used for the original night image of pending subelement is duplicated.

6. device as claimed in claim 4 is characterized in that, described processing unit comprises:

First handles subelement, is used for described first intermediate images is carried out threshold process, obtains comprising the gray level image of described original night picture noise;

Second handles subelement, is used for described second intermediate images is dimmed processing, obtains the 3rd intermediate images.

7. device as claimed in claim 6 is characterized in that, described first handles subelement comprises:

Search subelement, be used for finding out on described each pixel of first intermediate images component value maximum in R component value, G component value and the B component value, and the component value of described maximum is made as r ';

First computation subunit is used for each r ' to described first intermediate images, carries out the r component value in such a way and calculates:

$\left\{\begin{array}{c}r=0;r^{\&prime;}<\mathrm{Threshold}\\ r=(r^{\&prime;}-\mathrm{Threshold})*255/\mathrm{Feather};\mathrm{Threshold}\&le;r^{\&prime;}\&le;\mathrm{Threshold}+\mathrm{Feather},\\ r=255;r^{\&prime;}>\mathrm{Threshold}+\mathrm{Feather}\end{array}\right.$

Wherein, described r represents to calculate the r ' on each pixel in described first intermediate images and value on each pixel of obtaining; Described threshold value Threshold=70, described Feather=80; Described * represents multiplication sign, and is described/the expression division sign, described+the expression plus sige, described-the expression minus sign;

Assignment subelement, the r component value on each pixel that is used for first computation subunit is calculated assignment respectively obtain comprising the gray level image of described original night picture noise to the R component on the corresponding pixel points, G component and B component.

8. device as claimed in claim 6 is characterized in that, described second handles subelement comprises:

Second computation subunit is used for the R component value on each pixel of described second intermediate images, G component value and B component value are calculated respectively in such a way:

T=t '-t ' * Amount/255 obtains described the 3rd intermediate images,

Wherein, R, G, B component value on described each pixel of the 3rd intermediate images that R, G, B component value on described each pixel of second intermediate images of t ' expression, t are represented to calculate; Threshold value A mount=180; Described * represents multiplication sign, and is described/the expression division sign, described-the expression minus sign.

Images