CN106683054B - Method for inhibiting salt and pepper noise based on image dithering technology - Google Patents
Method for inhibiting salt and pepper noise based on image dithering technology Download PDFInfo
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- CN106683054B CN106683054B CN201611124700.7A CN201611124700A CN106683054B CN 106683054 B CN106683054 B CN 106683054B CN 201611124700 A CN201611124700 A CN 201611124700A CN 106683054 B CN106683054 B CN 106683054B
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- 235000002566 Capsicum Nutrition 0.000 title claims abstract description 22
- 239000006002 Pepper Substances 0.000 title claims abstract description 22
- 235000016761 Piper aduncum Nutrition 0.000 title claims abstract description 22
- 235000017804 Piper guineense Nutrition 0.000 title claims abstract description 22
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- 150000003839 salts Chemical class 0.000 title claims abstract description 22
- 238000005516 engineering process Methods 0.000 title claims abstract description 9
- 230000002401 inhibitory effect Effects 0.000 title claims abstract description 7
- 244000203593 Piper nigrum Species 0.000 title 1
- 241000722363 Piper Species 0.000 claims abstract description 21
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- 230000000007 visual effect Effects 0.000 abstract description 4
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- 201000004569 Blindness Diseases 0.000 description 1
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- 238000002591 computed tomography Methods 0.000 description 1
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
- G06T2207/20192—Edge enhancement; Edge preservation
Abstract
The invention discloses a method for inhibiting salt and pepper noise based on an image dithering technology, which comprises the following steps: inputting a pixel value of a certain point of the obtained image; determining the number n of pixel bits, and assigning a pixel value corresponding to the H bits from high to low to a first temporary storage A; assigning the pixel value corresponding to L to a second temporary storage B; let I be random (L), I be-2L‑1～2L‑1Random integers in between; let B be B + I; carrying out boundary check on the B value; assigning a new pixel value f (x, y) ═ a + B to the pixel at the (x, y) point; and repeating the operations on the whole image to finish the image processing. According to the method, the random integer value in a certain range is introduced into the low L position in the video image, so that salt and pepper noise can be inhibited, the image video is smoother, and the visual effect is better.
Description
Technical Field
The invention relates to an image enhancement technology in digital video image processing, in particular to a method for inhibiting salt and pepper noise based on an image dithering technology.
Background
The development of digital image processing began in the early 60 s, with the first practical successful application being the us jet propulsion laboratory. The astronautic detector 7 sends thousands of lunar photographs back in 1964 to a spaceflight detector loitering person, the photographs are processed by using image processing technologies, such as geometric correction, gray level transformation, noise removal and the like, the influence of the sun position and the lunar environment is considered, a lunar surface map is successfully drawn by a computer, and great success is achieved. Another significant achievement achieved by digital image processing is the result of medical acquisition. In 1972, Housfield, Engineer of England EMI, Inc. invented an X-ray computed tomography apparatus for cranial diagnosis, built into CT (computer Tomograph).
Noise can be understood as a factor that hinders human perception of the information of the received source. For example, if a black-and-white image has a luminance distribution assumed to be f (x, y), then the luminance distribution R (x, y) that interferes with the image is called image noise. Noise can be defined theoretically as "unpredictable, random error that can only be factored by probabilistic methods". Therefore, it is appropriate to consider the image noise as a multi-dimensional random process, and the method of describing the noise can fully borrow the random process and its probability distribution function and probability density function.
Digital images are often interfered by various noises in the processes of acquisition, transmission and the like, and the image effect is seriously influenced. Therefore, it is necessary to perform noise processing on the image before performing operations such as edge detection, image segmentation, feature extraction, pattern recognition, and the like. How to ensure that the image details can be protected to the maximum extent while processing is one of the hot problems of research in the field at present. The salt and pepper noise is noise which is widely existed in digital image processing and seriously damages the image quality, at present, a traditional median filtering algorithm is generally adopted for the salt and pepper noise, although the salt and pepper noise can be inhibited to a certain extent, the blindness is high, the same processing method is adopted for all pixel points, the noise is filtered, meanwhile, the pixel values of some non-noise points are changed, and the loss of the image details is caused to a great extent. Especially under the condition that some noise is particularly large and the required information needs to be obtained by naked eyes, if a filter is used for noise reduction, a lot of important information is lost.
Disclosure of Invention
The invention aims to provide a method for inhibiting salt and pepper noise based on an image dithering technology.
The technical scheme for realizing the purpose of the invention is as follows: a method for suppressing salt and pepper noise based on an image dithering technology comprises the following steps:
step 1, inputting a pixel value G (x, y) of a certain point of an obtained image, wherein x is the row number of the image where the point pixel is located, and y is the column number where the point pixel is located;
step 2, determining the number n of pixel bits according to the pixel value of the point pixel, and assigning the pixel value corresponding to the H bit from high to low to the first temporary storage amount A;
step 3, enabling L to be n-H, wherein L is the low-order bit number which is not recorded by the first temporary storage amount A, and assigning a pixel value corresponding to L to the second temporary storage amount B;
step 4, let I be random (L), I is-2L-1～2L-1Random integers in between;
step 5, enabling B to be B + I;
and 6, carrying out boundary check on the B value obtained in the step 5: if B is present<0, then let B equal to 0; if B is present>2LIf B is 2L(ii) a If B is more than or equal to 0 and less than or equal to 2LIf the value of B is not changed;
step 7, assigning a new pixel value f (x, y) to the pixel at the (x, y) point as a + B;
and 8, repeating the operations of the steps 1 to 7 on the whole image to finish the image processing.
Compared with the prior art, the invention has the following remarkable advantages:
the method does not adopt various filtering modes to remove salt and pepper noise, but introduces a random integer value in a certain range into the low L position in the video image, thereby inhibiting the salt and pepper noise, enabling the image video to be smoother and having better visual effect.
Drawings
Fig. 1 is a flowchart of a method for suppressing salt and pepper noise based on an image dithering technique according to the present invention.
Fig. 2 is a digital gray scale image containing a large amount of salt and pepper noise.
Fig. 3 is an image processed by the present invention.
Fig. 4 is a graph of the actual observed contrast effect.
Detailed Description
With reference to fig. 1, a method for suppressing salt and pepper noise based on an image dithering technique includes the following steps:
step 1, inputting a pixel value G (x, y) of a certain point of an obtained image, wherein x is the row number of the image where the point pixel is located, and y is the column number where the point pixel is located;
step 2, determining the number n of pixel bits according to the pixel value of the point pixel, and assigning the pixel value corresponding to the H bit from high to low to the first temporary storage amount A;
step 3, enabling L to be n-H, wherein L is the low-order bit number which is not recorded by the first temporary storage amount A, and assigning a pixel value corresponding to L to the second temporary storage amount B;
step 4, let I be random (L), I is-2L-1～2L-1Random integers in between;
step 5, enabling B to be B + I;
and 6, carrying out boundary check on the B value obtained in the step 5: if B is present<0, then let B equal to 0; if B is present>2LIf B is 2L(ii) a If B is more than or equal to 0 and less than or equal to 2LIf the value of B is not changed;
step 7, assigning a new pixel value f (x, y) to the pixel at the (x, y) point as a + B;
and 8, repeating the operations of the steps 1 to 7 on the whole image to finish the image processing.
Further, the pixel value in step 1 is a component value of R, G, B or a gray scale value.
The present invention is further illustrated by the following specific examples.
Examples
With reference to the drawings, a method for suppressing salt and pepper noise based on an image dithering technique of the embodiment includes the following steps:
step 1, inputting a pixel value G (x, y) of a certain point in fig. 2, where x is the number of rows of an image where the point pixel is located, and y is the number of columns where the point pixel is located;
fig. 2 is an image containing a large amount of salt and pepper noise, and the salt and pepper noise in the image is relatively obvious and seriously affects the subjective evaluation of the image.
Step 2, knowing that the image in fig. 2 has 256-level gray scale, the pixel value of each pixel point in the image can be represented by binary 8-bit data, and the pixel bit number of the image is 8; assigning a pixel value corresponding to the first 5 bit bits from high to low to a first temporary storage A;
step 3, assigning the pixel value corresponding to the low 3-bit number which is not recorded by the first temporary storage amount A to a second temporary storage amount B for the residual low 3-bit pixel number;
step 4, taking I equal to-22～22Random integers in between;
step 5, enabling B to be B + I;
and 6, carrying out boundary check on the B value obtained in the step 5: if B is present<0, then let B equal to 0; if B is present>23If B is 23(ii) a If B is more than or equal to 0 and less than or equal to 23The B value is unchanged;
step 7, assigning a new pixel value f (x, y) to the pixel at the point (x, y) as a + B, and the new pixel value f (x, y) obtained at the point (x, y) is the pixel value at the point (x, y) in fig. 3;
and 8, repeating the operations of the step 1 to the step 7 on the whole image to complete the processing of the whole image, and obtaining the image shown in the figure 3.
Although there is not much salt and pepper noise in fig. 3, the image becomes smoother and the contrast of salt and pepper noise becomes weaker than that in fig. 2. And the visual effect of the processed image is improved to a certain extent. Fig. 4 is a comparison graph of actual effects. It is evident from this figure that the right processed image has a better visual effect than the left.
Claims (2)
1. A method for inhibiting salt and pepper noise based on an image dithering technology is characterized by comprising the following steps:
step 1, inputting a pixel value G (x, y) of a certain point of an obtained image, wherein x is the row number of the image where the point pixel is located, and y is the column number where the point pixel is located;
step 2, determining the number n of pixel bits according to the pixel value of the point pixel, and assigning the pixel value corresponding to the H bit from high to low to the first temporary storage amount A;
step 3, enabling L to be n-H, enabling L to be the low-order bit number which is not recorded by the first temporary storage amount A, and assigning a pixel value corresponding to L to the second temporary storage amount B;
step 4, let I ═ random (L), I is-2L-1～2L-1Random integers in between;
step 5, enabling B to be B + I;
and 6, carrying out boundary check on the B value obtained in the step 5: if B is present<0, then let B equal to 0; if B is present>2LIf B is 2L(ii) a If B is more than or equal to 0 and less than or equal to 2LIf the value of B is not changed;
step 7, assigning a new pixel value f (x, y) to the pixel at the (x, y) point as a + B;
and 8, repeating the operations of the steps 1 to 7 on the whole image to finish the image processing.
2. The method for suppressing salt and pepper noise based on the image dithering technique as claimed in claim 1, wherein the pixel value in step 1 is R, G, B component values or gray scale values.
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| CN104809701A (en) * | 2015-04-16 | 2015-07-29 | 南京航空航天大学 | Image salt-and-pepper noise removal method based on mean value in iteration switch |
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| CN105719257A (en) * | 2016-01-28 | 2016-06-29 | 河南师范大学 | Method for removing super-high-density salt-and-pepper noises of image |
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| CN1738353A (en) * | 2005-08-16 | 2006-02-22 | 北京交通大学 | Digital watermark technology for resisting rotary extension and displacement attack |
| CN104809701A (en) * | 2015-04-16 | 2015-07-29 | 南京航空航天大学 | Image salt-and-pepper noise removal method based on mean value in iteration switch |
| CN104915938A (en) * | 2015-07-02 | 2015-09-16 | 中国人民解放军国防科学技术大学 | Restoration method for image with high density impulse noise pollution |
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