CN116883279B - Short wave infrared image enhancement method with low noise and high real-time performance - Google Patents
Short wave infrared image enhancement method with low noise and high real-time performance Download PDFInfo
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- CN116883279B CN116883279B CN202310848753.7A CN202310848753A CN116883279B CN 116883279 B CN116883279 B CN 116883279B CN 202310848753 A CN202310848753 A CN 202310848753A CN 116883279 B CN116883279 B CN 116883279B
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- 238000002054 transplantation Methods 0.000 abstract description 3
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
Abstract
The invention relates to the technical field of image processing, in particular to a short wave infrared image enhancement method with low noise and high real-time performance; in the method, 3*3 convolution processing is firstly required to be carried out on an image to be enhanced, then the average value and the Q value of other 8 point pixels except for a central point are calculated, finally the central point pixel value is compared with the average value, and the central point pixel value is recalculated and updated in a state of being larger than the average value and smaller than the average value respectively; the processing method adopted in the scheme can realize variance statistics in the region, further realize edge enhancement sharpening, ensure the high efficiency of an image enhancement algorithm, ensure a simpler operation process and meet the condition of easy hardware transplantation.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a short wave infrared image enhancement method with low noise and high real-time performance.
Background
Such enhancement features are known as image enhancement processes in order to make an image with some information more vivid, prominent, while weakening or removing some useless information. This process can improve the visual effect on the one hand and also facilitate machine analysis of the image on the other hand. Image enhancement techniques are widely used in the fields of medical imaging, remote sensing imaging, person photography, and the like.
The short-wave infrared image has the image characteristics of both visible light and infrared thermal imaging, and the traditional enhancement algorithm can cause the problems of noise increase of the short-wave infrared image, relatively insufficient sharpness of edges, low algorithm hardware transplanting instantaneity and the like.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a short wave infrared image enhancement method which has high real-time performance and low noise and high real-time performance and is easy for hardware transplantation.
In order to solve the technical problems, the technical scheme provided by the invention is as follows: the short wave infrared image enhancement method with low noise and high real-time performance comprises the following steps:
(1) Performing 3×3 convolution processing on the image to be enhanced to form a 3×3 pixel matrix, and defining a center point pixel as x 22 Defining other 8 points as x respectively 11 、x 12 、x 13 、x 21 、x 23 、x 31 、x 32 、x 33 ；
(2) Calculating an average avg of 8 point pixels except the center point;
(3) Calculating Q values of 8 point pixels except the center point;
(4) Comparing 3×3 pixels of the center point of the pixel matrix 22 The value of (2) and the avg value calculated in the step (2), if x 22 >avg, the center pixel value x of the 3×3 pixel matrix 22 Updated to x 1 _new 22 WhereinIf x 22 <avg, the center pixel value x of the 3×3 pixel matrix 22 Updated to x 2 _new 22 Wherein-> If x 22 =avg, then remain unchanged;
(5) Complete the pair x 22 Is updated and displayed in the image.
Further, in step (2), the calculation formula of the average avg is:
further, in the step (3), the calculation formula of the Q value is:
compared with the prior art, the scheme has the remarkable advantages that: the processing method adopted in the scheme can realize mean value and average deviation statistics in the region, further realize enhanced sharpening of the edge, ensure the high efficiency of the image enhancement algorithm, and ensure that the operation process is simpler and meets the condition of easy hardware transplantation.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of steps in an embodiment of the present invention;
fig. 2 and 3 are schematic diagrams of the other two embodiments and the enhanced schematic diagrams.
Detailed Description
The following description of preferred embodiments of the present invention is provided in connection with the accompanying drawings, and it is to be understood that the preferred embodiments described herein are for the purpose of illustration and explanation only and are not intended to limit the invention thereto.
As shown in FIG. 1, the method for enhancing the short-wave infrared image with low noise and high real-time performance comprises the following steps:
(1) Performing 3×3 convolution processing on the image to be enhanced to form a 3×3 pixel matrix, and defining a center point pixel as x 22 Defining other 8 points as x respectively 11 、x 12 、x 13 、x 21 、x 23 、x 31 、x 32 、x 33 ；
(2) The average value avg of the 8 point pixels except the center point is calculated, and the calculation formula of the average value avg is as follows:
(3) The Q values of the pixels of 8 points except the center point are calculated, and the calculation formula of the Q values is as follows:
(4) Comparing 3×3 pixels of the center point of the pixel matrix 22 The value of (2) and the avg value calculated in the step (2), if x 22 >avg, the center pixel value x of the 3×3 pixel matrix 22 Updated to x 1 _new 22 WhereinIf x 22 <avg, the center pixel value x of the 3×3 pixel matrix 22 Updated to x 2 _new 22 Wherein-> If x 22 =avg, then remain unchanged;
(5) Complete the pair x 22 Is updated and displayed in the image.
In the above technical solution, after excluding the center point, the Q value is a weight value of whether the 3×3 matrix is a smooth area or has edges or transition areas, the smaller the value is, the smoother the image is, and the larger the value is, the more edges or transition information the image has.
The whole scheme can be summarized as that the absolute difference (namely Q value) fluctuation between 8 surrounding neighborhood points and a neighborhood mean value is calculated, the fluctuation value is an effective criterion for judging whether a central point is an edge point, for example, if the fluctuation value is larger than 5, the fluctuation point is an effective edge point or a transition zone of an image convolution matrix, the difference between a current point and the surrounding points is judged through the value, the difference between the point and the surrounding points is amplified through a formula, the edge is more obvious, and the value is also determined according to hardware background noise.
As shown in fig. 2 and 3, the effects of the present embodiment are original figures and enhanced by the present embodiment.
Finally, it should be noted that: the foregoing is merely a preferred example of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. The short wave infrared image enhancement method with low noise and high real-time performance is characterized by comprising the following steps of:
(1) Performing 3×3 convolution processing on the image to be enhanced to form a 3×3 pixel matrix, and defining a center point pixel as x 22 Defining other 8 points as x respectively 11 、x 12 、x 13 、x 21 、x 23 、x 31 、x 32 、x 33 ；
(2) Calculating an average avg of 8 point pixels except the center point;
(3) Calculating Q values of 8 point pixels except the center point;
(4) Comparing 3×3 pixels of the center point of the pixel matrix 22 The value of (2) and the avg value calculated in the step (2), if x 22 >avg, the center pixel value x of the 3×3 pixel matrix 22 Updated to x 1 _new 22 WhereinIf x 22 <avg, the center pixel value x of the 3×3 pixel matrix 22 Updated to x 2 _new 22 Wherein-> If x 22 =avg, then remain unchanged;
(5) Complete the pair x 22 Is updated and displayed in the image;
in step (2), the calculation formula of the average avg is:
in the step (3), the calculation formula of the Q value is:
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| CN104580826A (en) * | 2015-02-03 | 2015-04-29 | 成都金本华科技股份有限公司 | Video signal processing method for improving image sharpness |
| CN108230258A (en) * | 2017-11-15 | 2018-06-29 | 浙江工业大学 | A kind of license plate area Enhancement Method calculated based on horizontal neighbors standard deviation |
| CN111105371A (en) * | 2019-12-10 | 2020-05-05 | 南京莱斯电子设备有限公司 | Low-contrast infrared image enhancement method |
| CN114298916A (en) * | 2021-11-11 | 2022-04-08 | 电子科技大学 | X-Ray image enhancement method based on gray stretching and local enhancement |
Family Cites Families (1)
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| EP1889223A1 (en) * | 2005-06-07 | 2008-02-20 | Thomson Licensing | Content-based gaussian noise reduction for still image, video and film |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1892696A (en) * | 2005-07-08 | 2007-01-10 | 深圳迈瑞生物医疗电子股份有限公司 | Supersonic image edge-sharpening and speck-inhibiting method |
| CN104580826A (en) * | 2015-02-03 | 2015-04-29 | 成都金本华科技股份有限公司 | Video signal processing method for improving image sharpness |
| CN108230258A (en) * | 2017-11-15 | 2018-06-29 | 浙江工业大学 | A kind of license plate area Enhancement Method calculated based on horizontal neighbors standard deviation |
| CN111105371A (en) * | 2019-12-10 | 2020-05-05 | 南京莱斯电子设备有限公司 | Low-contrast infrared image enhancement method |
| CN114298916A (en) * | 2021-11-11 | 2022-04-08 | 电子科技大学 | X-Ray image enhancement method based on gray stretching and local enhancement |
Non-Patent Citations (1)
| Title |
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| 基于局部均值和标准差的图像增强算法;马银平，江伟;《计算机工程》;第35卷(第22期);第205-207页 * |
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