CN102819833B - Platform histogram equalization method for infrared image - Google Patents
Platform histogram equalization method for infrared image Download PDFInfo
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- CN102819833B CN102819833B CN201110426482.3A CN201110426482A CN102819833B CN 102819833 B CN102819833 B CN 102819833B CN 201110426482 A CN201110426482 A CN 201110426482A CN 102819833 B CN102819833 B CN 102819833B
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Abstract
The invention relates to a platform histogram equalization method for an infrared image and belongs to the technical field of image enhancement. The method comprises the steps of firstly choosing a threshold value of an image input platform and then changing a gray value of an infrared image; and on the basis that the infrared image is fully analyzed to be poor in contrast ratio and weak in hierarchical sense, after the infrared image is subjected to platform threshold value selection, achieving subsection linear drawing histogram equalization process, so that the hierarchical sense of the image is enriched, and the infrared image is enhanced effectively.
Description
Technical field
The present invention relates to a kind of platform histogram equalization method for infrared image, belong to image enhancement technique field.
Background technology
Infrared image is the imaging of scene heat radiation distribution.Because the temperature difference of the object and background in scene is relatively little, so infrared image visual effect is poor, show as image blurring, poor contrast.In order to utilize given gray scale dynamic range the most fully, making infrared image visually have abundanter stereovision, strengthening picture contrast, therefore, propose a kind of infrared image platform improving histogram equalizing method that is used for and improve image quality.
Summary of the invention
The object of this invention is to provide a kind of platform histogram equalization method for infrared image, to solve existing infrared image poor visual effect, the problem of poor contrast.
For achieving the above object, a kind of platform histogram equalization method step for infrared image of the present invention is as follows:
(1) each gray-level pixels number of infrared image is added up;
(2) find out gray level maximal value and minimum value in statistics, and a of minimum value is doubly set to minimum plateau value, the b of maximal value is doubly set to maximum plateau value;
(3) gray-scale value being less than minimum plateau value is set to minimum plateau value, the gray-scale value being greater than maximum plateau value is set to maximum plateau value;
(4) image intensity value is divided into n sub-range;
(5) find out the gray-scale value of each sub-range starting point, terminal, terminal gray-scale value is deducted the product of starting point gray-scale value and variable c;
(6) in value step 5) obtained and this interval, pixel value product deducts this interval threshold value;
(7) value step 6) obtained and threshold value are added with the amassing of variable a.
Further, image intensity value is divided into the equal n of a pixel count sub-range in described step (4).
A kind of platform histogram equalization method for infrared image of the present invention, make full use of given gray scale dynamic range, platform Threshold selection is carried out to infrared image, the process of divided linear strength histogram equalization, make infrared image visually have abundanter stereovision, effectively enhance infrared image contrast.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the embodiment of the present invention;
Fig. 2 is the before treatment former figure of the embodiment of the present invention;
Fig. 3 is the image after the process of the embodiment of the present invention.
Embodiment
Be illustrated in figure 1 the process flow diagram of a kind of platform histogram equalization method embodiment for infrared image of the present invention, step is as follows:
(1) each gray-level pixels number of infrared image is added up;
(2) find out gray level maximal value and minimum value that pixel count is greater than 0, and a of minimum value times (a gets 1.1) is set to minimum plateau value, b times (b gets 0.8) of maximal value is set to maximum plateau value;
(3) gray-scale value being less than minimum plateau value is set to minimum plateau value, the gray-scale value being greater than maximum plateau value is set to maximum plateau value;
(4) n(n image intensity value being divided into pixel count roughly equal is taken as 64) individual sub-range;
(5) find out the gray-scale value of each sub-range starting point, terminal, terminal gray-scale value is deducted the product of starting point gray-scale value and variable c;
(6) in value step 5) obtained and this interval, pixel value product deducts this interval threshold value;
(7) value step 6) obtained and threshold value are added with the amassing of variable a.
Embodiment:
The one proposed for the present invention is used for infrared image platform improving histogram equalizing method, illustrates that concrete steps are as follows with instantiation:
1) as shown in Figure 2, in entire image from first pixel each gray-level pixels number of statistical picture;
2) gray level maximal value and minimum value that pixel count is greater than 0 is found out;
3) a times (between 1.0-1.2, a gets 1.1 to general value here) of the minimum value selecting step 2 to calculate, as minimum plateau value, selects b times (between 0.7-1, b gets 0.8 to general value) of maximal value as maximum plateau value here;
4) gray-scale value being less than minimum plateau value is set to minimum plateau value, the gray-scale value being greater than maximum plateau value is set to maximum plateau value;
5) image intensity value is divided into the roughly equal n of pixel count (n can be taken as the exponential depth of 2, and general n gets 64) sub-range;
6) grey scale pixel value of each interval starting point is obtained;
(2) gamma function conversion process
7) after platform Threshold selection completes, in each interval that step 5) obtains, end point values deducts threshold value and the general value of variable c(between 0.3-1, and c gets 0.8 here) product;
8) in value step 7) obtained and this interval, pixel value product deducts this interval threshold value;
9) value step 8) obtained is divided by this burst length;
10) value step 9) obtained and interval threshold value are added with the amassing of variable a, complete image procossing, as shown in Figure 3.
Claims (2)
1. for a platform histogram equalization method for infrared image, its feature exists, and the step of the method is as follows:
(1) each gray-level pixels number of infrared image is added up;
(2) find out gray level maximal value and minimum value in statistics, and a of minimum value is doubly set to minimum plateau value, the b of maximal value is doubly set to maximum plateau value;
(3) gray-scale value being less than minimum plateau value is set to minimum plateau value, the gray-scale value being greater than maximum plateau value is set to maximum plateau value;
(4) image intensity value is divided into n sub-range;
(5) in a described n sub-range, find out the gray-scale value of each sub-range starting point, terminal, terminal gray-scale value is deducted the product of starting point gray-scale value and variable c;
(6) in value step (5) obtained and this sub-range, pixel value product deducts this interval threshold value;
(7) value step (6) obtained and threshold value are added with the amassing of variable a;
Described a value is between 1.0-1.2, and b value is between 0.7-1, and the value of described c is between 0.3-1.
2. method according to claim 1, is characterized in that: in described step (4), image intensity value is divided into the equal n of a pixel count sub-range.
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| CN201110426482.3A CN102819833B (en) | 2011-12-19 | 2011-12-19 | Platform histogram equalization method for infrared image |
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| CN201110426482.3A CN102819833B (en) | 2011-12-19 | 2011-12-19 | Platform histogram equalization method for infrared image |
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| CN102819833B true CN102819833B (en) | 2015-06-03 |
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Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103065281A (en) * | 2011-12-17 | 2013-04-24 | 中国航空工业集团公司洛阳电光设备研究所 | Short wave infrared image intensification method and device based on field programmable gate array (FPGA) |
| CN104268840A (en) * | 2014-09-30 | 2015-01-07 | 成都市晶林科技有限公司 | Method for enhancing infrared image histogram redundancy elimination and gray level equal interval mapping |
| CN105354814A (en) * | 2015-08-17 | 2016-02-24 | 电子科技大学 | Infrared image segmentation method |
| CN105959584B (en) | 2016-04-29 | 2019-01-22 | 京东方科技集团股份有限公司 | A kind of image processing method, image processing apparatus and display device |
| CN107689212A (en) * | 2017-09-14 | 2018-02-13 | 遵义师范学院 | A kind of current limit algorithm of low-power consumption high image quality |
| CN109584175B (en) | 2018-11-21 | 2020-08-14 | 浙江大华技术股份有限公司 | Image processing method and device |
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| CN101620727A (en) * | 2009-08-10 | 2010-01-06 | 电子科技大学 | Self-adaptive enhancement algorithm of weighted histogram of infrared image |
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| US8218868B2 (en) * | 2007-06-13 | 2012-07-10 | Sensors Unlimited, Inc. | Method and apparatus for enhancing images |
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| CN101620727A (en) * | 2009-08-10 | 2010-01-06 | 电子科技大学 | Self-adaptive enhancement algorithm of weighted histogram of infrared image |
Non-Patent Citations (2)
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| 基于双平台直方图的红外图像增强算法;宋岩峰等;《红外与激光工程》;20080430;第37卷(第2期);308-311 * |
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