Image nonlinearity enhancement method based on histogram subsection transformation

A segmentation transformation and histogram technology, which is applied in the field of image processing, can solve the problems of image contrast enhancement, can not meet the visual characteristics of human eyes, and the image visual effect is stiff, and achieves the effect of increasing magnification and good visual effect.

Inactive Publication Date: 2012-12-19
THE 41ST INST OF CHINA ELECTRONICS TECH GRP
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[0009] The essence of the method of histogram equalization to enhance the image is to reduce the gray level in exchange for an increase in contrast. If the merged gray level constitutes important details, the image enhanced by the histogram equalization algorithm will lose detai

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  • Image nonlinearity enhancement method based on histogram subsection transformation
  • Image nonlinearity enhancement method based on histogram subsection transformation
  • Image nonlinearity enhancement method based on histogram subsection transformation

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[0028] Hereinafter, preferred embodiments of the present invention are given in conjunction with the drawings to illustrate the technical solutions of the present invention in detail. It should be noted that the implementation of the image nonlinear enhancement method based on the histogram piecewise transformation according to the present invention is merely an example, but the present invention is not limited to this specific implementation.

[0029] Such as figure 1 As shown, the image nonlinear enhancement method based on histogram segment transformation of the present invention includes the following steps:

[0030] S1. Calculate the probability density distribution of the image gray level. Assuming that the quantization of the image gray level is 8bit, the image gray range is [0, 255]. If the total pixels of an image are n, there are a total of L gray levels, n k Represents the kth gray level r k The frequency of occurrence, then the probability p of the k-th gray level app...

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Abstract

The invention discloses an image nonlinearity enhancement method based on histogram subsection transformation. The method comprises the following steps of: S1, calculating probability density distribution of image gray levels; S2, calculating accumulated probability density functions of the gray levels; S3, dividing the gray levels of the images into three parts, wherein the first part of gray level range is between 0 and 85, the second part of gray level range is between 86 and 170, and the third part of gray level range is between 171 and 255; respectively calculating gray level transformation functions of the three parts of gray levels according to the accumulated probability density functions, namely proposing sectional gray level transformation functions; and S4, transforming the gray levels of the original images by using the sectional gray level transformation functions to acquire the distribution of new gray levels. By the method, the definition of the image is further improved, the excessive enhancement of the image is avoided, and the image vision effect meets the requirement of an eye vision system.

Description

technical field [0001] The invention relates to image processing technology, in particular to an image non-linear enhancement method based on histogram subsection transformation. Background technique [0002] In multi-spectral information fusion, the infrared sensor is imaged through the thermal radiation of the target scene, and the detail information is not rich and the contrast is low; the visible light sensor is imaged through the reflection of the target scene, the detail information is rich, and the contrast is easily affected by the light. The fusion of infrared and visible light images can make full use of the complementarity of their information and improve the detection ability of the detection system. If the image contrast is low, it will affect the multi-spectral fusion effect. Therefore, low-contrast images need to be enhanced before multispectral fusion. [0003] At present, the most typical spatial domain enhancement algorithm is the histogram equalization a...

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Application Information

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IPC IPC(8): G06T5/40
Inventor 张鹏韩顺利
Owner THE 41ST INST OF CHINA ELECTRONICS TECH GRP
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