Soil image brightness controllable enhancement method based on double Gaussian fitting

Abstract

The invention provides a soil image brightness controllable enhancement method based on double Gaussian fitting, and the method comprises the following steps: taking a main peak point of a soil image Y component histogram as a segmentation point, and dividing the soil image Y component histogram into a left histogram and a right histogram, turning over the left histogram and the right histogram by taking a straight line which passes through the main peak point and is parallel to the longitudinal axis of the Y-component histogram coordinate system as a symmetric axis to obtain symmetric broken lines of the left histogram and the right histogram; performing Gaussian fitting on the original left histogram, the symmetric broken line corresponding to the original left histogram and the symmetric broken line corresponding to the original right histogram to form two Gaussian curves; a Gaussian curve segment corresponding to the original left histogram and a Gaussian curve segment corresponding to the original right histogram are taken from the two Gaussian curves to form a double-Gaussian fitting curve of the soil image Y component histogram; carrying out brightness migration processing on the double-Gaussian fitting curve, and then carrying out gray mapping processing to obtain a brightness gray level after brightness migration; and performing mapping correction on the brightness gray level to obtain a Y component of the soil image after brightness controllable enhancement, and fusing the Y component of the soil image with the U component and the V component of the original soil image to obtain a final brightness controllable soil image.

Description

technical field [0001] The invention relates to an image processing method, in particular to a soil image brightness controllable enhancement method based on double Gaussian fitting. Background technique [0002] Soil image recognition is used for soil research and analysis. In the prior art, soil images are generally collected by machine vision. However, when soil images are collected, they are generally operated in the field and are affected by climate and location. Field machine vision collection It is impossible for soil images to maintain the same natural lighting conditions, which makes the lighting conditions reflected in the images inconsistent, which seriously affects the subsequent soil species identification processing. At present, there is no effective means to solve the above problems. SUMMARY OF THE INVENTION [0003] In view of this, the purpose of the present invention is to provide a soil image brightness controllable enhancement method based on double Gau...

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Problems solved by technology

[0002] Soil image recognition is used for research and analysis of soil. In the prior art, machine vision is generally used to collect soil images. However, when soil images are collected, they are generally in the field. Affected by climate and location, field machine vision It is impossible for the soil image to maintain the same natural lighting conditions, so that the lighting conditions reflected in the image are inconsistent, which seriously affects the subsequent soil type recognition processing. At present, there is no effective means to solve the above problems

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