［Purposes］To reduce the accuracy influence that machine vision identifies soil species under the different imaging conditions, a soil image is adjusted to approximate closely a real soil image that is captured under specific natural illumination and its brightness is rated. A controlled brightness enhancement is proposed for soil images which are collected in the field environment. ［Methods］Firstly, asymmetric generalized Gaussian curve is utilized to fit the V component histogram of the soil images, and the target migration value is introduced into the fitted curve to accomplish the brightness migration of images, which realizes the brightness controllable enhancement of soil images based on the global. Then the global and local information are applied to estimate the brightness weight of an image in the spatial region. According to the weight and a given target brightness, the local increment is determined and superimposed to the original V component of the soil image to achieve its brightness enhancement. Next, the global brightness migration result of asymmetric generalized Gaussian curve is fused with the brightness enhancement result based on the local increment by taking advantage of the sigmoid curve. Finally, in accordance with the principle of color ratio invariance, the R, G and B components of the original soil image are corrected separately. ［Results］Experiment results demonstrate that the brightness absolute difference average of corresponding pixel between the enhanced image and the target image on the V component is 10.526 7, and its arithmetic mean is 0.245 1. The above indicators are 10.743 0 and 0.272 1 respectively when weakening brightness. The proposed algorithm can control image brightness with higher accuracy than other algorithms. Subjective evaluation illustrates that the effective range of soil image brightness enhancement is ［-30,30］. ［Conclusions］The simulation result proves that proposed method is effective for controllable brightness enhancement of soil image.