Abstract: Aiming at the quality degradation problems such as low brightness and contrast, non-uniform illumination of images captured in real environments, a non-uniform low illumination image enhancement algorithm based on Retinex theory was proposed. Firstly, the original image was converted from RGB(red, green, blue) space to HSV(hue, saturation, value) space by the algorithm, and the V-component was extracted for enhancement processing. The Retinex decomposition was implemented by the algorithm through combined window filtering, with side window filtering and full window filtering being used for the edge and texture of the image respectively to obtain a locally smooth and structure-preserving illuminance component. For the illuminance component, a luminance transformation method based on the quadratic curve is used for indirect adjustment to effectively enhance the low illuminance and correct the non-uniform illuminance. For the reflection component, hybrid filtering was used to suppress noise and sharpen edge details. Finally, the enhanced illumination component and reflectance component were recombined to obtain the enhanced V-component, and then converted back to RGB space to obtain the final enhanced image. The experimentalresults show that the NIQE(natural image qualityevaluator), NIQMC(no-reference image quality metric), CEIQ(content-enhanced image quality) and Entropy metrics for this method are 2.747, 5.380, 3.432 and 7.476, respectively, which are superior to most existing image enhancement algorithms. The proposed algorithm not only enhances the brightness and contrast, but also effectively corrects the non-uniformity of image illumination, making the visual effect clearer and texture details richer.