In order to solve the problems of uneven illumination and loss of details in the images of large crude oil tanks and chimneys, a new low illumination image enhancement algorithm is proposed in this paper, which combines homomorphic filtering and CLAHE technology. First of all, a new homomorphic filter transfer function based on Sigmoid function is adopted to improve the adjustment efficiency of the algorithm, and the local mean square error is introduced to highlight the local contour details. Then, the improved homomorphic filter is weighted and fused with CLAHE algorithm to improve the local contrast of the image and avoid noise amplification. Finally, by converting the image from RGB space to HSV space, a Gaussian pyramid is established for V-channel, and the fusion algorithm is used to deal with image features at different levels to achieve image smoothing and sharpening. We also stretch the S-channel linearly to solve the problem of color undersaturation of the image, and finally convert the image back to RGB space to get the final enhanced image. Through experimental simulation on ExDark data set and self-built sludge data set, and combined with quantitative and qualitative analysis, compared with other algorithms such as CLAHE algorithm and Retinex, this algorithm not only improves the overall brightness of the image, but also highlights the local details, which makes the visual feeling of the image clearer. There are also significant improvements in objective indicators, such as average gradient, contrast and peak signal-to-noise ratio.