Partial discharge ultrasonic signal monitoring is one of the commonly used methods to determine the insulation status of oil-immersed transformers. However, the on-site noise interference is difficult to avoid and often accompanied by white noise. Therefore, a denoising method based on improved variational mode decomposition and wavelet transform is proposed. Firstly, taking the kurtosis-permutation entropy criterion as the objective function, the ant colony optimization is used to determine the optimal decomposition level and penalty factor of the variational mode decomposition, and the noisy partial discharge ultrasound signal is decomposed into multiple intrinsic mode function. Then, the correlation coefficient method is used to divide the multiple intrinsic mode function into noise free function, noise containing function, and noise function. The maximum-minimum permutation entropy criterion is used as the objective function, and the ant colony optimization is used to determine the optimal wavelet threshold and propose an improved wavelet threshold function for wavelet denoising of the noisy function. Finally, the noise free function and the denoised wavelet function are reconstructed to complete the denoising of the partial discharge ultrasound signal. By denoising simulated and measured partial discharge ultrasound signals and comparing with four other denoising methods, the results show that the proposed denoising method has excellent performance. The signal-to-noise ratio and normalized correlation coefficient are average improved by 43.62% and 2.39% respectively compared with other methods, and root mean square error is average reduced by 35.46%.