Abstract: Image noise is the main factor affecting the accuracy of monocular vision positioning. Based onbidimensional empirical mode decomposition (BEMD) and threshold denoising, an interval threshold imagenoise filtering method based on bidimensional ensemble empirical mode decomposition (BEEMD) isproposed. The image is decomposed into multiple bidimensional intrinsic mode function (IMF) componentsand one residual component of different scales by BEEMD. The pure noise IMF components are eliminatedaccording to the 2-norm criterion and the probability density function method of image and IMFcomponents, the reasonable regulatory factor α is selected, and the image denoising is realized by theimproved interval threshold denoising method. The proposed algorithm is applied to monocular visionand compared with the BEMD algorithm. The results show that the method could not only effectivelysuppress the modal aliasing problem in BEMD, but also effectively reduce the influence of image noise, so theaccuracy and reliability of monocular vision are improved.