The retrieval precision of atmospheric turbulence intensity profile is affected directly by the signal noise from differential light column image motion lidar. A valid denoising method can improve the detection performance of lidar. To reduce the dependence of the combined denoising method with wavelet-empirical mode decomposition (EMD) on wavelet, an adaptive modulation strategy with the signal trend term is proposed for wavelet denoising signal, and then the modulated signal is denoised by EMD, which is called wavelet-trend-EMD method. The trend term is still extracted by EMD. To ensure the validity of modulation, a decision criteria of modulation suitable for coherent length (r0) profile is presented, and the detrended fluctuation analysis is carried out to identify the EMD denoising threshold adaptively. To illustrate the validity of the proposed method, four other methods of wavelet, EMD, ensemble empirical mode decomposition (EEMD) and wavelet-EMD are used for comparison. The numerical simulation and experimental results indicate that all the five methods can improve the signal-to-noise ratio of r0 profile and the retrieval precision. The two joint methods are better than the single method and the wavelet method is superior to EMD and EEMD methods. More importantly, wavelet-trend-EMD further improves the denoising ability of wavelet-EMD, which provides a new improvement consideration for the joint method of Wavelet-EMD.