The discrete Fourier transform is extensively applied in spectrum analysis. However, the sampled signal is random, and the discrete Fourier transform has its own specific limitations. Thus, errors will inevitably occur in time–frequency transformation work. The most common are the leakage effects of the spectrum that are caused from the scale of the spectrum not being able to match the characteristics of the signal. The optimal spectrum is proposed to overcome this defect by adjusting the frequency scale to fit signal characteristics. This includes three stages whereby frequency scale can match signal characteristics. Firstly, the signal parameters must be found. Secondly, the frequency scale can be determined from these signal parameters. Finally, the optimal spectrum can be realized using the adjustable spectrum with the new frequency scale. After processing the optimal spectrum, the leakage effects of the signal will be decreased to a minimum. This method preserves signal characteristics in the optimization process, which reaches the ideal of non-distortion.