With the industrial need of laser cleaning, new requirements are put forward for the cleanliness evaluation of material surfaces before and after cleaning. In this paper, the bidirectional reflection technology of surface roughness measurement is proposed to characterize the surface quality of materials, and the autocorrelation length (T) and the root mean square of surface roughness(σ) are taken as the key parameters to characterize the surface quality of samples. Based on the Beckmann-Kirchhorff integral scattering model and after a reasonable simplification on rough surfaces, we plot the ratio I_s/I₀ of the incident light intensity (I₀) to the reflected light intensity (I_s) versus the inverse square of wavelength (1/λ²). Under the simplified model, an ideal linear curve can be obtained in the vertical incident direction with a large g value. The parameter σ_g obtained by linear fitting can be used as the characterization value of surface cleanliness. In the experiment, a beam of white light (xenon lamp) is first used to irradiate the surface of the titanium alloy sheet TA15 sample at a vertical angle, and then the specular reflected light beam on the surface of the sample is collected. The experimental results confirm the correlation between the surface quality of the sample and the σ_g value. This method is a non-contact spectral detection method, which can realize high-speed scanning, is convenient and fast, and can be used to online judge the cleanliness after laser cleaning in practical work.