As a non-contact, couplant-free and nondestructive technique, the laser ultrasonic technology has great potential for detecting surface defects. However, the conventional approach of surface defect imaging is dependent on a single sensitive frequency and susceptible to the interference from boundary reflected wave. To this end, we propose a surface defect identification method based on the frequency-wavenumber analysis of broadband Rayleigh wave in an area scanning mode. Firstly, a particular low-pass filter is constructed in frequency-wavenumber domain to extract the scattered wave generated by the defects, and then a surface defect image can be reconstructed based on the broadband scattered wave wavenumber. Secondly, a threshold denoising method is employed to enhance the sharpness of imaging from scanning noise floor. Thirdly, the experimental validation is carried out, in which a laser ultrasonic detection system is used to detect the surface defects of aluminum alloy specimens and identify their different parameters. The experimental results verify that the proposed method can identify the location, size and orientation of surface defects effectively, meanwhile, its imaging effect shows significantly superior to that of the reflected wave energy and standing wave energy methods. Furthermore, the correlation between maximum imaging index value and the depth of defects is found, which can characterize the severity of the surface defects.