The space-time image velocimetry (STIV) is a time-averaged velocity measurement method,which takes a testing line as the interrogation area (IA), and detects the main orientation of texture (MOT) of a generated space-time image ( STI) to estimate the 1D velocity. It has the characteristics of high spatial resolution and real-time. In practical applications, the detection accuracy of MOT is inevitably affected by environmental disturbances such as turbulence, shadow, flare, obstacle, and rain on river surface, which result in gross errors in the measurement. The image filtering technology in frequency domain is an effective method for restraining noise, which can significantly improve the texture clarity of STIs. However, the existing researches are insufficient in the sensitivity analysis of filter parameters, which limit the applicability of this method. In view of this, the video data of river surface under different conditions are collected by establishing an online video-based flow measurement system at a hydrological station. The spatial and frequency domain characteristics of STIs in six typical scenarios are analyzed. The sensitivity of three parameters of a fan filter in frequency domain, including direction angle, passband angle and radius is determined. Experimental results show that the proposed ellipse integral region is better than the existing single-pixel-wide line to detect direction angle. When the passband angle is set to be ±5. 3° and the radius is R/ 2, the filter can effectively filter out the noise interference in the above scenarios. The detection accuracy of MOT reaches 0. 1° in the normal scene and is controlled within 0. 5° in the complex noisy scene. The relative error of the surface flow velocity measurement is less than 6. 2% .