Film grain, integral to analogue cinema's aesthetic, challenges video distribution in low-bitrate scenarios, often compromising its authenticity due to compression constraints. AV1 film grain synthesis technology addresses this by separating and estimating film grain parameters during encoding, which are then used to reconstruct grain during decoding. However, the choice of film grain block size impacts the quality of reconstruction, with larger blocks potentially introducing noticeable repetitive noise. We propose a novel perceptual quality assessment method to detect and penalize these repetitive patterns. By leveraging the human visual system's masking effect, our method normalizes decoded frames and assesses local cosine similarities with the film grain template to identify and quantify noise patterns. Implemented in the frequency domain, it processes high-resolution videos efficiently (around 2 FPS for UHD frames). Subjective experiments with expert viewers confirm high correlations (SRCC = 0.853, PLCC = 0.856) between our method and human judgments, validating its effectiveness in preserving film grain authenticity.