The HaiYang-1C (HY-1C) satellite is China’s first operational ocean color satellite. The Coastal Zone Imager (CZI) aboard on the HY-1C satellite, which has the advantages of wide range and short revisit period, has been widely used for large-scale ocean and coastal zone observation. As an optical sensor, CZI is seriously affected by clouds. The accurate detection of clouds is crucial for CZI data processing and application. However, CZI lacks cloud-sensitive bands such as infrared and short-wave infrared, which makes cloud detection difficult. So, this paper proposes a cloud detection method that combines multi-scale convolution and side window filtering. The multi-scale convolution is used to extract different scale features of clouds and the side window filtering is used to enhance the edge features and reduce the influence of image noise. The experimental results show that the proposed method can effectively detect cloud and performs well in cloud edge extraction, with F1-score of 92.77% and Kappa of 0.89. Compared with the currently existing cloud detection algorithms, the proposed method has obvious advantages of fast model training speed and less parameters, which will provide support for HY-1C CZI remote sensing image processing.