Hyperspectral sensors can acquire the radiance of a scene in a high resolution both in spatial and spectral dimensions, which produces good benefits for oil spill detection. Because the cloud background in hyperspectral scene severely interfere oil spill detection result, a new method is presented to reduce the cloud background in hyperspectal scenes. Firstly, the spectral reflectance characteristics of oil spill are analyzed. According to the spectral characteristics of the C-H bond of oil spill, the false color generation based oil spill detection method is introduced. Secondly, the radiance characteristics of seawater, oil spill and cloud is compared. Based on the radiation characteristics of cloud, a new model is build to extract the radiance features of cloud. On this basis, the difference of cloud and seawater, and oil spill are considered. And the band image which has maximum cloud radiance is selected. The cloud background suppression map is then generated by using the band image and the radiance feature of the cloud background. Finally, the background suppression result is obtained by multiplying the false color image by background suppression map. The proposed method is applied to the real Airborne Visible InfraRed Imaging Spectrometer hyperspectral image captured during the Deepwater Horizon oil spill in the Gulf of Mexico for oil spill detection. The results show that the proposed method can effectively suppress the cloud background for oil spill detection from hyperspectral data, and does not affect the oil spill detection performance.