A light field camera can simultaneously sample a scene from multiple viewpoints with a single exposure, which has unique advantages in portability and depth accuracy over other depth sensors. Noise is a challenging issue for light field depth estimation. Most of the traditional depth estimation methods for noisy scenes are only suitable for non-occluded scenes, and cannot handle the noisy scenes with occluded regions. To solve this problem, we present a light field depth estimation method based on inline occlusion handling. The proposed method integrates the occlusion handling into the anti-noise cost volume, which can improve the anti-occlusion capability while maintaining the anti-noise performance. After the cost volume is constructed, we propose a multi-template filtering algorithm to smooth the data cost while preserving the edge structure. Experimental results show that the proposed method has better performance over other state-of-the-art depth estimation methods in high noise scenes, and can better handle the occlusion problem of depth estimation in noisy scenes.