Light-field and plenoptic cameras are widely available today. Compared with monocular cameras, these cameras capture not only the intensity but also the direction of the light rays. Due to this specificity, light-field cameras allow for image refocusing and depth estimation using a single image. However, most of the existing depth estimation methods using light-field cameras require a prior complex calibration phase and raw data preprocessing before the desired algorithm is applied. We propose a homography-based method with plenoptic camera parameters calibration and optimization, dedicated to our homography-based micro-images matching algorithm. The proposed method works on debayerred raw images with vignetting correction. The proposed approach directly links the disparity estimation in the 2D image plane to the depth estimation in the 3D object plane, allowing for direct extraction of the real depth without any intermediate virtual depth estimation phase. Also, calibration parameters used in the depth estimation algorithm are directly estimated, and hence no prior complex calibration is needed. Results are illustrated by performing depth estimation with a focused light-field camera over a large distance range up to 4 m.