1. A computer-implemented method comprising: receiving, by a computer system, a first image and a second image that both depict a scene; identifying, by the computer system, first image patches from the first image and second image patches from the second image; iteratively evaluating, by the computer system, each of the first image patches over multiple depth hypotheses, wherein the iterative evaluation comprises, for each depth hypothesis and each of the first image patches: identifying a first blur kernel that is dependent on the depth hypothesis and a first configuration setting used to capture the first image, identifying a second blur kernel that is dependent on the depth hypothesis and a second configuration setting used to capture the second image, and determining a depth likelihood for the depth hypotheses based on convolving the image patch with the second blur kernel and convolving a respective one of the second image patches with the first blur kernel; determining, for each of the first image patches, a depth estimate for the image patch based on one of the depth hypotheses for which the iterative evaluation generates a maximal depth likelihood; and generating, by the computer system, a depth map using the depth estimate for each image patch.