An optimal algorithm for reconstructing images from binary measurements

We have studied a camera with a very large number of binary pixels referred to as the gigavision camera [1] or the gigapixel digital film camera [2, 3]. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor response curve, and reduced exposure time in low light conditions, due to its highly sensitive photon detection mechanism. We use maximum likelihood estimator (MLE) to reconstruct a high quality conventional image from the binary sensor measurements of the gigavision camera. We prove that when the threshold T is "1", the negative loglikelihood function is a convex function. Therefore, optimal solution can be achieved using convex optimization. Base on filter bank techniques, fast algorithms are given for computing the gradient and the multiplication of a vector and Hessian matrix of the negative log-likelihood function. We show that with a minor change, our algorithm also works for estimating conventional images fr...

• Type: Conference
• Year: 2010
• Where: CIMAGING
• Authors: Feng Yang, Yue M. Lu, Luciano Sbaiz, Martin Vetterli
• Keywords: Binary Images, CIMAGING 2010, Conventional Images, Gigavision Camera, Hardware