This paper addresses the problem of joint decoding of stereo JPEG image pairs. Such images typically contain a high degree of redundancy. Predictive coding could efﬁciently capture this redundancy, but cameras would have to implement proprietary encoding solutions in this case as no such standard technology is available. We propose to rather use the popular JPEG compression tools in the cameras, and focus on the joint decoding problem for quality enhancement. We formulate this as a constrained optimization problem and show how regularization leads to more consistent results. It is similar to a distributed source coding framework, where the exploitation of the correlation at the decoder permits to save on the overall bandwidth. Experiments on natural stereo images show an improvement in both visual quality and PSNR when compared to separate decoding.