Converting a conventional camera to a super-camera: Directional atmospheric scattering modeling for passive imaging in intense real-world scattering scenarios

Passive imaging through intense atmospheric scattering is a critical yet formidable challenge in optical imaging, with profound implications across various applications. Conventional cameras struggle under severe scattering conditions, fundamentally limiting their effectiveness. We propose a groundbreaking directional atmospheric scattering model that revolutionizes passive imaging capabilities, converting a conventional camera to a super-camera. The model precisely characterizes directional photon propagation through scattering media, transforming this historically ill-posed problem into a well-posed solution, based on which a 4D spatial-angular scattering reconstruction method is proposed, which leverages both ballistic photons and directionally resolved scattered light, without relying on any scene-specific priors, to achieve unprecedented passive imaging performance enabling color imaging through over 12 transport mean free paths at distances up to 1.76 km. Our system recovers targets contributing as little as 0.00016% of the total detected signal, enhancing a standard camera's signal recovery capacity by nearly 200×. To validate our approach, we introduce the first-ever real-world multiperspective scattering dataset, providing a critical benchmark for future research. We mark a paradigm shift in passive imaging, offering transformative potential for real-world applications under extreme atmospheric scattering conditions.