Advanced Remote Sensing, Inc. (ARSI) has developed Closed-form Method for Atmospheric Correction, (CMAC) to serve the smallsat image industry. The satellite image market is exploding through smallsats of restricted size and weight for economical launch in flocks. Thousands of satellites will generate hundreds of thousands of images daily that will require automated evaluation with artificial intelligence, at least as a first step to digest and interpret the data. Clear data generates clear results, but this utility is impeded by the variable content of suspended particles and water vapor that reflected light must pass through on its way from Earth to satellite that degrades the data. All satellite imagery requires atmospheric correction to clear haze and thin clouds from images and restore the data to surface reflectance. Until recently, existing methods could not directly correct smallsats, instead requiring cross-calibration with one of several very large and expensive satellites. This step assures data cannot be corrected in near real time and adds another layer of error. ARSI was formed to develop CMAC, not using any of the existing methods, but with an entirely different, empirically-derived method based on several critical observations of the behavior of light. To correct an image, CMAC first maps a grayscale of the atmospheric effect from scene statistics to adjust the correction; the brighter the grayscale the greater the correction. The grayscale is then translated into two inputs to an equation that reverses the atmospheric effect to deliver surface reflectance in a fraction of the runtime of existing methods without waiting hours to days for ancillary data from other satellites – Recon delivered when it's needed. CMAC software yields results that are more accurate across a wider window of atmospheric effect in near real-time. Sensor drift, notorious in orbit, is calibrated out in as few as one overpass: new satellites require no harmonization .