# VIIRS Day/Night Band--Correcting Striping and Nonuniformity over a Very Large Dynamic Range
## 1 Introduction  
The Day/Night Band (DNB) on the Visible Infrared Imaging Radiometer Suite (VIIRS) is part of Suomi National Polar-orbiting Partnership (S-NPP) satellite launched on 28 October 2011. The DNB is a panchromatic visible to near infrared band designed to detect radiance from the brightest daytime scenes down to very dim nighttime scenes illuminated by quarter moon. Its dynamic range comprises over seven orders of magnitude. The sensitivity of the DNB to very low radiance levels requires cross-calibration over three gain stages, and this makes maintaining uniformity on DNB much more difficult than for other bands on VIIRS. Other than uniformity, based on post-launch characterization, VIIRS DNB has met its radiometric and spatial resolution requirements [1]. Since the launch of S-NPP, the low-light detection capabilities of VIIRS DNB have opened new areas of research including the detection of nightglow and features illuminated by nightglow [2; 3] and development of long-term climate data records. Because of these new areas, the required quality of DNB data has been pushed beyond the originally intended design limits. Therefore, striping and other nonuniformities have become limiting factors in these new areas of research [4]. Reducing these artifacts would extend the usefulness of the DNB in these new areas. Striping is usually caused by detector-to-detector response that is not corrected by calibration. Banding occurs when there are differences in response for all detectors among scans, and for the DNB in particular, between aggregation zones. Figure 1 shows an example of the DNB striping and banding problems. This is a nighttime image from 23 October 2015 when the moon is waxing with phase about half way between the first quarter and full. It is of Hurricane Patricia at about the time it became the strongest Pacific hurricane on record. Unfortunately, in this image the eye of the hurricane is near the edge of the VIIRS swath where the DNB striping is typically the most extreme. At right weather analysts mostly depend on thermal-emissive infrared imagery to evaluate hurricanes and storms, but these images lack the texture and fine structure that Reflective Solar Band (RSB) images provide particularly with regard to low cloud fields which often provide insight to the structure of low-level circulation. The VIIRS DNB is one of the only instruments for which such nocturnal information is available, and so provides a very important insight when available. This example illustrates the magnitude of striping due to gain errors. Note the vertical banding just to the right of the hurricane's eye. This feature is prominent in most nighttime DNB imagery, and correcting this will be discussed later in this paper. This paper considers striping and other nonuniformities in the VIIRS DNB imagery on S-NPP. It considers the current methods of calibration, as well as recent changes, and diagnoses the root cause of residual striping that remains after calibration. It also presents a methodology for eliminating most nonuniformity for daytime, twilight and nighttime. We previously published results demonstrating destriping for imagery using the Moment Matching (MM) method, but this correction was limited to nighttime scenes with limited dynamic range [5]. Here we demonstrate for the first time destriping over the entire dynamic range of the DNB using the Histogram Matching Method (HMM). Examples of HMM applied to a variety of scenes and degrees of striping severity are shown. Because of the huge dynamic range of the DNB, there are special ensemble filtering processes required to enhance the standard procedures used for HMM that will be presented in this paper. Figure 1: Nighttime scene of Hurricane Patricia with striping from 23 October 2015 at 07:45 UTC over the Pacific Ocean west of Mexico during a waxing gibbous moon. The radiances are plotted on a linear scale over the range of 0 to \(6\times 10^{-9}\) W\(\cdot\)cm\({}^{-2}\cdot\)sr\({}^{-1}\) from black to white. The 500 by 700 pixels image is at left edge start of scan.