README: SM3A ERO observation of NGC 2392 This directory contains the drizzled images created for the SM3A ERO obervation of NGC 2392. The images are: Image File Drizzle Weight File Filter Exposure Time (s) F469N.fits F469Nw.fits F469N 1400 F502N.fits F502Nw.fits F502N 400 F656N.fits F656Nw.fits F656N 400 F658N.fits F658Nw.fits F658N 1400 The nebula was centered on chip3 of the WFPC2, and only this image (of the four group image) was processed. The flat used in this analysis was created before the servicing mission. The "delta" dark, used to correct pixels signficantly different from those in the "super" dark, was created from dark images taken with 24 hours of the ERO observations. Each final image was created from four dithered images, where the dither pattern was the standard WFPC2 four-point "box" dither. The weight files used in drizzling had values equal to either 0 or the exposure time of the input image, depending on whether a particular pixel was masked. As the image did not closely approach the edge of the chip, and the shifts of the "box" pattern are relatively small, no weighting for the curvature of the flat was used. Cosmic rays and other image defects were located and masked using the techniqe described in the Fruchter and Hook drizzling paper (see link in parent directory). The final output images have a pixel scale one-half that of the original WFPC2 images, or about 0."05. The user of these images should remember that because the noise in drizzled images is correlated, the true image noise over an area of N (>>1) pixels is greater than root(N) times the image r.m.s. In particular, with the drizzle parameters used here, scale=0.5 and pixfrac=0.6, the final the true image noise is about 1.66 times greater than that predicted by root(N). Note for users wishing to work on individual images: The dark calibration image used to process this data has been placed in the archive. It is now the "recommended" darkfile for these datasets, and will be used in calibration-on-the-fly processing by the archive of these datasets.