View source for Standard THEMIS IR Processing

{{DavinciWiki_Procedure|This procedure is designed to take an [[ISIS]] projected [[THEMIS]] Infrared image and run it through "standard processing", correcting for noises and producing an emissivity array.  [http://themis.asu.edu/files/thmprocdocs/Bandfield.pdf Click here] for a brief description of the standard processing steps, including when and how they should be used.
 
The data output of this should be identical to what can be generated using [http://thmproc.mars.asu.edu thmproc].  

NOTE: The example is shown for data containing 10 bands. If less bands are present, such as in a nighttime image, you can safely skip the autoradcorr step.
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[[drift|Undrift]] and [[wobble|Dewobble]] the unprojected [[RDR]] data.  There are several options to [[uddw]] that require access to the ASU Mars Space Flight Facility Database and file structure. The method described below requires none of these.

 dv>a &#61; uddw("I10418002")
 320x1808x10 array of float, bsq format [23,142,400 bytes]

Remove across track temperature gradients using [[tilt]]. This step could be skipped if the cube is being processed for highly rigorous spectral analysis, but is recommended for typical spectral analysis, DCS, and aesthetics. See Edwards et al. (2011) mosaicking paper for details.
 dv> a.cube &#61; rtilt(a.cube)

NOTE: If processing cold and/or nighttime images, remove the line and row correlated noise  related to the low temperatures before projecting the image.  Residual  [[plaid]] noise can removed after projection by applying thm.deplaid a second time as shown below.
 dv> a.data &#61; thm.deplaid(a.data, tmask_min&#61;0.05, tmask_max&#61;5.5, b10&#61;3)

Project the data using the ISIS projection software 

Read in the ISIS map projected 10 band THEMIS infrared image.  
 dv>a &#61; read("I10418002.irmc.cub")
 ..........577x1852x10 array of float, bsq format [42,744,160 bytes]

Rectify the image, which rotates and slightly warps the projected image into a rectangle for easy manipulation and to minimize storage requirements.
 dv>a &#61; thm.rectify(a)
 struct, 4 elements
    data: 301x1883x10 array of float, bsq format [22,671,320 bytes]
    leftedge: 1x1883x1 array of int, bsq format [7,532 bytes]
    width: 577
    angle: 3.052882433

Remove the line and row correlated noise [[plaid]].  Setting the output to a.data replaces the radiance cube.
 dv> a.data &#61; thm.deplaid(a.data)
 301x1883x10 array of float, bsq format [22,671,320 bytes]

Call the automatic radiance correction function to calculate the contribution of atmospheric dust to the measured radiance.  The returned structure has the element '.darkcol', which is a column of correction values that need to be subtracted from the radiance.
 dv> rc &#61; autoradcorr(a.data)
 ..
 struct, 4 elements
    avgdark: 1x1x10 array of float, bsq format [40 bytes]
    blackmask: 301x1883x1 array of byte, bsq format [566,783 bytes]
    dark: 7x38x10 array of float, bsq format [10,640 bytes]
    darkcol: 1x1883x10 array of float, bsq format [75,320 bytes]

Subtract the column of correction values from the data where the array is not the ignore value.
 dv>a.data[where a.data !&#61; -32768] &#61; a.data-rc.darkcol

OPTIONAL STEPS: (if applied, adjust thm.reconstitute command accordingly)

: 1) Remove the noise known as [[streak]].
 dv> rc.data &#61; destreak(rc.data, ignore &#61; -32768)
 dv> b.data&#61;rc.data

: 2) Remove [[rrmnoise_pca|white noise]]. Only recommended for qualitative products (e.g., DCS).
 dv> c &#61; rrmnoise_pca(rc.data, ignore &#61; -32768)

Return the data to its original map projection.  This reverses the rectify step.
 dv> a &#61; thm.reconstitute(a)
 577x1852x10 array of float, bsq format [42,744,160 bytes]

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*[[thm.rectify]]
*[[rtilt]]
*[[thm.deplaid]]
*[[autoradcorr]]
*[[destreak]]
*[[rrmnoise_pca]]
*[[thm.reconstitute]]
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*[[Convert THEMIS radiance to emissivity]]
*[[Add Two Arrays Together]]
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[[category:Procedures]]