= residuals.e =

Residuals tests the landmarks to look for problems.  It will give you a report based on landmarks, pictures and maps.

=== Input - files ===
 * [[LMKFILES]]
 * [[IMAGEFILES]]
 * [[PICTLIST.TXT]]
 * [[LMRKLIST.TXT]]

=== Input - stdin ===

 enter plim (px,km,km)

 * The number of pixels an images needs to be "off" to throw the chevron (>>) flag
 * The rms error of a landmark 
 * Sets the "bin" size for the final histogram (basically how many images are in which side categories).   

 input operation list
{{{ 
     2.5, 1, 001
}}}


=== Output ===
 * [[MAPINFO.TXT]]
 * [[PICINFO.TXT]]
 * [[LIMINFO.TXT]]
 * [[RESIDUALS.TXT]]

== PowerPoint Notes ==
=== Description ===
 * Compares predicted and observed pixel, line position of the landmarks in the images
 * Produces RSS of the diagonal convariance elements of each control point
  * Describes landmark position uncertainty
 * Flags landmarks with residuals over specified pixel value

=== Control Points ===

 * Inputs are weights for S/C uncertainties from measurement uncertainties and from a-prior shape constraints
 * Control points solution results in a 3x3 output covariance for each control point. Diagonal elements are uncertainties along maplet coord. system axes, i.e. two horizontal directions & height. Typically SPC produces comparable horizontal & height uncertainties. Results are summarized as a scalar standard deviation per degree of freedom in meters
 * Residuals check automatically flags errors beyond certain input values in dump file for ease of inspection  

===== Example =====
{{attachment:residuals_controlpoint1.jpg||width=700}}

=== Image Residuals ===

 * The post-fit residuals between predicted and actual control point positions in all images are captured in the residuals file
 * The post-fit residuals between predicted and actual control point difference between adjacent, overlapping maplets are captured in the residuals file
 * Outliers in both quantities are flagged automatically based on input threshold criteria 

===== Example =====
{{attachment:residuals_imageresiduals.jpg||width=500}}

=== Bad & Fixed Image ===

{{attachment:residuals_WhatWentWrong.jpg||width=700}}

=== Qualitative Checks ===

 * Qualitative checks are important to verify that the quantitative error estimates are believable
 * Render a single maplet, or a DEM synthesized by a collection of maplets, at the same geometry & illumination conditions as the images themselves 
  * Do all the features in the images appear in the DEM ?
  * Are the smallest discernible features in the images, e.g., boulders, craters etc. visible in the DEM as well ?
  * Is the relative albedo solution such that the relative brightness of adjacent image features matches that of the DEM ?
  * Are the heights solution such that the length and overall appearance of the shadows in the DEM matches that of the image ?

=== How are Uncertainties Introduced in the Data ===

 * Main types of uncertainties: 
  * S/C trajectory, camera pointing, image timestamp
   * Manifest themselves mostly in the projection of image template onto the surface.     Corrected by global geometry solution
  * Image noise, artifacts, smear, overall image quality
   * Manifest themselves in predicted image template brightness and in its fit to the extracted image brightness  
  * Photometric model and reflectance function models
   * Show up in slopes & heights integration
  * Poor choice of a-priori parameters & data weights
   * Evident at end of each estimation step; data won’t fit well

 * Often above contributions are correlated; individual contributors may not be separated until many processing steps have been taken

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CategoryPrograms