SPCC Spectrophotometric Color Calibration

Version released on 2022-11-21

updated: 2022-11-22

Purpose	SPCC Spectrophotometric Color Calibration: Calibrates the color of a linear deep-sky image based on Gaia catalogs. The SPCC tool performs a balancing of the colors of a linear RGB deep-sky image based on the following documentary criteria: Maximize information representation in the calibrated color image. Don't favor any particular color or spectral type as a white reference. Note that this is a spectrum-agnostic color calibration procedure, very different from other methods based on fixing a white reference with respect to a particular spectral type.
Activation	Process 🡺 All Processes 🡺 ColorCalibration
Input	Backnoise neutralized image, file names like “_i_c_DBE_BN.xisf”, "_i_c_ABE_BN" or "*_i_c_DBE_ABE_BN" from sub folder "aligned"
Output	Corrected image, file name “*_i_c_DBE_BN_CC.xisf” or similar into sub folder "aligned"
Previous Step	Background Improvement
Next Step	Any topic under Color Correction
Ressources	PixInsight Reference Documentation \| Spectrophotometry–based Color Calibration in PixInsight

WARNING: be careful if using a cropped image as the image parameters like focal length and pixel size acquired from the image may no longer fit and will probably result in a plate solver error! It's easier to use an uncropped version and crop later.

Gaia currently represents the state of the art in terms of stellar astrometry and photometry. The star catalogs and auxiliary data generated by Gaia are of the highest quality as they are based on measurements made from space. We at the PixInsight Development Team have already been using and recommending Gaia for all astrometry–related tasks in PixInsight for many years. Now we have implemented a new tool, SpectrophotometricColorCalibration (SPCC), which uses Gaia's mean BP/RP spectra[4] available since Gaia Data Release 3.[5] [6] [7] SPCC is the first of a series of tools we are developing to exploit the availability of Gaia mean spectrum data in PixInsight.

Switching from PCC to SPCC is straightforward. In both tools, we have the Catalog Search, Signal Evaluation and Background Neutralization sections. The only significant difference between these tools, for basic usage, is the ability to configure our own filters provided by SPCC. In PCC, we compare stars measured on our RGB image channels to the brightness of the same stars measured with the photometric filters used to build the APASS catalog. With the Gaia spectra database, we calculate the exact brightness of each star in the filters we have used to acquire our image. Hence, in the Calibration section, we can assign a filter for each color channel of the image:

Step	Action	Description
1	Calibration The default average spiral galaxy reference is the best choice for deep space objects. Irrespective of being a color image acquired with a monochrome or color camera, we should always select the three filters separately. As shown on the right, the default filters are those of a generic Sony color image sensor. The only difference regarding the type of camera is that, for a monochrome camera, we first need to create a color image with the ChannelCombination tool. (see documentation) When working with OSC cameras, we should always set the QE curve parameter to Ideal QE curve as shown on the right.
2	Catalog Search SPCC should always be used with local Gaia DR3/SP databases in XPSD format, which can be downloaded from our Software Distribution interface. Remarks: Installing and activating the local XPSD database server	Using a local Gaia - XPSD database:
3	Signal Evaluation
4	Background Neutralization The lower limit and upper limit parameters are now expressed in sigma units from the median of the background reference region, instead of literal pixel values. With this change, the background reference is sampled adaptively, solving several practical problems we have detected with previous versions. In practice, you rarely will need to change the default values of these parameters, and background neutralization will simply work in virtually all cases. Best option is to create a preview window on a portion of the image with now stars or clouds and enable the Region of Interest option and get the coordinates from the the preview as shown on the right.
5	After Successful Transformation If successful you will see the calibration results:
6	Save the corrected image	into a file like *_i_c_DBE_BN_SPCC.xisf (or 20170921_M8_FUJXT1_i_c_DBE_ABE_BN_SPCC.xisf in this case)