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Saturn's moon Titan is one of the most difficult objects to figure out true colors. To begin with, its surface is simply impossible to observe in the visible range because of the haze. Sufficiently transparent spectral bands begin only in the infrared, which means that only for the infrared it is possible to create a global map. Fortunately, we have Huygens landing probe, whose data was processed by Erich Karkoschka and Stefan E. Schröder [1]. The figure 6 was run through my program TrueColorTools (requiring some modifications along the way). The multiband images were interpolated and extrapolated (to blue range) there to a spectral cube and then convolved with the sensitivity of the human eye.
Having surface panoramas with a known color processing, all that is left is to extend that color to some infrared map. The best available option was a map from B. Seignovert et al. [2], which was first rid of artifacts and manually cleaned of pixilization. The Huygens landing site was selected from this map and matched to a previously processed projection of it in visible colors.
Now we need to find an unknown transformation over a piece of the infrared map so that it produces something as close as possible to the corresponding piece of the visible map, and then apply the found transformation to the entire infrared map. Assuming linearity of the transformation, it can be written in the form IR · X + C = VIS, where IR is a known 3-vector of some pixel color, X is an unknown 3x3 color transformation matrix, C is an unknown 3-vector and VIS is the resulted visible color 3-vector. The linearity assumption can be justified if the surface spectra in the visible and infrared are highly correlated with each other (which is true), but the infrared map used [2] contains nonlinear color transformations to highlight geologic features. Therefore, it was renormalized as follows before processing: R′ = G · B = 2.03/1.08 μm, G′ = R · B = 1.59/1.08 μm, B′ = B = 1.27/1.08 μm.
It turns out that we do not know the 3x3+3=12 parameters of X and C responsible for color conversion. They were found in 12-dimensional space as a result of optimization over all the landing site pieces pixels by the MNC method in Python. There was an attempt to add another matrix with quadratic form, but it failed: the result was too optimized and unrealistic.
Unfortunately, Huygens was only able to capture a small region of the surface, only one of two variations in the coloration of the dunes. Therefore, the unknown color of the second type of dunes had to be handpicked based on the assumption that there were no sharp brightness gradients on the surface, and run the optimization with this patch of handpicked influence. The color of the lakes is also handpicked, no suitable theoretical data has been found. Without these assumptions, the texture map cannot be completed. That's about as close to maximum color realism as we can achieve right now.
Lake delineations were obtained separately using radar data [3], which had noise and missing data. These regions were manually reconstructed from infrared data from Cassini, and the infrared map [2] itself was pre-warped to match the radar data (reprojected from the polar stereographic projection with another Python script).
Thanks to Pedro J. and Chara for their help and support!
History
August 2025: the Titan color map series was updated in accordance with the color processing updates in TrueColorTools (Tikhonov regularization for spectral reconstruction, color spaces management).
Contrast is slightly increased due to the darker presumed visible color of the second type of dunes.
January 2026: Did a little research on the color of liquid methane and ethane under Titan surface conditions. Turns out they're likely transparent, see this paper. The spherical albedo color was calculated from the refractive index "n" from [4] by integrating the Fresnel equations. The script makes the average color of the lakes calculated taking into account map distortions.
Info
Simple cylindrical projection, center longitude 0°.
Gamma corrected, albedo corrected.
Sources
[1] Karkoschka et al. (2016). Eight-color maps of Titan’s surface from spectroscopy with Huygens’ DISR
[2] B. Seignovert et al. (2019). Titan's global map combining VIMS and ISS mosaics (1.1). CaltechDATA
[4] Martonchik & Orton (1994). Optical constants of liquid and solid methane
Related
Saturn's moon Titan is one of the most difficult objects to figure out true colors. To begin with, its surface is simply impossible to observe in the visible range because of the haze. Sufficiently transparent spectral bands begin only in the infrared, which means that only for the infrared it is possible to create a global map. Fortunately, we have Huygens landing probe, whose data was processed by Erich Karkoschka and Stefan E. Schröder [1]. The figure 6 was run through my program TrueColorTools (requiring some modifications along the way). The multiband images were interpolated and extrapolated (to blue range) there to a spectral cube and then convolved with the sensitivity of the human eye.
Having surface panoramas with a known color processing, all that is left is to extend that color to some infrared map. The best available option was a map from B. Seignovert et al. [2], which was first rid of artifacts and manually cleaned of pixilization. The Huygens landing site was selected from this map and matched to a previously processed projection of it in visible colors.
Now we need to find an unknown transformation over a piece of the infrared map so that it produces something as close as possible to the corresponding piece of the visible map, and then apply the found transformation to the entire infrared map. Assuming linearity of the transformation, it can be written in the form IR · X + C = VIS, where IR is a known 3-vector of some pixel color, X is an unknown 3x3 color transformation matrix, C is an unknown 3-vector and VIS is the resulted visible color 3-vector. The linearity assumption can be justified if the surface spectra in the visible and infrared are highly correlated with each other (which is true), but the infrared map used [2] contains nonlinear color transformations to highlight geologic features. Therefore, it was renormalized as follows before processing: R′ = G · B = 2.03/1.08 μm, G′ = R · B = 1.59/1.08 μm, B′ = B = 1.27/1.08 μm.
It turns out that we do not know the 3x3+3=12 parameters of X and C responsible for color conversion. They were found in 12-dimensional space as a result of optimization over all the landing site pieces pixels by the MNC method in Python. There was an attempt to add another matrix with quadratic form, but it failed: the result was too optimized and unrealistic.
Unfortunately, Huygens was only able to capture a small region of the surface, only one of two variations in the coloration of the dunes. Therefore, the unknown color of the second type of dunes had to be handpicked based on the assumption that there were no sharp brightness gradients on the surface, and run the optimization with this patch of handpicked influence. The color of the lakes is also handpicked, no suitable theoretical data has been found. Without these assumptions, the texture map cannot be completed. That's about as close to maximum color realism as we can achieve right now.
Lake delineations were obtained separately using radar data [3], which had noise and missing data. These regions were manually reconstructed from infrared data from Cassini, and the infrared map [2] itself was pre-warped to match the radar data (reprojected from the polar stereographic projection with another Python script).
Thanks to Pedro J. and Chara for their help and support!
History
August 2025: the Titan color map series was updated in accordance with the color processing updates in TrueColorTools (Tikhonov regularization for spectral reconstruction, color spaces management).
Contrast is slightly increased due to the darker presumed visible color of the second type of dunes.
January 2026: Did a little research on the color of liquid methane and ethane under Titan surface conditions. Turns out they're likely transparent, see this paper. The spherical albedo color was calculated from the refractive index "n" from [4] by integrating the Fresnel equations. The script makes the average color of the lakes calculated taking into account map distortions.
Info
Simple cylindrical projection, center longitude 0°.
Gamma corrected, albedo corrected.
Sources
[1] Karkoschka et al. (2016). Eight-color maps of Titan’s surface from spectroscopy with Huygens’ DISR
[2] B. Seignovert et al. (2019). Titan's global map combining VIMS and ISS mosaics (1.1). CaltechDATA
[4] Martonchik & Orton (1994). Optical constants of liquid and solid methane
Related
Valle Orco, Parco nazionale del Gran Paradiso - Piemonte/Valle d'Aosta - Italia
AUTOPANO PRO 1.40RC2 Linux ed.
Pano-20 immagini-9113x2906-proiezione Spherical-interpolazione Bicubic Sharper-unione Multiband
The destructive results of a mighty supernova explosion reveal themselves in a delicate blend of infrared and X-ray light, as seen in this image from NASA’s Spitzer Space Telescope and Chandra X-Ray Observatory, and the European Space Agency's XMM-Newton.
The bubbly cloud is an irregular shock wave, generated by a supernova that would have been witnessed on Earth 3,700 years ago. The remnant itself, called Puppis A, is around 7,000 light-years away, and the shock wave is about 10 light-years across.
The pastel hues in this image reveal that the infrared and X-ray structures trace each other closely. Warm dust particles are responsible for most of the infrared light wavelengths, assigned red and green colors in this view. Material heated by the supernova’s shock wave emits X-rays, which are colored blue. Regions where the infrared and X-ray emissions blend together take on brighter, more pastel tones.
The shock wave appears to light up as it slams into surrounding clouds of dust and gas that fill the interstellar space in this region.
From the infrared glow, astronomers have found a total quantity of dust in the region equal to about a quarter of the mass of our sun. Data collected from Spitzer’s infrared spectrograph reveal how the shock wave is breaking apart the fragile dust grains that fill the surrounding space.
Supernova explosions forge the heavy elements that can provide the raw material from which future generations of stars and planets will form. Studying how supernova remnants expand into the galaxy and interact with other material provides critical clues into our own origins.
Infrared data from Spitzer’s multiband imaging photometer (MIPS) at wavelengths of 24 and 70 microns are rendered in green and red. X-ray data from XMM-Newton spanning an energy range of 0.3 to 8 keV (kiloelectron volts) are shown in blue.
Cuando se trata de corregir una imagen multibanda lo más importante es eliminar el efecto de sombra causado por la topografía, porque las sombras distorsionan las clasificaciones que se le puedan hacer a los píxeles. Para una imagen hiperespectral esa sombra no es relevante, porque lo más importante es identificar los patrones de absorción o reflectancia a distintos anchos de banda.
Siempre me equivoco en algo al dibujar. Necesito encontrar la forma de llegar a formas que resulten bien, que no tengan esos errores que distorsionan mi señal. No puedo dejar de insistir. Quiero aprender.
Hoy tuve que dibujar un luche en el suelo de la Escuela para una actividad de la escuela de dirigentes rurales. Ese luche salió misteriosamente parecido a la portada de la primera edición de Rayuela, de la editorial Eudeba. Pero en vez del Cielo que estaba en el último espacio dibujado en ese libro, se encontraba el Tiempo. Y nos costó lograr llegar a él con las piedritas.
Canciones descubiertas y escuchadas una y otra vez: la enredadera- leo quinteros/ azucar café- manuel garcía.
The NASA CE318-N Sun Sky photometer at the Mesa Lakes Ranger Station. The multiband photometer operates at daytime and takes optical measurements to provide quantification and physical-optical characterization of the aerosols.
Another shot, from the exterior of the MultiBand building, of Paul's balloon-filled cubicle. Many other people in the building were seen milling about the parking lot and the entry area, looking up and chuckling.
U.S. Marine Corps Cpl. Jan Kamphuis, participating in Weapons and Tactics Instructor (WTI) 1-15 Course from Marine Air Control Squadron (MACS) 2 Detachment B, Marine Aircraft Group (MAG) 28, 2nd Marine Aircraft Wing (MAW), uses a portable radio communications 117F multiband manpack radio to communicate with a KC-130J Hercules aircraft on Stoval Auxiliary Landing Field, Yuma County, Ariz., Sept. 23, 2014. WTI is a seven week training event hosted by Marine Aviation and Weapon Tactics Squadron (MAWTS-1) cadre. MAWTS-1 provides standardized advanced tactical training and certification of unit instructor qualifications to support Marine Aviation Training and Readiness and assists in developing and employing aviation weapons and tactics. (U.S. Marine Corps photo by Cpl. Allison J. Herman, COMCAM/Released)
U.S. Marine Corps Cpl. Jan Kamphuis, participating in Weapons and Tactics Instructor (WTI) 1-15 Course from Marine Air Control Squadron (MACS) 2 Detachment B, Marine Aircraft Group (MAG) 28, 2nd Marine Aircraft Wing (MAW), uses a portable radio communications 117F multiband manpack radio to communicate with a KC-130J Hercules aircraft on Stoval Auxiliary Landing Field, Yuma County, Ariz., Sept. 23, 2014. WTI is a seven week training event hosted by Marine Aviation and Weapon Tactics Squadron (MAWTS-1) cadre. MAWTS-1 provides standardized advanced tactical training and certification of unit instructor qualifications to support Marine Aviation Training and Readiness and assists in developing and employing aviation weapons and tactics. (U.S. Marine Corps photo by Cpl. Allison J. Herman, COMCAM/Released)
This swirling landscape of stars is known as the North America nebula. In visible light, the region resembles North America, but in this new infrared view from NASA's Spitzer Space Telescope, the continent disappears..
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Where did the continent go? The reason you don't see it in Spitzer's view has to do, in part, with the fact that infrared light can penetrate dust whereas visible light cannot. Dusty, dark clouds in the visible image become transparent in Spitzer's view. In addition, Spitzer's infrared detectors pick up the glow of dusty cocoons enveloping baby stars..
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Clusters of young stars (about one million years old) can be found throughout the image. Slightly older but still very young stars (about 3 to 5 million years) are also liberally scattered across the complex, with concentrations near the "head" region of the Pelican nebula, which is located to the right of the North America nebula (upper right portion of this picture)..
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Some areas of this nebula are still very thick with dust and appear dark even in Spitzer's view. For example, the dark "river" in the lower left-center of the image -- in the Gulf of Mexico region -- are likely to be the youngest stars in the complex (less than a million years old)..
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The Spitzer image contains data from both its infrared array camera and multiband imaging photometer. Light with a wavelength of 3.6 microns has been color-coded blue; 4.5-micron light is blue-green; 5.8-micron and 8.0-micron light are green; and 24-micron light is red.