Demosaicing

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The effects of this tool are only visible at a preview scale of 1:1 or more. Use a detail window (click on the Window-add.png icon under the main preview panel) to inspect a part of the image, or zoom the main preview to 100% (also called 1:1) Magnifier-1to1.png.


Cutaway illustration of a camera showing the light sensor with a Bayer filter.
Bayer pattern on sensor.
Profile/cross-section of sensor.

Introduction

Most digital cameras use a sensor which contains millions of homogeneous light-sensitive elements, called sensels or photosites. In order to capture color, a color filter array (CFA) is placed over the sensor, so that specific photosites register specific wavelengths of light. The "Bayer filter" is the most common - it uses a repetitive 2x2 matrix of green, blue, red and green patches. It is used by most camera manufacturers. There is also a filter arrangement called "X-Trans", used by some Fujifilm cameras, with a repetitive 6x6 matrix of patches. As each photosite is responsible for capturing only a specific band of light, there are three main problems that need to be dealt with:

  1. There is no concept of color yet, as each photosite registers only a single electric charge induced by the photons which pass through the filter and strike it,
  2. There are twice as many green photosites as either red or blue,
  3. and thus half (green) or three-fourths (red, blue) of each color channel consist of a lack of data (black, unexposed photosites, since there is for example only one red-filtered photosite out of every four).

Displaying an image from a camera with a Bayer or X-Trans sensor is therefore not straight-forward - the mosaic of discrete data points need to be converted into a cogent color image. This process is called demosaicing.

RawTherapee offers several demosaicing algorithms, each with its own characteristics. The differences between them can be subtle - one might need to zoom in to 100% or more to discern them. However, as the demosaiced image constitutes the foundation upon which all other tools work, the choice of demosaicing algorithm can have a visually significant effect on the end result, particularly when viewed up close. The most visible effects of the choice of demosaicing algorithm include the rendering quality of fine detail and the visibility of artifacts in the form of maze-like patterns.

Concerning Bayer cameras, AMaZE is generally the best method for lower-ISO images, while LMMSE or IGV are better for higher-ISO ones. Concerning X-Trans cameras, 3-pass (Markesteijn) is generally the best method.

On a side note, the Foveon X3 sensor does not use a color filter array and so images coming from camera with such a sensor do not need to be demosaiced. They are, however, unsupported by RawTherapee.

Demosaicing Methods

  • Common methods:
    Fast
    Very fast but simple and low quality demosaicing method, not recommended.
    Mono
    Only useful for users of monochrome cameras, or cameras with the color filter array removed.
    None
    No demosaicing is performed. This can be useful for diagnostics, but you would not use it for photography.
  • Bayer methods:
    AMaZE
    AMaZE (Aliasing Minimization and Zipper Elimination) is the default demosaicing method, as it yields the best results in most cases. In RawTherapee versions 2.4 and older VNG4 used to be the preferred algorithm for Olympus cameras, as AMaZE didn't exist yet and VNG4 eliminated certain maze pattern artifacts that might have been created by the other methods, but with the introduction of the AMaZE method in RawTherapee 3.0, Olympus users might prefer that instead.
    RCD
    RCD (Ratio Corrected Demosaicing) does an excellent job for round edges, for example stars in astrophotography, while preserving almost the same level of detail as AMaZE.
    DCB
    DCB produces similar results to AMaZE. AMaZE can often be slightly superior in recovering details, while DCB can be better at avoiding false colors especially in images from cameras without anti-aliasing filters.
    LMMSE and IGV
    These are recommended when working with very noisy, high ISO images, in conjunction with the Noise Reduction tool. They will prevent false maze patterns from appearing, and prevent the image from looking washed-out due to heavy noise reduction. IGV is also quite effective at mitigating moiré patterns.
    AHD, EAHD and HPHD
    AHD (Adaptive Homogeneity-Directed), EAHD (Horvath's AHD) and HPHD (Heterogeneity-Projection Hard-Decision) are old methods which are generally slow and inferior to the other methods.
    VNG4
    If you use a medium format technical camera with near-symmetrical wide angle lenses such as the Schneider Digitar 28mm or 35mm it's likely that the image captured by your sensor will contain some crosstalk between photosites, especially if the lens is shifted (due to the low angle of incoming light from these lenses some light leaks over to the next pixel on the sensor), and in this case you can get mazing artifacts with AMaZE and DCB because of the green channel separation caused by the crosstalk. If you combine a mirrorless camera using an adapter with a wide angle lens designed for film, you may also get crosstalk. It can then be better to use the VNG4 algorithm (Variable Number of Gradients), which handles this situation well, at the cost of some fine detail. An alternative is to enable green equilibration to even-out the green channel differences.
    Pixel Shift
    Some Pentax and Sony cameras support shooting in Pixel Shift mode, which shoots four frames with the sensor offset one pixel at a time in a circular direction, and then stores all four frames in one large raw file. RawTherapee can combine all frames into one image while automatically masking-out moving objects, thereby reducing the level of noise and increasing the image sharpness.
  • Fujifilm X-Trans methods:
    3-Pass
    For Fujifilm cameras with X-Trans sensors. It runs three passes over the image which leads to sharper results though you can only see this on low ISO photos. It is slower than 1-Pass.
    1-Pass
    For Fujifilm cameras with X-Trans sensors. It is faster than the 3-pass method but slightly inferior in quality, though this difference is only visible in low ISO shots. If speed is an issue, you can use this method on high ISO shots with no visual difference in quality.

How to Find the Best Demosaicing Method

A good image to test the demosaicing algorithms on. Zoomed in to 800%, you can clearly see that VNG4 is not a good choice for this Pentax K10D raw file, as there are dots where there should be none, and the detail of the wall’s brickwork (the orange part on the right) is all washed out.

Zoom in to at least 100% (1:1) and try all the demosaicing algorithms, see which works best for you. Try them on sharp photos with fine detail and tiny patterns, such as the wavy and repetitive fabric of a sweater (watch for maze pattern artifacts), a distant brick wall, a distant round road sign (watch for aliasing along the round edges), and test with both low and high ISO shots. Use photos from your own camera; what's best for Nikon raw images may not be what's best for Olympus ones.

Monochrome Cameras

A monochrome camera has a homogeneous filter in front of the sensor - you get a black-and-white image, and no demosaicing is required. Some of these cameras have no infrared filter and are thus sensitive to infrared light, which can be used for creative black and white photography.

RawTherapee supports monochrome cameras, but the user interface is not specifically adapted for it, so when you load a monochrome file all color tools will still be available.

There are a few additional factors to consider when working with monochrome files: some monochrome cameras report that they have only a single monochrome channel and a neutral color matrix (such as the Leica M Monochrom), while others report RGB channels in a Bayer configuration (such as the Phase One IQ260 Achromatic, or IR-modified cameras). If the camera reports only one channel, RawTherapee recognizes this and won't perform any demosaicing (the demosaicer selection is still enabled but does not do anything), and everything works normally. However, if the camera identifies as an RGB Bayer camera, demosaicing will be performed and a color matrix will be applied. To disable this, you should select the "Mono" demosaicing method, and select "No profile" as input profile in the Color Management panel.

Interface

The demosaicing methods and their associated settings are separated into two main tools, "Sensor with Bayer Matrix" and "Sensor with X-Trans Matrix", each of which is visible when editing a raw file which originates from a camera which uses the given filter matrix. The settings in one tool have no influence over the settings in the other - if you open a raw image from a Bayer-type sensor, only the settings from the "Sensor with Bayer Matrix" tool will be used, the settings from the "Sensor with X-Trans Matrix" tool will be ignored, and vice versa.

Method

The following demosaicing algorithms are available for raw files from Bayer sensors:

  • AMaZE
  • AMaZE+VNG4
  • RCD
  • RCD+VNG4
  • DCB
  • DCB+VNG4
  • LMMSE
  • IGV
  • AHD
  • EAHD
  • HPHD
  • VNG4
  • Fast
  • Mono
  • Pixel Shift
  • None

The following demosaicing algorithms are available for raw files from X-Trans sensors:

  • 3-pass+fast
  • 3-pass (Markesteijn)
  • 1-Pass+fast
  • 1-Pass (Markesteijn)
  • Fast
  • Mono
  • None

Dual Demosaic

The dual-demosaic methods, such as AMaZE+VNG4, allow you to demosaic areas of high contrast (i.e. detail) using one method and areas of low contrast (i.e. no detail, plain areas such as sky) using the other algorithm. As some algorithms are better at rendering fine detail while others are better at rendering smooth, plain areas, these dual-demosaic options allow you to combine the best of both worlds, this providing a better starting point for the other tools and mitigating the need for sharpening or noise reduction. The downside is that the image needs to be demosaiced twice, thus taking longer than using a single demosaicing method.

The threshold for adjusting the level of detail at which one demosaicing algorithms should be used over the other is controlled using the "contrast threshold" slider. The slider includes a checkbox which computes an optimal level automatically.

Border

Demosaicing may rely on sampling the pixels which surround a given pixel. When demosaicing a pixel which lies at the top edge of the raw image, there are no pixels above it, thus it cannot be demosaiced in the same way and at the same quality as those pixels which are surrounded by a sufficiently large number of pixels. Most raw converters thus crop off a few rows and columns from around the image periphery, as does RawTherapee by default. However, you can override this cropping by manipulating the "border" value. Setting it to "0" means no cropping occurs, and RawTherapee will do what it can to demosaic the border pixels, though artifacts may appear!

You should generally leave this setting at its default value, and change it to 0 only when absolutely needed, for example when processing 1080praw DNG frames where you need to preserve the 1920x1080 pixel count.

Sub-Image

Some raw files contain more than one image. When editing such an image, the sub-image option appears, and allows you to edit a specific sub-image, or to combine the sub-images in one way or another.

Some Fujifilm EXR cameras support "SN mode" at capture time, which stands for "Signal to Noise priority". When editing such an image, the sub-image combobox allows you to select "SN mode", which blends pixels from both sub-images using a mean average, leading to less noise.

False Color Suppression Steps

Sets the number of median filter passes applied to suppress demosaicing artifacts when applying the demosaicing algorithm. False colors (speckles) could be introduced during the demosaicing phase where very fine detail is resolved. False color suppression is similar to color smoothing. The luminance channel is not affected by this suppression.

False colors are generally more apparent in images from cameras without anti-aliasing filters. Note that it is foremost the selected demosaicing algorithm which is the deciding factor in how prominent will be the false color problem with which you will have to deal. In some situations it may be better to change the demosaicing algorithm than to enable false color suppression, as the latter reduces color resolution.