Raw Files

The unprocessed digital output of an image sensor is called RAW image data. In this document, we sometimes refer to raw files from commercial cameras or development systems as Camera raw to distinguish them from Bayer raw files, which are standard monochrome image files that contain undemosaiced (Bayer) data.

Imatest modules can analyze raw files directly or after demosaicing.

To be usable in most applications, raw files must be demosaiced (though many Imatest modules can analyze raw files directly). Demosaicing (sometimes spelled demosaicking) a form of interpolation that fills in the missing colors for each pixel. It is the primary function of raw converter programs (which may be either built into the camera or installed on a separate computer). In demosaicing, detail in the missing colors is inferred from detail in other, neighboring colors. Algorithms can be very mathematically sophisticated. A good example (which is the basis of Matlab’s gradient-corrected linear interpolation demosaic routine) in High-Quality Linear Interpolation for Demosaicing of Bayer-Patterned Color Images by Henrique S. Malvar, Li-wei He, and Ross Cutler of Microsoft.

In addition to demosaicing, converting raw images into standard interchangeable image formats may include

1. applying a gamma curve, often with an added tonal response curve (which often has a “shoulder”, i.e., a rounded region),
2. white balance and color (matrix) adjustment,
3. sharpening, usually in the neighborhood of contrasty features, and
4. software noise reduction, typically in the absence of contrasty features.

All these steps can affect Imatest measurements. To minimize their effects (to convert raw files without sharpening, noise reduction, and tonal response curves) Imatest uses the following techniques:

• For commercial raw files, which are proprietary to camera manufacturers (e.g., CR2 for Canon and NEF for Nikon) and contain proprietary metadata that may be packed (m pixels into n bits), Imatest uses LibRraw, a freely available program for converting commercial RAW images to useful file formats with minimal processing. LibRaw can optionally apply a simple gamma curve (with no additional tonal response curve) and white balancing (based on the camera setting), but it never sharpens or applies noise reduction.
• For the output of manufacturer’s development systems, which is typically pure binary data, 1 or 2 bytes per pixel, Imatest uses Generalized Read Raw, described below. Generalized read raw can optionally apply a simple gamma curve and white balancing (based on the crude “gray world” algorithm). Output images can be color-corrected (using a matrix) in Color/Tone Interactive or Color/Tone Auto and sharpened or noise-reduced in Image Processing. An extension has to be specified that corresponds to the file format (most importantly, the number of rows, columns, and bit depth). 

Raw files in Imatest

Imatest can use RAW files in two ways.

1. It can demosaic raw files, producing standard 3-color RGB image files in TIFF, PPM, PNG, or JPEG format, with TIFF as the default. The advantage of using LibRaw or Generalized Read Raw is that they apply no sharpening, no noise reduction, and a straight gamma curve. LibRaw offers several choices for gamma, including 1/2.2 (for typical displays), sRGB (close to gamma = 2.2, but with a linear region in the deep shadows), and 1.0 (true linear). If raw files are available, cameras and lenses from different manufacturers can be compared on a consistent, fair basis. LibRaw should be used with caution in Colorcheck and Stepchart because is performs autoexposure (automatic white level adjustment) by default. The Auto white level button should be unchecked to get the correct levels. According to the dcraw FAQ, “No matter how dark an image is, dcraw’s auto-exposure stretches it so that one percent of its pixels appear white. The “-W” option avoids this behavior.”
2. It can convert camera raw files into Bayer raw (undemosaiced) files stored in standard monochrome image file formats (TIFF, PNG, or PGM). Most Imatest Master modules can analyze Bayer raw files.Bayer Raw is valuable for measuring lateral chromatic aberration, which can be strongly distorted by the demosaicing process. It also allows the two raw green channels (Gr and Gb) to analyzed separately. Caution: LibRaw may apply some tonal processing, even though the documentation indicates it doesn’t, i.e., gamma measured by Stepchart and other modules may be quite different from the expected value of 1. (This may be due to uncorrected offsets the raw files themselves).

To use raw files in Imatest, either

• Click on an Imatest module (SFR, Stepchart, etc.) and open the file just as you would any other image file. If the file extension indicates a camera raw image file supported by LibRaw(CR2, NEF, etc.— even Phase One RAW TIF files), the dialog box shown below for setting Libraw (formerly dcraw) parameters is opened. If the file extension has been entered into Generalized Read Raw, the file will be read and decoded according to the Read Raw settings.
   
• Click on the LibRaw box on the right side of the Imatest main window (or click Modules, Run LibRaw) to run LibRaw as a standalone application: the output file will be saved but no Imatest module will run. The dialog box shown in the LibRaw section below is a graphic user interface (GUI) front-end to LibRaw that allows you to select several of LibRaw’s options.

Processing commercial raw files with LibRaw

The best way to be sure an image file used by Imatest faithfully resembles the raw file— that it has a straight gamma curve, no sharpening, and no noise reduction— is to read a raw file into Imatest and convert it to a standard format (TIFF, PPM, etc.) using LibRaw (or before 2021.1, Dave Coffin’s dcraw). If you select any of the standard raw formats (CR2, CR3, NEF, etc.) or if raw data is detected (e.g., Phase One TIF files) a dialog box appears. It is a front-end to LibRaw that allows you to choose between several raw conversion options. Presets are in the pink box on the right.

LibRaw settings window.
The Program dropdown, which is no longer needed, has been removed.

LibRaw can either (A) demosaic camera raw files with minimal processing— no sharpening, no noise reduction, and a simple gamma curve, or (B) convert them to standard 8 or 16-bit monochrome file formats (TIFF or PGM) that contain Bayer RAW (undemosaiced) data, which can be analyzed by several Imatest Master modules. This conversion has the following choices:

If the second or third option above (Raw 8-bit or Raw 16-bit) is selected, most the Demosaicing area (above) is grayed out and the output of LibRaw is a monochrome TIFF or PGM file that contains undemosaiced (Bayer raw) data from the image sensor.

Note: the pixel levels and gammas of undemosaiced (Bayer raw) files do not appear to be reliable as of July 2009, apparently because offsets in the raw image are not removed. Levels are too dark if Auto white level is unchecked, and the gamma is incorrect (for Canon CR2 raw files). Exposure and gamma are reliable with normal raw conversion (with demosaicing).

Support for LibRaw was added to Imatest version 2021.1, and supports a wide array of cameras. LibRaw options are still available in 2021.1, but has been deprecated in 2021.2.

If Normal raw conversion (demosaiced) has been selected, the Demosaicing box contains several options, most of which are explained in more detail in the dcraw Manpage (a comparable page on the LibRaw website has not been located). The following output color spaces are available for demosaiced output.

Profile tags are embedded in the output file for the four standard color spaces. Several demosaicing quality levels (using different algorithms) are available (and worth exploring). See the dcraw Manpage for details. Auto white level is the default. It can be turned off for tonal measurements.

LibRaw converts raw files into TIFF files by default, with the obscure PPM format available as an option. If check the box to delete the converted (TIFF) file, you may save the image in one of two compressed formats: PNG (lossless compression; takes longer) or JPEG (lossy compression; maximum quality; 24-bit only).

A list of supported cameras appears on the LibRaw site.

Monochrome/Bayer Raw (or RCCC) file selection

When a monochrome file is opened by an Imatest Master module that supports Bayer RAW analysis, the dialog box shown below appears. (It won’t appear if Do not display this window… has been checked. It can be restored by clicking Settings, Monochrome read dialog… in the Imatest main window.)

The four buttons on the left cause immediate action (the window closes and processing continues): Standard monochrome file ,  Bayer Raw (undemosaiced), and  Demosaic…. , and OK (Last setting)….

Standard monochrome file should be selected for ordinary monochrome image files that do not contain Bayer RAW or RCCC data.

For Bayer raw and RCCC files the color interpretation depends on the Pixel color mapping selection (Red in R1C1 for Canon; Red in R1C2 for Panasonic, etc.) The correct setting for Bayer raw images can be found by running the Rawview utility on an image with recognizable colors. Bit shift may be useful for 16-bit images that are often dark without a shift.

Bayer raw (undemosaiced) processes the image, which consists of four channels (Red, Green (Red row), Blue, and Green (Blue row)— abbreviated R, G(r), B, G(b)) without demosaicing. The primary channel to display (and in some cases analyze) is selected in the Primary channel to analyze dropdown menu. This setting may be overridden in individual modules (it’s not critical).

Demosaic… either demosaics the image (appropriate for Bayer sensors) or processes it as RCCC. The demosaicing or RCCC processing algorithm must be selected in the dropdown menu to the right of the Demosaic… button. Options are shown below.

This window appears whenever a monochrome file is opened.

The Demosaic drop-down menu has the following options.

White balance is available for the two demosaicing options. It does not apply to RCCC.

Recognizing Bayer Raw patterns

Bayer raw images are typically monochrome files (though they can be color if they are acquired using screen capture— Alt-PrtSc). They sometimes appear unexpectedly in development/prototyping systems. You can avoid serious headaches if you recognize them. They are characterized by square patterns similar to those shown on the right.

Bayer raw characteristic patterns

If a Bayer raw color has been selected, one of four image planes is selected, depending on Pixel color mapping and the button pressed (Red, Blue, etc.). (There is no universal standard mapping an image plane with a color.) Four planes that could be analyzed for the Red button are shown below. Note that the height and width in pixels of the image in each plane is half that of the image as a whole and the spacing between pixels is twice that of the sensor pixel spacing.

Rawview utility

The Rawview utility allows you to determine the color arrangement of Bayer raw files (Red in R1C1, R1C2, R2C1, or R2C2) by trying each and selecting the one that looks best.

Rawview will not work directly with binary raw or manufacturer’s raw files. 
These files should be converted into standard image file formats (PNG, JPEG, etc.),
typically without demosaicing, using Read Raw or LibRaw.

The image can be saved as an RGB file if needed. It can be opened by pressing the Rawview button in the Utility tab on the right of the Imatest main window. When Rawview is first opened, instructions similar to those shown below appear. (They are likely to be more up-to-date.)

After the image file has been read, the Rawview window looks like this:

The Rawview window (no zoom)

The zoom function is always active: the image can be zoomed in to better view key details. The Save button is enabled whenever the Red in RmCn selection is changed. It sets the default for opening Bayer raw files in Imatest modules, affecting some displays.

Note that Rawview performs no White Balance, so the balance you see represents the color balance in the sensor, which may be of interest. It is rarely neutral.

Two options are available for saving images as an RGB files: Save low res RGB file saves the image as a low resolution RGB file using the R, (one of the) G, and B channels without proper demosaicing. The vertical and horizontal resolution is half that of the original file (total pixel count is 1/4 of the original). Save full res demosaiced RGB file uses Matlab’s standard gradient-corrected linear interpolation demosaicing algorithm to save the image in a full resolution RGB file.

Rawview dropdown menus include display options and Save commands.

File

• Read Bayer Raw file Read the Bayer raw file (must be in a standard image file format: TIFF, etc.)
• Save Screen Save the contents of the screen. Optionally display it if the Display screen checkbox is checked. You need to set the viewer before the first time you display the screen this way. Irfanview is an excellent free viewer.
• Save image as RGB file Save the image as an RGB file, which has half the pixel dimensions (resolution) on the original file. This does not involve a demosaicing algorithm. The contents of the R, selected G (G(R) or G(B)), and B channels are identical to the undemosaiced channels.

Settings

• Adjust 16-bit images Brighten 16-bit images (which are linear or nearly so, i.e. gamma near 1.0) if needed to enhance display.
• Brighter 16-bit images Brighten 16-bit images further for additional display enhancement.

Help

• Online Help opens this page in your default web browser.

Generalized Read Raw

Read Raw lets you read and decode binary raw files created in engineering development systems, which are not supported by LibRaw. It has a great many options. For example, you can demosaic a file or leave it undemosaiced in order to measure MTF of any of the four channels (R, G_R, B, G_B) of undemosaiced (Bayer raw) files. Options are listed below.

Generalized Read Raw is primarily for binary files taken directly from manufacturer’s development systems. For the proprietary RAW formats from commercial cameras, which contain metadata and packed data, LibRaw should be used.

To read Generalized Raw files you must specify a file extension (up to 16 can be registered) and associate read settings with that extension. This can be done in the following steps.

Click the Read Raw button in the Utility tab on the right of the Imatest main window or click Utility, Read Raw. The following dialog box opens. Entries should be based on manufacturer’s data sheets where possible, but some trial-and-error is often required. If you know the image width and height (in pixels) setup is usually very fast. If you make an incorrect choice, a plot will be displayed (below) to help determine the correct width and height values.

Read Raw setup window

• File extension— Select one of the 16 extensions in the dropdown menu on the upper-left to edit. To recognize a new extension, enter the extension (3 or more alphanumeric characters) in the box to the right of the dropdown menu, and hit Enter. If possible, it should be one of the extensions not recognized by LibRaw. The settings for this extension will be saved when you click OK or Convert/Test (which tests extension settings by reading and displaying a file).

As of October 2009, the following extensions (in rawphoto.c, linked from www.dechifro.org/dcraw/) are recognized by LibRaw/dcraw: 3fr, arw, bay, bmq, cine, cr2, crw, cs1, dc2, dcr, dng, erf, fff, hdr, ia, jpg, k25, kc2, kdc, mdc, mef, mos, mrw, nef, nrw, orf, pef, pxn, qtk, raf, raw, rdc, rw2, sr2, srf, sti, tif, and x3f.

• Input pixel size— How pixels are stored in the file. Choices are uint8, uint16, and uint32 (unsigned 8, 16, and 32-bit formats, for 1, 2, or 4 bytes per pixel). Packed formats (for example where 2 12-bit pixels stored in 3 bytes)  are handled in the Unpack dropdown menu.
• Output pixel size— How pixels are stored in Imatest. Choices are uint8, uint16, or uint32 (for HDR files).
• Bit shift— The number of bits to shift so the lightest pixels aren’t too dark or saturated: Auto or 0, ±2, ±4, ±6, or ±8 are the choices for uint8 or uint16 output. Uses the very fast Matlab bitshift function. Often needed to get correct levels for analysis. Negative numbers darken the image. Auto is recommended unless absolute levels are required.

Auto bit shift works by finding the maximum pixel value m in the image excluding the two outer rows and columns (closest to the edge of the image), comparing the maximum to the maximum level for the output pixel size (255 for uint8, 65535 for unit16, etc.) then shifting the pixel levels so the maximum pixel value is between half the maximum and the maximum for the output pixel size. For example, if the maximum pixel level m for a uint16 image is 9120, the bits will be shifted by 2 pixels (equivalent to multiplication by 4) to make the maximum 36480.

• Pixel offset— An integer number to subtract from the pixel levels. Used when there is a black level offset or “pedestal”. Test carefully, especially if Bit shift is applied (it is applied before Bit shift). Note that the pedestal subtraction is applied after the decompanding (addressed in the Decompanding section). If pedestal subtraction is desired prior to decompanding then it must be set in the JSON decompanding file instead.

Auto offset will be deprecated in 2021.1. Auto offset finds the minimum pixel level (which is a function of pedestal, image content, and veiling glare) and subtracts it from the image. This ruins veiling glare measurements. We strongly discourage selecting Auto offset. An appropriate manual pixel offset is far more consistent.

• Byte ordering—I EEE Little or Big-Endian. Affects results when Input pixel size is uint16. See wikipedia.org/wiki/Endian.
• Width— Image width in pixels. Can usually be obtained from manufacturer’s data sheets. If you enter an incorrect number for width and height (if Width x Height × bytes per pixel ≠ file size in bytes), an additional plot is displayed (see below) to help you estimate the width.
• Height— Image height in pixels.
• Transpose— Switches rows and columns. Usually checked.
• Rotate/Mirror— Allows the image to be rotated by multiples of 90 degrees and/or mirrored.
• Pixels to skip— The number of pixels to skip at the start and end of the file.
• White balance— None or Simple White Balance (gray world; darken or lighten). Simple WB sets the gain on the four channels so their mean is identical (the lowest of the four means if “darken” is selected; the lightest if “lighten” is selected). It’s not a sophisticated algorithm— it only works for mostly gray test charts (some color is tolerated as long as the average is close to neutral gray). WB allows you to interpret the image as a standard monochrome file (rather than a Bayer RAW channel with only 1/4 the pixels) that can be analyzed for MTF with any of the sharpness modules (SFR, SFRplus, Log F-Contrast, Star Chart). An undeomsaiced slanted edge without and with WB is shown below. In this case, white balance was not far off to begin with. For full color correction, we recommend calculating  a Color Correction Matrix (CCM) using the decoded image.

SFR edges: without and with White Balance

• White level— No change or Auto: 99% of saturation. The Auto: 99% setting sets the highest pixel to 99% of the saturation level (252 for 8-bit files; 64880 for 16-bit files). This usually lightens the images, especially if Bit shift is not set to the optimum value.
• Unpack— Settings for unpacking specialized packed files (MIPI, Android). Updated on user request.
• Gamma— Apply gamma encoding to the image. Gamma = 1 is standard: it maintains the gamma (around 1) of the raw image. 0.4545 (1/2.2) (or 0.5) is close to standard color spaces.
• Decompanding— Provides the user with the option to apply decompanding on a raw image using the drop-down menu. To apply decompanding, the user must input their sensor’s companding data using a JSON file. Shown below is an example of a 16-bit to 12-bit companding for the AR0331 sensor. Clicking on the  ?  button to the right of the drop-down menu opens a window with brief instructions.

{
     "dcData": {
          "decompanding_data_source": "https://www.onsemi.com/pub/Collateral/AR0331-D.PDF",
          "decompanding_data_details": "Fig. 19 and Table 9, pp. 20-21",
          "user_comment": "",
          "decompand_type": "piecewise linear",
          "input_code_range_low": [0, 1024, 4096, 32768],                                                                   
          "input_code_range_high": [1023, 4095, 32767, 65535],
          "output_code_range_low": [0, 1024, 2560, 3456],
          "output_code_range_high": [1023, 2559, 3455, 3967],
          "pedestal": 0
     }
}

{
     "dcData": {
          "decompanding_data_source": "Customer-supplied data",
          "decompanding_data_details": "Input is uncompanded; output is companded",
          "user_comment": "",
          "decompand_type": "piecewise linear",
          "bitshift_first": -4,
          "kneePoints_input": [0, 2048, 65536, 1048576],
          "kneePoints_companded": [0, 2048, 3040, 4001],
          "pedestal": 16
     }
}

[dcData]
decompanding_data_source = Customer-supplied data
decompanding_data_details = Input is uncompanded; output is companded
user_comment = 
decompand_type = piecewise linear
bitshift_first = -4
kneePoints_input = 0 2048 65536 1048576
kneePoints_companded = 0 2048 3040 4001
pedestal = 16

The JSON format data above are based on entries in Table 9 of the AR0331 link. The JSON format data above are based on entries in Table 9 of the AR0331. The “input_code_range_…” refers to the image sensor data and the “output_code_range_…” refers to the companding data in the JSON file. For more information, refer to tables 9 and 10 in the AR0331 documentation. The  Decompand plot  button produces a plot of the decompanding file, useful to check on the JSON settings, which have a rather inflexible format. Either Decompanding or Companding can be selected (Decompanding is shown below). There is a small image in the center of the plot showing the approximate shapes of the two curves— important for avoiding errors caused by confusing input and output data.

Decompanding plot preview, showing contents of the JSON file

• Demosaicing—Choose between None (monochrome output), a demosaicing routine (for Bayer images; color output), or RCCC processing (monochrome output). Selections are similar to the Monochrome window (above; repeated here).

• Bayer arrangement (location of red channel).
• Output file Save the file. None (do not save; read-only), PNG, JPEG, TIFF or HDR (Radiance) file. Undemosaiced files can be opened with Rawview.
• Convert/Test Saves the settings, then reads and displays a raw image file or batch of files (example on right). If the actual size of the file read is not equal to the Pixel Width x Height, the image will be displayed with the same Width and an adjusted height and two diagnostic images (shown below; for estimating the correct width) are displayed. The text below the plot displays the specified Width, Height, and W x H and the actual number of pixels returned (which will equal W x H if the correct values have been chosen). Available output formats include PNG, JPEG, TIFF, and HDR 
• Save Saves the settings without closing the Read Raw window. Use this for testing Read Raw by directly reading images into Imatest modules.
• OK Saves the settings and closes the Read Raw setup window.
• Help (on the upper-right) opens this web page.

• Sequence of operations opens a window that displays the normal sequence of operations (shown below). Useful for answering frequent questions. Note that all of the operations are optional: they are only performed if specified. It’s surprising how many operations are performed on the Bayer image before demosaicing.

Estimating image width and height

If the number of pixels read from the file, excluding the skipped pixels at the beginning or end of the file, is unequal to the specified image Width x Height, a diagnostic plot displays estimated file periodicities (the largest periodicity is normally equal to the pixel width of the image) as well as several guesses for the image dimensions. The image below was obtained by a deliberately entering an incorrect value for Width.

The periodicity is derived by calculating the Fourier transform of the one-dimensional image data, finding the absolute value (i.e., removing the phase), then taking the inverse Fourier transform. The location of the largest peak (above 0) is the most likely periodicity. In this case it’s 4096, shown on the upper right. Since this estimate may not work for all images, additional possible widths (periodicities) are displayed. 

Read Raw diagnostics plot showing most likely periodicity and image size guesses

The guesses for pixel width * height are useful if the numbers are integers (no fractional parts). In this case the first guess (4096 * 3072, based on dividing the total pixels by the most likely periodicity) turned out to be correct, and the same dimensions appeared for the 4:3 aspect ratio. The other aspect ratios were clearly incorrect. The information in this plot can be used to improve the Width and Height entries in the Read Raw setup window.

Creating Synthetic Raw images

There are occasions where raw images are needed to analyze the performance of signal processing algorithms, but real raw images (from cameras) may not be available. For such situations, images used in Rescharts, Color/Tone Interactive, Uniformity-Interactive, and Image Processing can be saved as pseudo-raw images.

Where high quality images are needed, we recommend running the Test Charts module and saving the chart image. Test Charts produces two types of image file: bitmap charts, which can be loaded directly into any of the modules listed above, and SVG (Scalable Vector Graphics) files, which can be opened and edited in Inkscape (an outstanding free open-source program) and exported as bitmap (PNG) files. Both types of image can be edited, for example to change a black & white image to black and red or blue (worse cases for Bayer demosaicing). We frequently recommend the Image Processing module, which can read any file image and degrade the image (adding noise, blur, etc.) then enhance the image (using tone mapping, bilateral filter, Unsharp Mask, etc.).

To save a “pseudo-raw” file, click on the File dropdown menu on any of these modules, then click on Save pseudo-raw/remosaiced image. This opens the Save (re)mosaiced image dialog box.

Save (re)mosaiced image (as Bayer raw) dialog box

This window offers numerous processing and save options.

• Mosaicing or channel selection  determines the basic operation. Choices are

None (Normal color file output)
Remosaic (Bayer format)   (default— standard Bayer mosaicing.)
RCCC (Red-Clear-Clear-Clear): R bright
RCCC (Red-Clear-Clear-Clear): R = C/3
Monochrome (Y = luminance)
Monochrome (mean: equal weights)
Red
Green
Blue

• Red channel location  This applies to Bayer-mosaiced and RCCC images.

1. Red in R1C1  (RGGB)
2. Red in R1C2  (GRBG)
3. Red in R2C1  (GBRG)
4. Red in R2C2  (BGGR)

• Rotate/mirror

1. Keep orientation       (default)
2-4. Rotate CCW   90, 180, 270 degs
5. Mirror   (no rotate)
6-8. Mirror,  Rotate CCW   90, 180, 270

• Gamma adjust (multiplier)  (defaults to 1) This is used to more-or-less restore linear tonal response to pseudo-raw images derived from gamma-encoded images. For a typical color space file, with encoding gamma near 0.5, gamma = 2 is appropriate. Even better: use the inverse of encoding gamma measured from a grayscale chart.
• Save file format  selects format for saving the file. Four standard image file formats can be selected: PNG (default), JPG, TIF, and BMP. PNG is frequently a good choice because it’s losslessly-compressed, and smaller than TIF or BMP files. JPG produces compact file sizes (but JPEG is not generally recommended because lossy JPEG compression can affect isolation between channels). Standard image files can be examined with Rawview.
  Two binary formats can be selected: 8 and 16-bit. These can be decoded with Generalized Read Raw.
• Extension (for binary)  is only enabled when one of the binary formats (above) is selected. Select a name for the extension (often RAW, but a unique extension is recommended).
• Green channel emphasis  makes the saved file look more like typical raw files, where the green channel tends to have more energy than the other channels. Selections are
  No emphasis: RGB equal weighting    (default)
  Green  (Blue/2, Red/2)
  Green  (Blue/3, Red/3)
  Green  (Blue/2, Red/4)
  Green  (Blue/4, Red/2)

Preview opens a preview image, typically displayed as a mosaiced (Bayer-raw) monochrome image. Save the image and use Rawview to see what the demosaiced image will look like.