dcraw manual white balance

dcraw manual white balance

You’ll get either a JPEG or a PPM file, depending on the camera. Exit status is 0 if dcraw can decode the last file,Good for photographing black-and-white documents. Twice as fast as -q 0. Use this if the output shows false 2x2 meshes with VNG or mazes with AHD. The best threshold should be somewhere between 100 and 1000. If the result is too light or too dark, -b lets you adjust it. Default is 1.0. Default depends on the camera. To generate a dark frame, shoot a raw photo with no light and do dcraw -D -4 -j -t 0. If this is not found, print a warning and use another method. First do dcraw -j -t 0 and select an area of neutral grey color. These multipliers can be cut and pasted from the output of dcraw -v. This option only affects Olympus, Leaf, and Phase One cameras. Low numbers favor whites; high numbers favor colors. Try -H 5 as a compromise. If that’s not good enough, do -H 9,By default, dcraw applies the flip specified by the camera. -t 0 disables all flipping. For example, Fuji Super CCD SR cameras generate a second image underexposed four stops to show detail in the highlights. For cameras with non-square pixels, do not stretch the image to its correct aspect ratio. In any case, this option guarantees that each output pixel corresponds to one raw pixel. It must count as (probably) the greatest and most influential little program of the last 20 years. It isn't a library, and it's difficult to pull apart to tweak it in the directions I want, or even to understand. But what it does, it does well. As written by Dave Coffin, it doesn't have an option to name the output file.The Jasper library is only used for a type of camera I don't have, and my computer doesn't have the library. These are the Cygwin bash commands I use: My patch changes the behaviour of the program, so I don't (currently) call it dcraw.exe. I run it indirectly, via an environment variable. The idea is that if the maximum value is 75%, multiplying by 1.http://utopyainsaat.com.tr/fckfiles/cubase-5-manuale-italiano-pdf.xml

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3333 will use more of the range between 0 and 100%. ( dcraw won't also stretch the bottom, so if the minimum value was 10% it might become 13.333%. Why won't it stretch both ends.This is a lot of pixels. An area one-tenth of the image width and one-tenth of the height amounts to 1% of the image area. The whole point of using raw images (for me) is to get good pixels from the camera, giving me more flexibility than the in-camera JPEG provides, and hence better quality. Wrecking 1% of the pixels before I even begin the creative stuff is a bad start. The variable is used in a line that used to read. Multiplying channels can result in clipping. A larger number recorded the maximum signal, so the sensors were saturated (the amount of light was at or beyond the capacity of the sensors). (The camera has 35 M pixels, so the proportion of pixels that are clipped, 0.05%, isn't horribly bad.) We want to avoid increasing the numbers at either end. This normalises the WB channel multipliers so the smallest multiplier is 1.0, so values in other channels can increase, so this can cause clipping in those other channels. However, this clipping means that pixels recorded at or near 100% in all three channels will become exactly or nearly white after the balancing, which is normally the correct result. Modes from this upwards normalise the WB channel multipliers so the largest is 1.0. It also does other processing that I don't understand. Other parts of the image are darker than the previous version, and this is expected as the multiplier normalisation has reduced instead of increasing values. During the photography session, we include a standard colour card in one of the photos. We automatically find the patches, and the lightest patch should be a neutral gray, so this gives us the channel multipliers. In either case, we can't use -r to change the overall lightness of the image.http://www.ridendo.cz/files/cubase-5-manuale-italiano.xml

We could choose any pixel on that row to give us the multipliers for red and blue, compared to green, but the lightest patch will show a colour-cast most easily, so we choose it. We are not concerned with the absolute values in the channels (eg whether the patch is pure white or 90% white), but only with their relative values. This time, we include the conversion to sRGB. The others are fairly close, though not exact. We have ignored the camera's WB metadata, and used dcraw features to balance a stepped gray card. We can use the same settings to balance all photos (or video frames) taken under the same conditions. What happens then? We repeat the above with auto-brighten but without any clipping. So setmnsd needed a steeper curve to make the SD 0.166667, which has visibly increased the saturation. In my opinion, both results are satisfactory. I like the This multiples all the channels by the same number, after de-Bayering, but still in linear RGB space. If we have auto-brightened, some pixel values will already be at 100%, and -b will increase them further, causing more clipping. This seems to be caused by dcraw's conversion to sRGB. So, we can do that in IM instead. This changes the process from the second dcraw onwards, but we show the complete process for clarity. But what proportion is reasonable. I think 1% is far too high, but how can we determine the right amount. One possibility: any pixel that is already at maximum in at least one channel, and has high values in the other channels, can be safely clipped. Copyright: Copyright (C) 1999-2015 ImageMagick Studio LLC. License. Features: Cipher DPC Modules OpenMP. Delegates (built-in): bzlib cairo flif freetype gslib heic jng jp2 jpeg lcms lqr lzma openexr pangocairo png ps raw rsvg tiff webp xml zlib Anyone is permitted to use or adapt any of the code, scripts or images for any purpose, including commercial use. The software has the capability of converting raw image files from 202 cameras as of this writing.

For some cameras, this is the only piece of software that can read and convert the camera's raw format. The software is also executed on the command-line so that it is very flexible and powerful.Because it is a free software, written by an individual, and used by many power users, the learning process has been an ad hoc trial-and-error, I-know-what-I-am-doing approach. There are no instruction on how to use it and what kind of result you would produce with this software.So I have been processing the raw files with dcraw. However, with numerous command-line options, there could be endless results generated by the dcraw software. Without a good visual example of each option, and no manual to reference to, I have a hard time keeping track of what options I should be using. Each option is divided up into its own section with its own description and pictorial example. At the end of each section, I also show the detailed output message from dcraw for that specific option, because sometime the output contains interesting processing details. If the details look overwhelming to you, skip it.However, I present it here for reference.Valid options:The only time it produces output is when it encounters warnings and errors. By using the -v option, dcraw will output messages to update you on its progress along the way. Below is an example of messages it output while processing an image.Loading NIKON E950 image from dscn0040.jpg. Bilinear interpolation. VNG interpolation. Converting to sRGB colorspace. Writing data to dscn0040.ppm.Those will be covered later in each section.The following is an example output:Filename: dscn0040.jpg. Timestamp: Sat Jan 22 18:03:40 2005. Camera: NIKON E950. ISO speed: 188. Focal Length: 11 mm. Embedded ICC profile: no. Decodable with dcraw: yes. Full size: 2048 x 1203. Image size: 1616 x 1203. Output size: 1616 x 1203. Raw colors: 4. Filter pattern: YCGMYCGMYCGMYCGM. Daylight multipliers: 1.181930 1.000000 1.164520 1.

172500It simply processes the raw image data as seen by the sensor. If you evoke the -a option, it will use its own AWB algorithm to process your images. The following is an example of the default process (left) vs.Loading NIKON E950 image from dscn0040.jpg. Writing data to dscn0040.ppm.In the case of this image, the camera was set to AWB. The picture on the left was processed with no options. The picture on the right was processed with the -w option.Converting to sRGB colorspace.Converting to sRGB colorspace.If you don't specify this option, dcraw defaults to outputting the data into the sRGB color space.If you know how to display this file, please let me know.Loading NIKON E950 image from dscn0040.jpg. Building histograms. Writing data to dscn0040.pam.This is also the default mode of operation, so you don't need to specify this flag.So if you are writing a batch conversion script, and you know you always want your image to be in sRGB color space, then you need to explicitly specify this flag.The image on the left is an example of the sRGB color space. The image on the right is an example of the Adobe 1998 RGB color space.Loading NIKON E950 image from dscn0040.jpg. Converting to Adobe 1998 RGB colorspace. Writing data to dscn0040.ppm.The image on the left is an example of the sRGB color space. The image on the right is an example of the Wide Gamut D65 color space.Loading NIKON E950 image from dscn0040.jpg. Converting to Wide Gamut D65 colorspace. The image on the right is an example of the XYZ color space.Loading NIKON E950 image from dscn0040.jpg. Converting to XYZ colorspace. Writing data to dscn0040.ppm.The output is a gray scale image. This form of processing is faster because the process bypasses the bilinear interpolation and the VNG interpolation that are done in a normal color process.The image on the right is the Document Mode output.

The shrunken image on the right doesn't show the raw texture of the image, so the third image below shows a cropped version of the image at 1:1 ratio. Note the half-tone like texture.Loading NIKON E950 image from dscn0040.jpg. Writing data to dscn0040.pgm.I then process the exact same image with the -a (AWB) option and the -d (Document Mode) option. The results are shown in the pictures below.The picture on the right is processed with the Document Mode option.The picture on the right is an 1:1 ratio image of the text processed with the Document Mode option. And so far he has achieved that. DCRAW works in Linux so as in Windows and Mac. In this tutorial we will make use of the Windows version although it will work exactly the same way in the other two platforms since DCRAW has no graphic user interface being a 100% command line application. DCRAW requires no installation, just copy the executable file into the appropiate pathname and invoque it from a terminal console. There are several front-end interfaces that make DCRAW more easy to use such as UFRAW, although in my opinion they lack of that extra of power and flexibility that DCRAW provides for not presenting to the user all its options in a straightforward way. In addition to this it is usual that a new feature or improvement appears every month, so any front-end gets quickly old fashioned. Mi advice: to learn how to use straight DCRAW. DCRAW alone is not a friendly tool and because of this could not be ideal for your usual workflow. However thanks to the transparency and power of its low level control, it becomes the perfect tool to perform tricky RAW developments in specific cases such as: The key is to do in Photoshop all those extra features that other RAW developers can do apart from pure development, and consider DCRAW as a tool that provides a rough image without any kind of processing applied on it, just a high quality development under absolute control.

It is the only RAW developer I have found up to now that transmits the certainty of being performing on my RAW files exactly what I want to be applied to them and not what the RAW developer wants to; in fact as we will see it can do things that are out of reach in other more popular commercial RAW processors such as Adobe Camera Raw. You will learn a lot about RAW theory and sensor linearity when using DCRAW. It is a piece of software that makes you feel very close to your RAW data.Windows DCRAW versions require no installation since they consist of just a single compact.exe console application file. This file is named dcraw.exe and can be directly copied in the C:\WINDOWS\ path to be accesible from any folder when it is called in the command line.A window with a black background will pop up and we will type dcraw on it so that DCRAW will display all available options: Fig. 1 Command line displaying all DCRAW v8.82's available options. As we saw in the previous section DCRAW has multiple options for which a description can be found in David Coffin's manpage. I will only go through the options I consider more interesting for high quality RAW development. Options are used writing single letters preceded by a dash symbol after the dcraw command, and are: -v Provides textual information about the RAW development process (recommended). -e Extracts the JPEG embedded in the RAW file, i.e. the JPEG file the camera generated for the camera display preview which differs from the JPEG file obtained when the camera is set in JPEG mode. It is a very quick way to get a JPEG view for all the RAW files contained in a folder. These 4 values are the multipliers that will scale linearly all levels found in the RGBG channels in that order. The white balance means a scaling of image levels therefore all levels will move from their original positions which could not be desirable in certain cases. If we are not to perform any white balance we will use the option -r 1 1 1 1.

This feature will be also studied deeply in the white balance and highlights section. I mainly use the -H 0 option for its linearity and -H 2 when there is risk of blowing important parts of the image with the previous value. The -H 1 option guarantees that we will not blow any previously non blown channel but can lead to strange tones in the blown areas. The highlight recovery options are more sofisticated and slow down noticeably the execution speed. -k n1 and -S n2 Respectively set the black and saturacion levels that will be used in the RAW development. Although it is best to let DCRAW calculate the black level, it is very interesting however to set the saturation level by ourselves for our particular camera with -S. -D Extracts an image with the pure RAW data without any demosaicing or scaling applied. It is very useful to analyse the real captured levels in the sensor's native range of 12, 14 or 16 bits. -d As the previous command, it does not perform any demosaicing but goes one step ahead in the development process since it adjusts black and saturation points, white balance and rescales to the output 16-bit range. It is very interesting to get linearized (for substracting the black point) undemosaiced data in a 16-bit scale with dcraw -d -r 1 1 1 1 that allows to obtain histograms in stops of exposure with Histogrammar. It can also be used to study the Bayer pattern of the RAW file, permitting for instance to detect malfunction in the camera sensor or individual anomalous pixels: The more quality the more complex the algorithm will be and thus less quick, however DCRAW is very fast in all of them. I always use the last value which is an adaptive algorithm providing very good results, although according to the author DCRAW will use by default the best algorithm for each camera model. In this way for Fuji cameras the method -q 2 is better than -q 3. Fig. 3 Crops at 200% of different interpolation quality values.

-4 It generates a linear 16-bit file instead of an 8-bit gamma corrected file which is the default. I always use this option. -T It outputs a TIFF image file instead of PPM. -g gamma slope Applies a gamma correction to the output defined by the gamma value and the toe slope of the curve. If we make use of the -4 option the development will produce a 16-bit linear output. This is the mode to which I will refer in the rest of the tutorial since it is the mode that allows to take advantage of DCRAW's main strongholds. A linear image cannot be displayed due to its extreme darkness as the histogram is densely concentrated on the left side of the range, but as we will se later PS allows to display correctly this kind of images without altering its internal data. To see what a linear histogram looks like let us take the following scene: Fig. 4 RAW development sample image. The previous photograph developed with a gamma correction would have the following histogram distribution: Fig. 5 Resulting histogram of gamma corrected development. However when we develop it using DCRAW and the -4 option we get the following linear histogram: Fig. 6 Resulting histogram of linear development using DCRAW. There are obvious differences. We can see how the information is concentrated in the lowest f-stops corresponding the whole second half of this histogram to only the last f-stop (marked as 12) which is almost empty as it only contains the highlights of the scene. The next quarter of the histogram corresponds to the next f-stop (marked as 11), and so forth up to completing the 12 f-stops we can achieve to capture using the 12-bit RAW sample file used. We must not think that the higher concentration of information due to the linear development means we are losing tonal richness.

This is not like that at all, in fact a gamma corrected histogram starts from a linear one to which a gamma correction curve has been applied and that is why a lot of holes are created in the low end of gamma corrected histograms. The tonal richness is not increased nor reduced for using one or the other kind of image. For being the image information in a linear format, any possible linear transformation is very obvious; so the application of a white balance or exposure control become as we will see later very simple linear scaling operations over the levels.We will comment them in the same section for being closely interrelated. Depending on the highlights behaviour chosen, the white balance can lead to blow certain areas of the image that were not blown in the original RAW file data. This is common to all RAW developers and we will study this in detail later.We must point that a particular white balance does not mean an absolute set of values for all those multipliers, but the relative proportions between them. In this way the same white balance can be achieved with different sets of factors as long as they keep their relative proportions. The multipliers may have 3 different origins depending on the option used: -w White balance is set according to camera settings at the moment of the shot -a Automatic white balance calculated by DCRAW over the whole image -r m1 m2 m3 m4 Custom white balance by chosing the individual multiplying factors If none of these options is used, DCRAW will take by default a white balance preset corresponding to lighting a grey card with a standard D65 light source. The correct linear values to be applied will vary from one camera to another. To try to guess which values are to be used to get a correct white balance is not an easy task. However it is very simple to obtain the factors that correspond to each of the camera white balance presets which is a good start point.

To do this we just need to take a shot with each of the presets and develop the resulting RAW file with the -v -w commands that will display those numbers. Find here a table of the RGB multipliers to achieve different white balance presets in the Canon 350D: If doing so, we will be able to adjust later the white balance making use of the linearity of the histogram being this the best way to test different white balance values until we reach one that satisfies us. However this is not a recommended way to apply the white balance, just to calculate the multipliers. We should go back and use the calculated factor with the -r command as interpolaton Bayer algorithms are optimised to work on already balanced images.It is the -H command who will decide if values are taken in one range or another. With greater or equal to 1 multipliers we will guarantee that no tone artifacts will happen due to the white balance operation. As a drawback we will be in risk of blowing partially (not all channels) or totally certain areas of the image due to saturation as we are increasing the image exposure with these values. -H 0 is the default mode if the highlight option is not set. On the other hand less or equal to 1 multipliers will guarantee for all pixels that no channel that were not really blown in the RAW file will blow now because of the white balance scaling. All this sounds very complicated but it is not, let us take the previous example. In it with -w and -H 1 the following multipliers were generated: But there is a clear difference in what will happen when applying them: as -H 0 multipliers are greater or equal to 1 we could blow some channels that were not in the original RAW file. Anyone who has fiddled with the Temperature parameter in ACR will have noticed that moving this control may lead to blown areas or make previously blown areas not to be blown any more. It's the same effect here. But we must not think that for this -H 1 is always better.

In fact is usually the contrary, we must use this last parameter value very carefully, and only if we are sure our image has no pixel at all blown. In that case we can use -H 1 without any undesirable effect. However everytime an image has some blown area in the RAW file (and this includes metallic reflections, light bulbs, lamps,.) this is what we would get in case of using -H 0 and -H 1 respectively: Fig. 7 Result of development using -H 0 and -H 1 respectively. In the first image we have probably blown some channels that were not in the original RAW file, but we have preserved the white colour of the blown highlights. On the other hand, the second image because of making use of multipliers less than 1 in the R and G channels, leaving B unaltered, the proportions of those three channels in the blown areas have changed turning into an undesirable magenta cast. The phenomenon can be seen in the -H 0 vs -H 1 histograms (look at the decomposition of blown areas in three peaks in different level locations): Fig. 8 Histograms obtained when developing with -H 0 and -H 1 respectively. The -H 2 value has a similar behaviour to -H 1 as will force multipliers to be less or equal to 1, but will fix this problems by applying a slight non linear correction in the highlights to guarantee a netrual (grey) colour in the blown areas. To finish just to point that as the white balance means a scaling of all levels by a linear factor, we will be altering their exposure, which could be adjusted with the linear exposure control we will discuss later. This is the reason why the image developed with -H 0 (greater or equal than 1 multipliers) looked brighter than the one developed with -H 1 (less or equal than 1 multipliers).These modes will take the tone from the non blown areas in the neighbourhood to fill the blown areas.

The higher the parameter value is set, the more effort will be done in emulating the surrounding tones and less guarantee to obtain neutral (grey) tones in the burnt pixels. Following is an example of the different performance concerning highlight recovery in an image with partially blown areas in the RAW file (bright areas in the girl's skin) comparing ACR and DCRAW. While the first pushes the blown areas to neutral grey colours, in DCRAW we chose the -H 9 parameter to try to emulate the skin tones. Fig. 9 Highlight recovery comparision ACR (left) vs DCRAW (right). In this case DCRAW's strategy worked better as it imitates very well the skin tones minimising the perception of undesired shiny areas. This does not mean that DCRAW will work better in any case at all. That will depend on each case according to the characteristics of the image and its blown areas.It is best not to specify the black level with -k since DCRAW will calculate it much better than us from the hidden sensor pixels. However the saturation level -S is closely related to the behaviour of the RAW developer in the highlights so it is very interesting to be able to set it since DCRAW, like any other RAW developer, will use a standard saturation value for each camera model, but this value could be unadequate for our particular unit or ISO set, or could simply be wrong in David Coffin's source code: We shall take an example from a Canon 40D RAW file with blown highlight areas shot at ISO100: We can see DCRAW for this particular 14 bits camera applies a default saturation level of 16224 that produces wrong tones in the highlights. This is because this level value is too high for the tested camera. With the -D command we can analyse the RAW file to find out exactly at which level clips this sample of 40D: The camera under test saturates at level 13824, sensibly lower than DCRAW's default value.

We develop again now making use of this new saturation level and we can see how the magenta tones disapperar without losing any information at all: The reason for the histogram not to reach the maximum is because we made use of a white balance with lower or equal to 1.0 multipliers which guarantees that no information will get blown in the highlights producing a slight underexposure.In these cases I have found that the correct way to proceed is to choose the lowest available saturation point, so that any higher value will be considered as saturated by DCRAW with the guarantee of neutral highlights. For example let us take a RAW file from the Olympus E-510 with the following RAW histogram in the blown highlights: Fig. 13 Pure RAW histogram showing saturation levels. DCRAW uses by default a saturation value of 3946 for this camera, producing slightly magenta highlights.It would not be strange that the problem disappears just by using a different RAW developer. In the case of DCRAW the neutral highlights strategy with -H 2 works perfect, but it is quite common to find default saturation points unadequate for some cameras. For them we will have to calculate and apply it using the -S command. To find out more about this important parameter please refer to The RAW saturation level tutorial.When doing this PS will ask in which colour space the document must be open. If we told DCRAW to convert the data into some colour space PS will detect it and we just need to tell PS to assign that colour space. If we did not, and the TIFF file has not colour managed (option -o 0 ), we should tell PS to perform no colour management at all. The ideal situation however is none of these options but to have the profile of our camera, i.e. a profile generated after calibrating our own camera. In that case we would develop the RAW file withour any colour management (option -o 0 ), and in the file open operation we would assign our camera's own profile to it.

In the three cases the image data will be in linear format, but if we have asked DCRAW to convert it to some colour profile the program keeps some information into the TIFF file which will inform PS that the data is in linear format so it will automatically display it with a corrected gamma. On the other hand if we did not convert to any colour space the image will display tremendously dark, do not panic.By doing this we are not altering the image data at all which remain linear exactly as DCRAW produced them. We just need to display the image's histogram to see how concentrated to the left it is. If now we try to edit our image with curves for instance, it will be an impossible mission because of that concentration to the shadows. Unfortunately PS is not designed to do a proper linear edition, so its curves and the rest of tools do not have enough precision in the low end of a linear histogram to properly work on it. What we will be able to do now taking advantage of the linear state of the image data is: EXPOSURE CORRECTION USING CURVES. To perform this operation making use of a curve is as simple as: Fig. 15 Curves for exposure correction. Of course all intermedium levels are also possible for an exposure fine tuning.To find out the curve that models some particular multiplier we just need to do the conversion of it into the 0.255 range of the curve. All implications we studied about the influence on using a greater or equal to 1 or a less or equal to 1 multipliers set apply now. We must not be afraid of how radical these curves are as the histogram is linear and we already saw how deeply the information concentrated to the left. The good point of adjusting the white balance with curves is that we can set them in a adjustment layer and tune them till we get the right proportion of channels to perform a correct white balance.