I’m trying to superimpose a batch of hundred black and white images so that they blend with 1% opacity and “darken only”. The multiplicity of. Imagemagick has a convert utility which can perform brightness and where is to darken by 30 and +10 is to increase the contrast by Images darken when getting converted with ImageMagick. When using ImageMagick to manipulate images, you might see that images get darker when beeing.
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Whether it is to lighten or darken the image, or more drastic color modifications. To explore these technqiues we will need a test image Don’t worry above how I actually generated this image, it is not important for the exercise. I did design it to contain a range of colors, transparencies and other features, imagdmagick to give IM a good workout when used. The color processes below generally assumes the image is using a linear colorspace.
Most images are however saved using a sRGB or Gamma corrected colorspace, as such to get things right colorspace correction should also applied first.
Converting Color to Gray-Scale Gray scale images can be very useful for many uses, such as, furthering the processing of the original image or for use in background compositions.
The best method of converting an image to gray-scale is to just ask IM to convert the image into a gray-scale Color Space representation for the image. Normalise and other Histogram operators are really grayscale operators, caution is needed when using it with color images. This is equivelent to the use of the ‘ recluma ‘ conversion formula with the dedicated ” -grayscale ” operator Added IM v6.
Here for example is the other common greyscaling formula ‘ recluma ‘ convert test. For example, you can drain all the color out of the image by using the Modulate Operatorto set all color saturation levels to zero.
Another way is to use the FX DIY operator to average the three channels together to get a pure mathematical meaning of gray-scale.
Or the ‘I’ channel of HSI. Another technique is to simply add all three channels together a color measure known as manhatten distance and while the resulting image will not loose information due to ‘quantum rounding’ effects, you may loose information about the brightest colors. Unfortunately, you also loose the transparency channel, too. You can use the same adding channels technique to control the weighting of the individual color channels.
For example this is one DIY formula that you can use You can also use ‘intensity’ if you want the same meaning within the ” -fx ” operator. For more complex operations you can use the simpler Evaluate Operator” -evaluate “. The above would suffer from ‘quantization’ effects for a ImageMagick compiled at a ‘Q8’ Quality Level. That is because the results of the ” -evaluate ” will be saved into a small 8 bit integer, used for image values.
Only later are those values added together with the resulting loss of accuracy. Another new alternative is the Poly – Weighted Image Merging Operatorwhich will do the weighting and addition of the separated channel images in one operation, so avoiding ‘quantum rounding’ effects.
A similar technique can be used to generate a pure mathematical gray-scale, by directly averaging the three RGB channels equally. You can also use ” -type ” to tell IM to treat the image as gray-scale, when either reading or writing the image. The ” -type ” setting is generally only used as a guide when an image is being read or written to a file. As such its action is delayed to the final daeken of the image.
Its effect is also highly dependant on the capabilities of iamgemagick image file format involved and is used to dzrken ImageMagick’s normal determination during that process. See the Type examples for more information. This was fixed as soon as I noted the problem and reported it. There is a lesson here: Be warned that the ” -level ” operator treats the transparency channel as ‘matte’ values.
Please take this into account when using ” -level ” with a blurred shape image. This is most typically done after blurring an ‘shape’ image, to expand and stretch the results. For examples of this see Soft Edgesand Shadow Outlines. For reasons about why you should used this function see Gamma Correction. For those interested, the corrected formula for the ‘sigmoidal non-linearity contrast control’ is Here is a alternate version of the formula using intermedite variables.
That is, the graph always goes though the points 0,0 and 1,1. And the highest gradient of change is at the given threshold. Lucky for us IM v6. The histogram can be generated for each channel separately or as a global histogram which looks at values from all the channels combined.
Darkening gray text with ImageMagick – Dev pro tips
The result is often displayed as a image of a dqrken chart. In IM, this is done using the special Histogram: For practical reasons imagemaigck do with JPEG color inaccuracies see JPEG Color Distortion for more details and scanned image noise, ” -normalize ” does not expand the very brightest and darkest colors, but a little beyond those values. This means if highest and lowest color values are very close together, ” -normalize ” will fail, an no action will be taken. If you really want to expand the exact brightest and darkest color values to their extremes use ” -auto-level ” instead.
If you want the old ” -normalize ” behaviour before IM v6. For images that contain no alpha or matte channel, you can just use the ‘ all ‘ channel setting. Alternatively, you can normalize each channel as a separate image using the ” -separate ” operator as of IM v6.
Under Construction Linear-Stretch In many ways ” -linear-stretch ” is very similar to the previous ” -contrast-stretch image,agick operator. Both functions can take black-point and white-point arguments as either raw counts or as percentages of the total number of pixels involved.
However there are several important differences. One difference has to do with how the default black-point and white-point is computed. With ” -contrast-stretch “.
If only one value, the black-point, is provided, then the white point will be the same value. However, with ” -linear-stretch “, imagemagic, only one value, the black-point, is provided, then the white point will be the complement value. That is, if the black-point is specified as a raw count, then the white-point will darkenn the total pixels in the image minus the black-point count. The second difference has to do with where counts begin.
Consider a histogram with bins some ‘bins’ which may have zero counts going from graylevel 0 to graylevel In ” -contrast-stretch “, counts start at zero with the lowest min and highest max populated bins in the image which may or may not be at bin 0 or bin in the histogram. Likewise with counting from the bright side of the histogram.
With ” -linear-stretch “, the count starts at the ends of the histogram, namely, at bin 0 and bin Thus the amount burned-in at the dark side will always be the black-point value and the amount of burn-in at the bright side will always be the white-point value. As an example, lets take a gradient of pixels and look at its histogram. We see that none of the channels of the above image span the full dynamic range.
Also note that each of the channels spans a uniquely different range of values. However even direct use of color names is possible. Note that the number of parameters ‘ a ‘ to ‘ d ‘ in above needed for curve fitting, must equal the number of control points you provide. Dsrken such if you want five control points you darkej to include another ‘ e ‘ term to the function.
If your histogram curve goes though the fixed control points 0,0 and 1,1you really only need two parameters as ‘ d ‘ will be equal to ‘ 0 ‘, and ‘ c ‘ will be equal to ‘ 1-a-b ‘.
For example lets apply those curves to our test image From that version onwards, as you can see above, it now uniformly tints all pixels including fully transparent pixels. However from IM v6. See Alpha On for more details. Without this protection, colorize would have fully-blanked the canvas to the given color The ” -tint ” operator works by somehow taking the color and percentages given then then adjusting the individual colors in the image according to the ” -fill ” colors intensity, as per the following formula.
As you can see gives a complete replacement of the color for a pure mid-gray, with no adjustment for either white or black. At this time, the a pure mid-tone gray color will not be mapped to the ” -fill ” color. The percentage argument is not a ‘blend percentage’ but really more a ‘brightness percentage’. It will for example not work at all for a ‘black’ fill color.
I do not know why it was designed this way or the history behind it. It does however make exact control of the final colors when tinting grayscale images, very awkward. Using Overlay Compostion Tinting below will provide a more exact though very linear, rather than parabolic color tinting of mid-tone grays. For example here I quickly generate a colored overlay image, and compose it to tint the original image. The alpha composition method ‘ HardLight ‘ will produce the same results as ‘ Overlay ‘ but with the source and destination images swapped.
They are the same colorspace, but ‘V’ is a confusing term, as a value normally means ‘a stored number’. This was changed because of a bug report by a user about the above situation.
The point is for some images you are damned if you use HSL, and for other images you are damned if you use HSB colorspace. It just depends on what you are attempting to do! That is the ‘grayscale’ intensity equivelent is in the first ‘red’ channel and Hue is in the third ‘Blue’ channel of the image. This colorspace is exacty the same as ‘ LCHuv ‘ but with the channel order reversed Hue stored in Red channel of the image, it was just teh way that colorspace is defined.
This meant you had to also swap the various channels around to allow the Modulate Operator to work correctly. The ‘ LCHab ‘ and ‘ LCHuv ‘ colorspaces order the channels in the same way as ‘ HSL ‘, so as to allow modulate to work properly, and directly on the colorsapce without requiring channel re-ordering. Note that for very dark colors the ‘ LCHuv ‘ can generate color values with discontinuities.
This however should not happen for real images, only images generated directly in the cylindrical space. The matrix forms a special array, known as an ‘identity matrix’. By mixing up the rows you can use to swap the various channels around.