In Black And White Photography Colors Are Translated Into Many Different Values Of Gray

best black and white pictures In Black And White Photography Colors Are Translated Into Many Different Values Of Gray

best black and white pictures In Black And White Photography Colors Are Translated Into Many Different Values Of Gray

Black and white photography
Color changes induced by simultaneous contrast on lightness
Black and white conversion photoshop
Black and white photography
Traditionally black and white photography has been a contrasty medium in color photography big contrast is often discouraged in the days of film
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Mastering black and white photography the photographers almanac medium
Many photographers mix up the concepts of brightness value and contrast this photograph of the flower has a low brightness value but still displays a
Black and white was once the only means we had to communicate photographically that was long before most of us got involved with it but for some of us
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Levels curves
Chambered nautilus by pat david without color
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Via grayscale¶
Monochrome vs black and white photography high contrast abstract photo of wavy white

Color depth 1-bit monochrome 8-bit grayscale 8-bit color 15- or 16-bit color (high color) 24-bit color (true color) 30-, 36-, or 48-bit color (deep color) Related Indexed color Palette RGB color model Web-safe color                                

Original Color Photo Red Filter Green Filter Red-Green Combination

Desaturating the colors in an image is the simplest type of conversion, but often produces inadequate results. This is because it does not allow for control over how the primary colors combine to produce a given grayscale brightness. Despite this, it is probably the most commonly used way of converting into black and white. In Photoshop, this is accomplished by going from Image > Adjustments > Desaturate.

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If the original color image has no defined colorspace, or if the grayscale image is not intended to have the same human-perceived achromatic intensity as the color image, then there is no unique mapping from such a color image to a grayscale image.

Using the lightness channel in lab mode is quick and easy because it converts based on the luminosity value from each pixel’s RGB combination. Please see “Understanding Histograms: Luminosity and Color” for further reading on this topic.

Each window will be named “Hue/Saturation 1 or 2,” however I have given these custom names for this tutorial.

Note that the lightness channel may subsequently require significant levels adjustments as it may not utilize the entire tonal range of the histogram. This is because it requires all three color channels to reach their maximum for clipping, as opposed to just one of the three channels for an RGB histogram.

A colorimetric (or more specifically photometric) grayscale image is an image that has a defined grayscale colorspace, which maps the stored numeric sample values to the achromatic channel of a standard colorspace, which itself is based on measured properties of human vision.

Recall that the noise levels in each color channel can be quite different, with the blue and green channels having the most and least noise, respectively. Try to use as little of the blue channel as possible to avoid excess noise.

Grayscale as single channels of multichannel color images[edit]

Y s r g b = { 12.92   Y l i n e a r , Y l i n e a r ≤ 0.0031308 1.055   Y l i n e a r 1 / 2.4 − 0.055 , Y l i n e a r > 0.0031308. {displaystyle Y_{mathrm {srgb} }={egin{cases}12.92 Y_{mathrm {linear} },&Y_{mathrm {linear} }leq 0.

0031308.055 Y_{mathrm {linear} }^{1/2.4}-0.055,&Y_{mathrm {linear} }>0.0031308.end{cases}}}

Delete both the “a” and “b” channels to leave only the lightness channel (“a” and “b” refer the red-green and blue-yellow shift, or “chrominance”).

Contrary to what one might initially assume, traditional black and white photographers actually have to be quite attentive to the type and distribution of color in their subject.

Then adjust each of the red, green and blue sliders to produce an image to your liking. For an even more pronounced effect, some colors can even have negative percentages.

Technical uses (e.g. in medical imaging or remote sensing applications) often require more levels, to make full use of the sensor accuracy (typically 10 or 12 bits per sample) and to reduce rounding errors in computations. Sixteen bits per sample (65,536 levels) is often a convenient choice for such uses, as computers manage 16-bit words efficiently. The TIFF and PNG (among other) image file formats support 16-bit grayscale natively, although browsers and many imaging programs tend to ignore the low order 8 bits of each pixel. Internally for computation and working storage, image processing software typically uses integer or floating-point numbers of size 16 or 32 bits.

To convert a color from a colorspace based on a typical gamma-compressed (nonlinear) RGB color model to a grayscale representation of its luminance, the gamma compression function must first be removed via gamma expansion (linearization) to transform the image to a linear RGB colorspace, so that the appropriate weighted sum can be applied to the linear color components ( R l i n e a r , G l i n e a r , B l i n e a r {displaystyle R_{mathrm {linear} },G_{mathrm {linear} },B_{mathrm {linear} }} ) to calculate the linear luminance Ylinear, which can then be gamma-compressed back again if the grayscale result is also to be encoded and stored in a typical nonlinear colorspace.[4]

See also[edit] Channel (digital image) Halftone Duotone False-color Sepia tone Cyanotype Morphological image processing Mezzotint List of monochrome and RGB palettes – Monochrome palettes section List of software palettes – Color gradient palettes and false color palettes sections Achromatopsia, total color blindness, in which vision is limited to a grayscale.

Zone System Fifty Shades Of Grey References[edit]

There are also a number of third party plug-ins for Photoshop which help automate the process of conversion, and provide additional features such as sepia conversion or adding film grain.

First convert the image into the LAB color space by clicking on Image > Mode > Lab Color in Photoshop.

Levels and curves can be used in conjunction with black and white conversion to provide further control over tones and contrast. Keep in mind though that some contrast adjustments can only be made by choosing an appropriate color filter, since this adjusts relative contrast within and between color regions. Care should also be taken when using these because even slight color clipping in any of the individual color channels can become quite apparent in black and white (depending on which channel(s) is/are used for conversion).

The reverse is also possible: to build a full color image from their separate grayscale channels. By mangling channels, using offsets, rotating and other manipulations, artistic effects can be achieved instead of accurately reproducing the original image.

So which color filter is best? This depends on the goal of the image, but in general: one can increase contrast in a given region by choosing a filter color which is complimentary to that region’s color. In other words, we want to choose a filter whose color is on the opposite side of the color wheel (right) to the image’s color.

An alternative technique which may be a bit easier is to only add one Hue/Saturation adjustment layer and change the hue of the image itself. On the other hand, this does not allow one to go back and change the color filter hue if it is no longer in Photoshop’s undo history (at least not without unnecessarily destroying bit depth).LIGHTNESS CHANNEL IN LAB MODE

Ordinarily the best results are achieved when the image has the correct white balance. Removal of color casts means that the colors will be more pure, and so the results of any color filter will be more pronounced.

where Csrgb represents any of the three gamma-compressed sRGB primaries (Rsrgb, Gsrgb, and Bsrgb, each in range [0,1]) and Clinear is the corresponding linear-intensity value (Rlinear, Glinear, and Blinear, also in range [0,1]). Then, linear luminance is calculated as a weighted sum of the three linear-intensity values. The sRGB color space is defined in terms of the CIE 1931 linear luminance Ylinear, which is given by

These three particular coefficients represent the intensity (luminance) perception of typical trichromat humans to light of the precise Rec. 709 additive primary colors (chromaticities) that are used in the definition of sRGB. Human vision is most sensitive to green, so this has the greatest coefficient value (0.7152), and least sensitive to blue, so this has the smallest coefficient (0.0722). To encode grayscale intensity in linear RGB, each of the three color components can be set to equal the calculated linear luminance Y l i n e a r {displaystyle Y_{mathrm {linear} }} (replacing R l i n e a r , G l i n e a r , B l i n e a r {displaystyle R_{mathrm {linear} },G_{mathrm {linear} },B_{mathrm {linear} }} by the values Y l i n e a r , Y l i n e a r , Y l i n e a r {displaystyle Y_{mathrm {linear} },Y_{mathrm {linear} },Y_{mathrm {linear} }} to get this linear grayscale), which then typically needs to be gamma compressed to get back to a conventional non-linear representation.[6] For sRGB, each of its three primaries is then set to the same gamma-compressed Ysrgb given by the inverse of the gamma expansion above as

On the bottom adjustment layer, change the “Hue” slider to apply any of the entire spectrum of color filters. This is the main control for adjusting the look from this technique.

Normally these colorspaces are transformed back to nonlinear R’G’B’ before rendering for viewing. To the extent that enough precision remains, they can then be rendered accurately.

Note how the red and green filters make the parrot much brighter and darker than the background, respectively, whereas an intermediate combination of the two makes the parrot blend in more. Also note how the green and red-green filters enhance texture in the feathers, and that the red filter eliminates tonal separation between the feathers and the white skin.

For images in color spaces such as Y’UV and its relatives, which are used in standard color TV and video systems such as PAL, SECAM, and NTSC, a nonlinear luma component (Y’) is calculated directly from gamma-compressed primary intensities as a weighted sum, which, although not a perfect representation of the colorimetric luminance, can be calculated more quickly without the gamma expansion and compression used in photometric/colorimetric calculations. In the Y’UV and Y’IQ models used by PAL and NTSC, the rec601 luma (Y’) component is computed as

But if the luma component Y’ itself is instead used directly as a grayscale representation of the color image, luminance is not preserved: two colors can have the same luma Y’ but different CIE linear luminance Y (and thus different nonlinear Ysrgb as defined above) and therefore appear darker or lighter to a typical human than the original color. Similarly, two colors having the same luminance Y (and thus the same Ysrgb) will in general have different luma by either of the Y’ luma definitions above.[7]

The sum of the red, green, and blue percentages need to equal 100% in order to maintain roughly constant brightness, although overall brightness can also be adjusted by using the “Constant” slider at the bottom. If the aim is to mimic the luminosity perceived by the human eye, set: red=30%, green=59% and blue=11%.

You can get a feel for the distribution of color by first setting each of the color channels to 100% individually.

1 Numerical representations 2 Converting color to grayscale 2.1 Colorimetric (perceptual luminance-preserving) conversion to grayscale 2.2 Luma coding in video systems 3 Grayscale as single channels of multichannel color images 4 See also 5 References

Converting a digital color photo into black and white utilizes the same principles as with color filters in film photography, except filters instead apply to each of the three RGB color channels in a digital image (see bit depth). Whether you specify it or not, all conversion techniques have to use some weighted combination of each color channel to produce a grayscale brightness. Some techniques assume a combination for you, although the more powerful ones give you full control. Each makes its own trade-offs between power and ease of use, and so you may find some techniques are best suited only to certain tasks.

In computing, although the grayscale can be computed through rational numbers, image pixels are usually quantized to store them as unsigned integers, to reduce the required storage and computation. Some early grayscale monitors can only display up to sixteen different shades, which would be stored in binary form using 4-bits. But today grayscale images (such as photographs) intended for visual display (both on screen and printed) are commonly stored with 8 bits per sampled pixel. This pixel depth allows 256 different intensities (i.e., shades of gray) to be recorded, and also simplifies computation as each pixel sample can be accessed individually as one full byte. However, if these intensities were spaced equally in proportion to the amount of physical light they represent at that pixel (called a linear encoding or scale), the differences between adjacent dark shades could be quite noticeable as banding artifacts, while many of the lighter shades would be “wasted” by encoding a lot of perceptually-indistinguishable increments. Therefore, the shades are instead typically spread out evenly on a gamma-compressed nonlinear scale, which better approximates uniform perceptual increments for both dark and light shades, usually making these 256 shades enough (just barely) to avoid noticeable increments.

Shoot in RAW mode if possible, as 16-bit (per channel) images allow for the smoothest grayscale tones and greatest flexibility when using color filters. This also gives the ability to fine-tune the white balance based on the desired black and white look.

Y ′ = 0.2627 R ′ + 0.6780 G ′ + 0.0593 B ′ {displaystyle Y’=0.2627R’+0.6780G’+0.0593B’} .

Be sure to first click on the lower left tick box entitled “Monochrome” for black and white conversion.

Y ′ = 0.299 R ′ + 0.587 G ′ + 0.114 B ′ {displaystyle Y’=0.299R’+0.587G’+0.114B’}

This technique is particularly elegant because it allows you to apply any of the entire spectrum of color filters just by dragging the hue slider. This allows one to quickly assess which of the many combinations of color filters work best, without necessarily having one in mind when starting. It takes a little longer to setup than the channel mixer, but is actually faster to use once in place.

Any black and white conversion which utilizes a significant boost in color saturation may begin to show artifacts, such as increased noise, clipping or loss of texture detail. On the other hand, higher color saturations also mean that each color filter will have a more pronounced effect.

where we use the prime to distinguish these nonlinear values from the sRGB nonlinear values (discussed above) which use a somewhat different gamma compression formula, and from the linear RGB components. The ITU-R BT.709 standard used for HDTV developed by the ATSC uses different color coefficients, computing the luma component as

Color images are often built of several stacked color channels, each of them representing value levels of the given channel. For example, RGB images are composed of three independent channels for red, green and blue primary color components; CMYK images have four channels for cyan, magenta, yellow and black ink plates, etc.

Grayscale images are distinct from one-bit bi-tonal black-and-white images which, in the context of computer imaging, are images with only two colors: black and white (also called bilevel or binary images). Grayscale images have many shades of gray in between.

Colorimetric (perceptual luminance-preserving) conversion to grayscale[edit]

Open this tool by clicking on Image > Adjustments > Channel Mixer in Adobe Photoshop. GIMP and many other image editing programs also offer this tool, however its menu location may vary.

Because the three sRGB components are then equal, indicating that it is actually a gray image (not color), it is only necessary to store these values once, and we call this the resulting grayscale image. This is how it will normally be stored in sRGB-compatible image formats that support a single-channel grayscale representation, such as JPEG or PNG. Web browsers and other software that recognizes sRGB images should produce the same rendering for such a grayscale image as it would for a “color” sRGB image having the same values in all three color channels.

View the “Lightness” channel by clicking on it (as shown to the left) in the channel window. If not already open, the channel window can be accessed by clicking on Window > Channels.

Y l i n e a r = 0.2126 R l i n e a r + 0.7152 G l i n e a r + 0.0722 B l i n e a r {displaystyle Y_{mathrm {linear} }=0.2126R_{mathrm {linear} }+0.7152G_{mathrm {linear} }+0.0722B_{mathrm {linear} }} .[5]

The channel mixer tool allows the user to control how much each of the three color channels (red, green and blue) contribute to the final grayscale brightness. It is undoubtedly one of the most powerful black and white conversion methods, however it may take some time to master since there are many parameters which require simultaneous adjustment.

The intensity of a pixel is expressed within a given range between a minimum and a maximum, inclusive. This range is represented in an abstract way as a range from 0 (or 0%) (total absence, black) and 1 (or 100%) (total presence, white), with any fractional values in between. This notation is used in academic papers, but this does not define what “black” or “white” is in terms of colorimetry. Sometimes the scale is reversed, as in printing where the numeric intensity denotes how much ink is employed in halftoning, with 0% representing the paper white (no ink) and 100% being a solid black (full ink).

Just as with color photography, black and white photography can use color to make a subject stand out — but only if the appropriate color filters have been chosen. Consider the example below, where the original color image makes the red parrot stand out against the near colorless background. To give the parrot similar contrast with the background in black and white, a color filter should be chosen which translates bright red into a tone which is significantly different from the middle gray background. Move your mouse over the options below to view some of the possibilities.

Once all adjustments have been made, merge/flatten the layers to make these final.

The saturation slider can also be adjusted in this layer, but this time it fine-tunes the magnitude of the filter effect for a given hue.

Grayscale images can be the result of measuring the intensity of light at each pixel according to a particular weighted combination of frequencies (or wavelengths), and in such cases they are monochromatic proper when only a single frequency (in practice, a narrow band of frequencies) is captured. The frequencies can in principle be from anywhere in the electromagnetic spectrum (e.g. infrared, visible light, ultraviolet, etc.).

If we wished to maximize cloud contrast in a cyan-blue sky, then a reddish-yellow filter would achieve this goal. Of course, images rarely contain just one color. Although the red filter above decreases contrast in the feathers, it would do the opposite in a cyan-blue sky. Black and white conversion may therefore require interpretive decisions.

Notice the contrast changes both between and within regions of red, green and blue above. Pure red or primarily red color filters often work best for landscapes, as this increases texture in regions containing water, sky and foliage. On the other hand, color filters can also make contrast appear greater than what we would perceive with our eyes, or can darken/brighten some regions excessively.

For the common sRGB color space, gamma expansion is defined as

Y ′ = 0.2126 R ′ + 0.7152 G ′ + 0.0722 B ′ {displaystyle Y’=0.2126R’+0.7152G’+0.0722B’} .

The image below contains regions of red, green and blue; move your mouse over each filter and note its influence on the red rocks, green foliage and blue sea:

Color filters are often used in front of the lens to selectively block some colors while passing others (similar to how color filters are used for each pixel in a digital camera’s bayer array). Filters are named after the hue of the color which they pass, not the color they block. These can block all but a primary color such as red, green or blue, or can partially block any weighted combination of the primary colors (such as orange or yellow). Careful selection of these filters allows the photographer to decide which colors will produce the brightest or darkest tones.

Here is an example of color channel splitting of a full RGB color image. The column at left shows the isolated color channels in natural colors, while at right there are their grayscale equivalences:

In photography, computing, and colorimetry, a grayscale or greyscale image is one in which the value of each pixel is a single sample representing only an amount of light, that is, it carries only intensity information. Images of this sort, also known as black-and-white or monochrome, are composed exclusively of shades of gray, varying from black at the weakest intensity to white at the strongest.[1]

Converting a digital color photo into black and white goes beyond simply desaturating the colors, and can be made to mimic any of a wide range of looks created by using color filters in black and white film photography. Conversion which does not take into account an image’s color and subject of interest can dilute the artistic message, and may create an image which appears washed out or lacks tonal range. This section provides a background on using color filters, and outlines several different black and white conversion techniques — comparing each in terms of their flexibility and ease of use.

Although these are numerically the same coefficients used in sRGB above, the effect is different because here they are being applied directly to gamma-compressed values rather than to the linearized values. The ITU-R BT.2100 standard for HDR television uses yet different coefficients, computing the luma component as

Open the image in Photoshop and create two separate “Hue/Saturation Adjustment Layers” by following the menus: Layers > New Adjustment Layer > Hue/Saturation…

One can visualize other possibilities since all color filters would produce some superposition of the three images above (yellow would be half red, half green and zero blue). Each image may therefore require its own combination of red, green and blue filtering in order to achieve the desired amount of contrast and tonal range.

On the top adjustment layer (Saturation), set the blending mode to “Color” and set the saturation to its minimum of “-100,” shown below.

A common strategy is to use the principles of photometry or, more broadly, colorimetry to calculate the grayscale values (in the target grayscale colorspace) so as to have the same luminance (technically relative luminance) as the original color image (according to its colorspace).[2][3] In addition to the same (relative) luminance, this method also ensures that both images will have the same absolute luminance when displayed, as can be measured by instruments in its SI units of candelas per square meter, in any given area of the image, given equal whitepoints. Luminance itself is defined using a standard model of human vision, so preserving the luminance in the grayscale image also perserves other perceptual lightness measures, such as L* (as in the 1976 CIE Lab color space) which is determined by the linear luminance Y itself (as in the CIE 1931 XYZ color space) which we will refer to here as Ylinear to avoid any ambiguity.

C l i n e a r = { C s r g b 12.92 , C s r g b ≤ 0.04045 ( C s r g b + 0.055 1.055 ) 2.4 , C s r g b > 0.04045 {displaystyle C_{mathrm {linear} }={egin{cases}{rac {C_{mathrm {srgb} }}{12.92}},&C_{mathrm {srgb} }leq 0.

04045left({rac {C_{mathrm {srgb} }+0.055}{1.055}}ight)^{2.4},&C_{mathrm {srgb} }>0.04045end{cases}}}

Conversion of an arbitrary color image to grayscale is not unique in general; different weighting of the color channels effectively represent the effect of shooting black-and-white film with different-colored photographic filters on the cameras.

In Black And White Photography Colors Are Translated Into Many Different Values Of Gray