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| Vector pwns raster in this large format signage. Click to enlarge. |
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"Today's viewers however, are very sophisticated visually. They know full well that anything, literally, can be done to an image. They have seen dinosaurs and aliens portrayed with lifelike realism in the movies. Problems arise though because viewers expect to be fooled in the movies, and tend to get upset and feel betrayed when they are fooled in an allegedly factual medium such as the news business."
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| Photos composited and manipulated in Photoshop (Wikipedia) |
Photo manipulation is the application of image editing techniques to photographs in order to create an illusion or deception after the original photographing took place.[1] A mere enhancement or correction is known as retouching.
Types of digital photo manipulation
In digital editing, photographs are usually taken with a digital camera and input directly into a computer. Transparencies, negatives or printed photographs may also be digitized using a scanner, or images may be obtained from stock photography databases. With the advent of computers, graphics tablets, and digital cameras, the term image editing encompasses everything that can be done to a photo, whether in a darkroom or on a computer. Photo manipulation is often much more explicit than subtle alterations to color balance or contrast and may involve overlaying a head onto a different body or changing a sign's text, for examples. Image editing software can be used to apply effects and warp an image until the desired result is achieved. The resulting image may have little or no resemblance to the photo (or photos in the case of compositing) from which it originated. Today, photo manipulation is widely accepted as an art form.
There are several subtypes of digital image-retouching:
Technical retouching Manipulation for photo restoration or enhancement (adjusting colors / contrast / white balance (i.e. gradational retouching), sharpness, noise, removing elements or visible flaws on skin or materials, ...)
Creative retouching Used as an art form or for commercial use to create more sleek and interesting images for advertisements. Creative retouching could be manipulation for fashion, beauty or advertising photography such as pack-shots (which could also be considered inherently technical retouching in regards to package dimensions and wrap-around factors). One of the most prominent disciplines in creative retouching is image compositing. Here, the digital artist uses multiple photos to create a single image. Today, 3D computer graphics are used more and more to add extra elements or even locations and backgrounds. This kind of image composition is widely used when conventional photography would be technically too difficult or impossible to shoot on location or in studio.Photo manipulation alters the content of the images in a devious manner. It becomes difficult for the audience to differentiate between a manipulated image and reality. But Photoshop's popularity has proven to be divisive. While some laud it for its ability to allow subjects to look their best in a photograph, others see it as a vehicle for feeding our culture's desire for ultimate perfection. Manipulated images are created to deceive the audiences and form their understanding on how the media presents everything with perfection.[11] Therefore, with digital democratization[vague] increasing at a rapid rate it[vague] is creating problems. Since more people have access to technology it[vague] creates curiosity in the readers mind when they see an image published in newspapers or magazines. The reader begins to question the ethics of the publication which results in a debate. Photo images were considered as a reliable source and were known as a medium of communication to present the truth to the media.[2]
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| poynter.org |
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| A detail of a map from Food: An Atlas that shows sources of food found at farmer's markets in Berkeley, California. Cameron Reed/Food: An Atlas |
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| http://www.informationisbeautiful.net/ |
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| http://www.informationisbeautiful.net/ |
“These summary statements reflect the universal analytic issues of (1) causality, (2) comparison, and (3) multivariate complexity. Human activities, after all, take place in intensely comparative and multivariate contexts filled with causal ideas: intervention, purpose, responsibility, consequence, explanation, intention, action, prevention, diagnosis, strategy, decision, influence, planning.”
— Edward Tufte, Beautiful Evidence
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| (Source: Physicians Committee for Responsible Medicine in Good Medicine Magazine) http://www.smashingmagazine.com/2010/05/imagine-a-pie-chart-stomping-on-an-infographic-forever/ |
"Information graphics — or infographics — are graphic visual representations of information, data or knowledge. These graphics present complex information quickly and clearly, such as in signs, maps, journalism, technical writing, and education."
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| New America Foundation/Good/DeepLocal |
"Statistical literacy is more than learning the laws of statistics; it is about representations that the human mind can understand and remember. … If you design a visualization before correctly understanding the data on which it is based, you face the very real risk of summarizing incorrectly, producing faulty insights, or otherwise mangling the process of disseminating knowledge. If you do this to your audience, then you have violated an expectation of singular importance for any content creator: their expectation that you actually know what you’re talking about. …
"Unfortunately, curing statistical illiteracy isn’t as easy as reading an article about it or even taking a statistics course. While a solid understanding of statistics is beneficial for a wide variety of purposes, countering statistical illiteracy requires the cultivation of an active interpretative technique that is separate from knowledge of pure mathematics.
"Statistical literacy is only the bare minimum, though. The burden on designers is heavier because their uses of data often require them to go beyond interpretation and to perform some basic analysis, summarization or transformation of data. However, a formal education in research methods is probably too extreme. I believe that most mistakes of data could have been avoided had the designers focused on a limited skill set that is to a media producer what statistical literacy is to a media consumer. For now, let’s call this data mindfulness.
"Mindfulness means exhibiting care, caution, exactness, prudence, regard and many other virtues. Data mindfulness is similar to someone imploring another to “be mindful” of something potentially dangerous. As a designer, you can be careful about the sources of data you choose and can be cautious of the claims you make based on that data. Your exactness is reflected in the effort you put into correctly transforming the original data. Your prudence relates to whether you are honest in your intent and methods. But regard comes closest to the concept of data mindfulness: to be mindful of your data—to avoid mistakes with it and prevent the harm that would result from such mistakes—you should regard it with respect." [1]
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| http://mashable.com/2011/07/20/spotify-infographic/ |
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| Thevisible spectrum (above) can be visualized as a rainbow: red, orange, yellow, green, blue, violet. NASA image, Wikimedia Commons |
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The Visible Spectrum and a simple RYB (Red-Yellow-Blue) Color Wheel
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Photoshop's Color Picker
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In colorimetry and color theory, colorfulness, chroma, and saturation are related but distinct concepts referring to the perceived intensity of a specific color. Colorfulness is the difference between a color against gray. Chroma is the difference of a color against the brightness of another color which appears white under similar viewing conditions. Saturation is the difference of a color against its own brightness. …A highly colorful stimulus is vivid and intense, while a less colorful stimulus appears more muted, closer to gray. With no colorfulness at all, a color is a “neutral” gray (an image with no colorfulness in any of its colors is called grayscale). With three attributes—colorfulness (or chroma or saturation), lightness (or brightness), and hue—any color can be described.Saturation is one of three coordinates in the HSL and HSV color spaces. Note that virtually all computer software implementing these spaces use a very rough approximation to calculate the value they call "saturation," such as the formula described for HSV and this value has little, if anything, to do with the description shown here.The saturation of a color is determined by a combination of light intensity and how much it is distributed across the spectrum of different wavelengths. The purest color is achieved by using just one wavelength at a high intensity, such as in laser light. If the intensity drops, so does the saturation. To desaturate a color in a subtractive system (such as watercolor), you can add white, black, gray, or the hue's complement.
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| RGB Color Model -- Primaries, Secondaries and Neutral |
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| CMYK Composite image |
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How process color builds up to appear to be "full color"
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| Three examples of color halftoning with CMYK separations. From left to right: The cyan separation, the magenta separation, the yellow separation, the black separation, the combined halftone pattern and finally how the human eye would observe the combined halftone pattern from a sufficient distance. (Wikipedia) |
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| Grayscale image, halftone screen with black ink. Light areas have smaller dots, dark areas have larger dots. |
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| CMYK color image, halftone screens with process ink at different screen angles; correctly registered dots form rosettes. |
The term gamut was adopted from the field of music, where it means the set of pitches of which musical melodies are composed ….
In color theory, the gamut of a device or process is that portion of the color space that can be represented, or reproduced. Generally, the color gamut is specified in the hue–saturation plane, as a system can usually produce colors over a wide intensity range within its color gamut; for a subtractive color system (such as used in printing), the range of intensity available in the system is for the most part meaningless without considering system-specific properties (such as the illumination of the ink).
When certain colors cannot be expressed within a particular color model, those colors are said to be out of gamut. For example, while pure red can be expressed in the RGB color space, it cannot be expressed in the CMYK color space; pure red is out of gamut in the CMYK color space.
A device that is able to reproduce the entire visible color space is an unrealized goal within the engineering of color displays and printing processes. While modern techniques allow increasingly good approximations, the complexity of these systems often makes them impractical.
While processing a digital image, the most convenient color model used is the RGB model. Printing the image requires transforming the image from the original RGB color space to the printer's CMYK color space. During this process, the colors from the RGB which are out of gamut must be somehow converted to approximate values within the CMYK space gamut. Simply trimming only the colors which are out of gamut to the closest colors in the destination space would burn the image. There are several algorithms approximating this transformation, but none of them can be truly perfect, since those colors are simply out of the target device's capabilities. This is why identifying the colors in an image which are out of gamut in the target color space as soon as possible during processing is critical for the quality of the final product.
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| Color gamuts: A. Lab color gamut B. RGB color gamut C. CMYK color gamut |
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| A comparison of RGB and CMYK color spaces. The image demonstrates the difference between the RGB and CMYK color gamuts. The CMYK color gamut is much smaller than the RGB color gamut, thus the CMYK colors look muted. If you were to print the image on a CMYK device (an offset press or maybe even a ink jet printer) the two sides would likely look much more similar, since the combination of cyan, yellow, magenta and black cannot reproduce the range (gamut) of color that a computer monitor displays. This is a constant issue for those who work in print production. Clients produce bright and colorful images on their computers and are disappointed to see them look muted in print. (An exception is photo processing. In photo processing, like snapshots or 8x10 glossies, most of the RGB gamut is reproduced.) — http://en.wikipedia.org |
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What would you say about the color scheme of this logo?
What relationships do these colors have to each other? Cool? Warm? Complementary? Analogous? |
