Alpha Composting Explained

alpha composting explained

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Alpha Compositing is the process of combining an image with a background to create the appearance of partial or full transparency. It is often useful to render image elements in separate passes, and then combine the resulting multiple 2D images into a single, final image called the composite. For example, compositing is used extensively when combining computer-rendered image elements with live footage.

In order to combine these image elements correctly, it is necessary to keep an associated matte for each element. This matte contains the coverage information—the shape of the geometry being drawn—making it possible to distinguish between parts of the image where the geometry was actually drawn and other parts of the image that are empty.

Alpha compositing is a common image processing routine used to blend two or more images to create a final composite image. Alpha compositing is built upon the concept of layers — each image used in the composite image has a certain hierarchical layer. The image’s alpha channel determines how much of the images in layers underneath it can be seen at its own layer. In other words, the alpha channels control the transparency of the image, and alpha compositing uses the alpha channel to appropriately blend this image with another to exhibit this transparency.

The following picture from squarespace shows how to create advance visual graphics easily by super-imposing:

Composting Basics:

In a 2D image element, which stores a color for each pixel, additional data is stored in the alpha channel with a value between 0 and 1. A value of 0 means that the pixel does not have any coverage information and is transparent; i.e. there was no color contribution from any geometry because the geometry did not overlap this pixel. A value of 1 means that the pixel is opaque because the geometry completely overlapped the pixel.

If an alpha channel is used in an image, there are two common representations that are available: straight (unassociated) alpha, and premultiplied (associated) alpha.

With straight alpha, the RGB components represent the color of the object or pixel, disregarding its opacity.

With premultiplied alpha, the RGB components represent the color of the object or pixel, adjusted for its opacity by multiplication. A more obvious advantage of this is that, in certain situations, it can save a subsequent multiplication (e.g. if the image is used many times during later compositing). However, the most significant advantages of using premultiplied alpha are for correctness and simplicity rather than performance: premultiplied alpha allows correct filtering and blending. In addition, premultiplied alpha allows regions of regular alpha blending and regions with additive blending mode to be encoded within the same image.

Assuming that the pixel color is expressed using straight (non-premultiplied) RGBA tuples, a pixel value of (0, 0.7, 0, 0.5) implies a pixel that has 70% of the maximum green intensity and 50% opacity. If the color were fully green, its RGBA would be (0, 1, 0, 0.5).

However, if this pixel uses premultiplied alpha, all of the RGB values (0, 0.7, 0) are multiplied by 0.5 and then the alpha is appended to the end to yield (0, 0.35, 0, 0.5). In this case, the 0.35 value for the G channel actually indicates 70% green intensity (with 50% opacity). Fully green would be encoded as (0, 0.5, 0, 0.5). For this reason, knowing whether a file uses straight or premultiplied alpha is essential to correctly process or composite it.

It is often said that associativity is an advantage of pre-multiplied alpha blending over straight alpha blending, but both are associative. The only important difference is in the dynamic range of the colour representation in finite precision numerical calculations (which is in all applications): premultiplied alpha has a unique representation for transparent pixels, avoiding the need to choose a "clear color" or resultant artefacts such as edge fringes (see the next paragraphs). In other words, color information of transparent pixels is lost in premultiplied alpha, as the conversion from premultiplied alpha to straight alpha is undefined for alpha equal to zero. Premultiplied alpha has some practical advantages over normal alpha blending because interpolation and filtering give correct results.

Ordinary interpolation without premultiplied alpha leads to RGB information leaking out of fully transparent (A=0) regions, even though this RGB information is ideally invisible. When interpolating or filtering images with abrupt borders between transparent and opaque regions, this can result in borders of colors that were not visible in the original image. Errors also occur in areas of semi-transparancy because the RGB components are not correctly weighted, giving incorrectly high weighting to the color of the more transparent (lower alpha) pixels.

Premultiplication can reduce the available relative precision in the RGB values when using integer or fixed-point representation for the color components, which may cause a noticeable loss of quality if the color information is later brightened or if the alpha channel is removed. In practice, this is not usually noticeable because during typical composition operations, such as OVER, the influence of the low-precision colour information in low-alpha areas on the final output image (after composition) is correspondingly reduced. This loss of precision also makes premultiplied images easier to compress using certain compression schemes, as they do not record the color variations hidden inside transparent regions, and can allocate fewer bits to encode low-alpha areas.

With the existence of an alpha channel, it is possible to express compositing image operations using a compositing algebra. For example, given two image elements A and B, the most common compositing operation is to combine the images such that A appears in the foreground and B appears in the background. This can be expressed as A over B. In addition to over, Porter and Duff defined the compositing operators in, held out by, atop, and xor (and the reverse operators rover, rin, rout, and ratop) from a consideration of choices in blending the colors of two pixels when their coverage is, conceptually, overlaid orthogonally:

Alpha Blending

Alpha blending is the process of combining a translucent foreground color with a background color, thereby producing a new blended color. The degree of the foreground color's translucency may range from completely transparent to completely opaque. If the foreground color is completely transparent, the blended color will be the background color. Conversely, if it is completely opaque, the blended color will be the foreground color. Of course, the translucency can range between these extremes, in which case the blended color is computed as a weighted average of the foreground and background colors.

Alpha blending is a convex combination of two colors allowing for transparency effects in computer graphics. The value of alpha in the color code ranges from 0.0 to 1.0, where 0.0 represents a fully transparent color, and 1.0 represents a fully opaque color. This alpha value also corresponds to the ratio of "SRC over DST" in Porter and Duff equations.

For image and video composition algorithms, it is an important process and can do wonders to the graphic subjects it is applied to. It is a part of all major graphic processing applications from very simple apps to professional ones. It is used in your favorite image editing app even when you don't realize this is happening in background.

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