What is Alpha Channel? - Definition from Techopedia
gAMA chunk specifies the relationship between sample values and display output An alpha channel, representing transparency information on a per-pixel If no alpha channel nor tRNS chunk is present, all pixels in the image are to be . in tEXt and zTXt chunks, because they have no platform-independent meaning . Very few applications correctly process TIFF files with alpha channels. A major use of partial. Default transparency in a scenes 3D view on a texture with an alpha channel . If Objects in the 3D View still appear without transparency it may mean Blenders .. to incorrectly render surfaces and their relative relationships to one another;.
These techniques are controlled by the tRNS ancillary chunk type. If no alpha channel nor tRNS chunk is present, all pixels in the image are to be treated as fully opaque. Viewers can support transparency control partially, or not at all. Filtering PNG allows the image data to be filtered before it is compressed.
Filtering can improve the compressibility of the data. The filter step itself does not reduce the size of the data.
PNG (Portable Network Graphics) Specification, Version 1.2
All PNG filters are strictly lossless. PNG defines several different filter algorithms, including "None" which indicates no filtering. The filter algorithm is specified for each scanline by a filter-type byte that precedes the filtered scanline in the precompression datastream.
An intelligent encoder can switch filters from one scanline to the next. The method for choosing which filter to employ is up to the encoder. Interlaced data order A PNG image can be stored in interlaced order to allow progressive display.
The purpose of this feature is to allow images to "fade in" when they are being displayed on-the-fly. Interlacing slightly expands the file size on average, but it gives the user a meaningful display much more rapidly.
PNG Specification: Data Representation
Note that decoders are required to be able to read interlaced images, whether or not they actually perform progressive display. With interlace method 0, pixels are stored sequentially from left to right, and scanlines sequentially from top to bottom no interlacing.
Interlace method 1, known as Adam7 after its author, Adam M. Costello, consists of seven distinct passes over the image.
Each pass transmits a subset of the pixels in the image. The pass in which each pixel is transmitted is defined by replicating the following 8-by-8 pattern over the entire image, starting at the upper left corner: For example, pass 2 contains pixels 4, 12, 20, etc. The last pass contains the entirety of scanlines 1, 3, 5, etc.
The data within each pass is laid out as though it were a complete image of the appropriate dimensions. For example, if the complete image is 16 by 16 pixels, then pass 3 will contain two scanlines, each containing four pixels. When pixels have fewer than 8 bits, each such scanline is padded as needed to fill an integral number of bytes see Image layout.
Filtering is done on this reduced image in the usual way, and a filter-type byte is transmitted before each of its scanlines see Filter Algorithms. Notice that the transmission order is defined so that all the scanlines transmitted in a pass will have the same number of pixels; this is necessary for proper application of some of the filters.
If the image contains fewer than five columns or fewer than five rows, some passes will be entirely empty. Encoders and decoders must handle this case correctly. In particular, filter-type bytes are associated only with nonempty scanlines; no filter-type bytes are present in an empty pass.
Gamma correction PNG images can specify, via the gAMA chunk, the power function relating the desired display output with the image samples. Display programs are strongly encouraged to use this information, plus information about the display system they are using, to present the image to the viewer in a way that reproduces what the image's original author saw as closely as possible.
See Gamma Tutorial if you aren't already familiar with gamma issues. Gamma correction is not applied to the alpha channel, if any. Alpha samples always represent a linear fraction of full opacity. For high-precision applications, the exact chromaticity of the RGB data in a PNG image can be specified via the cHRM chunk, allowing more accurate color matching than gamma correction alone will provide.
See Color Tutorial if you aren't already familiar with color representation issues. Text strings A PNG file can store text associated with the image, such as an image description or copyright notice. Keywords are used to indicate what each text string represents. If it is necessary to convey characters outside of the Latin-1 set, the iTXt chunk should be used instead.
Character codes not defined in Latin-1 should not be used in tEXt and zTXt chunks, because they have no platform-independent meaning. If a non-Latin-1 code does appear in a PNG text string, its interpretation will vary across platforms and decoders. Some systems might not even be able to display all the characters in Latin-1, but most modern systems can. Fully green would be encoded as 0, 0.
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 premultiplied 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: 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[ citation needed ].
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 semitransparancy 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 usually abbreviated outatop, 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: