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The alpha channel stores transparency information—the higher the value, the more opaque that pixel is. No camera or scanner measures transparency, although physical objects certainly can possess transparency, but the alpha channel is extremely useful for compositing digital images together.
In computer graphics, alpha compositing or alpha blending is the process of combining one image with a background to create the appearance of partial or full transparency. [1] It is often useful to render picture elements (pixels) in separate passes or layers and then combine the resulting 2D images into a single, final image called the composite .
This image has partial transparency (254 possible levels of transparency between fully transparent and fully opaque). It can be transparent against any background despite being anti-aliased. Some image formats, such as PNG and TIFF, also allow partial transparency through an alpha channel, which solves the edge limitation problem.
In computer graphics, pixels encoding the RGBA color space information must be stored in computer memory (or in files on disk). In most cases four equal-sized pieces of adjacent memory are used, one for each channel, and a 0 in a channel indicates black color or transparent alpha, while all-1 bits indicates white or fully opaque alpha.
Research transparency is a major aspect of scientific research. It covers a variety of scientific principles and practices: reproducibility, data and code sharing, citation standards or verifiability. The definitions and norms of research transparency significantly differ depending on the disciplines and fields of research.
Social marketing intelligence is the method of extrapolating valuable information from social network interactions and data flows that can enable companies to launch new products and services into the market at greater speed and lower cost. This is an area of research however, companies using social marketing intelligence have achieved ...
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Social media can and should be measured consistently with other media channels. [5] ¬ Focus measurement on engagement, “conversation” and “communities”, not just “coverage” or vanity metrics [6] Measurement and evaluation should be transparent, consistent and valid. [5] ¬ Ensure integrity, honesty, openness, and ethical practices.