What is the format of webp?

Webp is an image file format that provides both lossy compression and lossless compression. WebP has two modes: static and dynamic. Dynamic WebP (Animated WebP) supports lossy and lossless compression, ICC color configuration, XMP interpretation data, and Alpha transparency channel.

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WebP (pronounced: weppy) is an image file format that provides both lossy compression and lossless compression (reversible compression). It is derived from the image encoding format VP8 and is considered a sister project of the WebM multimedia format. It was developed by Google after purchasing On2 Technologies and released under BSD licensing terms.

WebP was originally released in 2010 with the goal of reducing file size but achieving the same image quality as the JPEG format, hoping to reduce the time it takes for image files to be sent over the network. On November 8, 2011, Google began to allow WebP to support lossless compression and transparent color (alpha channel) functions, which were officially supported in the reference implementation libwebp 0.2.0 on August 16, 2012. According to earlier tests by Google, WebP's lossless compression reduced the file size by 45% compared to PNG files found on the Internet. Even if these PNG files were processed using pngcrush and PNGOUT, WebP could still reduce the file size by 28%.

The maximum number of pixels supported by WebP is 16383x16383. Lossy compression WebP only supports the 8-bit YUV 4:2:0 format. The lossless compression (reversible compression) WebP supports VP8L encoding and 8-bit ARGB color space. Whether it is lossy or lossless compression, it supports Alpha transparency channel, ICC color configuration, and XMP interpretation data.

WebP has two modes: static and dynamic. Dynamic WebP (Animated WebP) supports lossy and lossless compression, ICC color configuration, XMP interpretation data, and Alpha transparency channel.

WebP's lossless compression uses advanced techniques such as dedicated entropy codes for different color channels, 2D position using reverse reference distances and color caching of recently used colors. This complements basic techniques such as dictionary encoding, Huffman coding, and color index transformations.

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