GIF to WEBP converter

.gif

GIF, Graphics Interchange Format, is one of the most popular bitmap image formats on the World Wide Web, allowing you to share images. It also supports transparent views of various animations. Such files are used to develop web advertising with sequentially changing pictures and the graphics shell of video files. They use scan-line images with the depth parameters up to 256 colors of the RGB palette. The process of compressing files in GIF does not affect the quality in any way, as there is no loss because of the compression technique. Due to this, it is possible to convert to other formats while preserving the original image properties. Many applications open the extension to view and process images and video content installed on PCs and mobile devices regardless of OS.

The format was developed by Compuserve specialists, especially for its use in the web environment, which provided broad public access to data on such files. The extension uses the LZW algorithm to carry out a parallel process with the removal of segments containing insufficient information. This ensures the preservation of high-quality pictures. Thanks to the Lempel-Ziv-Welch algorithm, the format handles graphic files with repeating sections well, particularly images with a large number of single-color pixels horizontally. Interlaced data storage is also possible. Scan-line data is compressed to the smallest size. Reducing the number of colors required to create an image is provided by removing shades unnecessary to perform this process. The range of available GIF colors is from 2 (black and white) to 256 while reducing the number of colors leads to a decrease in the file size.

CompuServe

.webp

Google Chrome

Google developed the WEBP image format in 2010. According to their claim, this format can save files up to 34% smaller than the JPEG or PNG files. It allows saving images in both lossy and lossless compression. Yet, it is not supported by all image viewers.

Lossy compression in this format is obtained by prediction. In this compression, an image is divided into some blocks, and predictions are made depending on the surrounding blocks' pixels. Here the difference between the main image and the forecast is recorded by encryption. The prediction is good enough to ensure no difference according to the actual image. It reduces the file size. Lossless compression is gained by the pieces of the image previously examined to Build the rest of the picture.

Google