PNGWolf employs a genetic algorithm to find better filter combinations than traditional heuristics. It is, however, infeasible for non-trivial images to find the best filters so typical encoders rely on a couple of heuristics to find good filters. Choosing the right filters for each scanline can make the image data more compressible. The PNG format supports a number of scanline filters that transform the image data by relating nearby pixels mathematically. The main factor is the quality of the Deflate compression used to compress the image data, which is in turn affected by the quality of the compressor and how well the data to be compressed is arranged. There are a number of factors that affect the size of PNG image files, such as the number of colors in the image and whether the image data is stored as RGBA data or in the form of references to a color palette. Zopfli Compression Algorithm was created by Lode Vandevenne and Jyrki Alakuijala, based on an algorithm by Jyrki Alakuijala. Zopfli Compression Algorithm is a compression library programmed in C to perform very good, but slow, deflate or zlib compression. The good encoders are at least applying the filtering heuristics. The maximum size of the LZ77 sliding window in Deflate is 32768 bytes, and the LZ77 matches can be between 3 and 258 bytes long. The combination of the last two stages is referred to as the Deflate compression, a widely-used, patent-free algorithm for universal, lossless data compression. In the second stage, the filtered byte sequence is passed through the Ziv-Lempel algorithm (LZ77), producing LZ77 codes that are further compressed by the Huffman algorithm in the third and final stage. Filtering does not compress or otherwise reduce the size of the data, but it makes the data more compressible. In the first stage, the image pixels are passed through a lossless arithmetic transformation named delta filtering, or simply filtering, and sent further as a (filtered) byte sequence. The PNG compression works in a pipeline manner. The purpose of this article is to provide information about these factors, and to give advice on implementing efficient PNG encoders. A good PNG encoder must be able to take informed decisions about the factors that affect the size of the output. Unlike other lossless compression schemes, PNG compression does not depend solely on the statistics of the input, but it may vary within wide limits, depending on the compressor’s implementation. The compression engine is based on the Deflate method. The Portable Network Graphics (PNG) is a format for storing compressed raster graphics. Program uses ImageMagick for test PSNR of result images. – Number of threads for ECT and OxiPNG (1-16). – You can set «Run in background (without console output)» or uncheck it for manual process control. – Option “Preserve file attributes (time stamps, file access rights, etc.)”. – Supported formats: PNG, GIF, BMP, PNM, TIFF. – Full compatible with original PNG format. – Compression of graphic files/images without loss in quality (Lossless) up to 5-30%! Program will be especially useful for webmasters to optimize images on sites to increase places in search results. Reduce the size of your PNG files in one click without quality loss! Program optimizes your file to new one with «_optimized» name ending (source file will remain intact). Convert from PNG, GIF, BMP, PNM, TIFF to smallest PNG! It uses 10 programs and selects the best result: OptiPNG, Pingo, TruePNG, ECT (Efficient Compression Tool), Zopfli, AdvanceCOMP, PNGWolfZopfli, OxiPNG, DeflOpt, Defluff. Optimize and convert your graphic files/images to smaller PNG files (up to 5-30%) lossless! Full compatible with source PNG format.
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