![]() First, Install pngquant package for your system.Pngquant usually is the best option as it seems to optimize the file size the most without sacrificing much on quality. Pngquant can help you to reduce the size of a PNG image in Linux by performing lossy and lossless compression. PNGquant and OptiPNG are programs that optimize PNG images to smaller size without losing any information or their original quality. Here are two simple command line utilities to optimize images and they are: PNG utilizes lossless image compression, which results in high-quality images though sometimes they can be relatively big.Īlso if you have a lot of images, and want to compress them without losing its original quality There are plenty of GUI applications available which will help you to optimize the images. ![]() This is a fundamental part of lossy image compression, and the primary reason we use working files.PNG or Portable Network Graphics is an image file format meant to replace GIF. The compression algorithm gives you highly detailed graphics without losing any essential data, making them a great file type for prominent photos, company logos and other valuable web images. What this means is that JPEG and other lossy formats using this are very good at describing gradients, but not very good at describing sharp contrasts.Ĭonversely, lossless image compression techniques are really good at describing images with few colors thus sharp contrasts, but are not good to compress images with a lot of gradients.Īnother big difference between lossy and lossless images is that lossy file formats will degrade if you re-encode them, that is, if you load a JPEG into Krita edit a little, resave, edit a little, resave, each subsequent save will lose some data. PNG - which stands for Portable Network Graphic - is a lossless image file type that allows you to restore the original file after compression. This works because humans are much more sensitive to differences in lightness than we are to differences in hue and saturation.Īnother thing it does is to use cosine waves to describe contrasts in an image. One of the primary things JPEG for example does is chroma sub-sampling, that is, to split up the image into a grayscale and two color versions (one containing all red-green contrast and the other containing all blue-yellow contrast), and then it makes the latter two versions smaller. That the image will not be edited anymore after this allows for the use of the context of a pixel to be taken into account when compressing, meaning that we can rely on psychological and statistical tricks. This is necessary for final products where having a small filesize is preferable such as a website. Lossy compression techniques are for when we want to permanently reduce the file size of an image. Then, when describing the pixels, we only write down said number, so that we don’t need to write the color definition over and over. Within image formats, examples of such compression is by for example ‘indexed’ color, where we make a list of available colors in an image, and then assign a single number to them. We use best compression options to reduce image file size without losing visual quality. Everyone knows ‘etc.’ expands to ‘etcetera’, meaning that you can half the 8 character long ‘etcetera’ to the four character long ‘etc.’. In text, the use of abbreviations is a good example of a lossless compression technique. ![]() As the name implies, they compress without losing information. Lossless compression techniques are for when we want to temporarily reduce information. When we compress a file, we do this because we want to temporarily make it smaller (like for sending over email), or we want to permanently make it smaller (like for showing images on the internet). ![]()
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