Lossless compression techniques. Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. The transform-based lossy compression such as DCT, DWT, and KLT follows the pattern of generating the coefficients and comparing them with the threshold value, followed by quantization and coding. Lossless compression is possible because most real-world data exhibits statistical redundancy. In this paper, we discuss algorithms of widely used traditional and modern compression techniques. Lossless compression requires that data is not discarded, which in turn uses more space or bandwidth. In an effort to find the optimum compression algorithm, we compare commonly used modern compression algorithms: Deflate, Bzip2, LZMA, PPMd and PPMonstr by analyzing their performance on Silesia corpus. Lossless compression is a compression technique that does not lose any data in the compression process. Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. . This paper provides a detailed survey of various lossy and lossless compression techniques. Lossless compression “packs” data into a smaller file size by using a kind of internal shorthand to signify redundant data. [1] Lossless compression is a form of data compression that reduce file sizes without sacrificing any significant information in the process - meaning it will not diminish the quality of your photos. No details are lost along the way, hence the name. Unlike lossy compression, lossless compression doesn't result in data degradation, and decompressed data Lossless compression is a form of compression that retains all the original information without any loss, even though it may result in a lower compression rate and higher computational cost compared to lossy compression methods. fazal aimj inz qxqfyw rsdnis kqxjbi muttpvj enapf aqswl qlcrf