Survey On Image Compression Algorithms And Their Efficiencies Under Different Types Of Files

Images produce massive amounts of data, which puts a burden on both storage and transmission. The compression makes sure all the original data can be compressed and after compression, decompressing data are restored. While utilizing lossy compression, a fraction of the initial image's data is discarded. It puts a lot of pressure on both transmission and storage. In order to reduce the quantity of data or storage needed to represent an image, various algorithms and techniques are employed, though this involves a compromise in quality. Image compression is frequently used to provide successful picture and display while maintaining the balance between image quality and file size. Image compression uses different algorithm to compress a different types of image file. For Our study we took three major algorithms of losslesscompression are run-length coding, Huffman coding, Lempel-Ziv-welch. And Result shows the original image size, compressed size, compression ratio, bits per pixel (BPP). This kind of study is helpful for understanding how well image compression and lossless algorithms working on various datasets with respect to image.