Image Compression Essay

9240 Words19 Pages

CHAPTER 1 PROBLEM DEFINITION Image compression is the art and science of reducing the amount of data required to represent an image. The purpose for image compression is to reduce the amount of data required for representing sampled digital images and therefore reduce the cost for storage and transmission. Image compression plays a key role in many important applications, including image database, image communications, remote sensing. LZW compression, one of the lossless image compression methods and invented by Abraham Lempel, Jacob Ziv, and Terry Welch, compresses a file into a smaller file using a table-based lookup algorithm. It works best for files containing lots of repetitive data. This is often the case with text and monochrome …show more content…

LZW is an adaptive technique. As the compression algorithm runs, a changing dictionary of (some of) the strings that have appeared in the text so far is maintained. LZW compression is the best technique for reducing the size of files containing more repetitive data. The decompression algorithm always follows the compression algorithm. LZW algorithm is efficient because it don't need to pass the string table to the decompression code. The table can be recreated as it was during compression, using the input stream as …show more content…

Hlavac and J. Fojt?k [11], in 1998, proposed a new method for lossless image compression of grey-level images. The image is treated as a set of stacked bit planes. The compressed version of the image is represented by residuals of a non-linear local predictor spanning the current bit plane as well as a few neighbouring ones. Predictor configurations are grouped in pairs differing in one bit of the representative point only. The frequency of predictor configurations is obtained from the input image. The predictor, as adapts automatically to the image and is able to estimate the influence of neighbouring cells, copes even with complicated structure or fine texture. The residuals between the original and the predicted image are those that correspond to the less frequent predictor configurations. Efficiently coded residuals constitute the output image. Good results were obtained for binary images, grey-level cartoons and man-made

More about Image Compression Essay

Open Document