Kompresi File Citra dengan Algoritma Transformasi Walsh-Hadamard

Abstract

Image compression was developed to facilitate image storage and transmission. Current compression techniques allow the image to be compressed so that its size is much smaller than the original size. In general, data compression methods can be divided into two groups, namely lossy and losseless. Lossy is image compression where the compression result of the compressed image is not the same as the original image because there is missing information, but it can still be tolerated by eye perception. The eye can distinguish small changes to the image. This method produces a higher compression ratio than the lossless method. In this study, the algorithms used to compare data compression are the Walsh-Hadamard Transform and Run Length Encoding (RLE). Image transformation is a very important subject in image processing. The image resulting from the transformation process can be re-analyzed, interpreted and used as a reference for further processing. The purpose of applying image transformation is to obtain clearer information (feature extraction) contained in an image. The walsh-hadamard transformation is an orthogonal transformation that turns a signal into a set of waves in the form of perpendicular (orthogonal) and rectangular (rectangular). The Run Length Encoding (RLE) algorithm works based on a sequence of consecutive characters. This algorithm works by moving the repetition of the same byte in a row (continuously). This method is used to compress images that have groups of pixels with the same gray degree.