Image Compression using Wavelet and Modified Extreme Learning Machine

Abstract

The development of Internet and multimedia technologies that grow exponentially, resulting in the amount of information managed by computer is necessary. This causes serious problems in storage and transmission image data. Therefore, should be considered a way to compress data so that the storage capacity required will be smaller. This paper presents a method of compressing still images combining the powerful features of modified extreme learning machine (MELM) for learning with discrete wavelet transform (DWT) in image transformation. DWT, based on the haar wavelet, has been used to transform the image and the coefficients acquired from DWT are then trained with MELM. MELM has the property that it selects a minimal number of coefficients to model the training data. The coefficients are then quantized and encoded using the Huffman coding algorithm. The performance of the proposed method is aspiring and comparable with the existing image compression standards.