Year: 1993
Type: book-chapter
Abstract: A wavelet analysis of a signal can separate information present at different scales.Moreover, wavelet bases are orthonormal.Therefore, the wavelet transformation can be used to remove redundancy from a signal.In this paper, it is demonstrated how the wavelet transform can be used for image compression. §1 Introduction to data compressionImage compression techniques and, in general, data compression techniques are techniques for storing or sending images using as few bits as possible for encoding a complete image.A compressed image can either be exactly equal to the original image, or differ from it in a limited and controlled way.An image typically consists of 256 x 256 pixels, each having an 8-bit grey value.Images produced by satellites can be much larger and contain more bits per pixel.The number of possible images of the mentioned format is (2 8 ) 256 X 256 .A straightforward coding of such an image would require 524288 bits.The images one usually comes across can be coded in a much smaller number of bits.This is due to the fact that natural images contain a large amount of structure, making pixel values predictable.The idea that predictable information can be coded more efficiently than random information is due to Shannon [5].Predictable information can be coded in fewer bits than unpredictable information.This can be seen from a simple example.Suppose that one wants to encode a message which is either A, B, C, or D. There are four possible messages, and these can be coded in two bits per message, for example using the identifications A +-> 00, B +-+ 01, C ..... 10, D ..... 11.
Source: WORLD SCIENTIFIC eBooks
Author: Peter Nacken
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2147589246