Yuval Fisher

Fractal Image Compression Using Iterated Transforms

This article presents background, theory, and specific implementation notes for an image compression scheme based on fractal transforms. Results from various implementations are presented and compared to standard image compression techniques.

Fractal Image Encoding and Analysis

I Fractal Image Encoding.- 1 Why Fractal Block Coders Work.- 2 On Fractal Compression and Vector Quantization.- 3 On the Use of Subsampling in Fractal Image Compression.- 4 On the Benefits of Basis Orthogonalization in Fractal Compression.- 5 On the Dimension of Fractally Encoded Images.- 6 Fractal Image Compression via Nearest Neighbor Search.- 7 Fractal Image Coding: Some Mathematical Remarks on Its Limits and Its Prospects.- 8 Linear Time Fractal Quadtree Coder.- 9 Fractal Encoding of Video Sequences.- 10 Theory of Generalized Fractal Transforms.- 11 Inverse Problem Methods for Generalized Fractal Transforms.- 12 Fractal Compression of ECG Signals.- II Fractal Image Analysis.- 13 Dimensions of Fractals and Multifractals.- 14 Velocity, Length, Dimension.- 15 A Local Multiscale Characterization of Edges Applying the Wavelet Transform.- 16 Local Connected Fractal Dimension Analysis of Early Chinese Landscape Paintings and X-Ray Mammograms.- 17 Introduction to the Multifractal Analysis of Images.- List of Participants.

MPEG-4's binary format for scene description

The new MPEG-4 standard provides a suite of functionalities under one standard: streaming multimedia content, good compression, and user interactivity. This paper provides an introduction to the use and internal mechanisms of these functions.

Fractal (self-VQ) encoding of video sequences

We present results of a scheme to encode video sequences of digital image data based on a quadtree still-image fractal method. The scheme encodes each frame using image pieces, or vectors, from its predecessor; hence it can be thought of as a VQ scheme in which the code book is derived from the previous image. We present results showing: near real-time (5 - 12 frames/sec) software-only decoding; resolution independence; high compression ratios (25 - 244:1); and low compression times (2.4 - 66 sec/frame) as compared with standard fixed image fractal schemes.

Fractal encoding with HV partitions

In this chapter we describe a way to partition images that gives significantly better results. The method, which we call fractal encoding with HV partitioning, also includes several optimizations in the storage of the transformations, the coding, and the decompression algorithm. The partitioning method used to generate the ranges is based on rectangles. A rectangular portion of the image is subdivided, either horizontally or vertically, to yield two new rectangles. The main advantage of this method over the quadtree method is clear: the ranges are selected adaptively,1 with partitions that can correspond to image edges (at least horizontal and vertical ones). This strength also leads to the main drawback: since the domain size is a multiple of the range size, the large number of range sizes leads to a large number of domains and thus to a large number of domain-range comparisons. Also, there are many ways to select the location of the partition, and we will only describe our final implementation. Our search through all the possible implementations was neither systematic nor complete, and it is clear that further work could yield improvements. Nevertheless, this method gives results better than any similar method of which we are aware.

Comparison of fractal methods with discrete cosine transform (DCT) and wavelets

The paper contains a brief description of fractal image compression methods with sample compression results. We also present comparative results between two fractal schemes, discrete cosine transform and a wavelet method. We show that, with the PSNR as a measure of image quality, some fractal schemes perform best over the range of compressions of most interest.

How the Web Works

Typically the resource found is file written using HTML or HyperText Markup Language. This file specifies the text which will be displayed on the webpage and the structure of the text, such as where the headings and paragraphs are. It often specifies additional files which will be needed by the web browser to display the webpage. These files may include a CSS (Cascading Style Sheet) file used to provide formatting information. The HTML file will also specify the locations of any image files, sound files, or video files which are needed by the webpage. All these additional files will be transferred using the same HTTP protocol used by the original HTML file.

What, How, Where?

This chapter tells what the World Wide Web (WWW) is, how to begin using the information on the WWW, and where to start. The WWW is a method of presenting and receiving information over the Internet, the global conglomeration of computer networks that is undergoing explosive growth. The simple and appealing presentation of information on the WWW has made this the most popular segment of the Internet. Its most potent feature is the relative simplicity of becoming an information publisher with potentially millions of readers; it’s never been easier. Unlike television, where hundreds of channels are available, the WWW has many thousands of information sources. Unlike television, where the consumer is passive, on the WWW the consumer must (still) be active. Perhaps best of all, no one owns the WWW. It and the Internet are still self-administered and self-regulated.

Advanced HTML Examples

Advanced HTML is an oxymoron. HTML is too young and simple to be particularly advanced. Obscure is about it. In this chapter we include some chocolaty HTML examples; these are examples that use commonly unused attributes, examples that mix several types of elements, or examples that contain Netscape Navigator extensions or HTML 3. This chapter is aimed at the learn-by-example sort of person. People who prefer to read about HTML elements should refer to Chapter 7.