Yuval Fisher

Bio: Yuval Fisher is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Fractal compression & Fractal transform. The author has an hindex of 13, co-authored 19 publications receiving 2192 citations.

Fractal Image Compression: Theory and Application

Abstract: From the contents: Recent theoretical results on fast encoding and decoding methods, various schemes for encoding images using fractal methods, and theoretical models for the encoding/decoding process.- Working C code for a fractal encoding/decoding scheme capable of encoding images in a few seconds, decoding at arbitrary resolution, and achieving high compression rations.- Experimental results from various schemes showing their capability and forming the basis for a sophisticated implementation.- A list of previously unresearched projects containing both new ideas and inhancements to the schemes discussed in the book.- A comparison of the fractal schemes in the book with JPEG, commercial fractal software, and wavelet methods.

Fractal Image Compression

Abstract: This paper begins by presenting a simple explanation of the main ideas in fractal image compression. It then presents a brief discussion of the current state of the art along with some results comparing fractal encoding, JPEG, and a wavelet scheme. The conclusion contains references to many of the latest theoretical and implementation results.

Fractal Image Compression Using Iterated Transforms

Abstract: 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

Abstract: 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.

Ergonomic man-machine interface incorporating adaptive pattern recognition based control system

Abstract: An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Adaptive pattern recognition based control system and method

Abstract: An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation that may be efficiently processed to determine correspondence. Applications of the interface and system include a video cassette recorder (VCR), medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Fractal Image Compression

Abstract: The top-selling multimedia encyclopedia Encarta, published by Microsoft Corporation, includes on one CD-ROM seven thousand color photographs which may be viewed interactively on a computer screen. The images are diverse; they are of buildings, musical instruments, people’s faces, baseball bats, ferns, etc. What most users do not know is that all of these photographs are based on fractals and that they represent a (seemingly magical) practical success of mathematics. Research on fractal image compression evolved from the mathematical ferment on chaos and fractals in the years 1978–1985 and in particular on the resurgence of interest in Julia sets and dynamical systems. Here I describe briefly some of the underlying ideas. Following Hutchinson [7], see also [5], consider first a finite set of contraction mappings wi, each with contractivity factor s < 1, taking a compact metric space X into itself, i = 1,2, . . .N. Such a setup is called an iterated function system (IFS), [1]. Use this IFS to construct a mapping W from the space H of nonempty compact subsets of X into itself by defining, in the self-explanatory notation, W (B) = N ⋃

Internet appliance system and method

Abstract: An Internet appliance, comprising, within a single housing, packet data network interfaces, adapted for communicating with the Internet and a local area network, at least one data interface selected from the group consisting of a universal serial bus, an IEEE-1394 interface, a voice telephony interface, an audio program interface, a video program interface, an audiovisual program interface, a camera interface, a physical security system interface, a wireless networking interface; a device control interface, smart home interface, an environmental sensing interface, and an environmental control interface, and a processor, for controlling a data transfer between the local area network and the Internet, and defining a markup language interface communicated through a packet data network interface, to control a data transfer or control a remote device.

Fractal image coding: a review

Abstract: An approach to image coding based on a fractal theory of iterated contractive transformations defined piecewise is described. The main characteristics of this approach are that it relies on the assumption that image redundancy can be efficiently captured and exploited through piecewise self-transformability on a block-wise basis, and it approximates an original image by a fractal image, obtained from a finite number of iterations of an image transformation called a fractal code. This approach is referred to as fractal block coding. The general coding-decoding system is based on the construction, for an image to be encoded, of a fractal code-a contractive image transformation for which the original image is an approximate fixed point-which, when applied iteratively on any initial image of the decoder, produces a sequence of images which converges to a fractal approximation of the original. The design of a system for the encoding of monochrome digital images at rates below 1 b/pixel is described. Ideas and extensions from the work of other researchers are presented. >