Though Huffman codes [2,3,4,5,9] have shown their power in data compression, there are still some issues that are not noticed. In the present paper, we address the issue on the random property of compressed data via Huffman coding. Randomized computation is the only known method for many notoriously difficult #P-complete problems such as permanent, and some network reliability problems, etc [1,...

Codes may be characterized by how general they are with respect to the distribution of symbols they are meant to code. Universal coding techniques assume only a nonincreasing distribution. Golomb coding assumes a geometric distribution [1]. Fiala and Greene’s (start, step, stop) codes assume a piecewise uniform distribution function with each part distributed exponentially [2]. Huffman codes ar...

Fix a random variable X having as its possible values entries of a set X . Let Σ∗ denote the set of strings whose characters are taken from an alphabet Σ. In the case Σ has two elements, we can interpret elements of Σ∗ as bit strings, for example. Let Y denote a set of target symbols and C denote a code, a function of the form X → Y∗. The extension of a symbol code, a code of the form C : X → Y...

A Method for the Construction of Minimum-Redundancy Codes PDF.HUFFMAN CODES. Corollary 28 Consider a coding from a length n vector of source symbols, x x1x2.xn, to a binary codeword of length lx. Then the.Correctness of the Huffman coding nitro pdf reader 32 bit 1 1 1 13 create pdf files algorithm. A binary code encodes each character as a binary. Code that encodes the file using as few bits as...

We contrast language modeling for binary response typing interfaces with the more standard use of language models for full sequence disambiguation in applications like speech recognition. We highlight a key issue for construction of these language models: using Huffman coding versus simpler binary coding tree topologies. We then introduce novel methods for handling of selection error within the...

image data require huge amounts of disk space and large bandwidths for transmission. hence, imagecompression is necessary to reduce the amount of data required to represent a digital image. thereforean efficient technique for image compression is highly pushed to demand. although, lots of compressiontechniques are available, but the technique which is faster, memory efficient and simple, surely...

This paper explores the subject of compression in the graphics pipeline. While there are several components of the pipeline that could stand to benefit from compression, we chose to focus on the Z-buffer and the framebuffer. We describe a method of compression using pixel differencing and Huffman coding along with a caching system designed around tiles. We examine the effects of tile size, pixe...

An innovative algorithm for automatic generation of Huffman coding tables for semantic classes of digital images is presented. Collecting statistics over a large dataset of corresponding images, we generated Huffman tables for three images classes: landscape, portrait and document. Comparisons between the new tables and the JPEG standard coding tables, using also different quality settings, hav...

Individuals with severe motor impairments commonly enter text using a single binary switch and symbol scanning methods. We present a new scanning method -Huffman scanning - which uses Huffman coding to select the symbols to highlight during scanning, thus minimizing the expected bits per symbol. With our method, the user can select the intended symbol even after switch activation errors. We des...

The paper deals with formal description of data transformation (compression and decompression process). We start by briefly reviewing basic concepts of data compression and introducing the model based approach that underlies most modern techniques. Then we present the arithmetic coding and Huffman coding for data compression, and finally see the performance of arithmetic coding. And conclude th...