Showing papers on "Run-length encoding published in 2002"

Image data compression apparatus for compressing both binary image data and multiple value image data

Abstract: An image data compression apparatus which compresses code data obtained by compressing image data by a fixed length encoding method so as to reduce a scale of hardware and reduce a development cost of software for an image data compression a binary image data processing part processes binary image data in accordance with a run length encoding method, the binary image data processing part including an encoding part which encodes run lengths of the binary image data by an encoding part. A multiple value image data processing part processes multiple value image data in accordance with a prediction encoding method. The encoding part of the binary image data processing part is commonly used by the multiple image data processing part so that the encoding part compresses both the binary image data and the multiple value image data.

Method for burying data in image, and method for extracting the data

Abstract: There are disclosed a method for burying data in an image, by which a standard decoder can decode an image in which data is buried during JPEG encoding, the data buried in the decoding can be extracted completely even if an irreversibly encoding method is used, and the image deterioration caused by burying the data is little; and a method for extracting the data. The method is characterized in that an original image is divided into blocks in units of 8 x 8 pixels, a DCT of each block of the entire image is carried out, each block is quantized with reference to a quantization table, data of 1 bit is substituted for the quantized coefficient value, thus burying data in an image, a run length encoding and a Huffman encoding are sequentially done, and the value of the quantization table corresponding to the substituted coefficient value after the quantization is replaced with 1.

A method of compressing and storing data based on genetic code

Abstract: PURPOSE: A method for compressing and storing information by the genetic code is provided to compress, record and display information in a continuous pair type like the configuration of the genetic code, using 4 fundamental elements composed of 2 bits. CONSTITUTION: Source data are inputted(S10). The source data are compressed by sequentially using an RLE(Run Length Encoding) compression algorithm, an LZ(Lempel Ziv) compression algorithm, and a Huffman compression algorithm(S20). The compressed information is converted into the genetic code, to generate temporary or intermediate data(S30). Each surface of a Rubik's Cubic pyramid is repetitively rotated for sorting the compressed genetic code(S40). The sorted and compressed genetic code is compressed again by using the RLE compression algorithm, to generate a final compressed file(S50). Whether to compress the genetic code is decided(S60). If so, the initial step(S10) is returned, and if not, the steps are ended.

TRLE - an efficient data compression scheme for image composition of parallel volume rendering systems

Abstract: In this paper we present an efficient data compression scheme, the template run-length encoding (TRLE) scheme, for image composition of parallel volume rendering systems. Given an image with 2n/spl times/2n pixels, in the TRLE scheme, the image is treated as n/spl times/n blocks and each block has 2/spl times/2 pixels. Since a pixel can be a blank or non-blank pixel, there are 16 templates in a block. To compress an image, the TRLE scheme uses the templates to encode blocks row by row. Blocks in the same row are encoded as a TRLE-sequence. By packing all TRLE-sequences in a packet, the packet is the compressed partial image that can be sent/received among processors. To evaluate the performance of the TRLE scheme, we compare the proposed scheme with the BR, the RLE, and the BRLC schemes. Since a data compression scheme needs to cooperate with some data communication schemes, in the implementation, the binary-swap (BS), the parallel-pipelined (PP), and the rotate-tiling (RT) data communication schemes are used. By combining the four data compression schemes with the three data communication schemes, we have twelve image composition methods. These twelve methods are implemented on a PC cluster The data computation time and the data communication time are measured. The experimental results show that the TRLE data compression scheme with the RT data communication scheme outperforms other eleven image composition methods.

Apparatus to provide fast data compression

Abstract: A lossless data compressor (10) has a content addressable memory dictionary (30) and a coder (38) having between them a critical path including a feedback loop forming a dictionary adaptation path; circuit means (42) is connected in the feedback loop so that the dictionary can be updated from a previous comparison cycle at the same time as the coder codes a current comparison cycle; and run length encoding means (46) is connected to receive the output of the coder (38). The encoding means (46) is arranged to count the number of times a match consecutively occurs at a predetermined location in the dictionary (30), that is, the number of times the same search tuple is loaded into the same address of the dictionary. Two or more lossless data compressors may be arranged in parallel in accordance with an aspect of the invention.

The compression performance of grammar-based codes revisited

Abstract: A grammar-based code (GC) refers to a new type of universal lossless source code. The authors consider the following two questions: (1) Based on run-length encoding (RLE) can one propose a class of interesting algorithms which is superior to arithmetic coding (AC) algorithms with finite contexts and can also be used as a benchmark to evaluate GCs? (2) For each sequence x, is there a better quantity than r/sub k/*(x) such that it can be used to derive a stronger redundancy bound for GCs? They show that the answer to both questions is yes and summarize the main results.