Arithmetic Coding for Images
Arithmetic Coding For Images
1. Sanjay Bellani, 2. Shikha Bhagwanani
1. Plot No.421(a),Ward 2b . Adipur (Kutch) INDIA
2. Plot No.107,Ward 3b. Adipur(Kutch) INDIA
a. Innocentboy.sanju@yahoo.com, b. Shikha.bhagwanani@gmail.com
Keywords: data compression, arithmetic coding, Wavelet-based algorithms
Abstract. Data compression is a common requirement for most of the computerized applications. There are number of data compression algorithms, which are dedicated to compress different data formats. Even for a single data type there are number of different compression algorithms, which use different approaches.
This paper examines lossless data compression algorithm “Arithmetic Coding”
In this method, a code word is not used to represent a symbol of the text. Instead it uses a fraction to represent the entire source message. The occurrence probabilities and the cumulative probabilities of a set of symbols in the source message are taken into account. The cumulative probability range is used in both compression and decompression processes. In the encoding process, the cumulative probabilities are calculated and the range is created in the beginning.
While reading the source character by character, the corresponding range of the character within the cumulative probability range is selected. Then the selected range is divided into sub parts according to the probabilities of the alphabet. Then the next character is read and the corresponding sub range is selected. In this way, characters are read repeatedly until the end of the message is encountered.
Finally a number should be taken from the final sub range as the output of the encoding process. This will be a fraction in that sub range. Therefore, the entire source message can be represented using a fraction. To decode the encoded message, the number of characters of the source message and the probability/frequency distribution are needed.
Introduction. Compression is the art of
1. Sanjay Bellani, 2. Shikha Bhagwanani
1. Plot No.421(a),Ward 2b . Adipur (Kutch) INDIA
2. Plot No.107,Ward 3b. Adipur(Kutch) INDIA
a. Innocentboy.sanju@yahoo.com, b. Shikha.bhagwanani@gmail.com
Keywords: data compression, arithmetic coding, Wavelet-based algorithms
Abstract. Data compression is a common requirement for most of the computerized applications. There are number of data compression algorithms, which are dedicated to compress different data formats. Even for a single data type there are number of different compression algorithms, which use different approaches.
This paper examines lossless data compression algorithm “Arithmetic Coding”
In this method, a code word is not used to represent a symbol of the text. Instead it uses a fraction to represent the entire source message. The occurrence probabilities and the cumulative probabilities of a set of symbols in the source message are taken into account. The cumulative probability range is used in both compression and decompression processes. In the encoding process, the cumulative probabilities are calculated and the range is created in the beginning.
While reading the source character by character, the corresponding range of the character within the cumulative probability range is selected. Then the selected range is divided into sub parts according to the probabilities of the alphabet. Then the next character is read and the corresponding sub range is selected. In this way, characters are read repeatedly until the end of the message is encountered.
Finally a number should be taken from the final sub range as the output of the encoding process. This will be a fraction in that sub range. Therefore, the entire source message can be represented using a fraction. To decode the encoded message, the number of characters of the source message and the probability/frequency distribution are needed.
Introduction. Compression is the art of
References: [1] Amir Said,Introduction to Arithmetic Coding Theory and Practice, Hewlett-Packard Laboratories Report, HPL-2004-76, Palo Alto, CA, April 2004. [2] C. Sidney Burrus, Ramesh A. Gopinath, Haitato, "Introduction to Wavelets and Wavelet Transforms, Aprimer," Prentice-Hall, New Jersey, 1998. [3] M. D. Adams and F. Kossentini, "Reversible Integer-to-Integer Wavelet Transforms for Image Compression: Performance Evaluation and Analysis," IEEE Trans. on Image Processing, vol. 9, no. 6, pp. 1010-1024, Jun. 2000. [4] Paul G. Howard AND Jeffrey Scott Vitter, "Arithmetic Coding for Data Compression", Proceedings of the IEEE, vol. 82, no.6, June 1994.