In some cases,the Shannon code does not perform optimally. Consider a Bernoulli random variable X with parameter 0.0001. An optimal encoding requires only one bit to encode the value of X. The Shannon code would encode 0 by 1 bit and encode 1 by log 104 bits. This is good on average but bad in the worst case. We can also compare the Shannon code to the Huffman code. The Huffman code always has ...

This report presents the results of applying different compression algorithms to the network protocol of an online game. The algorithm implementations compared are zlib, liblzma and my own implementation based on LZ77 and a variation of adaptive Huffman coding. The comparison data was collected from the game TomeNET. The results show that adaptive coding is especially useful for compressing lar...

Communication between a sender and receiver needs security. It can be done in any form, like plain text or binary data. Changing the information to some unidentifiable form, can save it from assailants. For example, plain text can be coded using schemes so that a stranger cannot apprehend it. Cryptography is a subject or field which deals with the secret transmission of messages/ data between t...

Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on Block-DCT, where DCT is used to transform original image (cover image) blocks from spatial domain to frequency domain. Firstly a gray level image of size M × N is divided into no joint 8 × 8 blocks and a two dimensional Discrete Cosine Transform(2-d DCT...

Image Compression is the application of Data Compression on digital image. The techniques used for the image compression are broadly divided into lossy and lossless compression techniques. One of the lossless compression techniques is Huffman encoding. In this paper, the new method MH Encoding (Median Filter + Huffman Encoding) is used to compress the images. Here the images are preprocessed us...

Satisfiability of word equations problem is: Given two sequences consisting letters and variables decide whether there is a substitution for the that turns this equation into true equality. The exact computational complexity remains unknown, with best lower upper bounds being, respectively, NP PSPACE . Recently, novel technique recompression was applied to problem, simplifying known proofs lowe...

Compression is a technique to reduce the quantity of data without excessively reducing the quality of the multimedia data.The transition and storing of compressed multimedia data is much faster and more efficient than original uncompressed multimedia data. There are various techniques and standards for multimedia data compression, especially for image compression such as the JPEG and JPEG2000 s...

We discuss a set of metrics, which aims to facilitate the formation of symbol groups from a pseudoergodic information source. An optimal codification can then be applied on the symbols(such as Huffman Codes [1]) for zero memory sources where it tends to the theorical limit of compression limited by the entropy. These metrics can be used as a fitness measure of the individuals in the Vasconcelos...

We propose solutions to enhance the Inside-Outside Recursive Neural Network (IORNN) reranker of Le and Zuidema (2014). Replacing the original softmax function with a hierarchical softmax using a binary tree constructed by combining output of the Brown clustering algorithm and frequency-based Huffman codes, we significantly reduce the reranker’s computational complexity. In addition, enriching c...

Abstract— With the fast progression of data exchange in electronic way, information security is becoming more important in data storage and transmission. While storing and transmitting multimedia data are not easy and they need large storage devices and high bandwidth network systems. Compression and encryption technologies are important to the efficient solving of network bandwidth and securit...