New lower and upper bounds are obtained for the compression of optimal binary prefix codes according to various nonlinear codeword length objectives. Like the coding bounds for Huffman coding — which concern the traditional linear code objective of minimizing average codeword length — these are in terms of a form of entropy and the probability of the most probable input symbol. As in Huffman co...

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 ...

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...

• Arithmetic Coding is universal • Arithmetic coding is suitable for small alphabet (binary sources) with highly skewed probabilities. • Huffman cannot allocate fractional bits to symbols: , but the algorithm will assign 1 bit. Huffman needs at least one bit per symbol. If, however, the alphabet is large and probabilities are not skewed, Huffman rate is pretty close to entropy (H). , 01 . 0 , 9...

In this paper, complementary Huffman coding techniques are proposed for test data compression/decompression of complex SOC designs during manufacturing testing. Instead of the compatible relationship between test data blocks, complementary features between test blocks are also exploited. Based on this property, more test data blocks can share the same codeword and the size of the modified Huffm...

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...

A simple parallel algorithm for decoding a Huffman encoded file is presented, exploiting the tendency of Huffman codes to resynchronize quickly, i.e. recovering after possible decoding errors, in most cases. The average number of bits that have to be processed until synchronization is analyzed and shows good agreement with empirical data. As Huffman coding is also a part of the JPEG image compr...

This research paper proposes a method for the compression of medical images using an efficient hybrid algorithm. The objective of this hybrid (DWT,DCT and Huffman quantization) scheme is to calculate the compression ratio, peak signal to noise ratio and mean square error by changing the DWT level and Huffman quantization factor. The goal is to achieve higher compression ratio by applying differ...

In compressed data a single bit error propagates because of the corruption of the decoder’s state. This work is a study of error resilience in compressed data and, in particular, of the recovery of as much data as possible after a bit error. It is focused on Huffman codes. In a message encoded with a Huffman code a bit error causes the decoder to lose synchronization with the coder. The error p...

Algoritme Huffman dan Weaven-Hankamer adalah dua algoritme pengodean sumber yang diterapkan secara umum untuk teks. Kedua ini membutuhkan lebih banyak waktu menyelesaikan prosesnya karena memiliki tahapan. Oleh itu, penelitian bertujuan membuat user interface menggunakan MATLAB dapat menyimulasikan proses kedua mampu memberikan hasil sangat akurat dengan cepat. Ada skenario pada ini. Terdapat d...