Abstract: While dealing with large data array required in various applications, the memory required for the data storage and data transfer of that bulk data becomes difficult. If the array size can be reduced without losing the data, the problem of storage and data transfer can be avoided. In this paper, a Huffman Coding based data compression algorithm is proposed and tested in MATLAB environment which will significantly reduce the size of one dimensional data array. Though the algorithm is tested with number array only, the algorithm can be extended to be applied with character array with slight modification.

Abstract: Code compression technique is used for the reduction of codes to allow transportation of digital data from the transmitter (source) to the receiver (destination). These fixed length codes are converted into variable length codes having varied number of bits. The Huffman coding technique is found to be an optimal solution of transportation of data. It generally follows the Lossless Compression technique where symbols in encoded data are converted into a binary symbol and this precomputed text availed is further divided into blocks having variable lengths and condensed under efficient algorithm encoding procedure using code words having limited value. To increase the compression ratio these code words could be reused for encoding different compatible blocks. An Android app is been created to portray this technique for the ease understanding.

Abstract: In order to familiarize and comprehend the learning of Huffman algorithm in a simpler way, we have implemented Huffman algorithm in Julia language which can be visualized in an interactive platform called IJulia supported by Jupyter and it creates a learning platform that increases the understanding of the coding technique for students. It involves a set of commands that are understandable and familiar to the user. Data compression is an essential requirement for lossless data transmission. Message bits are encoded in the transmitter end so as to avoid errors and redundancy during the transmission of information. Huffman code is a prefix type code which compresses the message bits by knowing the frequency of occurrence of each character or probability of each symbol. A Huffman/binary tree is formed based on the occurrence of the symbols and symbols are then encoded. Huffman algorithm implements bottom-up approach. Each symbol encoded with the Huffman tree logic is decodable. Each encoded information can be decoded by tracing from the top of the tree to the required symbol. This paper introduces the implementation of this algorithm using Julia programming language supported by Jupyter platform. This encoding algorithm is the most efficient way of compressing data.

Abstract: Two approaches to reducing effort in switch-based text entry for augmentative and alternative communication devices are word prediction and efficient coding schemes, such as Huffman. However, character distributions that inform the latter have never accounted for the use of the former. In this paper, we provide the first combination of Huffman codes and word prediction, using both trigram and long short term memory (LSTM) language models. Results show a significant effect of the length of word prediction lists, and up to 41.46% switch-stroke savings using a trigram model.

Abstract: Due to the improvement in quality of multimedia and video services, peoples are more experienced. Because of bandwidth requirements and resolution problem the designers still search for new robust coding technique. This paper narrates a systematic method for video compression using a new technique: collaboration of fast curve let transform, burrows wheeler transform and Huffman coding. Modify the number of element in each matrix at the output of fast curve let transform. Then we apply burrows wheeler and Shannon fano encoding. Burrows wheeler transform BWT is mainly used for compressing any category of data anyhow of its information content. The Huffman coding principle is, compact binary string is used to represent a compressed stream. Huffman codes can be properly reconstructed because no code can be placed before the another code. This technique is used for gray scale as well as color videos.

Abstract: A storage circuit stores a decoded image of a coded image that is coded before a coding target image included in a video to which the still-image coding and the video coding are applied. A video coding circuit codes the coding target image by inter prediction coding that uses the decoded image as a reference image when the still-image coding is applied to the mage that is one image previous to the coding target image and the video coding is applied to the coding target image.

Abstract: This remark presents a correction to Algorithm 673 (dynamic Huffman coding) [Vitter 1989] and its translation to MATLAB.

Abstract: Image compression is a task of reducing the image size without image quality degradation. It provides solution to both the problems of limited storage and long transmission time. This paper presents a method of combinational coding using Huffman and Arithmetic technique. The Embedded Zerotree Wavelet method which provides embedded bit stream is employed for image compression. The EZW symbols obtained are first coded using Huffman method. The Huffman bit stream is converted into byte stream and then into equivalent decimal. The final integer stream obtained is coded using Arithmetic coding. The proposed method of joint coding provides improved compression ratio as compared with Huffman coding alone.

Abstract: Residual coding is an effective way to enhance the coding performance in video coding. This paper proposed a new inter-layer residual coding method based on orthogonal matching pursuit (OMP) to obtain the sparse representation vectors as the transform coefficients. To achieve this purpose, a content adaptive dictionary is constructed in I frame based on the analysis of the coding unit complexity. Experimental results show that the proposed method achieves 2.3% bitrate saving on average when compared to the HM-16.12.

Abstract: The present invention is made to enable switching between lossless coding which prioritizes compatibility with a lossy coding process and lossless coding which prioritizes compression performance An image coding apparatus of the present invention includes the following configuration The image coding apparatus which encodes an image on a block-by-block basis includes a first coding unit and a second coding unit The first coding unit performs irreversible compression coding on a received first block The second coding unit performs reversible compression coding on a received second block The second coding unit encodes the second block by using either of a first intra prediction mode for performing intra prediction on a block-by-block basis and a second intra prediction mode for performing intra prediction on a pixel-by-pixel basis

Abstract: The growing trend of online image sharing and downloads today mandate the need for better encoding and decoding scheme. This paper looks into this issue of image coding. Multiple Description Coding is an encoding and decoding scheme that is specially designed in providing more error resilience for data transmission. The main issue of Multiple Description Coding is the lossy transmission channels. This work attempts to address the issue of re-constructing high quality image with the use of just one descriptor rather than the conventional descriptor. This work compare the use of Type I quantizer and Type II quantizer. We propose and compare 4 coders by examining the quality of re-constructed images. The 4 coders are namely JPEG HH (Horizontal Pixel Interleaving with Huffman Coding) model, JPEG HA (Horizontal Pixel Interleaving with Arithmetic Encoding) model, JPEG VH (Vertical Pixel Interleaving with Huffman Encoding) model, and JPEG VA (Vertical Pixel Interleaving with Arithmetic Encoding) model. The findings suggest that the use of horizontal and vertical pixel interleavings do not affect the results much. Whereas the choice of quantizer greatly affect its performance.

Abstract: To further increase the hiding capacity of MP3 files, an improved algorithm is proposed in this paper. Compare to previous work, this algorithm searches out additional 10 Huffman codeword pairs which meet the transparence requirements. With the newly found pairs, the hiding capacity is increased and the transparence is still preserved. Keywords-MP3; concealed message; Huffman codeword; codeword pair

Abstract: With the recent development of 3D display technologies, there is an increasing demand for realistic 3D video. However, efficient transmission and storage of depth data still presents a challenging task to the research community in these applications. Consequently a new method, called 3D Image Warping Based Depth Video Compression (IWDVC) is proposed for fast and efficient compression of 3D video by using Huffman coding. The IW-DVC method is to exploit the special properties of the depth data to achieve a high compression ratio which preserves the quality of the captured images. This method combines the egomotion estimation and 3D image warping techniques and includes a lossless coding scheme which is capable of adapting to depth data with a high dynamic range. IWDVC operates in high-speed, suitable for real-time applications, and is able to attain an enhanced motion compensation accuracy compared with the conventional approaches. Also, it removes the existing redundant information between the depth frames to further increase compression efficiency without sacrificing image quality.

Abstract: Recently, the information security issues are watched closely. Numerous researchers have exploited data hiding to develop secure communications. This study proposes a lossless data hiding scheme for side match vector quantization (SMVQ) compressed images based on the search order coding (SOC) algorithm. In the SMVQ index table, the difference between the current index and one of its adjacent SMVQ indices is calculated and encoded into an indicator generated from the Huffman coding where the codeword length is variable. The indicator also contains some bits to identify different embedding cases. The experimental results indicate that our proposed scheme can achieve a high compression ratio.

Abstract: A coding method for information storage of DNA Sequences is described. The coding method developed in this paper is compared to a method which improved upon the Huffman coding technique to store DNA in various forms. The method used in this research, entails the utilization of specific mapping of base pairs to a numerical assignment through bit manipulation that enables efficient coding of characters, allowing eight alleles per integer. Therefore, the research presented below decreases the required storage space by one fourth. The methodology of this paper uses a lookup table based library with efficient and reliable information retrieval and assembly with uniquely designed mapping is described. The coding method is illustrated by translating existing DNA sequences into a numerical representation of the same sequence. The method discussed below, provides advantages over traditional Huffman coding by providing a simple, unambiguous method that lends itself to saving space when storing DNA.

Abstract: This work is devoted to study the effect of applying a hybrid encoding/decoding algorithm to textual data. The sole purpose is to analyze the effect on the size as well as the complexity of the output encoded data. The proposed combination is that of Huffman and Run-Length algorithms. This study focuses on the sequence of applying the two algorithms to see if it has an effect on the output data or not, and the impact of input data format on the result. Results show that the data format and the sequence in which the algorithms are applied actually affect the output. Moreover, it is shown why these two algorithms were chosen and each of them contribute to the overall result.

Abstract: The telemedicine and ambulatory monitoring development motivates many researchers to focus on the lossless electroencephalogram (EEG) compression in recent years. Nevertheless, most of these studies could not present the potential of compression techniques such as discrete cosine transform (DCT), and Huffman coding due to lack of attention to the signal and technique characteristics. In this work, we developed a lossless hybrid EEG compression method based on the characteristic of DCT frequency spectrum and the Huffman coding. In our method, we calculate the DCT coefficients below 40 Hz (dominant components) of the EEG segments. Then, we code these quantized DCT coefficients using a Huffman coder in the transmitter site. In the receiver site, we add a zero set for the DCT coefficients above 40 Hz, and then reconstruct the EEG segments using the inverse DCT. We applied our method for the five sets (denoted A-E) of the Bone University database. The results indicate that our algorithm can improve the average compression ratio of these sets up to 1.78, 1.94, 2.66, 3.35, and 1.78 times of the best results in the literature, respectively. Therefore, our hybrid method could compress the single-channel signal satisfactory enough.

Abstract: A novel method for the calculation of DNA sequence similarity is proposed based on simplified pulse-coupled neural network (S-PCNN) and Huffman coding. In this study, we propose a coding method based on Huffman coding, where the triplet code was used as a code bit to transform DNA sequence into numerical sequence. The proposed method uses the firing characters of S-PCNN neurons in DNA sequence to extract features. Besides, the proposed method can deal with different lengths of DNA sequences. First, according to the characteristics of S-PCNN and the DNA primary sequence, the latter is encoded using Huffman coding method, and then using the former, the oscillation time sequence (OTS) of the encoded DNA sequence is extracted. Simultaneously, relevant features are obtained, and finally the similarities or dissimilarities of the DNA sequences are determined by Euclidean distance. In order to verify the accuracy of this method, different data sets were used for testing. The experimental results show that the proposed method is effective.