Abstract: This paper proposes joint-probability-based adaptive Golomb coding (JPBAGC) to improve the performances of the Golomb family of codes, including Golomb coding (GC), Golomb–Rice coding (GRC), exp-Golomb coding (EGC), and hybrid Golomb coding (HGC), for image compression. The Golomb family of codes is ideally suited to the processing of data with geometric distribution. Since it does not require a coding table, it has higher coding efficiency than Huffman coding. In this paper, we find that there are many situations in which the probability distribution of data is not only geometric, but also depends on the probability distribution of the other data. Accordingly, we used the joint probability of generalizing the Golomb family of codes and exploiting the dependence between neighboring image data. The proposed JPBAGC improves the efficiency of many image and video compression standards, such as the joint photographic experts group (JPEG) compression scheme and the H.264-intra JPEG-based image coding system. Simulation results demonstrate the superior coding efficiency of the proposed scheme over those of Huffman coding, GC, GRC, EGC, and HGC.

Abstract: Incorporating sample-based prediction during lossless coding can significantly improve coding performance. However, its use within a codec designed for lossy coding requires a modification of the available prediction scheme. When implementing the codec, two different prediction processes will have to be implemented. This paper describes a lossless coding scheme that delays the sample-based prediction till the residue coding stage of the codec and carries out prediction in the residual domain. In this way, the prediction scheme of the lossy coder can be retained while realizing the coding gains associated with sample-based prediction. The proposed scheme improves lossless intra coding performance in HEVC Main Profile by an average of 6.5%.

Abstract: AVS2 is a next-generation audio and video coding standard currently under development by the Audio Video Coding Standard Workgroup of China. In this paper, a coefficient-group based transform coefficient coding design for AVS2 video coding standard is presented, which includes two main coding tools, namely, two-level coefficient coding and intra-mode based context design. The two-level coefficient coding scheme allows accurate coefficient position information to be used in the context model design and improves the coding efficiency. It also helps increase the entropy coding throughput and facilitate parallel implementation. The intra-mode based context design further improves coding performance by utilizing the intra-prediction mode information in the context model. The two coding tools combined provide consistent rate-distortion performance gains under standard test conditions. Both tools were adopted into the AVS2 working draft. Furthermore, an improved rate-distortion optimized quantization algorithm is designed based on the proposed scheme, which significantly reduces the encoder complexity.

Abstract: Compression is a technology for reducing the quantity of data used to represent any content witho ut excessively reducing the quality of the picture. The need for a n efficient technique for compression of images ever increasing because the raw images need large amounts of disk space seems to be a big disadvantage during transmission & storage. Compression is a technique that makes storing easier for large amount of data. It also reduces the number of bits required to store a nd transmit digital media. In this paper, a fast lossless compr ession scheme is presented and named as HL which consists of two stages. In the first stage, a Huffman coding is used to compress t he image. In the second stage all Huffman code words are concatenated together and then compressed with Lempel Ziv coding. This technique is simple in implementation and utilizes less memory. A software algorithm has been developed and implemented to compress and decompress the given image using Huffman coding techniques in MATLAB software.

Abstract: Distributed arithmetic coding (DAC) is similar to syndrome coding, in the sense that message sequences sharing the same interval can be considered a coset of the space of the source sequences, and the codeword is the index of the coset. In this paper, the minimum Hamming distance of cosets is studied and it is proved that such a distance is as small as one. By only allowing the sequences with a large Hamming distance to overlap in the same interval, an improved DAC scheme is proposed. Simulation results show that, for equiprobable memoryless sources, this approach outperforms DAC in terms of decoding error rate at the same coding cost. In addition, at small sequence length, the decoding error rate of the proposed scheme is lower than that of distributed source coding based on low-density parity-check codes for highly correlated sources.

Abstract: Provided are scalable video encoding and decoding based on coding units having a tree structure. A scalable video encoding method includes: encoding a lower layer image based on coding units having a tree structure including completely split coding units among hierarchically split coding units of maximum coding units of an image; determining scalable coding modes for performing scalable encoding on a higher layer image based on the coding units having the tree structure by referring to the lower layer image; predicting and encoding the higher layer image by referring to encoding information of the lower layer image based on the determined scalable coding modes; and outputting coding modes and predicted values of the lower layer image and the determined scalable coding modes of the higher layer image based on the determined scalable coding modes, wherein, among spatially split maximum coding units of the image of a video, each maximum coding unit is split into a plurality of coding units, and each coding unit is determined, individually from adjacent coding units, to split into smaller coding units.

Abstract: A naive storage of a Huffman model on a text of length n over an alphabet of size σ requires O(σlog n) bits. This can be reduced to σ logσ + O(σ) bits using canonical codes. This overhead over the entropy can be significant when σ is comparable to n, and it also dictates the amount of main memory required to compress or decompress. We design an encoding scheme that requires σlog log n+O(σ+log2 n) bits in the worst case, and typically less, while supporting encoding and decoding of symbols in O(log log n) time. We show that our technique reduces the storage size of the model of state-of-the-art techniques to around 15% in various real-life sequences over large alphabets, while still offering reasonable compression/decompression times.

Abstract: Systems, articles, and methods for coding unit size dependent simplified depth coding for 3D video coding

Abstract: “A complex idea can be conveyed in just single still image”. Storage and transmission of digital image has become more of a necessity than luxury these days, hence the importance of Image compression. Image data files commonly contain considerable amount of information that is redundant and irrelevant leading to more disk space for storage. Image compression [7][9] is minimizing the size in bytes of an image file without degrading the quality of the image to an unacceptable level. During a step called quantization, where part of compression occurs, the less frequencies [1] are discarded. This paper represent the lossless image compression on still image, which is based on Hashing and Huffman Coding technique to show the better compression.

Abstract: Storing, transmitting and security of DNA sequences are well known research challenge. The problem has got magnified with increasing discovery and availability of DNA sequences. We have represent DNA sequence compression algorithm based on Dynamic Look Up Table (DLUT) and modified Huffman technique. DLUT consists of 4 3 (64) bases that are 64 sub-stings, each sub-string is of 3 bases long. Each sub-string are individually coded by single ASCII code from 33(!) to 96(`) and vice versa. Encode depends on encryption key choose by user from four base pair {a,t.g and c}and decode also require decryption key provide by the encoded user. Decoding must require authenticate input for encode the data. The sub-strings are combined into a Dynamic Look up Table based pre-coding routine. This algorithm is tested on reverse; complement & reverse complement the DNA sequences and also test on artificial DNA sequences of equivalent length. Speed of encryption and security levels are two important measurements for evaluating any encryption system. Due to pro liferate of ubiquitous computing system, where d igital contents are accessible through resource constraint biological database security concern is very important issue. A lot of research has been made to find an encryption system which can be run effectively in those biological databases. Informat ion security is the most challenging question to protect the data from unauthorized user. The proposed method may protect the data from hackers. It can provide the three tier security, in tier one is ASCII code, in t ier two is nucleotide (a,t,g and c) choice by user and tier three is change of label or change of node position in Huffman Tree. Compression of the genome sequences will help to increase the efficiency of their use. The greatest advantage of this algorithm is fast execution, small memory occupation and easy implementation. Since the program to implement the technique have been written originally in the C language, (Windows XP platform, and TC compiler) it is possible to run in other microcomputers with s mall changes (depending on platform and Compiler used). The execution is quite fast, all the operations are carried out in fraction of seconds, depending on the required task and on the sequence length. The technique can approach an effective compression ratio of 1.98 bits/base and even lower. When a user searches for any sequence for an organism, an encrypted compressed sequence file can be sent from the data source to the user. The encrypted compressed file then can be decrypted & decompressed at the client end resulting in reduced transmission time over the Internet. An encrypt compression algorithm that provides a moderately high compression with encryption rate with minimal decryption with decompression time.

Abstract: This research paper presents a proposed method for the compression of medical images using hybrid compression technique (DWT, DCT and Huffman coding). The objective of this hybrid scheme is to achieve higher compression rates by first applying DWT and DCT on individual components RGB. After applying this image is quantized to calculate probability index for each unique quantity so as to find out the unique binary code for each unique symbol for their encoding. Finally the Huffman compression is applied. Results show that the coding performance can be significantly improved by the hybrid DWT, DCT and Huffman coding algorithm. Keywords- Image compression, hybrid, quantization, DWT, DCT, Huffman encoding, medical image.

Abstract: In this paper, we present a very fast method for performing content-based image retrieval of JPEG compressed images Our method works directly in the compressed domain of JPEG but in contrast to previous techniques does not require to undo the entropy coding stages of the compression The reason for this is that, as we show, image adapted Huffman tables can be directly employed as image descriptors and image similarity defined as similarity between the corresponding tables To do this, we extract both DC and AC Huffman tables and compare the lengths of assigned prefix codes, which give an indication of the frequencies of the related DC and AC values, and use this to compare images Since the Huffman tables reside in the header of JPEG images, our approach is extremely fast, as not only does it not require any kind of decompression it also needs reading in only a fraction of the file We evaluate our method on benchmark databases of varying sizes up to in excess of 1 million images, and show that our approach achieves retrieval performance similar to other techniques, while providing a speedup more than 30-fold compared to JPEG compressed domain algorithms and more than 150-fold compared to common pixel domain techniques for online image retrieval

Abstract: The low-complexity encoding, as fundamental requirement of Distributed Video Coding, relies on performing the bulk of computation at decoder, including tasks as the generation of side information and particularly, inter-camera registration in the case of multi-view systems with complete-overlapped views and free motion of the cameras (e.g., video surveillance). In Ciobanu and Corte-Real (Multimedia Tools Appl 48(3):411---436, 2010) we introduced a codec-independent solution for such tasks at decoder. In this paper, we present a multi-view Wyner---Ziv codec (IWZ) designed for the architecture and scenarios from Ciobanu and Corte-Real (2010) (e.g., free motion of the cameras, no a priori knowledge of the instant camera positions, no feedback channel), based on transform domain (DCT), block-based coset coding. We aimed to achieve a compromise between the low encoder complexity and the rate-distortion performance. A detailed evaluation is presented for comparison with conventional coding (Intra 4×4 and Intra 16×16). Practical results show a better overall performance of the proposed codec at low bitrates.

Abstract: The coding scheme presented in this chapter is developed on the basis of the theoretical considerations sketched out in the previous chapter. In other words, the coding scheme is the result of the operationalization of the theoretical considerations. In our case, it is created in such a way that it follows from general concepts to specific questions. The coders apply the coding scheme directly on the text (the party statutes).

Abstract: HIBASE compression technique simply replaces the attribute values in a tuple with fixed length code-words. However, fixed length coding system is not an optimal compression technique because some redundancies occur in the compressed table. This redundancy can be avoided if we use Huffman code-words. Moreover, using Huffman code-word will ensure optimal compression as well as high performance operation. The objectives of the research are to i) develop a dictionary by applying the principle of Huffman coding, ii) compress the relational storage of HIBASE by applying dynamic Huffman coding, iii) develop algorithm to perform query operation on the compressed storage, iv) analyze the performance of the proposed system in terms of both storage and queries. The main contribution of this research is to develop a compression technique. It implies the enhancement of HIBASE technique using HUFFMAN coding (H-HIBASE) with better compression capability.

Abstract: This paper proposes a new MPEG-2 AAC Huffman decoding algorithm which is designed to find multiple symbols in a single search. The analysis and experimental results show that the computational complexity of the proposed method is lower by more than 46% when compared with those of the up-to-date methods.

Abstract: In this paper, a simple hybrid lossy image compression system is introduced; it is based on a combination of two techniques that exploits the spatial domain efficiently of linear polynomial approximation model to decompose image signal followed by block truncation coding of two-level quantizer on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, the compressed information encoded using a simple run length coding and Huffman coding techniques. The test results shown in this paper are promising in terms of high compression rate achieved due to integrates the flexibility of polynomial model in overcoming the limitations of extra overhead information required compared to traditional predictive, along with effectiveness of block truncation coding as a 1-bit quantizer moments preserving.

Abstract: Huffman coding is a statistical lossless coding method with high efficiency The principal and implementation of Huffman coding is discussed and Huffman coding is implemented to the compression of vector maps The property of the algorithm is discussed Experiments demonstrated that the algorithm proposed can compress vector maps with high efficiency and no loss

Abstract: The color satellite image compression technique by vector quantization can be improved either by acting directly on the step of constructing the dictionary or by acting on the quantization step of the input vectors. In this paper, an improvement of the second step has been proposed. The k-nearest neighbor algorithm was used on each axis separately. The three classifications, considered as three independent sources of information, are combined in the framework of the evidence theory. The best code vector is then selected, after the image is quantized, Huffman schemes compression is applied for encoding and decoding.

Abstract: The lossless compression algorithm specified in ITU-T Recommendation G.711.0 provides bit-exact G.711 speech coding at reduced bit-rates. We introduce two Look-Up Coders (LUCs) that also offer bit-exact G.711 speech coding at reduced rates but the LUCs do not use arithmetic operations and hence eliminate the need for a processor. Instead they read in eight G.711 symbols, reinterpret those 64 bits to form eight new symbols that carry temporal information, then look up Huffman codes for those new symbols. When compared to G.711.0, LUC rates are 9% to 40% higher and they require 2 to 8 kB additional ROM, but LUCs eliminate about one million weighted arithmetic operations per second. LUCs reduce the 8 b/smpl G.711 rate to 3.8 to 6.7 b/smpl, depending on speech and noise levels.

Abstract: In this paper, Compression and improving the Quality of images during the transmission using SPIHT algorithm combined with Huffman encoding over OFDM channel has been proposed. Initially decompose the image in to different level, the compressed coefficients are arranged in descending order of priority and mapped over the channels. The coefficients with lower importance level, which are likely to mapped over the bad sub channels, are discarded at the transmitter to save power without significant loss of reception quality. Next SPIHT embedded encoder algorithm combined with Huffman encoder is applied for further compression. Finally the Huffman and SPIHT decoding of the embedded encoder is done. In this technique reduce the number of encoding bits and improving the Quality of image.

Abstract: ABSTRCT : SPIHT (Set Partitioning In Hierarchical Tree) is computationally very fast among the best image compression algorithm, In order to enhance the working efficiency, to reduce its complexity, to implement easily in software and hardware, In this paper a different approach to the original SPIHT algorithm has been proposed which is based on Set Partitioning In Row/Column-wise (SPIR) algorithm. This algorithm is easily implementable compared to the BP-SPIHT (Block-based passparallel SPIHT algorithm) and other compression techniques. This algorithm applies on wavelet decomposed image, Then to check the row/column wise pixel values. Output bit stream of SPIR encoding algorithm, combined with Huffman encode, proposes a simple and effective method.

Abstract: This paper reviews the embedding and extraction algorithm proposed by “A. Nag, S. Biswas, D. Sarkar and P. P. Sarkar” on “A Novel Technique for Image Steganography based on Block-DCT and Huffman Encoding” in “International Journal of Computer Science and Information Technology, Volume 2, Number 3, June 2010” [3] and shows that the Extraction of Secret Image is Not Possible for the algorithm proposed in [3]. 8 bit Cover Image of size is divided into non joint blocks and a two dimensional Discrete Cosine Transformation (2-D DCT) is performed on each of the blocks. Huffman Encoding is performed on an 8 bit Secret Image of size and each bit of the Huffman Encoded Bit Stream is embedded in the frequency domain by altering the LSB of the DCT coefficients of Cover Image blocks. The Huffman Encoded Bit Stream and Huffman Table

Abstract: It is necessary to develop an efficient MVD coding scheme to improve the video coding performance. In this paper, combined codeword and joint codeword are suggested from analyses on statistical distributions of MVD according to the quantization steps and the conventional codeword structure. Based on these codewords, we propose new MVD coding scheme where one of the suggested codewords is employed to encode the MVD according to the coding environment. Simulation results show that the proposed scheme enhances the coding performance without the quality degradation.

Abstract: Embedded Zero-tree Wavelet (EZW) is a wavelet based image compression scheme. It is basically a quantization stage that incorporates some characteristics of the wavelet decomposition. The EZW approach and its descendants significantly outperform some of the generic approaches. The wavelet coefficients in different sub bands represent the same spatial location in the image. This is an important characteristic used by EZW. In case of decomposition, since the size of the different sub bands is different, then a single coefficient in the smaller sub band may represent the same spatial location as multiple coefficients in the other sub bands. This paper describes hardware implementation of EZW encoding algorithm along with Huffman encoding and decoding architectures. After performing lifting based DWT technique and EZW algorithm, Huffman coding ensures further compression of the image. In Huffman coding no bit string is a prefix of any other bit string. Hence each code is uniquely decodable.

Abstract: A reversible image steganographic scheme implemented in the SMVQ compression domain of image is proposed. The goal of this scheme is to hide secret data into the compression codes of image by applying the SMVQ state codebook. In addition to reversibility and high-payload, the bit rate of the compressed cover image is another consideration in the proposed scheme since the secret data are delivered through the compression codes of cover image. To compact the volume of the overall data needed to be transmitted, the Huffman coding technique is applied. By the proposed scheme, the original VQ-compressed cover image can be restored losslessly at the receiver. Simulation results demonstrate the feasibility of the proposed scheme.

Abstract: Huffman Compression, also known as Huffman Coding, is one of many compression techniques in use today. The two important features of Huffman coding are instantaneousness that is the codes can be interpreted as soon as they are received and variable length that is a most frequent symbol has length smaller than a less frequent symbol. The traditional Huffman coding has two procedures: constructing a tree in O(n 2 ) and then traversing it in O(n). Quantum computing is a promising approach of computation that is based on equations from Quantum Mechanics. Instantaneousness and variable length features are difficult to generalize to the quantum case. The quantum coding field is pioneered by Schumacher works on block coding scheme. To encode N signals sequentially, it requires O(N 3 ) computational steps. The encoding and decoding processes are far from instantaneous. Moreover, the lengths of all the codewords are the same. A Huffman-coding-inspired scheme for the storage of quantum information takes O(N(log N) a ) computational steps for a sequential implementation on non-parallel machines. The proposed algorithm, Quantum-inspired Huffman coding of symbols with equal frequencies, also has two procedures : calculating a quantum system state in O(n (lg n) 2 ) and then multiplying it by the inputs in O((lg n) 2 ).

Abstract: This paper represents the Algorithm for various Coding standards such as Huffman coding, Syntax based arithmetic coding and Context Adaptive Binary Arithmetic Coding used in MPEG, H.263 and H.264 respectively and their analysis. We found that average bit per symbol (average code word length) for Huffman coding is nearly equal to Entropy which is the basic requirement, for different bit rate PSNR is calculated with and without SBAC and finally we discuss Block diagrams of CABAC codec of H.264/AVC and Modified parallel algorithm for CABAC. Experiments demonstrate that this SBAC provide the improvement of up to 1dB over conventional H.263. For a set of test sequences representing typical material used in broadcast applications and for a range of acceptable video quality of about 30 to 38 dB, average bit-rate savings of 9%-14% are achieved.

Abstract: In this paper, we compare Huffman coding and Arithmetic coding with ASCII coding to observe their contribution to steganography. This way is to compress the embedded information first for enhance the payload of a cover image. There are many wonderful coding methods to compress this kind of string, such as Huffman coding and Arithmetic coding. The experiment results indicate that Huffman coding and Arithmetic coding as an important preprocess step of steganography can effectively reduce the amount of secret information with efficient encoding performance. And a theory opinion related to payload calculation is proposed which can be used to describe the relationship among the three parameters of steganography: imperceptibility, information embedding efficiency and payload.