A digital image is a numerical representation of visual perception that can be manipulated according to specifications. In order reduce the cost storage and transmission, images are compressed. Depending upon quality reconstruction, compression methods categorized as Lossy Lossless compression. The lossless techniques, where exact recovery data possible, most challenging task considering tradeo...

A new class of image compression algorithms has been developed for exploiting dependencies between the hierarchical wavelet coefficients using zerotrees. This paper deals with a fuzzy inference filter for image entropy coding by choosing significant coefficients and zerotree roots in the higher frequency wavelet subbands. Moreover, an adaptive quantization is proposed to improve the coding perf...

This paper presents a practical realisation in hardware of the concepts of variable order Markov modelling using multi-symbol alphabets and arithmetic coding for lossless compression of universal data. This type of statistical coding algorithms has long been regarded as being able to deliver very high compression ratios close to the information content of the source data. However, their high co...

Decoding a fractal compressed image can be seen as solving an aane two-scale functional equation. If the aane term is zero, the dilation equation becomes linear and the solution is similar to the scaling functions from wavelet theory. In both cases a linear operator, parameter-ized with a few variables determines a complicate looking function. We present two classes of algorithms for gray image...

The recently ratified new video compression standard H.264/MPEG-4 AVC is reviewed. Its basic concepts as well as all important features/algorithms are explained in detail, it is put into the historical context of other video coding standards, and an objective and subjective performance evaluation is given. Compared to previous standards, the coding improvements of H.264 are, in terms of PSNR, a...

We present a new arithmetic coding algorithm based on a small cache memory. The complexity of multilevel arithmetic coding has been reduced by restricting the operations to those symbols stored in the cache. We analyze the best organisation of the cache, trying out different configurations, associativity and replacement algorithms. Finally, a new architecture for encoding and decoding has been ...

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...

Introduction: The problem of compressed pattern matching deals with ways to find a pattern within a compressed file, without decompressing it first. The techniques for solving this problem fall into two major categories – creating a unique compression scheme that enables efficient pattern matching; or using some known compression scheme and develop algorithms to search the files it produces. In...

Decoding a fractal compressed image can be seen as solving an a ne two-scale functional equation. If the a ne term is zero, the dilation equation becomes linear and the solution is similar to the scaling functions from wavelet theory. In both cases a linear operator, parameterized with a few variables determines a complicate looking function. We present two classes of algorithms for gray image ...

Speech compression is a mature technology with many applications. Over the past decade, huge advances have been made in the area of speech coding for reduced bit-rate transmission. With perceptual audio coding, the signal is coded efficiently using a psychoacoustic model, as in MPEG standards. In this paper, two well known algorithms, LPC (Linear Predictive Coding) and subband coding are combin...