Improving SPIHT-based Compression of Volumetric Medical Data

Volumetric medical data (CT,MR) are useful tools for diagnostic investigation however their usage may be made diffcult because of the amount of data to store or because of the duration of communication over a limited capacity channel. In order to code such information sources we present a progressive three dimensional image compression algorithm based on zerotree wavelet coder with arithmetic coding. We make use of a 3D separable biorthogonal wavelet transform and we extend the zerotree SPIHT algorithm to three dimensions. Moreover we propose some improvements to the SPIHT encoder in order to obtain a better rate distortion performance without increasing the computational complexity. Finally we propose an efficient context-based adaptive arithmetic coding which eliminates high order redundancy. The results obtained on progressive coding of a test CT volume are better than those presented in recent similar works both for the mean PSNR on the whole volume and for the PSNR homogeneity between various slices

3D Wavelet Transformation for Visual Data Coding With Spatio and Temporal Scalability as Quality Artifacts: Current State Of The Art

Several techniques based on the three–dimensional (3-D) discrete cosine transform (DCT) have been proposed for visual data coding. These techniques fail to provide coding coupled with quality and resolution scalability, which is a significant drawback for contextual domains, such decease diagnosis, satellite image analysis. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and mainly investigates various types of compression techniques those exists, and putting it all together for a conclusion on further research scope

Cyclostationary error analysis and filter properties in a 3D wavelet coding framework

The reconstruction error due to quantization of wavelet subbands can be modeled as a cyclostationary process because of the linear periodically shift variant property of the inverse wavelet transform. For N-dimensional data, N-dimensional reconstruction error power cyclostationary patterns replicate on the data sample lattice. For audio and image coding applications this fact is of little practical interest since the decoded data is perceived in its wholeness, the error power oscillations on single data elements cannot be seen or heard and a global PSNR error measure is often used to represent the reconstruction quality. A different situation is the one of 3D data (static volumes or video sequences) coding, where decoded data are usually visualized by plane sections and the reconstruction error power is commonly measured by a PSNR[n] sequence, with n representing either a spatial slicing plane (for volumetric data) or the temporal reference frame (for video). In this case, the cyclostationary oscillations on single data elements lead to a global PSNR[n] oscillation and this effect may become a relevant concern. In this paper we study and describe the above phenomena and evaluate their relevance in concrete coding applications. Our analysis is entirely carried out in the original signal domain and can easily be extended to more than three dimensions. We associate the oscillation pattern with the wavelet filter properties in a polyphase framework and we show that a substantial reduction of the oscillation amplitudes can be achieved under a proper selection of the basis functions. Our quantitative model is initially made under high-resolution conditions and then qualitatively extended to all coding rates for the wide family of bit-plane quantization-based coding techniques. Finally, we experimentally validate the proposed models and we perform a subjective evaluation of the visual relevance of the PSNR[n] fluctuations in the cases of medical volumes and video coding

Embedded Morphological Dilation Coding for 2D and 3D Images

Current wavelet-based image coders obtain high performance thanks to the identification and the exploitation of the statistical properties of natural images in the transformed domain. Zerotree-based algorithms, as Embedded Zerotree Wavelets (EZW) and Set Partitioning In Hierarchical Trees (SPIHT), offer high Rate-Distortion (RD) coding performance and low computational complexity by exploiting statistical dependencies among insignificant coefficients on hierarchical subband structures. Another possible approach tries to predict the clusters of significant coefficients by means of some form of morphological dilation. An example of a morphology-based coder is the Significance-Linked Connected Component Analysis (SLCCA) that has shown performance which are comparable to the zerotree-based coders but is not embedded. A new embedded bit-plane coder is proposed here based on morphological dilation of significant coefficients and context based arithmetic coding. The algorithm is able to exploit both intra-band and inter-band statistical dependencies among wavelet significant coefficients. Moreover, the same approach is used both for two and three-dimensional wavelet-based image compression. Finally we the algorithms are tested on some 2D images and on a medical volume, by comparing the RD results to those obtained with the state-of-the-art wavelet-based coders

Low Bit-rate Color Video Compression using Multiwavelets in Three Dimensions

In recent years, wavelet-based video compressions have become a major focus of research because of the advantages that it provides. More recently, a growing thrust of studies explored the use of multiple scaling functions and multiple wavelets with desirable properties in various fields, from image de-noising to compression. In term of data compression, multiple scaling functions and wavelets offer a greater flexibility in coefficient quantization at high compression ratio than a comparable single wavelet. The purpose of this research is to investigate the possible improvement of scalable wavelet-based color video compression at low bit-rates by using three-dimensional multiwavelets. The first part of this work included the development of the spatio-temporal decomposition process for multiwavelets and the implementation of an efficient 3-D SPIHT encoder/decoder as a common platform for performance evaluation of two well-known multiwavelet systems against a comparable single wavelet in low bitrate color video compression. The second part involved the development of a motion-compensated 3-D compression codec and a modified SPIHT algorithm designed specifically for this codec by incorporating an advantage in the design of 2D SPIHT into the 3D SPIHT coder. In an experiment that compared their performances, the 3D motion-compensated codec with unmodified 3D SPIHT had gains of 0.3dB to 4.88dB over regular 2D wavelet-based motion-compensated codec using 2D SPIHT in the coding of 19 endoscopy sequences at 1/40 compression ratio. The effectiveness of the modified SPIHT algorithm was verified by the results of a second experiment in which it was used to re-encode 4 of the 19 sequences with lowest performance gains and improved them by 0.5dB to 1.0dB. The last part of the investigation examined the effect of multiwavelet packet on 3-D video compression as well as the effects of coding multiwavelet packets based on the frequency order and energy content of individual subbands

High-Performance Embedded Morphological Wavelet Coding

Morphological analysis can be applied in wavelet domain to analyze and represent the position of significant coefficients. New operators have to be introduced which are able to exploit both the multiresolution and the filter bank peculiarities of the subband representation of visual information. In this paper an efficient morphological wavelet coder is proposed. The clustering trend of significant coefficients is captured by a new kind of multi resolution binary dilation operator. The layered and adaptive nature of this subband dilation makes it possible for the coding technique to produce an embedded bit-stream with a modest computational cost and state-of-the-art Rate-Distortion performance. Morphological wavelet coding appears promising because the localized analysis of wavelet coefficient clusters is adequate to capture intrinsic patterns of the source which can have substantial benefits for perceptual or even object-based reconstruction quality concerns. Here we test the performance of our algorithm and compare the effects of different wavelet filters. We obtain state of the art coding performance and good perceptual results both for 2D and 3D images, with a new technique that seems to be well suited for further developments

3D encoding/2D decoding of medical data

We propose a fully three-dimensional wavelet-based coding system featuring 3D encoding/2D decoding functionalities. A fully three-dimensional transform is combined with context adaptive arithmetic coding; 2D decoding is enabled by encoding every 2D subband image independently. The system allows a finely graded up to lossless quality scalability on any 2D image of the dataset. Fast access to 2D images is obtained by decoding only the corresponding information thus avoiding the reconstruction of the entire volume. The performance has been evaluated on a set of volumetric data and compared to that provided by other 3D as well as 2D coding systems. Results show a substantial improvement in coding efficiency (up to 33%) on volumes featuring good correlation properties along the z axis. Even though we did not address the complexity issue, we expect a decoding time of the order of one second/image after optimization. In summary, the proposed 3D/2D Multidimensional Layered Zero Coding System (3D/2D MLZC) provides the improvement in compression efficiency attainable with 3D systems without sacrificing the effectiveness in accessing the single images characteristic of 2D ones

Lossy to lossless object-based coding of 3-D MRI data

We propose a fully three-dimensional object-based coding system exploiting the diagnostic relevance of the different regions of the volumetric data for rate allocation. The data are first decorrelated via a 3D discrete wavelet transform. The implementation via the lifting steps scheme allows to map integer-to-integer values, enabling lossless coding, and facilitates the definition of the object-based inverse transform. The coding process assigns disjoint segments of the bitstream to the different objects, which can be independently accessed and reconstructed at any up-to-lossless quality. Two fully 3D coding strategies are considered: Embedded Zerotree Coding (EZW-3D) and Multidimensional Layered Zero Coding (MLZC), both generalized for Region of Interest (ROI) based processing. In order to avoid artifacts along region boundaries, some extra coefficients must be encoded for each object. This gives rise to an overheading of the bitstream with respect to the case where the volume is encoded as a whole. The amount of such extra information depends on both the filter length and the decomposition depth. The system is characterized on a set of head magnetic resonance images. Results show that MLZC and EZW-3D have competitive performances. In particular, the best MLZC mode outperforms the other state-of-the-art techniques on one of the datasets for which results are available in the literature