In this paper a new fully scalable - wavelet based - video coding architecture is proposed, where motion compensated temporal filtered subbands of spatially scaled versions of a video sequence can be used as base layer for inter-scale predictions. These predictions take place between data at the same resolution level without the need of interpolation. The prediction residuals are further transformed by spatial wavelet decompositions. The resulting multi-scale spatiotemporal wavelet subbands are coded thanks to an embedded morphological dilation technique and context based arithmetic coding. Dyadic spatio-temporal scalability and progressive SNR scalability are achieved. Multiple adaptation
decoding can be easily implemented without the need of knowing a predefined set of operating points. The proposed coding system allows to compensate some of the typical drawbacks of current wavelet based scalable video coding architectures and shows interesting visual results even when compared with the single operating point video coding standard AVC/H.264.
This paper presents some ideas which extend the functionality and the application fields of a spatially selective coding within a JPEG2000 framework. At first, the image quality drop between the Regions of Interest (ROI) and the background (BG) is considered. In a conventional approach, the reconstructed image quality steeply drops along the ROI boundary; however, this effect could be considered or perceived objectionable in some use cases. A simple quality decay management is proposed here, which makes use of concentric ROI with different scaling factors. This allows the technique to be perfectly consistent with the JPEG2000 part 2 ROI definition and description. Another considered issue is the extension of the selective ROI coding to a 3D Volume of Interest coding. This extension is currently under consideration for the part 10 of JPEG2000, JP3D. An easy and effective 2D to 3D extension for the VOI definition and description is proposed here: a VOI is defined by a set composition of ROI generated solids, where ROI are defined along one or more volume cutting direction, and is described by the relative set of ROI parameters. Moreover, the quality decay management can be applied to this extension. The proposed techniques could have a significant impact on the selective coding of medical images and volumes. Image quality issues are very important but very critical factors in that field, which also constitutes the dominant market for 3D applications. Therefore, some experiments are presented on medical
images and volumes in order evaluate the benefits of the proposed
approaches in terms of diagnostic quality improvement with respect to
a conventional ROI coding usage.
Interactivity is a main requirement for 3D visualization of
medical images in a variety of clinical applications. The good
matching between segmentation and rendering techniques allows
to design easy to use interactive systems which assist the physicians
in dynamically creating and manipulating 'diagnostically relevant'
images from volumetric data sets. In this work we consider the
above problem within an original interactive visualization
paradigm. By this paradigm we want to highlight the twofold
clinical requirement of a) detecting and visualizing structures of
diagnostic interest (SoDI's) and b) adding to the 3D scene some other
structures to create a meaningful visual context. Being the
opacity modulation of the different structures a crucial point,
we propose an opacity management which reflects the paradigm
ideas and operates by means of a twofold indexed look-up table (2iLUT). The 2iLUT consists of a combination of attribute based and object based opacity management and is here designed and tested in order to combine the time interaction benefits of an indexed opacity setting with the effective handling of the above classification and visualization clinical requirements.
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.
This work addresses the delicate problem of lossy compression of medical images. More specifically, a selective allocation of coding resources is introduced based on the concept of 'diagnostic interest' and an interactive methodology based on a new measure of 'diagnostic quality'. The selective allocation of resources is made possible by a selection a priori of regions of specific interest for diagnostic purpose. The idea is to change the precision of representation in a transformed domain of region of particular interest, through a weighting procedure by an on- line user-defined quantization matrix. The overall compression method is multi-resolution, provides for an embedded generation of the bit-stream and guarantees for a good rate-distortion trade-off, at various bit-rates, with spatially varying reconstruction quality. This work also analyzes the delicate issue of a professional usage of lossy compression in a PACS environment. The proposed compression methodology gives interesting insights in favor of using lossy compression in a controlled fashion by the expert radiologist. Most of the ideas presented in this work have been confirmed by extensive experimental simulations involving medical expertise.
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