Data Prefetching for Smooth Navigation of Large Scale JPEG 2000 Images

Descampe, Antonin; Ou, Jianliang; Chevalier, P; Macq, Benoît

doi:10.1109/icme.2005.1521571

Cited by 5 publications

(6 citation statements)

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“…Cache is a rapid access to a space of memory in which it is stored the portions of the megaimage that shall be visited in the future (Davison, 1999). Prefetching is the anticipated uploading of those parts of the mega-image to which the navigation will be addressed in the future (Descampe et al, 2005). These techniques have shown to highly improve navigation times (Aperio, 2005;Descampe et al, 2005), but their performance depends on the prediction capacity of the system (Descampe et al, 2007;Rhodes and Ramakrishnan, 2005).…”

Section: Introductionmentioning

confidence: 98%

A model for predicting pathologist's velocity profiles when navigating virtual slides

Gómez

Romero

2009

Microscopy Res & Technique

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Navigation through large microscopic images is a potential benefit for histology or pathology teaching, for improving the quality of diagnosis in pathology, or for communicating pathologists in some telemedicine applications. However, the size of this kind of images is prohibitive for navigation with conventional techniques. This article presents a soft computing model, which permits to anticipate the pathologist trajectories in diagnosis tasks when exploring virtual slides. The Bayesian strategy combines an offline model of a baseline pathologist knowledge (the prior) and a prediction online module (the likelihood) that captures a particular pathologist navigation pattern. While optimal parameters for the biologically inspired offline model are calculated using an Expectation-Maximization strategy, prediction is carried out by a particle filter. Parameters are estimated from several series of actual navigations performed by several pathologists in different virtual slides. The present approach is compared with other conventional prediction methods and decreases the calculated MSE in about a 50% for the entire group of pathologists.

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Section: Introductionmentioning

confidence: 98%

A model for predicting pathologist's velocity profiles when navigating virtual slides

Gómez

Romero

2009

Microscopy Res & Technique

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“…To define our navigation model, we adopt the formalism introduced in [7]. We assume that the user only browses through various image resolutions and spatial locations and that he has only 6 possible actions : zoom-in, zoom-out, up, down, right and left.…”

Section: User Navigation and Reaction Modelsmentioning

confidence: 99%

“…A natural way to schedule data is to first feed the current WoI as long as there are packets relevant to this WoI (and not till the threshold Θ has been achieved, as for the oracle). Once this is done, data for future WoI is pre-fetched, because it is always better to transmit some additional image data than not transmit any information [7].…”

Section: Natural Pre-fetchingmentioning

confidence: 99%

“…In contrast, our paper solves the pre-fetching problem in a formal rate-distortion (RD) framework. In [7], the authors combine JPEG2000 flexibility with a user navigation model to manage the client cache and pre-fetch data. However, the authors in [7] assume that user navigation commands are regularly spaced.…”

Section: Introduction and Related Workmentioning

confidence: 99%

“…In [7], the authors combine JPEG2000 flexibility with a user navigation model to manage the client cache and pre-fetch data. However, the authors in [7] assume that user navigation commands are regularly spaced. So, they neglect the fact that the data displayed at the client play a key role on the release of a novel request by the user.…”

Section: Introduction and Related Workmentioning

confidence: 99%

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Pre-Fetching Strategies for Remote and Interactive Browsing of JPEG2000 Images

Descampe

Vleeschouwer

Iregui

et al. 2006

2006 International Conference on Image Processing

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This paper considers the remote interactive browsing of large JPEG2000 images. In contrast with previous contributions, we focus on the dynamic nature of the system. Practically, we study the conditions under which a priori knowledge about the user behavior may help to improve the browsing system reactivity, when combined with appropriate pre-fetching mechanisms. In particular, our simulations show that, due to the latency inherent to client/server exchanges, a benefit can be drawn by scheduling future window of interest (WoI) data before all current WoI data have been sent to the client. They also reveal that an accurate knowledge of the user behavior is not necessary to get important improvements over conventional scheduling approaches.

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