Compression of Earth Science Data with JPEG2000

Kulkarni, Prajit; Bilgin, Ali; Marcellin, Michael W.; Dagher, Joseph C.; Kasner, James H.; Flohr, Thomas; Rountree, Janet

doi:10.1007/0-387-28600-4_12

Cited by 23 publications

(10 citation statements)

References 11 publications

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“…The complementary problem of the optimization of the bitrate for a target quality is addressed in [17,18], reducing the computational load of Tier-1 too. Specific techniques of rate-distortion optimization are also developed in scenarios such as scanbased applications [19], the coding of hyperspectral data [20], implementations of motion JPEG2000 [21], and for images containing tiles [22]. Most of the proposed methods of rate-distortion optimization can be employed to allocate successive layers of quality at increasing bitrates.…”

Section: Review Of Layer Formation and Rate-distortion Optimizationmentioning

confidence: 99%

Enhanced JPEG2000 Quality Scalability through Block-Wise Layer Truncation

Aulí-Llinàs

Serra-Sagristà

Bartrina-Rapesta

2010

EURASIP J. Adv. Signal Process.

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Quality scalability is an important feature of image and video coding systems. In JPEG2000, quality scalability is achieved through the use of quality layers that are formed in the encoder through rate-distortion optimization techniques. Quality layers provide optimal rate-distortion representations of the image when the codestream is transmitted and/or decoded at layer boundaries. Nonetheless, applications such as interactive image transmission, video streaming, or transcoding demand layer fragmentation. The common approach to truncate layers is to keep the initial prefix of the to-be-truncated layer, which may greatly penalize the quality of decoded images, especially when the layer allocation is inadequate. So far, only one method has been proposed in the literature providing enhanced quality scalability for compressed JPEG2000 imagery. However, that method provides quality scalability at the expense of high computational costs, which prevents its application to the aforementioned applications. This paper introduces a Block-Wise Layer Truncation (BWLT) that, requiring negligible computational costs, enhances the quality scalability of compressed JPEG2000 images. The main insight behind BWLT is to dismantle and reassemble the to-be-fragmented layer by selecting the most relevant codestream segments of codeblocks within that layer. The selection process is conceived from a rate-distortion model that finely estimates rate-distortion contributions of codeblocks. Experimental results suggest that BWLT achieves near-optimal performance even when the codestream contains a single quality layer.

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Section: Review Of Layer Formation and Rate-distortion Optimizationmentioning

confidence: 99%

Enhanced JPEG2000 Quality Scalability through Block-Wise Layer Truncation

Aulí-Llinàs

Serra-Sagristà

Bartrina-Rapesta

2010

EURASIP J. Adv. Signal Process.

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“…The final prediction for a pixel is obtained by a combination of linear predictions involving weights from different clusters, pondered by the degrees of membership of the pixel to each cluster. It is worth mentioning that wavelet-based compressors such as JPEG2000 (Taubman & Marcellin, 2002) have been successfully used for lossy compression of multiband images, either hyperspectral (Blanes & Serra-Sagrista, 2010;Fowler & Rucker, 2007) or general earth data (Kulkarni et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

The Wavelet Transform as a Classification Criterion Applied to Improve Compression of Hyperspectral Images

Acevedo¹,

Ruedin²

2012

Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

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“…The focus of this paper is the application of a relatively new image compression technique that is both established and well known in the digital image processing community to the challenging task of the solar physics community to cope with the ever-growing amount of data available. While the impetus for this article is handling solar physics data, similar requirements of accessing, browsing and searching image data exist for applications in other areas such as the earth sciences and medical research [4,5,6].…”

Section: Introductionmentioning

confidence: 99%

JHelioviewer: Visualizing Large Sets of Solar Images Using JPEG 2000

Müller¹,

Fleck²,

Dimitoglou

et al. 2009

Comput. Sci. Eng.

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Across all disciplines that work with image data -from astrophysics to medical research and historic preservation -there is a growing need for efficient ways to browse and inspect large sets of high-resolution images. We present the development of a visualization software for solar physics data based on the JPEG 2000 image compression standard. Our implementation consists of the JHelioviewer client application that enables users to browse petabyte-scale image archives and the JHelioviewer server, which integrates a JPIP server, metadata catalog and an event server. JPEG 2000 offers many useful new features and has the potential to revolutionize the way high-resolution image data are disseminated and analyzed. This is especially relevant for solar physics, a research field in which upcoming space missions will provide more than a terabyte of image data per day. Providing efficient access to such large data volumes at both high spatial and high time resolution is of paramount importance to support scientific discovery.

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Compression of Earth Science Data with JPEG2000

Cited by 23 publications

References 11 publications

Enhanced JPEG2000 Quality Scalability through Block-Wise Layer Truncation

Enhanced JPEG2000 Quality Scalability through Block-Wise Layer Truncation

The Wavelet Transform as a Classification Criterion Applied to Improve Compression of Hyperspectral Images

JHelioviewer: Visualizing Large Sets of Solar Images Using JPEG 2000

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