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Real-time realistic rendering and hi...

Xu, Ruifeng.

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Real-time realistic rendering and high dynamic range image display and compression.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Real-time realistic rendering and high dynamic range image display and compression./
作者:	Xu, Ruifeng.
面頁冊數:	192 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5516.
Contained By:	Dissertation Abstracts International66-10B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3193515
ISBN:	9780542362545

Real-time realistic rendering and high dynamic range image display and compression.
Xu, Ruifeng.

Real-time realistic rendering and high dynamic range image display and compression. - 192 p.

Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5516.

Thesis (Ph.D.)--University of Central Florida, 2005.

This dissertation focuses on the many issues that arise from the visual rendering problem. Of primary consideration is light transport simulation, which is known to be computationally expensive. Monte Carlo methods represent a simple and general class of algorithms often used for light transport computation. Unfortunately, the images resulting from Monte Carlo approaches generally suffer from visually unacceptable noise artifacts. The result of any light transport simulation is, by its very nature, an image of high dynamic range (HDR). This leads to the issues of the display of such images on conventional low dynamic range devices and the development of data compression algorithms to store and recover the corresponding large amounts of detail found in HDR images. This dissertation presents our contributions relevant to these issues.

ISBN: 9780542362545Subjects--Topical Terms:

626642
Computer Science.

Real-time realistic rendering and high dynamic range image display and compression.
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500 $a Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5516.
500 $a Major Professor: Sumanta N. Pattanaik.
502 $a Thesis (Ph.D.)--University of Central Florida, 2005.
520 $a This dissertation focuses on the many issues that arise from the visual rendering problem. Of primary consideration is light transport simulation, which is known to be computationally expensive. Monte Carlo methods represent a simple and general class of algorithms often used for light transport computation. Unfortunately, the images resulting from Monte Carlo approaches generally suffer from visually unacceptable noise artifacts. The result of any light transport simulation is, by its very nature, an image of high dynamic range (HDR). This leads to the issues of the display of such images on conventional low dynamic range devices and the development of data compression algorithms to store and recover the corresponding large amounts of detail found in HDR images. This dissertation presents our contributions relevant to these issues.
520 $a Our contributions to high dynamic range image processing include tone mapping and data compression algorithms. This research proposes and shows the efficacy of a novel level set based tone mapping method that preserves visual details in the display of high dynamic range images on low dynamic range display devices. The level set method is used to extract the high frequency information from HDR images. The details are then added to the range compressed low frequency information to reconstruct a visually accurate low dynamic range version of the image.
520 $a Additional challenges associated with high dynamic range images include the requirements to reduce excessively large amounts of storage and transmission time. To alleviate these problems, this research presents two methods for efficient high dynamic range image data compression. One is based on the classical JPEG compression. It first converts the raw image into RGBE representation, and then sends the color base and common exponent to classical discrete cosine transform based compression and lossless compression, respectively. The other is based on the wavelet transformation. It first transforms the raw image data into the logarithmic domain, then quantizes the logarithmic data into the integer domain, and finally applies the wavelet based JPEG 2000 encoder for entropy compression and bit stream truncation to meet the desired bit rate requirement. We believe that these and similar such contributions will make a wide application of high dynamic range images possible. (Abstract shortened by UMI.)
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