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Multiscale geometric image processing.

Romberg, Justin K.

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Multiscale geometric image processing.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multiscale geometric image processing./
作者:	Romberg, Justin K.
面頁冊數:	114 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 1010.
Contained By:	Dissertation Abstracts International65-02B.
標題:	Engineering, System Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3122530
ISBN:	0496698804

Multiscale geometric image processing.
Romberg, Justin K.

Multiscale geometric image processing. - 114 p.

Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 1010.

Thesis (Ph.D.)--Rice University, 2004.

Since their introduction a little more than 10 years ago, wavelets have revolutionized image processing. Wavelet based algorithms define the state-of-the-art for applications including image coding (JPEG-2000), restoration, and segmentation. Despite their success, wavelets have significant shortcomings in their treatment of edges. Wavelets do not parsimoniously capture even the simplest geometrical structure in images, and wavelet based processing algorithms often produce images with ringing around the edges.

ISBN: 0496698804Subjects--Topical Terms:

1018128
Engineering, System Science.

Multiscale geometric image processing.
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100 1 $a Romberg, Justin K. $3 1928073
245 1 0 $a Multiscale geometric image processing.
300 $a 114 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-02, Section: B, page: 1010.
500 $a Chair: Richard G. Baraniuk.
502 $a Thesis (Ph.D.)--Rice University, 2004.
520 $a Since their introduction a little more than 10 years ago, wavelets have revolutionized image processing. Wavelet based algorithms define the state-of-the-art for applications including image coding (JPEG-2000), restoration, and segmentation. Despite their success, wavelets have significant shortcomings in their treatment of edges. Wavelets do not parsimoniously capture even the simplest geometrical structure in images, and wavelet based processing algorithms often produce images with ringing around the edges.
520 $a As a first step towards accounting for this structure, we will show how to explicitly capture the geometric regularity of contours in cartoon images using the wedgelet representation and a multiscale geometry model. The wedgelet representation builds up an image out of simple piecewise constant functions with linear discontinuities. We will show how the geometry model, by putting a joint distribution on the orientations of the linear discontinuities, allows us to weigh several factors when choosing the wedgelet representation: the error between the representation and the original image, the parsimony of the representation, and whether the wedgelets in the representation form "natural" geometrical structures. We will analyze a simple wedgelet coder based on these principles, and show that it has optimal asymptotic performance for simple cartoon images.
520 $a Next, we turn our attention to piecewise smooth images; images that are smooth away from a smooth contour. Using a representation composed of wavelets and wedgeprints (wedgelets projected into the wavelet domain), we develop a quadtree based prototype coder whose rate-distortion performance is asymptotically near-optimal. We use these ideas to implement a full-scale image coder that outperforms JPEG-2000 both in peak signal to noise ratio (by 1--1.5dB at low bitrates) and visually.
520 $a Finally, we shift our focus to building a statistical image model directly in the wavelet domain. For applications other than compression, the approximate shift-invariance and directional selectivity of the slightly redundant complex wavelet transform make it particularly well-suited for modeling singularity structure. Around edges in images, complex wavelet coefficients behave very predictably, exhibiting dependencies that we will exploit using a hidden Markov tree model. We demonstrate the effectiveness of the complex wavelet model with several applications: image denoising, multiscale segmentation, and feature extraction.
590 $a School code: 0187.
650 4 $a Engineering, System Science. $3 1018128
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710 2 0 $a Rice University. $3 960124
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790 1 0 $a Baraniuk, Richard G., $e advisor
790 $a 0187
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3122530