A Comparison of Some State of the Art Image Denoising Methods

Seo, Hae Jong; Chatterjee, Priyam; Takeda, Hiroyuki; Milanfar, Peyman

doi:10.1109/acssc.2007.4487266

Cited by 11 publications

(5 citation statements)

References 4 publications

(5 reference statements)

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“…Wavelet coefficient modelling approaches are further subdivided into deterministic and statistical modelling of wavelet coefficients. Accordingly, interesting reviews can be found in Buccigrossi and Simoncelli (1999), Romberg et al (2001), Buades et al (2005), Seo et al (2007).…”

Section: Wavelet Domain Filtersmentioning

confidence: 97%

RETRACTED ARTICLE: Document image analysis: issues, comparison of methods and remaining problems

Saba

Sulong

2010

Artif Intell Rev

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Image analysis is an interesting research area with a large variety of challenging applications. Researchers have worked from decades on this topic, as witnessed by the scientific literature. However, document image analysis is the special case in image analysis as their spatial properties are different from natural images. Therefore, the main focus of this paper is to describe image denoising issues in general and document image issues in particular. Since the field of document processing is relatively new, it is also dynamic, so current methods have room for improvement and innovations are still being made. Several algorithms proposed in the literature are described. Critical discussions are reported about the current status of the field and open problems are highlighted. It is also demonstrated that, there are rarely definitive techniques for all cases of a certain problem. We surveyed the state of art, analyzed recent trends and tried to identify challenges for future research in this field.

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Section: Wavelet Domain Filtersmentioning

confidence: 97%

RETRACTED ARTICLE: Document image analysis: issues, comparison of methods and remaining problems

Saba

Sulong

2010

Artif Intell Rev

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“…In Figure 12 we compare the proposed algorithm with state of the art denoising algorithms [64] on a noisy Lena image. We present comparisions with Non-local Means filter [65] and Iterative steering kernel regression [66] using standard parameter settings.…”

Section: Resultsmentioning

confidence: 99%

Left-invariant evolutions of wavelet transforms on the similitude group

Sharma

Duits

2015

Applied and Computational Harmonic Analysis

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Enhancement of multiple-scale elongated structures in noisy image data is relevant for many biomedical applications but commonly used PDE-based enhancement techniques often fail at crossings in an image. To get an overview of how an image is composed of local multiple-scale elongated structures we construct a continuous wavelet transform on the similitude group, SIM (2). Our unitary transform maps the space of images onto a reproducing kernel space defined on SIM (2), allowing us to robustly relate Euclidean (and scaling) invariant operators on images to leftinvariant operators on the corresponding continuous wavelet transform. Rather than often used wavelet (soft-)thresholding techniques, we employ the group structure in the wavelet domain to arrive at left-invariant evolutions and flows (diffusion), for contextual crossing preserving enhancement of multiple scale elongated structures in noisy images. We present experiments that display benefits of our work compared to recent PDE techniques acting directly on the images and to our previous work on left-invariant diffusions on Coherent state transforms defined on Euclidean motion group.

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“…Designed to process single images, nonparametric kernel-based filters such as Data-adaptive Kernel Regression and Optimal Spatial Adaption are a general solution to grain removal, but tend to soften some characteristics of CG renders such as high-frequency texture detail and irregular noise patterns [Seo et al 2007]. However, if motion reference is available, a temporal filter will produce better results on any slow moving sequence by sampling across multiple frames, with the results only diminishing under extreme motion or dynamic lighting.…”

Section: Overviewmentioning

confidence: 99%

Silencing the noise on Elysium

Goddard

2014

ACM SIGGRAPH 2014 Talks

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Figure 1: Closeup of Neill Blomkamp's Elysium. c 2013 CTMG.During Neill Blomkamp's sci-fi epic Elysium (Fig.1), we experienced severe noise issues when ray-tracing the glossy reflections and heavy indirect lighting on the colossal habitat, within a tight production schedule. We present a new solution to the common issue of ray-traced noise, drastically reducing render times by expanding the use of a temporal filter to attenuate the weighting of a non-local means algorithm which selectively refines it's result.

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A Comparison of Some State of the Art Image Denoising Methods

Cited by 11 publications

References 4 publications

RETRACTED ARTICLE: Document image analysis: issues, comparison of methods and remaining problems

RETRACTED ARTICLE: Document image analysis: issues, comparison of methods and remaining problems

Left-invariant evolutions of wavelet transforms on the similitude group

Silencing the noise on Elysium

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