S. Süsstrunk

Publications
Influence

SLIC Superpixels Compared to State-of-the-Art Superpixel Methods

R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, S. Süsstrunk
Mathematics, Computer Science
IEEE Transactions on Pattern Analysis and Machine…
1 November 2012

We empirically compare five state-of-the-art superpixel algorithms for their ability to adhere to image boundaries, speed, memory efficiency, and their impact on segmentation performance. Expand

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Frequency-tuned salient region detection

R. Achanta, S. Hemami, F. J. Estrada, S. Süsstrunk
CVPR
20 June 2009

We introduce a method for salient region detection that outputs full resolution saliency maps with well-defined boundaries of salient objects. Expand

2,188
435

Frequency-tuned salient region detection

R. Achanta, S. Hemami, F. J. Estrada, S. Süsstrunk
Computer Science
IEEE Conference on Computer Vision and Pattern…
2009

We introduce a frequency-tuned approach to estimate center-surround contrast using color and luminance features that offers three advantages over existing methods: uniformly highlighted salient regions with welldefined boundaries. Expand

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161
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SLIC Superpixels ?

R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, S. Süsstrunk
2010

Superpixels are becoming increasingly popular for use in computer vision applications. However, there are few algorithms that output a desired number of regular, compact superpixels with a low… Expand

A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution

P. Vandewalle, S. Süsstrunk, M. Vetterli
Computer Science
EURASIP J. Adv. Signal Process.
2006

We propose a frequency domain technique to precisely register a set of aliased images, based on their low-frequency, aliasing-free part of the images. Expand

Saliency detection using maximum symmetric surround

R. Achanta, S. Süsstrunk
Computer Science
IEEE International Conference on Image Processing
3 December 2010

We present a novel saliency detection algorithm based on the idea of maximum symmetric surround. Expand

Salient Region Detection and Segmentation

R. Achanta, F. J. Estrada, P. Wils, S. Süsstrunk
Computer Science
ICVS
12 May 2008

We present a novel method to determine salient regions in images using low-level features of luminance and color. Expand

Multi-spectral SIFT for scene category recognition

Matthew A. Brown, S. Süsstrunk
Mathematics, Computer Science
CVPR
20 June 2011

We show that the addition of near-infrared information leads to significantly improved performance in a scene-recognition task, and that the improvements are greater still when an appropriate 4-dimensional colour representation is used. Expand

Linear demosaicing inspired by the human visual system

D. Alleysson, S. Süsstrunk, J. Hérault
Computer Science, Medicine
IEEE Transactions on Image Processing
1 April 2005

We have developed a Fourier-domain model for spatial multiplexing of color, common to CFA images and the human retina, allowing for demosaicing by spatial frequency filtering. Expand

Superpixels and Polygons Using Simple Non-iterative Clustering

R. Achanta, S. Süsstrunk
Computer Science
IEEE Conference on Computer Vision and Pattern…
1 July 2017

We present an improved version of the Simple Linear Iterative Clustering (SLIC) superpixel segmentation. Expand

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