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

Achanta, Radhakrishna; Shaji, Appu; Smith, Kevin; Lucchi, Aurélien; Fua, Pascal; Süsstrunk, Sabine

doi:10.1109/tpami.2012.120

Cited by 7,967 publications

(5,448 citation statements)

References 32 publications

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“…Fourth, the intermediate step of referring the weighted green index to regular grid cells could be optimized. Rather than using regular grid cells, methods of superpixel generation, such as SLIC (Achanta et al, 2012) could be used to create an intermediate level that is closer to the actual spectral characteristics of the underlying image. The seed pixels could match the centroid of (multiples of) the European reference grid as proposed by Lang and Csillik (2017).…”

Section: Discussion and Outlookmentioning

confidence: 99%

Urban green valuation integrating biophysical and qualitative aspects

Lang

2017

European Journal of Remote Sensing

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Urban green mapping has become an operational task in city planning, urban land management, and quality of life assessments. As a multi-dimensional, integrative concept, urban green comprising several ecological, socio-economic, and policy-related aspects. In this paper, the author advances the representation of urban green by deriving scale-adapted, policy-relevant units. These so-called geons represent areas of uniform green valuation under certain size and homogeneity constraints in a spatially explicit representation. The study accompanies a regular monitoring scheme carried out by the urban municipality of the city of Salzburg, Austria, using optical satellite data. It was conducted in two stages, namely SBG_QB (10.2 km², QuickBird data from 2005) and SBG_WV (140 km², WorldView-2 data from 2010), within the functional urban area of Salzburg. The geon delineation was validated by several quantitative measures and spatial analysis techniques, as well as ground documentation, including panorama photographs and visual interpretation. The spatial association pattern was assessed by calculating Global Moran’s I with incremental search distances. The final geonscape, consisting of 1083 units with an average size of 13.5 ha, was analyzed by spatial metrics. Finally, categories were derived for different types of functional geons. Future research paths and improvements to the described strategy are outlined.

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Section: Discussion and Outlookmentioning

confidence: 99%

Urban green valuation integrating biophysical and qualitative aspects

Lang

2017

European Journal of Remote Sensing

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“…Both d1 and d2 terms are explained next. We oversegment the image I into superpixels via the SLIC algorithm [32] for computational efficiency. For region ri , we express the saliency measurements via the above distances d1 and d2 as:…”

Section: Saliency Refinement Via Foreground and Background Cuesmentioning

confidence: 99%

Correspondence Driven Saliency Transfer

Yang

Shen

Shao

et al. 2016

IEEE Trans. on Image Process.

138

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Abstract-In this paper, we show that large annotated data sets have great potential to provide strong priors for saliency estimation rather than merely serving for benchmark evaluations. To this end, we present a novel image saliency detection method called saliency transfer. Given an input image, we first retrieve a support set of best matches from the large database of saliency annotated images. Then, we assign the transitional saliency scores by warping the support set annotations onto the input image according to computed dense correspondences. To incorporate context, we employ two complementary correspondence strategies: a global matching scheme based on scene-level analysis and a local matching scheme based on patch-level inference. We then introduce two refinement measures to further refine the saliency maps and apply the random-walk-with-restart by exploring the global saliency structure to estimate the affinity between foreground and background assignments. Extensive experimental results on four publicly available benchmark data sets demonstrate that the proposed saliency algorithm consistently outperforms the current state-of-the-art methods.

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“…Simple Linear Iterative Clustering SLIC (Simple Linear Iterative Clustering) was proposed by Süsstrunk [24]. It is a fast and efficient superpixel like method.…”

Section: Related Workmentioning

confidence: 99%

Robust Interactive Segmentation Using Color Histogram and Contourlet Transform

Huang¹,

Pun²

2015

IJCTE

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 Abstract-Efficient and accurate image segmentation is an important task in computer vision and object recognition. Since fully automatic image segmentation is hard to handle with natural images and texture images with complex background, thus interactive scheme with a few simple user inputs is a very good addition to image segmentation. For the purpose to accurately extract objects from different images, this paper presents a color histogram and Contourlet transform based interactive image segmentation. In the initialization stage, a superpixel based initial segmentation is applied to the original image. After that, the original image will be divided into a certain number of superpixels. Then, each superpixel will be represented by a novel superpixel feature based on color histogram and Contourlet transform. Finally, by using user-defined strokes, we merge the superpixels which are similar to marked object superpixels and merge the superpixels similar to marked background superpixels, until classify all superpixels. The computational complexity is analyzed, and comparative experimental results show that the proposed scheme can reliably and rapidly extract the desired object from the complex background.

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

Cited by 7,967 publications

References 32 publications

Urban green valuation integrating biophysical and qualitative aspects

Urban green valuation integrating biophysical and qualitative aspects

Correspondence Driven Saliency Transfer

Robust Interactive Segmentation Using Color Histogram and Contourlet Transform

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