Image enhancement for point feature detection in built environment

Lehtola, Ville V.; Rönnholm, Petri

doi:10.1109/icsai.2014.7009389

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…It has been shown that contrast enhancement increases the performance of keypoint detectors (e.g. (Lehtola and Ronnholm, 2014)). The work of (Ballabeni et al, 2015) investigates the influence of multiple image preprocessing techniques including color balancing, image denoising, RGB to gray conversion, and content enhancement on the performance of the 3D reconstruction pipeline.…”

Section: Related Workmentioning

confidence: 99%

Reconstructing White Walls: Multi-View, Multi-Shot 3d Reconstruction of Textureless Surfaces

Ley¹,

Hänsch²,

Hellwich³

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The reconstruction of the 3D geometry of a scene based on image sequences has been a very active field of research for decades. Nevertheless, there are still existing challenges in particular for homogeneous parts of objects. This paper proposes a solution to enhance the 3D reconstruction of weakly-textured surfaces by using standard cameras as well as a standard multi-view stereo pipeline. The underlying idea of the proposed method is based on improving the signal-to-noise ratio in weakly-textured regions while adaptively amplifying the local contrast to make better use of the limited numerical range in 8-bit images. Based on this premise, multiple shots per viewpoint are used to suppress statistically uncorrelated noise and enhance low-contrast texture. By only changing the image acquisition and adding a preprocessing step, a tremendous increase of up to 300% in completeness of the 3D reconstruction is achieved.

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Section: Related Workmentioning

confidence: 99%