Estimation of scene illuminant chromaticity by using single image

2014 22nd Signal Processing and Communications Applications Conference (SIU)

2014

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Özetçe -Sahnelere ait derinlik bilgisini elde etmede kullanılan stereo imgeleme yöntemlerinin bas¸arımları, sahnedeki nesnelerin yansıtıcı yüzey özellikleri ve kamera ile ıs¸ık kay-nag˘ının bag˘ıl konumundaki olası deg˘is¸imler sebebiyle olumsuz yönde etkilenmektedir. Bu çalıs¸mada, düzlemsel aynalar kullanılarak olus¸turulmus¸ katadioptrik bir çok bakıs¸lı imgeleme sistemi önerilmis¸tir. Sahnedeki aynasal yansımalardan kaynaklı stereo es¸les¸tirme problemleri vurgulanmıs¸ ve bu problemlerin polarizasyon imgeleri kullanılarak önemli ölçüde giderilebileceg˘i gösterilmis¸tir.Anahtar Kelimeler-polarizasyon imgeleri, stereo kars¸ılıklılık problemi, katadioptrik çok bakıs¸lı stereo, aynasal yansıma.Abstract-Performance of stereo imaging methods, which are used to find depth information of a scene, can be adversely affected by surface reflection properties of subjects in the scene and possible change in relative camera and light source positions. In this study a catadioptric multiview imaging system, which is constructed by using planar mirrors, is proposed. Stereo matching problems which are caused by the specular reflections in the scene are highlighted and it is shown that those problems can be significantly alleviated by using polarization images.

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Section: Introductionunclassified

Enhancing multiview 3D reconstruction using polarization imaging

2014 22nd Signal Processing and Communications Applications Conference (SIU)

2014

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“…In [4], we presented a method which can determine the illuminant chromaticity (G) by using the dichromatic reflection model and inverse-intensity (1/ I i , where [5]. By applying chromaticity definitions and algebra, (1) can be rearranged as (2) (for further detail see [5]).…”

mentioning

confidence: 99%

“…In [4], first the pixels of the specular region are selected roughly by thresholding the S and I components of HSI colour space. If a candidate point from the chromaticity axis is taken (consider it to be G ′ ), and every single line drawn from data points in IICS to G ′ is considered, (some of these lines are shown for two G ′ values on the blue channel chromaticity axis, 0.10 and 0.55, in Fig.…”

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confidence: 99%

Enhancing stereo matching performance by colour normalisation and specularity removal

2011

Electron. Lett.

A method to enhance the performance of stereo matching is presented. The position of the specular light reflection on an object surface varies due to the change in the position of the camera, light source, object or all combined. Additionally, there may be situations exhibiting a colour shift owing to a change in the light source chromaticity or camera white balance settings. These variations cause misleading results when stereo matching algorithms are applied. In this reported work, a single-imagebased statistical method is used to normalise source images. This process effectively eliminates non-saturated specularities regardless of their positions on the object. The effect of specularity removal is tested on stereo image pairs.Introduction: Stereo matching is an active research area and a vast number of algorithms for finding correspondences in multi-frame images have been presented. A comprehensive performance analysis of these methods is given by Sharstein and Szeliski [1].The main goal of stereo methods is to generate a disparity map from image pairs. Specular reflections, especially in cases where the position of the specular reflection changes drastically, cause unwanted results. This position change is mostly due to a change in the relative orientation of the object surface with respect to the camera. The light source position may also change independently.In [2], a stereo-enhanced colour processing method which deals with the unwanted effect of specular variations on surfaces is given by Lin et al. This method uses an image sequence to remove specularity with a strict assumption that all scene points present diffuse reflection in at least one of the views.In [3], Bhat and Nayar embedded a physically based model of reflected light into a stereo matching method to obtain a better stereo matching result in the specular regions of images, but their analysis required controlled lighting conditions and fully calibrated camera positions.In this Letter, the proposed method does not have restrictive assumptions. Furthermore, it does not require a complicated experimental setup. The only assumption in the method proposed is that the pixel values in the images are not saturated. This assumption holds in most cases where exposure settings avoid saturation and objects do not contain mirror-like highly reflective parts.

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Enhancing stereo matching performance by using polarization images

2013 21st Signal Processing and Communications Applications Conference (SIU)

2013