This paper presents a method for automatically extracting a scene depth map and the alpha matte of a foreground object by capturing a scene through RGB color filters placed in the camera lens aperture. By dividing the aperture into three regions through which only light in one of the RGB color bands can pass, we can acquir three shifted views of a scene in the RGB planes of an image in a single exposure. In other words, a captured image has depth-dependent color misalignment. We develop a color alignment measure to estimate disparities between the RGB planes for depth reconstruction. We also exploit color misalignment cues in our matting algorithm in order to disambiguate between the foreground and background regions even where their colors are similar. Based on the extracted depth and matte, the color misalignment in the captured image can be canceled, and various image editing operations can be applied to the reconstructed image, including novel view synthesis, postexposure refocusing, and composition over different backgrounds.

https://web.media.mit.edu/~bandy/rgb/SIGA08rgb.pdf

Extracting depth and matte using a color-filtered aperture

We propose modifying the aperture of a conventional color camera so that the effective aperture size for one color channel is smaller than that for the other two. This produces an image where different color channels have different depths-of-field, and from this we can computationally recover scene depth, reconstruct an all-focus image and achieve synthetic re-focusing, all from a single shot. These capabilities are enabled by a spatio-spectral image model that encodes the statistical relationship between gradient profiles across color channels. This approach substantially improves depth accuracy over alternative single-shot coded-aperture designs, and since it avoids introducing additional spatial distortions and is light efficient, it allows high-quality deblurring and lower exposure times. We demonstrate these benefits with comparisons on synthetic data, as well as results on images captured with a prototype lens.

/pdf/depth-and-deblurring-from-a-spectrally-varying-depth-of-1ajf5i1353.pdf

Depth and deblurring from a spectrally-varying depth-of-field

We propose a novel multi-frequency color-marked fringe projection profilometry approach to measure the 3D shape of objects with depth discontinuities. A digital micromirror device projector is used to project a color map consisting of a series of different-frequency color-marked fringe patterns onto the target object. We use a chromaticity curve to calculate the color change caused by the height of the object. The related algorithm to measure the height is also described in this paper. To improve the measurement accuracy, a chromaticity curve correction method is presented. This correction method greatly reduces the influence of color fluctuations and measurement error on the chromaticity curve and the calculation of the object height. The simulation and experimental results validate the utility of our method. Our method avoids the conventional phase shifting and unwrapping process, as well as the independent calculation of the object height required by existing techniques. Thus, it can be used to measure complex and dynamic objects with depth discontinuities. These advantages are particularly promising for industrial applications.

Multi-frequency color-marked fringe projection profilometry for fast 3D shape measurement of complex objects.

A new coding method is proposed for measuring the three-dimensional (3D) shape of spatially isolated objects .
Based on Gray Code and sinusoidal stripe, this coded fringe pattern whose RGB components comprise the
multiplications of three different frames in Gray Code and sinusoidal stripes, appears to be digital color coded sinusoidal
fringes. The digital color coded sinusoidal fringe pattern is created by software on a computer and then projected to the
tested object's surface by a projector, and the image of the object is captured by a camera positioned at an angle different
from that of the projector, then the image is processed, color Gray Codes are used to obtain the phase order and
sinusoidal stripes are used to get the wrapped phase, then the wrapped phase can be unwrapped and the 3D surface
information can be retrieved. With only one image, 3D shape of the isolated objects can be exactly reconstructed, thus
the speed is limited only by the frame rate of camera. The principle of this technique is described and an actual
measurement is presented, the result of the reconstructed shapes proves the correctness and feasibility of this new coding
method.

A new color structured light coding method for three-dimensional measurement of isolated objects

In three dimensional (3D) shape measurement based on fringe projection, a serial of well designed color strips is used to
encode each period of the projected sinusoidal fringe. It is considered one of the most reliable techniques for recovering
3D shape of a tested objects, even with spatially isolated surface. The sinusoidal fringe intensity is used to extract the
phase information of the tested object, and the color strips with known order is assisted to recover its corresponding
natural phase distribution. Principles of this technique and three color encoding methods with difference color
codification are described in this paper. Some experimental results are also presented. In each method, each fringe order
only depends on its own corresponding color information, has nothing to do with the neighborhood fringes in space,
thus, unwrapping error is limited in a small area and won't expand to other pixels. It takes great convenience for 3D
measurement of an object with spatially isolated surface. With only one image, 3D shape of the tested object can be
exactly reconstructed, thus the speed is limited only by the frame rate of camera, so these methods can also be used in 3D
shape measurement for dynamic object.

3D shape measurement based on color-encoded sinusoidal fringe projection

This paper proposes a new fast and high-resolution color structured-light-based 3D imaging system. Unlike the expensive laser-based 3D imaging system, our hand-held system contains a commercial digital camera and two special designed projectors, the cost is much lower. Only two images are necessarily to reconstruct the 3D model with textures. One projector illuminates white light for texture imaging, the other projector projects special designed pattern for 3D information imaging. 384 vertical color bars (comprised of six primary colors) with special coding are projected onto the target, our proposed algorithm detects edges between any two successive color bars. From decoding algorithm the correct locations of edges are derived. Then the calibration algorithm finds accurate positions of edges in 3D space with triangulation. Color bars can be seriously distorted by colorful objects. Edges and colors of the object may cause edges of color bars to be broken segments. And some bars even show very different colors. A curve reconstruction algorithm is developed to reconstruct the complete edge from residual edge segments. And a robust color decoding algorithm can recover the correct color sequence even when many color bars are seriously distorted. The suggested approach has been implemented and the preliminary results show the resolution can compete with laser 3D imaging systems and -0.2~+0.2 mm accuracy is achieved.

New fast high-resolution 3D imaging system with color structured light

The paper presents a novel 3-D hand-held camera to get the depth information from a single snap shot. Traditionally, a stereo system needs two cameras to reconstruct the 3-D shape. We propose a technique which can be applied to the commercial digital signal camera, and make the 2D camera be able to capture 3D information. The proposed 3-D hand-held camera contains three major components: a flash, a commercial camera, and a tri-aperture lens. The flash projects the speckle pattern onto the object and the camera captures a single snap shot at the same time. In order to embed the 3-D information in one captured image, we use a novel lens containing three off-axis apertures, where each aperture was attached one color filter. Therefore, a captured image carries the information from three different viewing directions. A hierarchical pseudo sub-pixel correlation algorithm is proposed to compute the disparity vectors at a fast speed. It is an adaptive block-based correlation process based on the sparse array of the extracted features. The experimental results show that our approach is robust and convincing.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Novel 3D handheld camera based on triaperture lens

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New fast high-resolution 3D imaging system with color structured light

Novel 3D handheld camera based on triaperture lens