Multispectral camera as spatio-spectrophotometer under uncontrolled illumination.

Multispectral constancy enables the illuminant invariant representation of multi-spectral data. This article proposes an experimental investigation of multispectral constancy through the use of multispectral camera as a spectrophotometer for the reconstruction of surface reflectance. Three images with varying illuminations are captured and the spectra of material surfaces is reconstructed.

Illuminant estimation in multispectral imaging.

With the advancement in sensor technology, the use of multispectral imaging is gaining wide popularity for computer vision applications. Multispectral imaging is used to achieve better discrimination between the radiance spectra, as compared to the color images. However, it is still sensitive to illumination changes.

3D reconstruction of external and internal surfaces of transparent objects from polarization state of highlights.

A vision-based method is proposed to measure the 3D shape of external and internal surfaces (not accessible) of smooth transparent objects. Looking at the reflections of point sources on a specular surface with a polarimetric camera, we combine the measurements of two techniques: shape from distortion and shape from polarization. It permits us to recover the position and orientation of the specular surface for each detected point.

Noise estimation from digital step-model signal.

This paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model. It is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image. The proposed approach uses polarized/directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution (e.

A nonlinear derivative scheme applied to edge detection.

This paper presents a nonlinear derivative approach to addressing the problem of discrete edge detection. This edge detection scheme is based on the nonlinear combination of two polarized derivatives. Its main property is a favorable signal-to-noise ratio (SNR) at a very low computation cost and without any regularization.

Optical tomography from focus.

A model and a method providing a 3D reconstruction of a given translucent object from a series of image acquisitions performed with various focus tunings is proposed. The object is imaged by transmission; refraction, reflection and diffusion effects are neglected. It is modeled as a stack of translucent parallel slices and the acquisition process can be described by a set of linear equations.