From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Multispectral image acquisition considerably improves color accuracy in comparison to RGB technology. A common multispectral camera design concept features a filter-wheel consisting of six or more optical bandpass filters. By shifting the filters sequentially into the optical path, the electromagnetic spectrum is acquired through the channels, thus making an approximate reconstruction of the spectrum feasible. However, since the optical filters exhibit different thicknesses, refraction indices and may not be aligned in a perfectly coplanar manner, geometric distortions occur in each spectral channel: The reconstructed RGB images thus show rainbow-like color fringes. To compensate for these, we analyze the optical path and derive a mathematical model of the distortions. Based on this model we present two different algorithms for compensation and show that the color fringes vanish completely after application of our algorithms. We also evaluate our compensation algorithms in terms of accuracy and execution time.

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Multispectral Filter-Wheel Cameras: Geometric Distortion Model and Compensation Algorithms

An embodiment generally relates to systems and methods for estimating heart rates of individuals using non-contact imaging. A processing module can process multi-spectral video images of individuals and detect skin blobs within different images of the multi-spectral video images. The skin blobs can be converted into time series signals and processed with a band pass filter. Further, the time series signals can be processed to separate pulse signals from unnecessary signals. The heart rate of the individual can be estimated according to the resulting time series signal processing.

Systems and methods for non-contact heart rate sensing

Methods and apparatus for video rate or near video rate quantitative imaging of tissue physiological and morphological properties from visible/NIR light spectral images obtain rapid multi-spectral reflectance images by illuminating with a series of spectra containing multiple narrow wavelength bands. An iterative light- transport based inversion algorithm may be applied for correcting the intensity of the spectral images from the geometry/coupling effect as well as from the scattering amplitude distortions. The method can produce video rate absorption as well as scattering spectral images that can be further analyzed very rapidly, using matrix-based rapid inversion algorithms to produce more detailed quantitative images containing information relevant to tissue physiology and morphology.

Rapid multi-spectral imaging methods and apparatus and applications for cancer detection and localization

https://hal.archives-ouvertes.fr/hal-00783985/document

Integration of 3D and multispectral data for cultural heritage applications: Survey and perspectives

Capturing natural scenes with high dynamic range content using conventional RGB cameras generally results in saturated and underexposed and therefore compromising image areas. Furthermore the image lacks color accuracy due to a systematic color error of the RGB color filters. The problem of the limited dynamic range of the camera has been addressed by high dynamic range imaging1, 2 (HDRI): Several RGB images of different exposures are combined into one image with greater dynamic range. Color accuracy on the other hand can be greatly improved using multispectral cameras,3 which more accurately sample the electromagnetic spectrum. We present a promising combination of both technologies, a high dynamic range multispectral camera featuring a higher color accuracy, an improved signal to noise ratio and greater dynamic range compared to a similar low dynamic range camera.© (2008) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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Multispectral high dynamic range imaging

High-fidelity colour reproduction requires multispectral cameras for image acquisition, which, unlike RGB cameras, divide the visible electromagnetic spectrum into more than 3 channels. This can be achieved by successively placing narrow-band optical filters with different passbands between object lens and sensor of a standard b/w camera. The filters are arranged on a filter wheel, the rotation of which moves the filters sequentially into the optical path. In practice, these filters exhibit different thicknesses and refraction indices, and are also not perfectly coplanar, resulting in geometric distortions between the recorded spectral components. We derive a mathematical model for these distortions. We additionally measure the effects of chromatic aberration, and incorporate these into our model. Based on this model, we then develop a registration algorithm which robustly estimates the parameters of an appropriate affine coordinate transformation. Experimental results using a seven-channel multispectral camera confirm both the validity of our model as well as the accuracy of the registration algorithm.

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Nils Schulte

Papers

Multispectral Filter-Wheel Cameras: Geometric Distortion Model and Compensation Algorithms

Multispectral high dynamic range imaging

Modeling and compensation of geometric distortions of multispectral cameras with optical bandpass filter wheels