Rank-based camera spectral sensitivity estimation

Rank-based camera spectral sensitivity estimation.

In order to accurately predict a digital camera response to spectral stimuli, the spectral sensitivity functions of its sensor need to be known. These functions can be determined by direct measurement in the lab-a difficult and lengthy procedure-or through simple statistical inference. Statistical inference methods are based on the observation that when a camera responds linearly to spectral st...

Spectral estimation based on structured low rank matrix pencil

This paper proposes a new parameter estimation algorithm for damped sinusoidal signals. Parameter estimation for damped sinusoidal signals with additive white noise is a problem of signiicant interest in many signal processing applications, like analysis of NMR data and system identiication. The new algorithm estimates the signal parameters using a matrix pencil constructed from the measured da...

Rank-Based Illumination Estimation

A new two-stage illumination estimation method based on the concept of rank is presented. The method first estimates the illuminant locally in subwindows using a ranking of digital counts in each color channel and then combines local subwindow estimates again based on a ranking of the local estimates. The proposed method unifies the MaxRGB and Grayworld methods. Despite its simplicity, the perf...

sensitivity evaluation of spectral vegetation indices using sensitivity functions for stand volume estimation

identification of the best vegetation indices (vis) for use in quantitative analyzes of vegetation is one of the important issues for ecologists. the objective of this study was sensitivity evaluation of vegetation indices to a stand volume for identification of the best vegetation index (vi) in stand volume estimation using a statistical sensitivity method. also, another objective of this stud...

Performances of classic and weighted versions of some selected methods in estimation of spectral data from camera responses