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Generation of Multispectral Filter Array

This paper explores the development of multispectral filter arrays (MSFA) and color filter arrays (CFA) to improve the sensing capabilities of CCD sensors across visible and near-infrared wavelengths. By utilizing hexagonal and rectangular grid configurations, we aim to model the human visual system more accurately. It outlines design criteria, including uniform distribution and spectral sensitivity, and presents various algorithms for constructing filter arrays. The goal is to enhance data capture across multiple spectral bands, thereby enriching image quality and color consistency.

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Generation of Multispectral Filter Array

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  1. Generation of Multispectral Filter Array Lidan Miao 01/22/04

  2. Motivation • Color image (Color filter array). Sensing the wavelengths in the visible spectrum (400~700nm). • Multispectral image (Multispectral filter array). CCD sensors can detect light (NIR:700~1100nm)outside the sensitivity of HVS. Additional information can be obtained from these spectral bands.

  3. Objective • CFA and MSFA Each sensor sense one spectral band and the unmeasured spectral bands can be interpolated. • Rectangular array and Hexagonal array The hexagonal grid can model the human visual system more precisely.

  4. Design criteria of CFA • Uniform distribution • Equal sample frequency. • Color consistency. • Spectral sensitivity. Bayer color filter array

  5. MSFA in the rectangle domain

  6. Breakup algorithm • Checkboard pattern

  7. Breakup algorithm • Binary tree and MSFA

  8. Characteristics • Symmetrical and uniform distribution. • Each band has the same number of neighbors of certain spectrum and the relative position of different spectra is fixed. • The percentage of each spectrum is determined by the separation process. (a)Equal Probability (b)Unequal Probability

  9. MSFA in the hexagon domain(3 methods)

  10. Method 1 • Directly apply the algorithm in the rectangle array. “Checkboard” pattern

  11. Method 2 • Apply a new coordinate system. (a) Coordinate system

  12. Method 2 “Checkboard” pattern

  13. Method 3 • Based on the distance between the adjacent pixels. • Each pixel has 4 immediate neighbors (distance =1) and 4 secondary neighbors (distance = sqrt(2)). • For each pixel, half of its neighbors are chosen. • As we increase the distance, the percentage decreases.

  14. Method 3

  15. Limitation • Cannot generate all the filter arrays with equal probability. Rectangular array: 3, 5, 7 bands… Hexagonal array (method 3): 4, 5, 6, 7 bands… • The probability is restrict to 1/2, 1/4, 1/8,…… or 1/3, 2/3, 2/9, 1/9……

  16. Comparison • (a) has all the characteristics in the rectangle domain. • (b) is sensitive to cross talk. • (c) has the property of equal distance. (c) Method 3 (a) Method 1 (b) Method 2

  17. Which one do you like?

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