ANALYSIS OF IMAGE NOISE IN MULTISPECTRAL COLOR ACQUISITION

TLDR

Multispectral image capture system design is influenced by application needs, and image noise—stemming from detector and processing sources—causes colorimetric errors that affect system performance. This study analyzes and predicts the image‑noise characteristics of multispectral imaging systems to guide design and performance evaluation. The authors apply a multivariate error‑propagation model that accounts for detector noise, quantization, and signal‑correlation effects to a prototype system, and they provide recommendations for detector specifications and processing strategies.

Abstract

Peter D. BurnsSubmitted to the Center for ImagingScience in partial fulfillment of therequirements for Ph.D. degree atthe Rochester Institute of TechnologyMay 1997The design of a system for multispectral image capture will be influenced by the imagingapplication, such as image archiving, vision research, illuminant modification or improved(trichromatic) color reproduction. A key aspect of the system performance is the effect ofnoise, or error, when acquiring multiple color image records and processing of the data.This research provides an analysis that allows the prediction of the image-noisecharacteristics of systems for the capture of multispectral images. The effects of bothdetector noise and image processing quantization on the color information are considered,as is the correlation between the errors in the component signals.The above multivariate error-propagation analysis is then applied to an actual prototypesystem. Sources of image noise in both digital camera and image processing are related tocolorimetric errors. Recommendations for detector characteristics and image processing forfuture systems are then discussed.