Digital Manipulation of Brightfield and Fluorescence Images: Noise Reduction, Contrast Enhancement, and Feature Extraction

Abstract

Publisher Summary As image processing allows the investigator to convert the microscope/detector system into a quantitative device, this chapter focuses on three basic problems—reducing noise, enhancing contrast, and quantifying intensity of an image. These techniques can then be applied to a number of different methodologies such as video-enhanced differential interference microscopy, nanovid microscopy, fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, fluorescence resonance energy transfer, and fluorescence ratio imaging. In all the cases, knowledge of the basic principles of microscopy, image formation, and image-processing routines is absolutely required to convert the microscope into a device capable of pushing the limits of resolution and contrast. There are different ways to reduce noise, and the methods of noise reduction chosen depend on many different factors, including the source of the noise, the type of camera employed for a particular application, and the contrast of the specimen. The chapter distinguishes between temporal and spatial techniques to increase the signal-to-noise ratio (SNR) of an image. To optimize contrast enhancement digitally, it is imperative that the microscope optics and the camera are adjusted so that the full dynamic range of the system is utilized. The judicious choice of image-processing routines can greatly enhance an image and can extract features, which are not otherwise possible. When applying digital manipulations to an image, it is imperative to understand the routines that are being employed and make use of well-designed standards when testing them out.