Contrast-enhancement techniques for particle-image velocimetry

Abstract

In video-based particle-image velocimetry (PIV) systems for fluid mechanics research, it is sometimes desirable to image seed particles to be smaller than a camera pixel. However, imaging to this size can lead to marginal image contrast such that significant numbers of erroneous velocity vectors can be computed, even for simple flow fields. A variety of image-enhancement techniques suitable for a low-cost PIV system that uses video cameras are examined and tested on three representative flows. Techniques such as linear contrast enhancement and histogram hyperbolization are shown to have good potential for improving the image contrast and hence the accuracy of the data-reduction process with only a 15% increase in the computational time. Some other schemes that were examined appear to be of little practical value in PIV applications. An automated shifting algorithm based on mass conservation is shown to be useful for displacing the second interrogation region in the direction of flow, which minimizes the number of uncorrelated particle images that contribute noise to the data-reduction process.

The application of laser measurement techniques to aerospace flows

“…These methods include wavelet-based image denoising [86], contrastenhancement techniques [87,88] and applying a Gaussian mask to the images [89]. The method of storage of the PIV images is also shown to affect the accuracy of the results, particularly if MJPEG-based methods are used to compress images [90].…”

Considerations When Applying Large-Scale PIV and PTV for Determining River Flow Velocity

“…Frequently used image enhancement techniques include: intensity normalisation, histogram equalisation, contrast limited histogram equalisation, and binarisation, which are all further explained below (Thielicke and Stamhuis, 2014;The Mathworks Inc., 2020). One of the most important processes for most image velocimetry techniques is to enhance imagery through contrast enhancement steps (Dellenback et al, 2000). Improving the contrast of images helps tracers stand out more in comparison to their environment, making tracking more effective and increasing displacement peak detectability, ultimately improving velocity fields (Deen et al, 2010).…”

Evaluating Image Tracking Approaches for Surface Velocimetry With Thermal Tracers

“…In order to improve the appearance of tracers, image contrast enhancement methods such as gamma correction (Forsyth & Ponce, ), intensity capping (Shavit et al, ), and histogram equalization (Dellenback et al, ) are frequently applied as preprocessing algorithms for RGB imagery. However, for uncooled thermal cameras, which suffer from heavy nonuniformity problems such as vignetting effect, radiometric calibration is more efficient.…”