New analytical expression for speckle contrast of spectral light broadening

Abstract

A new analytical expression for the average speckle contrast is derived for surfaces of random roughness at reflection. Rayleigh and Simpson phase probability density distributions of non-zero phase mean value are assumed for the roughness of the surface. The behavior of a speckle contrast with a roughness root mean square of phase deviation is presented. The effect of the spectral light profile, its spectral width, the density of the scatterers of the rough surface and the average time delay between the interfering beams are taken into consideration.

Effect of an Interfering Reference Beam on Partially Developed Speckle Contrast

“…Therefore, the referencebeam will be more effective in decreasing the speckle contrast. The case of Є = 0 means that the reference beam is not present, the speckle contrast given by the present derived formula (26) tends to the published formula for the speckle contrast [16,17]. It emphasis the present theoretical view.…”

Effect of the Illuminating Point Spread Function and Roughness on the Speckle Correlation Field

“…The speckle contrast reaches one as ϕ σ takes large values and thus the central limit theorem is reached [3]. As a consequence of the obtained formula of…”

“…Due to the random roughness heights of the surface, the interfering beams are of random phases. This leads to intensities of random values with random spatial distribution called speckle patterns [1] [2] [3]. The statistical properties of laser speckle patterns are of great importance in speckle metrology techniques.…”

Comprehensive Evaluation Study of Innovative Measurement Techniques in Surface Roughness within Manufacturing Processes

“…Analyzing these speckles, which carry contour information, yields data about the surface profile. Nicklawy et al [5] established a model for surface roughness based on average speckle contrast, which increases with the root mean square of surface roughness. Dias et al [6] used Tsallis entropy to determine the threshold for digital image segmentation of speckles, discovering that the Tsallis threshold could detect roughness.…”