Automated compensation of light attenuation in confocal microscopy by exact histogram specification

Abstract

Confocal laser scanning microscopy (CLSM) enables us to capture images representing optical sections on the volume of a specimen. The images acquired from different layers have a different contrast: the images obtained from the deeper layers of the specimen will have a lower contrast with respect to the images obtained from the topmost layers. The main reasons responsible for the effects described above are light absorption and scattering by the atoms and molecules contained in the volume through which the light passes. Also light attenuation can be caused by the inclination of the observed surface. In the case of the surfaces that have a steep inclination, the reflected light will have a different direction than the one of the detector. We propose a technique of digital image processing that can be used to compensate the effects of light attenuation based on histogram operations. We process the image series obtained by CLSM by exact histogram specification and equalization. In this case, a strict ordering among pixels must be induced in order to achieve the exact histogram modeling. The processed images will end up having exactly the specified histogram and not a histogram with a shape that just resembles to the specified one, as in the case of classical histogram specification algorithms. Experimental results and theoretical aspects of the induced ordering are discussed, as well as a comparison between several histogram modeling techniques with respect to the processing of image series obtained by confocal microscopy.

Compensating Light Intensity Attenuation in Confocal Scanning Laser Microscopy by Histogram Modeling Methods

“…If the contrast is increased too match, false contours may appear along with an enhancement of the noise. In order to eliminate these drawbacks, Stanciu et al (2010) have introduced a different technique based on histogram modeling aiming to compensate the light attenuation in the case of CSLM images. In the proposed method instead of a uniform or a normalized histogram, the histogram of the best visual quality image of the stack is specified to the other images in the stack.…”

“…It can be observed very clearly the difference between the results obtained by the three different techniques. The complete details of the method presented in this section can be found in the original publication (Stanciu et al, 2010). Fig.…”

“…When the laser beam encounters an inclined surface instead of reflecting backwards towards the objective, it will reflect in a direction normal to the plane of that surface as illustrated in Fig 2. The light that reaches the detector in the case of the interaction between the laser beam and regions with morphology of this type will have a low intensity. An example on such a scenario can be found in (Stanciu et al 2010), where CSLM images collected on Photonic Quantum Ring Laser devices that have a deficient aspect due to this situation are presented. Fig.…”

“…The standard histogram was computed according to a normalization procedure proposed by Nyul et al (2000) which consists on matching landmarks in histograms. Stanciu et al (2010), propose in the same purpose a method based on exact histogram specification. In their method to each of the images in the CSLM stack is exactly specified the histogram of a reference frame.…”

“…The reference frame is elected by using an estimator which takes into account aspects such as brightness, contrast and sharpness. Semechko et al (2011), propose an intensity attenuation correction method which combines the ones of Capek et al (2006) and Stanciu et al (2010). In this method, the authors use as reference the standard histogram proposed in Capek (2006), specify it in its exact shape to the other images of the stack by using the algorithm of Coltuc (2006) and finally nonlinear diffusion filtering is used aiming to suppress noise and homogenize locally over-enhanced image regions.…”