A method of removing reflected highlight is proposed on polarimetric imaging. Polarization images (0°, 45°, 90°, and 135°) and the reflection angle are required in this reflected light removal algorithm. This method is based on the physical model of reflection and refraction, and no additional image processing algorithm is necessary in this algorithm. Compared to traditional polarization method with single polarizer, restricted observation angle of Brewster is not demanded and multiple reflection areas of different polarization orientations can be removed simultaneously. Experimental results, respectively, demonstrate the features of this reflected light removal algorithm, and it can be considered very suitable in polarization remote sensing.
It is a common phenomenon that the mirror reflection of water surface produces the sun glitters; thus it heavily affects the image quality of remote sensing on the water surface and other mirror surfaces, such as ice or glass [
Over the past decades, several methods were proposed to reduce the influence of reflected highlight on images in the water quality remote sensing field. For the first method, we need to choose special time to take the remote images in order to avoid the appearance of sun glitters, but it may mismatch the essential observing time. The second method is a design of mechanical structure which can rotate the camera on the same target zone with the observing angle of forward, vertical, and backward, so we can get a final composite image without reflected highlight [
Therefore, in contrast with the limitations of the traditional methods mentioned above, we proposed a novel method of removing reflected highlight on images based on polarimetric method which has more effective and adaptive performance by using the physical model of Fresnel’s reflection and refraction formula and Stokes parameters. Particularly compared to the traditional polarizing way, the new method could disregard the restricted demand of Brewster angle and could remove glitters from multiple polarizing orientations from multiple reflection mirror surface. Our reflected highlight removal method could reserve the original characteristics of observed targets, so it can be easily efficiently applied to the ocean remote sensing [
The theoretical basis of the highlight removing method is based on the Fresnel reflection and refraction formula [
The basic Fresnel reflection and refraction model.
For the reflected light
To the polarized light, the basic definition of degree of linear polarization (DoLP)
So taking (
The polarization degrees of reflected and refracted lights to the incidence angle.
Besides the basic definition of polarization degree, Stokes vector
The basic imager observing model with glitter on water surface is shown in Figure
The basic imager observing model with glitter on water surface, where
So, the total light intensity
Here, we use the basic definition of polarization degree to analyze the relations between
For common situations, the light source of sunlight and light of detected targets underwater are usually unpolarized. With the refraction index of air and water assumed to be
(a) and (b) are the simulated polarization characteristics of the reflected light
According to the polarization characteristics and physical behaviors, we can note that refracted light of target has a much less polarization degree and a much weaker light intensity than the reflected sunlight. So a key approximate can be set up as
Finally, we substitute (
Two experiments are conducted to verify this reflected highlight removing method. The first one is used to show the clear recovery result of our algorithm, and the other shows the effective result in removing highlight from multiple mirror surfaces with different reflected orientations. An 8-bit black and white industrial polarimetric CCD camera is used in our polarimetric imaging, which can take polarization image from different specified polarization orientations.
Figure
(a) is the original image with highlight reflection on water surface and Chinese characters under water. (b) is the result of observation through a single polarizer. The observing angle mismatching the Brewster angle results in an obvious residual of reflected light on the image.
Then we use our method to remove this glitter. We snap four polarization images at the polarization orientations of 0°, 45°, 90°, and 135° from our polarization CCD camera, respectively. In this experiment, the measured reflection angle is 34°, so we can calculate the specific DoLP of reflection
Images in (a) are acquired by our polarization CCD camera at polarization orientations of 0°, 45°, 90°, and 135°, respectively. (b) is the result through our reflected highlight removing method, where only tiny residual can be found.
For more details, we find that the removing result by our algorithm has weaker efficiency at the edge of reflected highlight than the center in Figure
To make a more distinct contrast of different methods, we put original image, highlight removed image by single polarizer, and highlight removed image by our algorithm together in Figures
(a)–(c) present the results of original image, image by single polarizer, and image by our reflected highlight removal algorithm; (d)–(f) and (g)–(i) are the respective histograms and partial histograms of these three images.
Then, the histogram of result by our highlight removal algorithm in Figure
While the mirror reflection on water surface only generates polarization of single polarization orientation, the second experiment is used to demonstrate the ability of removing reflection from multiple areas with different polarization orientations. Two cars outdoors with reflection on their windows are used as the experimental model, shown in Figure
(a) is the image taken by the normal camera, and reflection occurs on the rear and side glass. (b) and (c) show clearly the results by single polarizer with polarized angle of 25° and 60°, and the reflection in the red and blue areas cannot be removed at the same time. (d) is the final reflected highlight removing result with the reflected highlight removal algorithm.
In this paper, we demonstrate a new method of removing reflected highlight based on polarimetric imaging, and this algorithm can break the limitation of observing at Brewster angle and polarimetric method with single polarized orientation. We need to snap four polarization images at orientations of 0°, 45°, 90°, and 135° and measure the angle of reflection to fulfill the conditions of this reflected highlight removal algorithm. Two experiments of different scenes, respectively, demonstrate the advantages compared with traditional polarization methods. The first experiment clearly shows that our algorithm could effectively remove the reflected highlight without restricted observation angle of Brewster angle and reserve the original characteristics of observed targets. In the second experiment, a scene with glass of several car windows outdoors is used to verify the effect of removing multiple glitters with different polarized orientations. If we apply this reflected highlight removal algorithm to real-time polarized imaging, it might be very effective in remote sensing fields such as marine remote sensing and water quality monitoring.
The authors declare that they have no competing interests.
This work is supported by the National Natural Science Foundation of China under Grants 11327303, 11573058, 61405239, and 61501456.