Comparison of Polarimetric Cameras

Of the four characteristics of light used in scene analysis, wavelength, amplitude, coherence, and polarization, polarization is relatively new to the remote sensing community. Polarization can be used to distinguish features in both natural and manmade objects that other detection modes used in remote sensing cannot. The use of polarization imaging is not as prevalent as panchromatic and multispectral techniques. Evaluation of polarimetric cameras can help in its adoption. Jarrad A. Smoke, of the Naval Postgraduate School in Monterey, CA, is doing just this. In his thesis, he compared two polarization imaging technologies to access their capabilities and potential use in remote sensing.

Smoke compared two different polarimetric imaging systems: the Bossa Nova Salsa polarimetric camera and the FluxData FD-1665P. He collected images with both systems and evaluated their performance. The two systems operate on different principles. The Salsa uses a Division of Time Polarimeter (DoTP), which is sensitive to movement, and FluxData’s camera uses a Division of Amplitude Polarimeter (DoAmP), which is designed to split the incoming light without errors from scene movement. The objective of this study was to determine the similarities and differences of the images captured and compare how well each camera assessed and depicted the effects of polarization noting the advantages/disadvantages of each technique.  His analysis aimed at a better understanding of how imaging can be utilized to find a common ground for polarization imaging.

The Bossa Nova Tech Salsa polarization camera consists of both polarization analysis and regular digital video camera capabilities. The main feature of the Salsa camera is its ability to display full Stokes parameters and calculations in real time on each pixel. The camera technology uses a patented polarization filter based on a ferroelectric liquid crystal, which reduce the acquisition time when taking images and separates polarized light onto a 782 x 582 pixel detector operating in the 400 to 700 nm range. The camera has a standard 1 megapixel 12-bit CCD sensor and an interchangeable F mounted lens. The camera is powered by fifteen-volt DC and has FireWire and USB connections for data input/output to a connected computer. The Salsa uses a division of time polarimeter (DoTP) to capture imagery. Using sequential images taken with the polarization filter rotated to different orientations, the camera constructs the linear Stokes vectors pixel by pixel using a modified Pickering method. Because of the filter rotation, movement in the scene results in miscalculations which limits the Salsa’s use to static scenes.

The FD-1665P 3 CCD Camera captures video and images at three linear polarization directions simultaneously, in full color. By doing so, all timing and movement issues are eliminated. The Stokes parameters can be calculated on the output images or video stream by the user and is not built-in to the camera’s processing. The camera sensor type is a Progressive Scan Charge Coupled Device (CCD), Sony ICX285, with a sensor size of 1628 x 1236 pixels. At full resolution, the FD-1665P is capable of 30 frames per second. The sensor converts light into electric charges that process to electronic signals for digital images. The camera offers 1.4 megapixels and an interchangeable F mount lens. The three CCD sensors on three polarizers utilizes division of amplitude polarimeters (DoAmP), which avoids timing issues observed with DoTP. With DoAmP, the images are captured simultaneously through a non-polarizing 3-way beam splitter prism which pass through three non-color selective polarizers before being refocused onto the sensors.

FluxData Input/Output Channels (left) and Registered Images (right)

For this study, the FD-1665P polarization filters were oriented at 0, 135 and 90 degrees (traditionally they are oriented at 0, 45, and 90 degrees). By reversing the sign of the calculations, it allowed the Stokes vector calculation to produce results corresponding to those obtained from the Salsa. The ability to output data prior to Stokes calculations is a feature that is not available on the Salsa. Each channel of the FD-1665P offers a set of features to control analog and digital controls of the process, as displayed in the image above. The ability to manipulate each channel gives the user control to counter the effects of gain and saturation effects.

Smoke collected imagery in and around Monterey by mounting the cameras on tripods next to each other and capturing images at approximately the same time to get similar sun angles in both systems.

The aspect of how the cameras determine polarization were compared using the ENVI and IDL software packages commonly used in remote sensing. The comparison of cameras and images followed the method of testing used in modern day cameras on phones. Ease of use, quality of photos, cost, support and various other aspects were all analyzed to determine the best use of each camera and how a customer would use each technology. Stokes vectors and products were calculated for the FD-1665P using ENVI and IDL I in real time. Band algebra and histogram manipulation were used to compare the FluxData and Salsa images. The total intensity captured by both cameras varied greatly and manipulation of the histogram scale in ENVI was utilized to scale the image and eliminate noise and saturation.

08 September, 2016. Hermann Hall, Monterey, CA. FluxData (left) Salsa (right)

Again, it is easier to distinguish and identify objects using the FD-1665P. When zooming in and capturing values of DoLP,

the FD-1665P gave higher values on objects such as windows and cars. The Salsa loses much of its detail when zooming in on objects.

The first objective in comparing the cameras was to compare the Stokes images. The resulting calculations from each camera portrayed similar results. However, the FD-1665P displayed a higher resolution image with more detail as compared to the Salsa Stokes. One huge advantage of the FD-1665P being the detail and differences captured in the background. The DoTP of the Salsa is affected by movement and gives false data for moving objects such as trees, whereas FluxData’s DoAMP is not affected by movement (but registration errors do occur from very small errors in the alignment of the frames on the camera in shadows and along some objects outlines).

The remaining analysis in Smoke’s study focused on the FD-1665P.  This camera’s higher resolution and DoAmP technology allows a more accurate pixel calculation of Stokes vectors in moving scenes. In addition, the FD-1665P captures a color image and the Umov effect was explored to see how wavelength and color affect polarization for its use in classifying objects.

Smoke found that although both cameras provide similar polarization representations, FluxData’s division of amplitude polarimeter minimizes the effects of false polarization because of scene movement. The advantage of this technique over the Salsa’s division of time polarimeter allows the camera to be used on moving vehicles and aircraft because it is not affected by rotating filter to calculate Stokes. In future work, FluxData’s DoAmP technique can be used on ground and air vehicle to capture overhead angles to help expand the library of polarization scenes. Additionally, FluxData has the capability to calculate Stokes in real time with software and code implementations. Future work with real time imagery will allow the user to select areas of interest more easily and adjust angles to best capture a scene and identify objects.

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Multispectral Imaging Used to Improve the Detection of Pre-Cancerous Lesions

Recent advances in computing and imaging have allowed doctors to better identify and treat malignancies in patients, specifically, malignancies which develop without symptoms and are poorly identified in their early stages.

Worldwide, gastric cancers accounted for 6.8% of all cancers in 2012, with mortality rates of 8.8%, ranking it as one of the top five most deadly forms of cancer. Due to the possibility of rapid growth, detecting such malignancies early on is crucial because it allows for less aggressive treatments.

To date, the diagnosis of such gastric pathologies falls into two procedures: gastroendoscopy (visual exploration of the stomach under white light) and biopsies for the collection of tissue for analysis. Although biopsies provide the medical field with highly-accurate results, they have proven to be very demanding and time consuming.  If done correctly, biopsies are not only effective, but crucial in identifying such malignancies, but the chance for error is high. Results of biopsies are strongly dependent on the accuracy of samples collected from the damaged tissue.  Because of this, there was a demand to find additional sources to help identify target areas for biopsy collection.

Sergio Ernesto Martinez Herrera, at the Universite of Paris-Saclay and Universite Versailles Saint-Quentin en Yvelines, considered multispectral imaging to help identify tissue to sample, in hopes of improving accuracy and decreasing the time of the overall procedure. Herrera argues that multispectral imaging could be a great method for identifying areas to sample due to chemical and structural changes in the gastric tissue during the development of malignancies and the different ways in which histopathological tissues may reflect light of different wavelengths compared to normal tissue. Multispectral imaging allows the medical professional to analyze absorption, scattering coefficients and blood content, which can provide important information for identifying precancerous lesions. Overall, multispectral imaging can be used to analyze, both spectrally and spatially, the surface of the gastric mucosa.

FluxData’s FD-1665 was one of the technologies used in Herrera’s study of multispectral imaging to improve the detection of pre-cancerous lesions in digestive endoscopies. In this research, specifically, Herrara chose to look at the reflection of gastritis pathology under various conditions. Gastritis is part of the stages of cancer development which results from a chronic infection by H. pylori (which is directly linked to gastric lesions). Herrara studied mice that developed a chronic infection after inoculation of H. pylori. A total of 25 mice were used for this study, 15 of which were infected with H. pylori (pathological group) and 10 that were not (control group). The mice were then sacrificed at different times post inoculation, to analyze changes in tissue during the development of the pathology. The tissues were analyzed using multispectral imaging to identify spectral regions that show significant changes as the disease progresses. The goal is to link these spectral signatures to the diagnosis of gastritis and the development of cancer.

(Image by: Sergio Ernesto Martinez Herrera)

Segmentation of the stomach from mice. a) Original image b) monoband image centered at 520 nm c) result from a sobel filter d) opening on the image e) threshold and inversion f) entropy filter and identification of the centroid of the stomach g) estimated mask of the stomach and h) segmented stomach. 

FluxData’s FD-1665 was used in Herrara’s research to overcome limitations with other imaging systems. Using the FD-1665, he could increase the spectral range of the system by acquiring the NIR wavelengths and the reduction of the acquisition time by collecting a multispectral image in a single shot. It is known that light encodes chemical and structural information from the tissue in a non-invasive way providing quantitative information for objective diagnosis.  NIR is a strong candidate for the differentiation of pathology due to its ability to express biological changes in water content and light scatter due to oxygen saturation.

The results from the mice model study show significant variations in the mucosa measured at different stages of the pathology between the two groups analyzed. The conclusions from such analysis show that three wavelength bands are candidates for the diagnosis of gastritis: between 430 to 450 nm, 460 to 590 nm, and 620 to 680 nm.

This research shows that the introduction of multispectral imaging for malignancy detection may provide a practical and accurate tool that can be used routinely for medical procedures of various types. This technique can be beneficial in the early stages by offering information to improve detection of gastric lesions, or it can be beneficial later in tracking the performance of medical treatments and the tissue’s response to various medications. Additionally, extending multispectral imaging techniques to other diseases which are difficult to detect early can help in the diagnoses and evaluation of these as well. 

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