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Lab Color Space Assignment for Decomposed Fully Polarization Pi-SAR Data
Cheng-Yen Chiang1,3
, Kun-Shan Chen2, Chih-Yuan Chu
3, Y. Yamaguchi
4, Kuo-Chin Fan
1
1Department of Computer Science and information Engineering, National Central University, Jhongli, Taiwan
2Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China
3G-AVE Technology Corp., Taipei, Taiwan
4Electrical and Information Engineering, Niigata University, Niigata, Japan
Abstract - Color encoding or assignment of multi-
polarization or fully polarimetric synthetic aperture radar
(PolSAR) image is vital for visual display and interpretation of the polarimetric information. In this paper, based on the Lab color space that is uniformly perceptual, we propose a color
assignment framework aiming at a better visual perception and information interpretation for Pi-SAR-L Quad-Pol data. It is shown that the new color assignment scheme not only
preserves the color tone of the polarization signatures, but also enhances the target information embedded in the total returned power. Using the property the Euclidean distance of
color, the five channels derived from four components decomposition method can be mapping to Lab color space intuitively.
Index Terms — Lab Color Space, Pi-SAR, Four Components Decomposition, Synthetic Aperture Radar.
1. Introduction
Color presentation to a color space for different frequency
or polarization channels is useful for analyzing the
elements within a single pixel by human eye. However, a
question generally raised is that what kind the color coding
scheme is the best or optimally suited for a particular
context and objective in a general image domain?
Target decomposition of a Quad-Pol SAR image proves a
powerful tool to characterize the terrain features. It is useful
to interpret the scattering mechanisms by applying the
coherent or model-based decomposition techniques [1-5].
For visual inspection and interpretation, a simple way is to display individual component monotonically. For PolSAR
image visualization, the main objective of color encoding
or color mapping is to explore the capability of quantitative
and qualitative detection or classification for objects of
mixed scattering mechanism in SAR image. In four
component decomposition [4-5], for example, a simple
RGB is commonly used in mapping three components:
double bounce, volume and surface scattering but the fourth
component, the helix scattering, is independently displayed
in grayscale, e.g, or simply by heuristic color mixing. So
the power of four components decomposition is not fully
presented in pseudo-color image space. The basic principle
is color composition without losing information offered by
target decomposition of scattering mechanisms. The
organization of this paper is as follows. In next section, we
give a rational why we chosen the Lab color space for fully
polarization data. The uniform perceptual color assignment,
Lab color space, and the framework of transformation from
information data to display device monitor was introduced
in section 2 also. Section 3 presents the Pi-SAR-L
experimental results and discussions. Finally, conclusion is
drawn from this study.
2. Color Encoding for PolSAR Images
In total, five channels data are generated, including total
power channels in the Yamaguchi’s four components
decomposition with rotation [4-5], known as Y4R. The four
components include volume, double bounce, surface and
helix scattering, each exhibits different behavior of
scattering mechanisms, while the total power channel
retains the geometrical properties of the target being
observed. The Lab color space is colorimetric, perceptually
uniform. Hence, it is intuitive to map the polarization
signature in CIE-Lab color space, which defines a*, b* and
brightness axis L* with respective to xyz-axis in Cartesian
coordinates, where a* extends from green to red, while b*
from blue to yellow. Referring to Fig. 1 we may assign the
total power to the brightness axis to represent the target’s
structure and thus to enhance the contrast of the boundary.
Basically, two stages are constructed in the proposed
color assignment framework: the first is mapping from
PolSAR data space onto perceptually uniform color space
with respect to the four component decomposition channels
and CIE-Lab color space; and the second is the
transformation between the perceptually uniform and
device dependent color spaces. Notice that because the
conversion in stage two is nonlinear, the loss of certain
color in the difference of gamut area is inevitable, and
irreversible.
Fig.1 Resemble of Poincare Sphere (above, from [6]) and
generic Lab Color Sphere (below).
The four decomposition components in Lab color space
such that the target information can be strongly and yet
effectively brought out for visual analysis. To begin with,
let us linearly assign the volume scattering to negative
value and double bounce scattering to positive value in the
a- axis, and in the b-axis the surface and helix scattering
components are assigned to negative and positive values,
respectively, followed by formulating the linear
combination for chroma of Lab color space taking into
account the perceptually uniform property.
When it comes to coding in Lab color space, it is possible
to align the channel of main interest to a* axis while
rotating the other channels away from b* axis. In Fig. 2a,
we see that the pairs Pv –Pd, Ps –Pc are aligned with a and b
Proceedings of ISAP2016, Okinawa, Japan
Copyright ©2016 by IEICE
3D1-3
626
axis, respectively. Indeed, we might keep one pair
alignment fixed, while adjust the other pair out of a or b
axis. For example, in order to enhance a weaker scattering
component, e.g., helix scattering, we turn Pv and Pd 30
degrees away from a axis, but keep Ps -Pc aligned with b
axis as shown in Fig. 2b. Another option is to suppress the
scattering component that is of no interest. Fig. 2c is an
example to vanish the helix scattering by turning Pd 60
degrees away from a axis and Ps 30 degrees away from b
axis. From this example, we also see coding in Lab space
offers large flexibility depending upon users’ inclination
and objective.
Fig.2 Realignment of the four scattering components on a
color wheel of Lab color space. (a) all alignment, (b) Ps
alignment, (c) Pv alignment.
3. Experimental Result
We used a Pi-SAR-L data [8], which was acquired over a
calibration site with eight kinds corner reflectors deployed
at Tottori- dune, Japan on 4 October 2000. Fig. 3 shows a
comparison of color-encoding using sRGB and Lab for
Pauli basis composition, three components, with local and
global data slicing, 4 components decomposition. As in
previously case, Ps-Pc alignment was applied in Lab color-
encoding with 5% data slicing in total return power. In
sRGB color space, it can be seen that visual difference
exists when applying local and global data slicing. With the
local data slicing, the visual recognition can be improved
but paying the price of degrading identifiability of different
color channels. Recalled that in Lab color-encoding we
adjust the double and volume scattering with 30 degrees to
preserve, and enhance, the helix component.
Fig. 3 Comparison of color-encoding using sRGB and
Lab for (a) Pauli basis composition, (b) three components
with 5% local data slicing, (c) three components with 5%
global data slicing, and (d) four components decomposition
To further exploit the power of Lab, we analyze the
calibration site as enclosed by white rectangular in Fig. 4.
We see that from an array of corner reflectors, being strong
scattering targets, several targets tend to be in blue,
indicating surface scattering dominant in sRGB color space.
This of course is not true. This distortion is corrected, to
great extent, in Lab color space, where no surface scattering
was falsely appearing in corner reflectors.
Fig. 4 Comparison of sRGB and Lab color-encoding for
an array of corner reflectors indicated by enclosed white
rectangular
4. Conclusion
In this paper, we proposed a color-encoding framework for Pi-SAR-L Quad-Pol data based on a perceptually uniform Lab color space. In particular, Yamaguchi’s four components decomposition with rotation (Y4R) was adopted for target decomposition into four scattering mechanisms. It is found that not only the chroma by four components can be well preserved and presented, but also the inclusion of the total power enables us to enhance more correctly the targets structure. By so doing, the target contrast in the same scattering component but with different intensity can be more easily differentiated. It is advantageous to perform color encoding in Lab color space so that four scattering components can be displayed simultaneously to enrich the target information content for visualization. We can conclude that Lab color space is very suitable for color-encoding the PolSAR data. .
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