Proceedings Article | 13 May 2010
Proc. SPIE. 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI
KEYWORDS: Statistical analysis, Image processing, Digital filtering, Feature extraction, Lung, Signal processing, Color image processing, Image enhancement, Filtering (signal processing), RGB color model
Bidimensional empirical mode decomposition (BEMD) decomposes an image into several bidimensional intrinsic
mode components, which is useful for various image enhancement and/or feature extraction applications. However,
because of the requirement of scattered data interpolation and associated difficulties, the classical BEMD
methods appear unsuitable for many applications. Recently, a fast and adaptive BEMD (FABEMD) method
is proposed, which alleviates some of the difficulties, otherwise encountered in classical BEMD approaches. On
the other hand, existing BEMD methods are proposed for gray scale images only. This paper first presents a
novel BEMD approach for color images known as color BEMD (CBEMD), which employs FABEMD principle
and decomposes a color image into color bidimensional intrinsic mode components based on hierarchical local
spatial variation of image intensity and color. In fact, FABEMD facilitates the extension of the BEMD process
for color images in a convenient and useful way, whereas the other interpolation based BEMD techniques appear
unsuitable for this purpose. In FABEMD, order statistics filters are employed to estimate the envelope surfaces
from the data instead of surface interpolation, which enables fast decomposition and well characterized bidimensional
intrinsic mode components. Second, the CBEMD is utilized in this paper for adjusting and/or modifying
the trend of color images. In this process, the image is reconstructed by adding the color bidimensional intrinsic
mode components after applying suitably selected weights. Test results with real images demonstrate the
potential of the proposed CBEMD method for color image processing, which include color trend adjustment.
