Color image trend adjustment using a color bidimensional empirical mode decomposition method

摘要

Bidimensional empirical mode decomposition (BEMD) technique decomposes an image into several bidimensional intrinsic mode functions (BIMFs) and a bidimensional residue (BR). Classical BEMD methods require some form ofsuriace interpolation to estimate envelope suriaces, which causes various problems. On the other hand, existing surface interpolation-based BEMD methods are proposed and/or are suitable for gray-scale images only. This paper presents a novel BEMD approach for color images known as color BEMD (CBEMD), which employs order-statistics filter (OSF)-basedenvelope estimation to avoid some of the difficulties, otherwise encountered in classical BEMD approaches. The CBEMD can decompose a color image into several color BIMFs and a color BR based on hierarchical local spatial variation of image intensity and color. Since the color BR represents the trend of a color image in terms of global intensity and color distribution, it is utilized for trend adjustment of color images. Both formulation of the CBEMD and finding and adjusting the color image trend are known to be the first approaches in corresponding issues. Experimental results with several real images demonstrate the potential of the proposed CBEMD method for color image processing, which include trend adjustment of color images.