Design of complex adaptive multiresolution directional filter bank and application to pansharpening. Issue 2 (February 2017)

• Record Type: Journal Article
• Authors: Gajbhar, Shrishail; Joshi, Manjunath
• Is Part Of: Signal, image and video processing. Volume 11:Issue 2(2017)
• Page Start: 259
• Page End: 266
• Publication Date: 2017-02
• Subjects: Multiresolution directional filter bank -- Adaptive transform -- Pansharpening; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-016-0931-4
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract This paper proposes a new 2-D transform design, namelycomplex adaptive multiresolution directional filter bank, to represent the spatial orientation features of an input imageadaptively . The proposed design is completelyshift invariant and represents the input image by one low-pass and multiscaleN directional band-pass subbands. Here, N represents estimated number of dominant directions present in the input image. Our design consists of two main filter bank stages. A fix partitioned complex-valued directional filter bank (CDFB) is at the core of the design followed by a novel partition filter bank stage. Fine partitioning of the CDFB subbands is used to get the adaptive nature of the proposed transform. The partitioning decision is made based on the directional significance of range of CDFB subband angle selectivity in the input image. Partition filter bank stage whichnonuniformly partitions the CDFB subbands provides totalN dominant direction selective subbands. Local orientation map of the input image is used to determine the dominant directions and henceN . For better sparsity properties, we design the multiresolution stage with filters having highvanishing moments and better frequency selectivity. Applicability of the proposed adaptive design is shown for pansharpening of multispectral images. Our proposed pansharpening approach is evaluated on images captured using QuickBird and IKONOS-2 satellites. Results obtained using the proposed approach on these datasets show considerable improvements in qualitative as well as quantitative evaluations when compared to state-of-the-art pansharpening approaches including transform-based methods.