Improved Image Pansharpening Technique using Nonsubsampled Contourlet Transform with Sparse Representation
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RESEARCH ARTICLE
Improved Image Pansharpening Technique using Nonsubsampled Contourlet Transform with Sparse Representation Shailesh Panchal1 • Rajesh A. Thakker2
Received: 9 March 2016 / Accepted: 14 June 2016 Ó Indian Society of Remote Sensing 2016
Abstract Multispectral (MS) and panchromatic (PAN) images contains complementary information. High spatial and spectral resolution is a prerequisite for images to be useful, which can be achieved through image pansharpening. In this paper, we propose a new pansharpening technique which is a combination of nonsubsampled contourlet transform (NSCT) and sparse representation (SR), called NSCT–SR. NSCT is a shift-invariant version of the contourlet transform which combines nonsubsampled pyramid (NSP) and the directional filter banks. NSP splits input MS and PAN images into low-pass and high-pass sub-bands. Fusion of high-pass sub-bands is done using local energy information while low-pass sub-bands are fused using SR. Finally, fused low-pass and high-pass subbands are combined to obtain image with high spatial and high spectral resolution. We have quantitatively compared NSCT–SR with other multiresolution algorithms by calculating spatial and spectral quality parameters. It is observed that spatial quality is improved by 0.93 % (for seaside image) and 1.54 % (for urban image). While spectral quality is improved maximum up to 31.39 and 40.47 %, for respective images. NSCT–SR also compared with other state-of-art algorithms by calculating various performance parameters including quality with no
Shailesh Panchal: IEEE professional membership. & Shailesh Panchal [email protected] 1
Department of Computer Engineering, CHARUSAT, Changa, Gujarat, India
2
Department of Electronics Communication, VGEC Chandkheda, Chandkheda, Gujarat, India
reference. It is found that, overall; NSCT–SR performs better compared to algorithms considered in work. Keywords Pansharpening Nonsubsampled contourlet transform Sparse representation
Introduction Spaceborne sensors deployed in the various earth observation satellites for global coverage of earth surface. IKONOS, Quickbird, Worldview-2, Landsat, etc. satellites provide images at different spatial, temporal and spectral resolutions.1 The spatial resolution of image is expressed as area of the ground covered by one pixel of the image. As pixel size is reduced, objects in the image are delineated with high accuracy. The instantaneous field of view (IFOV) is the portion of the ground, which is sensed by the sensor. Spatial resolution depends on the IFOV (Liu 2000).2 Multispectral (MS) observations, exhibit limited ground resolution may be inadequate for specific object identification. Images taken using MS bands contain coarser resolutions. Panchromatic (PAN) band contains reflectance data that covers a broad spectral range while maintaining a high signal-to-noise ratio, which allows smaller detectors to be utilized. Therefore, images captured in MS bands and PAN band contains complementary information. Pansharpening is an approac
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