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MTF driven adaptive multiscale bilateral filtering for pansharpening

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ABSTRACT The recently proposed Bilateral Filter Luminance Proportional (BFLP) method extracts the high-frequency details from panchromatic (Pan) image via a multiscale bilateral filter and adds them proportionally to the multispectral… Click to show full abstract

ABSTRACT The recently proposed Bilateral Filter Luminance Proportional (BFLP) method extracts the high-frequency details from panchromatic (Pan) image via a multiscale bilateral filter and adds them proportionally to the multispectral (MS) image. Although this approach seems similar to other multiresolution (MRA) based schemes such as Additive Wavelet proportional Luminance (AWLP) or Generalized Laplacian (GLP) methods, multiscale bilateral filter obtains the detail planes to be injected to MS image by the combination of two Gaussian kernels controlling the transfer of details and performing successively in spatial and range domains, thus it has two parameters to be defined, namely spatial and range parameters. Since the parameter determination step considerably affects the efficiency of the method, in this paper we propose a single parameter bilateral filter by approximating the Gaussian kernel with the bicubic kernel of à trous wavelet transform (ATWT) or modulation transfer function (MTF). Moreover, we adopt an adaptive injection scheme where the range parameter is determined adaptively so as to follow the statistics of the images to be fused. The pansharpening results are compared with ATWT-based methods, as well as some state-of-the-art methods and BFLP. The visual and quantitative comparisons for Système Pour l’Observation de la Terre 7 (SPOT 7) and Pléiades 1A images, field studies supported with UAV (Unmanned Aerial Vehicle) images and digitization results of the chosen areas in Istanbul Technical University (ITU) Maslak campus confirm the superiority of the proposed detail injection approach.

Keywords: adaptive multiscale; mtf driven; bilateral filter; multiscale bilateral; driven adaptive

Journal Title: International Journal of Remote Sensing
Year Published: 2019

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