Haze-Guided Weight Map 기반 다중해상도 변환 기법을 활용한 가시광 및 SWIR 위성영상 융합 = Visible and SWIR Satellite Image Fusion Using Multi-Resolution Transform Method Based on Haze-Guided Weight Map

다국어 초록 (Multilingual Abstract)

With the development of sensor and satellite technology, numerous high-resolution andmulti-spectral satellite images have been available. Due to their wavelength-dependent reflection,transmission, and scattering characteristics, multi-spectral satellite images can provide complementaryinformation for earth observation. In particular, the short-wave infrared (SWIR) band can penetratecertain types of atmospheric aerosols from the benefit of the reduced Rayleigh scattering effect, whichallows for a clearer view and more detailed information to be captured from hazed surfaces comparedto the visible band. In thisstudy, we proposed a multi-resolution transform-based image fusion methodto combine visible and SWIR satellite images. The purpose of the fusion method is to generate a singleintegrated image that incorporates complementary information such as detailed background informationfrom the visible band and land cover information in the haze region from the SWIR band. For thispurpose, this study applied the Laplacian pyramid-based multi-resolution transform method, which isa representative image decomposition approach for image fusion. Additionally, we modified the multiresolution fusion method by combining a haze-guided weight map based on the prior knowledge thatSWIR bands contain more information in pixels from the haze region. The proposed method wasvalidated using very high-resolution satellite images from Worldview-3, containing multi-spectralvisible and SWIR bands. The experimental data including hazed areas with limited visibility causedby smoke from wildfires was utilized to validate the penetration properties of the proposed fusionmethod. Both quantitative and visual evaluations were conducted using image quality assessmentindices. The results showed that the bright features from the SWIR bands in the hazed areas were successfully fused into the integrated feature maps without any loss of detailed information from thevisible bands.

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