Fusion of MultiSpectral and Panchromatic Images Based on Morphological Operators

International audienceNonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper we discuss the application of this methodology to a popular remote sensing application called pansharpening, which consists in the fusion of a low resolution multispectral image and a high resolution panchromatic image. We design a complete pansharpening scheme based on the use of morphological half gradients operators and demonstrate the suitability of this algorithm through the comparison with state of the art approaches. Four datasets acquired by the Pleiades, Worldview-2, Ikonos and Geoeye-1 satellites are employed for the performance assessment, testifying the effectiveness of the proposed approach in producing top-class images with a setting independent of the specific sensor

Multi-scale metric for objective synthesized image quality assessment for FTV

Основни допринос ове докторске дисертације је развој алгоритама за објективну процену визуелног квалитета слике синтетизоване применом ДИБР (Depth Image Based Rendering) техника које узрокују неуниформна изобличења у области ивица. Применом нелинеарних морфолошких филтара у мултирезолуционој декомпозицији слика код израчунавања предложене метрике, важне геометријске информације као што су ивице су добро очуване без помака и замућења у сликама на различитим скалама мултирезолуционе репрезентације. Израчунавањем МСЕ по подопсезима који садрже ивице, пиксел по пиксел, прецизно се мери разлика две мултирезолуционе репрезентације. Тако се највећи значај у процени квалитета додељује области ивица. Процене предложене метрике се добро поклапају са субјективним оценама.Osnovni doprinos ove doktorske disertacije je razvoj algoritama za objektivnu procenu vizuelnog kvaliteta slike sintetizovane primenom DIBR (Depth Image Based Rendering) tehnika koje uzrokuju neuniformna izobličenja u oblasti ivica. Primenom nelinearnih morfoloških filtara u multirezolucionoj dekompoziciji slika kod izračunavanja predložene metrike, važne geometrijske informacije kao što su ivice su dobro očuvane bez pomaka i zamućenja u slikama na različitim skalama multirezolucione reprezentacije. Izračunavanjem MSE po podopsezima koji sadrže ivice, piksel po piksel, precizno se meri razlika dve multirezolucione reprezentacije. Tako se najveći značaj u proceni kvaliteta dodeljuje oblasti ivica. Procene predložene metrike se dobro poklapaju sa subjektivnim ocenama.The main contribution of this doctoral thesis is the development of algorithms for objective DIBR-synthesized view quality assessment. DIBR algorithms introduce nonuniform geometric distortions affecting the edge coherency in the synthesized images.The non-linear morphological filters used in multi-scale image decompositions of the proposed metric maintain important geometric information such as edges across different resolution levels.Calculating MSE pixel-by-pixel through subbands in which the edges are extracted, the difference of the two multiresolution representations, the reference and the synthesized image, is precisely measured. In that way the importance of edge areas which are prone to synthesis artifacts is emphasized in the image quality assessment. The proposed metric has very good agreement with human judgment

Multiresolution Maximum Intensity Volume Rendering by Morphological Adjunction Pyramids

We describe a multiresolution extension to maximum intensity projection (MIP) volume rendering, allowing progressive refinement and perfect reconstruction. The method makes use of morphological adjunction pyramids. The pyramidal analysis and synthesis operators are composed of morphological 3-D erosion and dilation, combined with dyadic downsampling for analysis and dyadic upsampling for synthesis. In this case the MIP operator can be interchanged with the synthesis operator. This fact is the key to an efficient multiresolution MIP algorithm, because it allows the computation of the maxima along the line of sight on a coarse level, before applying a two-dimensional synthesis operator to perform reconstruction of the projection image to a finer level. For interpolation and resampling of volume data, which is required to deal with arbitrary view directions, morphological sampling is used, an interpolation method well adapted to the nonlinear character of MIP. The structure of the resulting multiresolution algorithm is very similar to wavelet splatting, the main differences being that (i) linear summation of voxel values is replaced by maximum computation, and (ii) linear wavelet filters are replaced by (nonlinear) morphological filters.

Multiresolution Maximum Intensity Volume Rendering by Morphological Adjunction Pyramids

We describe a multiresolution extension to maximum intensity projection (MIP) volume rendering, allowing progressive refinement and perfect reconstruction. The method makes use of morphological adjunction pyramids. The pyramidal analysis and synthesis operators are composed of morphological 3-D erosion and dilation, combined with dyadic downsampling for analysis and dyadic upsampling for synthesis. In this case the MIP operator can be interchanged with the synthesis operator. This fact is the key to an efficient multiresolution MIP algorithm, because it allows the computation of the maxima along the line of sight on a coarse level, before applying a two-dimensional synthesis operator to perform reconstruction of the projection image to a finer level. For interpolation and resampling of volume data, which is required to deal with arbitrary view directions, morphological sampling is used, an interpolation method well adapted to the nonlinear character of MIP. The structure of the resulting multiresolution rendering algorithm is very similar to wavelet splatting, the main differences being that i) linear summation of voxel values is replaced by maximum computation, and ii) linear wavelet filters are replaced by nonlinear morphological filters.