Synthesis and analysis of periodically distributed satellite image components by independent component analysis

In analyzing multispectral satellite images, the existence of mixels caused by high altitude observation makes it difficult to distinguish pure spectra from the coverage. In this paper, we firstly propose an analytic method which enable us to separate the change of vegetation into qualitative one due to biological characteristics such as the chlorophyll quantity, and the coverage quantity by utilizing the characteristic feature of the spatial distribution of crops, i.e. periodicity, for independent component analysis (ICA). As the second proposal, we introduce a synthetic method which aims at the estimation of the spatial frequency and direction of periodically distributed pattern from noisy and diffused images by synthesizing the data based on the combination of multi-directional scanning, multiple bandpass filtering and ICA.