Partial unmixing categorizes each pixel based on a particular mineral while a pixel may contain several minerals. Hence, it seems that the full unmixing procedure is essential to make real results. In this study, at first, the hydrothermal alteration minerals have been mapped by directed matched filtering (DMF) algorithm as a partial unmixing method on the most important porphyry copper deposit in the Kerman province in Iran, then the full unmixing procedure was performed based on a pattern recognition network. In fact, the pattern recognition network uses results of the DMF algorithm to measure the amount of each alteration mineral in each pixel. According to the achieved results, the pure pixels of alteration minerals show high mixing with each other so that the average purity of kaolinite, muscovite, chlorite and alunite pixels are 80%, 70%, 95%, and 92%, respectively. Moreover, the spectral results of 30 samples and 212 chemical analysis of field samples by other research in this area validated those obtained by the full unmixing procedure.

中文翻译：

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模式识别网络与定向匹配滤波算法集成的全解热液蚀变矿物成图

部分解混会根据特定矿物对每个像素进行分类，而一个像素可能包含多种矿物。因此，似乎完整的混合过程对于获得真实结果至关重要。在这项研究中，首先，通过定向匹配过滤（DMF）算法将热液蚀变矿物映射为伊朗克尔曼省最重要的斑岩铜矿床的部分分解方法，然后基于该方法进行完全分解程序。模式识别网络。实际上，模式识别网络使用DMF算法的结果来测量每个像素中每种蚀变矿物的量。根据获得的结果，蚀变矿物的纯像素相互混合程度很高，因此高岭石，白云母，绿泥石和亚辉石像素的平均纯度为80％，70％，95％和92％。此外，该领域其他研究对30个样品的光谱结果和212个野外样品的化学分析结果验证了通过完全分解程序获得的结果。