Urban residential environment surveillance plays an important role in modern intelligent city. Satellite images have been applied in various fields, and the analysis and processing of satellite images has become an important means to obtain the information perceived by satellites. This paper focuses on city residential environment surveillance based on massive-scale visual information retrieval. Since the shortcomings of low contrast, blurred boundary, large amount of information and susceptibility to noise, the performance of satellite image segmentation is not satisfactory, which will affect residential environment surveillance. We design an improved rough set fuzzy C-means clustering algorithm combined with ant colony algorithm. More specifically, satellite images are classified based on the gradient of pixels according to the indistinguishable relation of the image combined with rough set theory. Then, the traditional fuzzy set-based fuzzy C-means clustering algorithm is applied to the satellite image segmentation technology. Subsequently, the improved algorithm-quantum ant colony algorithm and rough set fuzzy clustering C-means algorithm are combined to achieve accurate segmentation of satellite images. Afterwards, we propose a satellite image retrieval algorithm, which can assist city residential environment surveillance. Comprehensive experiment show that our proposed method is effective and robust in residential environment surveillance.

城市居民环境监测在现代智能城市中发挥着重要作用。卫星图像已经应用于各个领域，并且卫星图像的分析和处理已经成为获取卫星感知信息的重要手段。本文重点研究基于大规模视觉信息检索的城市居住环境监测。由于对比度低，边界模糊，信息量大，易受噪声影响等缺点，卫星图像分割的性能不能令人满意，会影响居住环境的监测。设计了一种结合蚁群算法的改进的粗糙集模糊C均值聚类算法。进一步来说，结合粗糙集理论，根据图像的不可区分关系，根据像素的梯度对卫星图像进行分类。然后，将传统的基于模糊集的模糊C均值聚类算法应用于卫星图像分割技术。随后，将改进的算法-量子蚁群算法和粗糙集模糊聚类C-均值算法相结合，以实现卫星图像的精确分割。之后，我们提出了一种卫星图像检索算法，该算法可以协助城市居民环境的监测。综合实验表明，本文提出的方法在居住环境监测中是有效且鲁棒的。传统的基于模糊集的模糊C均值聚类算法被应用于卫星图像分割技术。随后，将改进的算法-量子蚁群算法和粗糙集模糊聚类C-均值算法相结合，以实现卫星图像的精确分割。之后，我们提出了一种卫星图像检索算法，该算法可以协助城市居民环境的监测。综合实验表明，本文提出的方法在居住环境监测中是有效且鲁棒的。传统的基于模糊集的模糊C均值聚类算法被应用于卫星图像分割技术。随后，将改进的算法-量子蚁群算法和粗糙集模糊聚类C-均值算法相结合，以实现卫星图像的精确分割。之后，我们提出了一种卫星图像检索算法，该算法可以协助城市居民环境的监测。综合实验表明，本文提出的方法在居住环境监测中是有效且鲁棒的。可以协助城市居民环境监测。综合实验表明，本文提出的方法在居住环境监测中是有效且鲁棒的。可以协助城市居民环境监测。综合实验表明，本文提出的方法在居住环境监测中是有效且鲁棒的。