This paper observes the application of the Compressive Sensing in reconstruction of the under-sampled iris images. Iris recognition represents form of biometric identification whose usage in real applications is growing. Compressive Sensing represents a novel form of sparse signal acquisition and recovering when small amount of data is a available. Different sparsity domains are considered and compared using various number of available image pixels. The theory is verified on iris images.
翻译:本文观察了压缩遥感在重建未充分抽样的虹膜图像中的应用情况。Iris识别是生物鉴别的一种形式,在实际应用中使用这种形式正在增加。压缩遥感是一种新形式,即当有少量数据可用时,获取和恢复的信号很少。考虑不同的宽度域,并使用各种现有图像像素进行比较。该理论在iris图像上得到验证。