像素
计算机科学
图像分辨率
帧速率
人工智能
压缩传感
计算机视觉
投影(关系代数)
帧(网络)
分辨率(逻辑)
亚像素分辨率
光学
图像处理
图像(数学)
物理
算法
电信
数字图像处理
作者
Fernando Soldevila,Eva Salvador-Balaguer,Pere Clemente,Enrique Tajahuerce,Jesús Láncis
摘要
Abstract During the past few years, the emergence of spatial light modulators operating at the tens of kHz has enabled new imaging modalities based on single-pixel photodetectors. The nature of single-pixel imaging enforces a reciprocal relationship between frame rate and image size. Compressive imaging methods allow images to be reconstructed from a number of projections that is only a fraction of the number of pixels. In microscopy, single-pixel imaging is capable of producing images with a moderate size of 128 × 128 pixels at frame rates under one Hz. Recently, there has been considerable interest in the development of advanced techniques for high-resolution real-time operation in applications such as biological microscopy. Here, we introduce an adaptive compressive technique based on wavelet trees within this framework. In our adaptive approach, the resolution of the projecting patterns remains deliberately small, which is crucial to avoid the demanding memory requirements of compressive sensing algorithms. At pattern projection rates of 22.7 kHz, our technique would enable to obtain 128 × 128 pixel images at frame rates around 3 Hz. In our experiments, we have demonstrated a cost-effective solution employing a commercial projection display.
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