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Efficient Spatially-Variant Single-Pixel Imaging Using Block-Based Compressed Sensing
Journal of Signal Processing Systems ( IF 1.8 ) Pub Date : 2021-09-08 , DOI: 10.1007/s11265-021-01689-5
Zhenyong Shin 1 , Tong-Yuen Chai 1 , Chang Hong Pua 1, 2 , Sing Yee Chua 1, 2 , Xin Wang 3
Affiliation  

Single-pixel imaging is an important alternative to conventional camera. Only a single-pixel detector is needed to capture image data by measuring the correlation of the target scene and a series of sensing patterns. Conventionally, Nyquist-Shannon theorem requires measurements not less than the image pixels for an error-free reconstruction. Compressed sensing (CS) enables image reconstructions with fewer measurements but the image quality and computational cost remain the primary concerns. This paper presents an efficient single-pixel imaging technique based on blocked-based CS in which the sensing matrices are designed based on spatially-variant resolution (SVR). The proposed method decreases the number of measurements as well as the image reconstruction time using the SVR sensing patterns. Furthermore, it takes advantage of block-based CS to reduce the expenses of computational resources. The proposed method is evaluated and compared to conventional uniform resolution (UR) image reconstruction in terms of image quality and reconstruction time. The results show that the proposed method consistently reduces the reconstruction time and able to give better image quality at lower sampling ratio (SR). This provides an efficient reconstruction for single-pixel imaging which is desirable in practical application and situations where low sampling rate is required.



中文翻译:

使用基于块的压缩传感的高效空间变化单像素成像

单像素成像是传统相机的重要替代方案。通过测量目标场景和一系列传感模式的相关性,只需要一个单像素探测器来捕获图像数据。通常,Nyquist-Shannon 定理需要不小于图像像素的测量值才能进行无差错重建。压缩感知 (CS) 能够以较少的测量值重建图像,但图像质量和计算成本仍然是主要问题。本文提出了一种基于基于块的 CS 的高效单像素成像技术,其中基于空间变化分辨率 (SVR) 设计传感矩阵。所提出的方法使用 SVR 传感模式减少了测量次数和图像重建时间。此外,它利用基于块的 CS 来减少计算资源的开销。在图像质量和重建时间方面对所提出的方法进行评估并与传统的均匀分辨率(UR)图像重建进行比较。结果表明,所提出的方法一致地减少了重建时间,并且能够在较低的采样率(SR)下提供更好的图像质量。这为单像素成像提供了有效的重建,这在实际应用和需要低采样率的情况下是可取的。结果表明,所提出的方法一致地减少了重建时间,并且能够在较低的采样率(SR)下提供更好的图像质量。这为单像素成像提供了有效的重建,这在实际应用和需要低采样率的情况下是可取的。结果表明,所提出的方法一致地减少了重建时间,并且能够在较低的采样率(SR)下提供更好的图像质量。这为单像素成像提供了有效的重建,这在实际应用和需要低采样率的情况下是可取的。

更新日期:2021-09-09
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