Robustness and confidence are crucial in super-resolution tasks for X-ray radiological imaging, both in terms of X-ray sensors and image processing techniques. Due to the extremely short wavelengths of X-rays, optical modulation in X-ray imaging systems is highly challenging. Consequently, single-image super-resolution techniques in computer vision have become a popular approach in medical imaging. However, these methods can lead to artifacts and the plasticity phenomenon, potentially compromising image quality and diagnostic accuracy. In this manuscript, we introduce an on-chip coded aperture design that is both cost-effective and helps overcome the additional constraints and limitations commonly found in traditional computational-imaging-based super-resolution X-ray systems. This design generates sub-pixel physical coding on X-ray sensors, and thus a three-dimensional (3D) computational decoding approach is presented that transforms the two-dimensional (2D) super-resolution reconstruction into a 3D compressed sensing problem. Unlike super-resolution restoration in computer vision, this problem can be mathematically solved to yield interpretable reconstructions under the constraints of the restricted isometry property. Our experimental results, complemented by qualitative analysis, demonstrate the superiority of our design in X-ray radiological imaging, effectively mitigating artifacts and the “plastic-like” appearance frequently associated with conventional super-resolution techniques.
Coded x-ray diffraction imaging (CXRDI) is an emerging computational imaging approach that aims to solve the phase retrieval problem in x-ray crystallography based on the intensity measurements of encoded diffraction patterns. Boolean coding masks (BCMs) with complementary structures have been used to modulate the diffraction pattern in CXRDI. However, the optimal spatial distribution of BCMs still remains an open problem to be studied in depth. Based on the spectral initialization criterion, we provide a theoretical proof for the premise that the optimal complementary BCMs should obey the blue noise distribution in the sense of mathematical expectation. In addition, the benefits of the blue noise coding strategy are assessed by a set of simulations, where better reconstruction quality is observed compared to the random BCMs and other complementary BCMs.
more » « less- PAR ID:
- 10218298
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Applied Optics
- Volume:
- 60
- Issue:
- 10
- ISSN:
- 1559-128X; APOPAI
- Format(s):
- Medium: X Size: Article No. 2751
- Size(s):
- Article No. 2751
- Sponsoring Org:
- National Science Foundation
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